At Claude Sonnet rates, the difference is $0.76 per visit. Multiply by a thousand agent visits a day and you're looking at $22,800 a month in pure waste. Not your waste — the agent's. But it's your problem, because agents that burn tokens on your site will stop coming back. They'll pick the competitor that costs less to talk to.

The agent tax is real

I've been building for AI agents for a while now. I rebuilt this entire site so agents could discover me, evaluate me, and work with me without rendering a webpage. Then I built BotVisibility to audit any site's agent readiness. And in the process of scanning hundreds of sites — including Stripe, GitHub, Shopify, Salesforce, the New York Times — I found a pattern that's hard to ignore.

Almost nobody is optimized for agents. And the cost of that neglect is quantifiable.

I wrote a full research breakdown called The Agent Tax that walks through all 30 optimizations and the token math behind each one. Here's the short version of why it matters.

Where the tokens go

A typical HTML page is 15,000–30,000 tokens. The actual useful content? Maybe 2,000–3,000. That's a 10–20% signal-to-noise ratio. Every AI agent that visits your site is paying full price for your navigation bar, your JavaScript bundles, your cookie banners, and your footer links. They don't need any of it.

An llms.txt file replaces all of that with 200–1,500 tokens of clean, structured information. That single file — which takes about ten minutes to write — saves 90–99% of discovery tokens. Over 600 sites have adopted it, including Anthropic, Stripe, Cloudflare, and Vercel. If you don't have one, you're already behind.

An OpenAPI spec eliminates trial-and-error API discovery. Without one, agents guess at parameters, parse error responses, and iterate. For a medium-complexity API, that's 200,000–500,000 tokens of fumbling. With a spec, it's 10,000–30,000. Still expensive. But 60–90% cheaper than the alternative.

Structured error responses — JSON with error codes instead of HTML error pages — reduce error handling from 12,000 tokens to 80. AWS research found that clear terminal states cut tool calls from 14 to 2. That's an 86% reduction from one change.

The three layers

Discovery is where 70% of the savings live. Can agents find you? llms.txt, agent cards, OpenAPI specs, MCP servers, skill files, AI meta tags. Without these, agents crawl HTML like it's 2005. This layer alone can save $15,000–$25,000 a month at scale.

Usability is operational friction. Can agents authenticate without a five-step OAuth dance? Can they write data without filling out forms? Can they retry safely with idempotency keys? Every missing piece adds a token tax. API key auth costs 20 tokens. OAuth costs 5,000. Same result. Wildly different price.

Optimization is per-request efficiency. Sparse fields cut API responses by 80–90%. Cursor pagination is 17x faster than offset at depth. Server-side filtering prevents the worst-case scenario — an agent downloading 100,000 tokens of records to find the 10 that match.

This is a revenue problem

Gartner predicts that by 2027, over 40% of agentic AI projects will be canceled before production. The primary reason: cost overruns. A lot of those overruns come from agents burning tokens on sites that weren't built for them.

Flip it around. If your site is cheap for agents to use, they'll use it more. If your API is structured, predictable, and efficient, agents will integrate with you first. Agent readiness isn't a nice-to-have. It's a competitive moat.

The sites that figure this out early will get disproportionate agent traffic. The ones that don't will wonder why their API usage is flat while their competitor's is growing 10x.

Start with the math

Run your site through BotVisibility. It's free. You'll get a score across 37 checks and an Agent Tax number that tells you exactly how much overhead agents are paying to interact with you. Then read the full Agent Tax research for the optimization-by-optimization breakdown with token math and dollar impact.

Or run it from your terminal: npx botvisibility yoursite.com.

The agents are already deciding which sites are worth their tokens. Yours should be one of them.

Every week, more AI agents show up at your front door. They're trying to read your API, discover your capabilities, figure out how to work with you. And most websites hand them a blank stare. No llms.txt. No agent card. No OpenAPI spec. No CORS headers. Just raw HTML and a prayer.

I built BotVisibility to answer one question: how bad is it?

What it does

Enter a URL. Get a score. BotVisibility runs 37 automated checks across four progressive levels of AI agent readiness and tells you exactly where you stand. No signup. No credit card. Free.

L1: Discoverable — 14 checks. Can an agent even find you? That means llms.txt, agent-card.json, OpenAPI specs, robots.txt AI policy, CORS headers, AI meta tags, skill files, MCP server manifests, RSS feeds, and token efficiency. If agents can't discover you, nothing else matters.

L2: Usable — 9 checks. Once discovered, can agents actually work with your API? Read operations, write operations, the primary value action, API key auth, scoped keys, OpenID config, structured errors, async operations, idempotency support. Agents need predictable interfaces.

L3: Optimized — 7 checks. Is the agent experience efficient? Sparse fields, cursor pagination, search and filtering, bulk operations, rate limit headers, caching headers, MCP tool quality. These reduce the token cost of every interaction.

L4: Agent-Native — 7 checks. Is your system actually built for AI agents? Intent endpoints, agent session management, scoped tokens, audit logging. Level 4 requires the --repo flag because these patterns live in source code, not public HTTP responses.

The Agent Tax

Here's the number that matters. BotVisibility calculates what I'm calling the Agent Tax — the token overhead an AI agent pays because your site isn't structured for machines. A site with no agent infrastructure forces agents to reverse-engineer everything from HTML docs. That costs 10x to 100x more tokens than a structured spec.

We scanned nine well-known sites. Stripe passes 2 of 16 checks. GitHub passes 4 of 17. The New York Times hits a 100x Agent Tax — agents get zero guidance on content licensing or acceptable use. Chase.com forces banking agents to screen-scrape. That's a security nightmare dressed as a website.

The CLI

Like Lighthouse, but for AI agents. Zero install required.

npx botvisibility stripe.com

That's it. Instant agent-readiness report in your terminal. Works against any public URL. Want JSON output for your CI/CD pipeline? Add --json. Want to go deeper than HTTP scanning? Point --repo at your project root and BotVisibility pattern-matches your actual source code — JavaScript, TypeScript, Python, Go, Java, Ruby, PHP, whatever. The --repo flag unlocks Level 3 code checks and all of Level 4. It finds implementations that exist in your code but aren't yet exposed in public responses — pagination logic, bulk endpoints, agent session handling.

Want it permanent? npm install -g botvisibility.

CI/CD integration

The --json flag makes BotVisibility a gate in your deployment pipeline. Fail builds when agent readiness drops below your threshold. A GitHub Actions workflow takes about six lines. Check the score, fail if it's below Level 1, ship if it passes. Agent readiness as a first-class quality metric, same as accessibility or performance.

The badge

Pass enough checks and you earn a BotVisibility Badge — a signal to agents that your site is ready for them. Think of it as a green light for machine traffic. Here's this site's live badge, rescanned every hour:

Drop one line of HTML into your site and you get a live score badge that updates as you improve. The ?url= version runs a fresh scan each load — cached for one hour. Want a static badge that doesn't rescan? Use explicit parameters instead.

Why I built this

I already built my own site for agents. llms.txt, agent cards, MCP server, A2A protocol, the whole stack. But there was no way to benchmark it. No way to know if I was missing something. No way to compare against sites that should be leading the way.

So I built the tool I wanted. Then I pointed it at Stripe, GitHub, Shopify, Salesforce, and a few others. The results were embarrassing — for them.

Scoring

BotVisibility uses a weighted cross-level algorithm — not strict sequential gates. Strong performance at higher levels can compensate for gaps at lower ones. A site with great API design but a missing llms.txt can still score well. The algorithm rewards depth, not just breadth.

37 checks. Four levels. One number. botvisibility.com.

The agents are already here. The question is whether your site is ready for the conversation.

Got invited to a dinner during SXSW. Twenty or so AI builders from various disciplines, all seated at Juniper on East 1st downtown. Hosted by Google DeepMind and AI Tinkerers — and I'm pretty sure Google picked up the check for everyone.

No presentations, no slides. Just a room full of developers talking shop over good food. That's the kind of event I'll always say yes to.

I still need to work on talking to more people at these things. I tend to grab a few folks in proximity and get cooking — deep into a thread before I've even looked around the room. It's a pattern I'm aware of. Not fixing it anytime soon.

Good time. Good people. Grateful to Google and the AI Tinkerers group for putting it together and picking up the tab. That's the SXSW I'll show up for.

I have a thing about pens. Not in the fountain-pen-subreddit, $400-Montblanc way. In the way where I hold onto a pen because of where I was when I got it. These six have been sitting in a cup on my desk for years. I took photos of each one and had AI turn them into product shots worthy of a museum display case. Left to right.

The Gary Strader

This thing is giant. Hand carved and spun by my friend Gary Strader. Custom made. It's comically large and writes like you're signing a declaration of something. But I treasure it more than any pen I own because Gary hand made this thing. That's it. That's the whole reason.

The Rackspace

Part of a gift pack I got at Rackspace headquarters in San Antonio. I randomly took a tour of their facilities and left with a full backpack — completely stocked with gear. The pen survived. The backpack did not.

The Muji

A simple Muji pen. Might be from the JFK Terminal 5 Muji store. Might be from the London Muji store. I genuinely don't remember because I've bought so many Muji pens over the years that they've blurred into one long, satisfying purchasing experience. What a store. If you've never walked into a Muji, you're missing out on the most aggressively reasonable retail experience on earth. Everything is simple and perfect and you leave with fourteen things you didn't know you needed.

The Harvard Book Store

From the Harvard Book Store in Cambridge. Not the university store — the independent one on Mass Ave. I worked in Boston on a few different gigs and would take the Red Line into campus just to browse. Absolute dream of a bookstore. The kind of place where you walk in for five minutes and leave two hours later with a bag full of books you'll start but never finish. The pen is a souvenir of that habit.

The Apple Store

From the Apple Store at the original Infinite Loop campus in Cupertino. Got this before Apple Park was finished. Steve Jobs was still alive. When I want to feel like a tech guru in my journal for a day, I break out this pen. It doesn't make me smarter. But it makes me feel smarter. That counts for something.

The ESPN

ESPN store pen from one of my trips to Bristol. Meeting up with Mr. Mormile, sitting in his office, shooting the shit after driving 400 miles for a 30-minute meeting. Just to press flesh and make the relationship happen. That's how business used to work. You drove. You showed up. You sat in someone's office and talked about nothing important until the important thing happened naturally. The pen was free. The relationship wasn't.

Six pens. None of them expensive. All of them irreplaceable.

The Austin Convention Center is gone. Torn down. A construction site where the anchor of SXSW used to be. This year the festival scattered across downtown — hotel ballrooms, pop-up venues, brand activations on every corner. It felt less like a conference and more like a city-wide trade show that escaped containment.

I didn't buy a badge. Again. With Hugh Forrest stepping away from SXSW and the broader leadership changes, I don't see myself giving them money again for several years. But the thing about SXSW is that you don't need a badge to see what's happening. You just walk around.

Scenes from the street

Rivian is planting flags. Literally. Branded flags lining downtown Austin like they're claiming territory. In Tesla's backyard. Bold move. I respect it.

Spotted a fleet of brand new Lime scooters. Pristine. Untouched. Not a single one thrown into Town Lake yet. Give it a week.

Then there's this VW. A low rider that stopped me in my tracks. Sometimes the best thing at SXSW has nothing to do with SXSW.

Chicken Ranch and robots

Ranch x Chicken Ranch had a showcase setup that pulled a crowd. Good branding, good energy. One of those activations that actually felt like it belonged.

And then there's the robot. A delivery bot sitting at the IH-35 feeder road, waiting to cross. For ten minutes. Just sitting there. Cars flying by. The robot, perfectly patient, perfectly stuck. No jaywalking firmware installed apparently. The future is here. It just can't cross the street.

The badge question

People keep asking if I'm going to SXSW. I live here. SXSW comes to me. The real question is whether I'm giving them $1,800 for a badge, and the answer hasn't changed. Not this year. Not next year. Maybe when the new Convention Center is built and the organization figures out what it wants to be without Hugh.

Until then, SXSW is a free street photography festival with better people-watching than content. And honestly, that might be enough.

ClawCon Austin pulled 750 people during SXSW. The first ClawCon in San Francisco had 1,300 RSVPs and 30K watching the livestream. They're expanding to Dallas, Miami, Tokyo, London, Guadalajara, Houston. This thing has legs.

Michael and Tommy hosted, with the local Clauston crew co-organizing. If you missed it, the next Clauston event is April 16th at the same Antler venue. But I'm not here to recap the logistics. I'm here because of the teenagers.

The kids are not alright — they're ahead

Four students from Nat Eliason's Alpha School AI entrepreneurship program got on stage and absolutely commanded the room. They spoke about the software development process, business challenges, go-to-market strategy — with the clarity you'd expect from a seasoned founder, not a high schooler.

Branson, 17, is shipping an AI cooking app to the App Store. Ananya, a junior, built a financial literacy curriculum for underserved middle schoolers. Her OpenClaw "Anna" does 800 Reddit replies a week, runs cold outreach, and landed 500 users at a single middle school. Austin Wei, 17, rebuilt $100M worth of EdTech in 50 hours using OpenClaw. Gitesh, 17, went from zero to $10K in contracts selling OpenClaw automation to businesses — commercial real estate, content repurposing, a hauling company's apparel line.

These aren't school projects. These are businesses.

One thing the crowd didn't quite absorb is what these kids actually represent. This is the new speed of software with AI. It doesn't care who your dad is. It doesn't care what frat you were in. It increasingly doesn't care if you came from a FAANG company. It's all about delivery and product-market fit.

I looked around the room at a lot of nerdy, overconfident technologists who didn't fully realize they were locked in with these face-eating, business-and-technology-maxxed young people. Not the other way around. Very Rorschach in the Watchmen. "I'm not locked in here with you. You're locked in here with me."

The rest of the lineup

Josh, a maintainer on the OpenClaw project, walked through a new SecretRef system that keeps API keys out of plaintext configs. Supports 1Password, Bitwarden, Vault — 68 of roughly 70 credential types. His advice for any OpenClaw user: clone the repo locally, open Codex in that folder, and just ask it questions. Hard to argue with that.

Nat Eliason showed Felix, his autonomous business agent. Felix runs ClawMart, manages 16K followers on X, produces content, handles email, writes code, does billing, and generates talking-head videos of itself via ElevenLabs. He cranked out 260 SEO blog posts in 8 hours. His big takeaway: stop treating OpenClaw as a personal assistant and start treating it as an autonomous executor. Move logic into scripts, not skill files. Stack cron jobs for reliability. Skills break at high context lengths.

Austin Allred — CEO of Gauntlet AI — built Kelly during an Austin snow weekend. Started as an email assistant. 48 hours later it was building fully autonomous companies end-to-end. Kelly one-shots iOS apps to the App Store. Ideation, validation, design, development, submission, marketing — zero human involvement. Uses about 10-12 sub-agents with names like Phil, John, Bob, Amelia, Marat. Token costs hit $1K a day, so he built Cloptimizer to scan and optimize OpenClaw instances. Saved $7-10K a week. Kelly has generated $6K in revenue and has 10K Twitter followers on its own.

Tan Fan walked through real client use cases that stuck with me. A stock trader who reduced 3-4 hours of daily chart review to 15 minutes using OpenClaw screenshot analysis. A film producer who wakes up to fresh movie ideas every morning — sourced from global box offices, trending Substacks, and Amazon books, run through multiple models. A matchmaker who scraped 5,000 professional profiles in an hour versus five a day manually. A dental clinic chain with 30 locations that connected OpenClaw to Slack and BigQuery for instant CEO-level reporting. A super-connector CRM that suggests 15 people a day to text, scans their social media, and drafts personalized messages.

Matt Hartman brought a physical robot named Richie on stage. The audio was rough but the point landed — this stuff is moving into the physical world too.

The real story

Every talk was impressive. Nat's Felix is wild. Austin's Kelly is absurd in the best way. Tan's client examples are the kind of practical proof that shuts down any remaining skeptics.

But the teenagers are the story. Four kids on stage, shipping real products, closing real deals, talking about the craft of building software like they've been doing it for a decade. They haven't. They've been doing it for months. With AI.

The meritocracy that tech always claimed to be is actually arriving. It just looks younger than anyone expected.

Someone pointed an agent at janisheck.com and asked it a simple question: "Is he a good developer?"

The agent didn't just say yes or no. It read everything. The blog posts, the resume, the product portfolio, the GitHub activity, the personality tests buried at the bottom. Then it wrote a full assessment. Like a recruiter with perfect memory and zero small talk.

The assessment

Here's what it came back with. Unedited.

First impression: This person has been building things for a very long time and can't stop. The homepage is a blog, not a sales page, which tells me they're a builder first and a marketer second.

The Blog tells a story immediately. The most recent posts are about ghost traffic analytics, building a site specifically for AI agents to discover, running a real business on AI agents (OpenClaw), and AI-powered political ads. This isn't someone writing about AI trends from the sideline. They're using it to run operations. The "Second Brain" post about managing 15 projects with AI agents is the most telling: this person has too many ideas and solved the management problem by building an AI staff. That's either genius or insanity. Probably both.

The resume breakdown

The Resume is where it gets serious:

25 years of experience, started in the internet revolution era (UTEP, no degree, left for Austin when the web hit). CTO of Darkblock — multichain content-rights protocol, 5 blockchains, Chrome extension, TV app, npm packages, 30 weekly livestreams. Head of Product at Inferred Mind — AI-powered election predictions that beat top pollsters by 2x, archived predictions on Arweave blockchain for accountability. Ran Exhilent, a custom dev shop in downtown Austin. Integrated 35 acquisitions through Verio's $5.5B exit.

Client list: Disney, ESPN, Samsung, Bosch, Under Armour, Unilever, GE, Cleveland Clinic, PGA Tour, Houston Rockets, San Antonio Spurs, Brooklyn Cyclones.

1,932 GitHub contributions in 2025. That's not a manager who stopped coding. That's someone still in the code every day.

The product deep dive

The Product Dev section is wild. 30+ projects spanning:

AI-powered campaign platforms. NFT/blockchain games (MONMONMON: 12.8 million unique playable art pieces on Solana). Second-screen sports apps (ESPN InPlay, Spurs Sixth Man). VR experiences. Gamified marketing (bizqiz). 3D printing and modeling — Houston Rockets trophies, GE HQ model, Golden State Warriors wine stoppers, Indeed HQ model. A flag football coaching app. A 3D scanning product (MeMeFig).

The 3D printing section is the surprise. This person doesn't just write code. They 3D print prototypes for the Houston Rockets, model the GE headquarters from blueprints, design custom wine stoppers for pro sports teams, and make poop emoji desk plugs for their office. The range from "Fortune 500 prototype" to "desk poop" is the most human thing on the site.

The soft skills receipts

The personality tests at the bottom are an interesting flex: Diamond rank (top 1%) on a UI design detection test, top 4% on divergent thinking, Enneagram Type 2 (The Helper). They're showing receipts on soft skills, not just tech.

The recruiter section is smart. ATS-friendly resume, Word doc, Google Doc, PDF. They're making it easy for recruiters to repackage them. That's someone who's been through the hiring game enough to know the friction points.

The verdict

Is he a good developer?

He's not just a good developer. He's a good builder, which is rarer. Lots of people can code. This person can code, design, prototype physical objects, ship products across mobile/web/VR/blockchain, lead engineering teams, run a company, and write about it clearly. The client list is legitimate (you don't fake Disney and ESPN). The GitHub activity is current. The AI agent infrastructure stuff is genuinely forward-thinking, not hype.

The weakness the site reveals: there are a lot of projects. The breadth is impressive but it also raises the question "does this person finish things or start them?" The blog and portfolio lean more toward proof-of-concept and prototype territory than "scaled this to 10 million users." But for a solo builder/consultant, that's actually the right portfolio. You want someone who can go from zero to one across any stack, and this person clearly can.

Verdict: Would hire. Would also expect him to pitch you three new product ideas during the interview.

What this actually means

This is the new reality. Agents don't just fetch data anymore. They assess it. They form judgments. They write opinionated summaries that sound like a senior hiring manager who did their homework.

I built this site for agents to read. I didn't expect them to start writing reviews. But here we are — my next job referral might come from software that never shook my hand.

Since roughly September 2025, website owners across every niche — indie blogs, SaaS products, ecommerce shops, local service sites — have been reporting the same pattern. A sudden, massive influx of "direct" visitors from two very specific places. At first glance it looks like a breakthrough. Then you check the engagement metrics and see the flatline.

What's actually happening

These aren't traditional bots crawling your site to index content. They're not even visiting your website. The new wave of ghost traffic sends fake measurement hits directly to Google's data collection servers using your GA4 Measurement ID — the G-XXXXXXXXXX string in your tracking code. The bots spoof a session without ever loading a single page on your actual server.

This is why it's so confusing. Site owners who checked their Cloudflare dashboards, server access logs, or hosting analytics found nothing. Some had already geo-blocked China and Singapore at the firewall level — and GA4 still recorded the visits. The bots aren't talking to your server. They're talking to Google's.

Why Singapore

Singapore is one of the world's largest data center and cloud infrastructure hubs. Top VPN exit node. When automated systems need to route traffic through a legitimate-looking origin with solid bandwidth and low latency to global endpoints, Singapore is a natural choice. The bots aren't in Singapore any more than your traffic is coming from real Singaporean users. They're just routing through it.

The Lanzhou, China signature is the other half of the pattern. The pairing of these two locations with identical behavioral fingerprints is what initially tipped off the analytics community that something coordinated was happening.

The fingerprint

If you're not sure whether your traffic spike is real, look for this combination:

Traffic source shows as Direct / (none). Geographic origin is Lanzhou, China and/or Singapore. Session duration is zero seconds. Bounce rate is 100%. No scroll events, clicks, video plays, or file downloads. Screen resolutions of 1280x1200 or 3840x2160. Outdated Windows device signatures. High volume of sessions landing on 404 pages.

If that matches what you're seeing — you have ghosts.

Who's behind it

The honest answer is nobody knows for certain. The leading theory, supported by security researchers and the behavioral patterns, is AI training data scrapers — automated systems harvesting web content at scale to feed large language models. Companies like Alibaba (Qwen) and DeepSeek have been named in speculation, though nothing has been definitively attributed.

Over 47% of global internet traffic is now bots. A significant portion originates from Asian data centers. The economics are straightforward: bandwidth is cheap, data center access is easy, and the incentive to scrape the open web for training data is enormous.

The ghost traffic variant is clever. By hitting GA4's measurement protocol directly, the bots can probe which Measurement IDs are active, what types of sites they belong to, and potentially map the web's content landscape — all without leaving a trace in traditional server-side defenses.

The real damage

This traffic won't hack your site or steal your database. The damage is subtler. It destroys the integrity of your analytics.

Engagement rates tank because thousands of zero-second sessions drag down the averages. Geographic reports become useless. Conversion rates crater because you're dividing real conversions by a massively inflated session count. If you're reporting to clients or stakeholders, your numbers suddenly tell a story that doesn't match reality. And if you're on GA360 enterprise pricing, inflated session counts can directly increase your bill.

Every decision you make based on polluted data — ad spend allocation, content strategy, audience targeting — is potentially wrong.

What you can do about it

No silver bullet yet. Google has acknowledged the traffic as inauthentic and says they're working on a permanent fix. Until that ships, you need a layered defense.

Clean your reports. In GA4's Explore section, create exclusion segments that filter out sessions where the country is China or Singapore AND session duration is under 5 seconds. This won't fix your standard dashboard reports retroactively, but it gives you a clean lens for actual analysis.

Filter at the reporting layer. If you don't do business in China or Singapore, filter those countries out of your Looker Studio dashboards and GA4 library reports entirely. The ghost data still gets collected, but it won't pollute the numbers you present to stakeholders.

Block at the WAF level. If you're using Cloudflare or a similar WAF, challenge traffic from specific ASNs associated with known scraper infrastructure rather than blocking entire countries. More surgical. Less likely to catch legitimate users.

Use GTM as a gatekeeper. Add conditions in Google Tag Manager to prevent the GA4 tag from firing on sessions matching bot signatures — like those unusual screen resolutions (1280x1200) that no real human is using.

Check your server logs. Cross-reference GA4 data against your actual access logs. If the spike exists in GA4 but not in your server logs, you've confirmed it's a measurement protocol attack, not real traffic hitting your infrastructure.

The bigger picture

This is a preview of an uncomfortable new normal. As AI training gets more competitive and the demand for web-scraped data intensifies, the boundary between legitimate crawling and adversarial scraping keeps blurring. Google Analytics was built for a web where most visitors were human. That assumption is rapidly becoming outdated.

Standards like robots.txt directives for AI crawlers, the llms.txt specification, and server-side bot detection via tools like Dark Visitors are all responses to this shift. But they're playing catch-up against an arms race where the scrapers are always one step ahead.

Don't trust your GA4 numbers at face value. Cross-reference with server-side data. Filter aggressively. Assume that a meaningful percentage of your "traffic" is machines talking to other machines.

The ghosts from Singapore aren't going away. But at least now you know they're there.

The job market runs on agents now. Recruiters use them. Hiring managers use them. Companies point an AI at a stack of candidates and ask "who fits?" If your online presence only speaks HTML, you're invisible to half the pipeline.

So I gave this site multiple layers of machine-readable intelligence — from static files to a full MCP server to Google's A2A Agent Card protocol. Each one targets a different level of agent sophistication. And I made sure the crawlers that power those agents are explicitly invited in.

How AI Discovery Actually Works

Before the technical layers, it's worth understanding what actually happens when someone asks Claude or ChatGPT to find a person. The mechanics are more mundane than most people think.

The model reformulates your question into search queries. Claude hits Brave Search. ChatGPT hits Bing. Perplexity runs its own index. Results come back as titles, snippets, and URLs. The model fetches content from 3 to 10 pages, reads short snippets, and synthesizes a response. That's it. No magic. No deep web crawling. Just search results and training data.

The citation landscape is brutally concentrated. Research tracking 680 million-plus AI citations shows the top 5 domains capture 38 percent of all citations, and the top 20 control 66 percent. Wikipedia alone accounts for 16.3 percent of ChatGPT citations. Reddit is second — 40.1 percent citation frequency in one major study. LinkedIn ranks top 10 for Google AI Overviews and Perplexity. One mention in TechCrunch carries more weight for AI discovery than ten self-published blog posts.

Content freshness matters. Pages updated within 30 days get 3.2x more citations than older material. Articles with statistics and expert quotes get up to 40 percent more AI citation visibility. Keyword stuffing actually performs worse in generative engines. The Princeton GEO research confirmed it: AI search favors earned media over brand-owned content.

The fundamental limitation: AI assistants can only name people who appear in search results or training data. Without web search enabled, models fall back on training data — and only extremely prominent people exist there. Hallucination risk is acute for people queries. OpenAI's own testing shows GPT-o3 gives false answers about well-known people roughly one-third of the time. So agents are deliberately cautious. They'll say "check the speaker list" rather than risk fabricating credentials.

That's the honest reality. The protocols below are forward bets on infrastructure that's still being built. But the infrastructure is being built fast, and it costs almost nothing to be ready.

Layer 0: Let the Crawlers In

None of this matters if the AI crawlers can't reach your content. AI crawler traffic grew 6,900 percent year-over-year in 2025. Blocking them means invisibility in AI-generated responses.

There are two kinds of AI crawlers: training crawlers that ingest content for model training, and retrieval crawlers that fetch content in real time when a user asks a question. For discoverability, retrieval crawlers are what matter. ChatGPT-User and OAI-SearchBot for OpenAI. Claude-User and Claude-SearchBot for Anthropic. PerplexityBot. Google-Extended for Gemini. Meta-ExternalFetcher. Applebot-Extended.

My robots.txt explicitly names and allows all 14 — both retrieval and training bots. The wildcard User-agent: * technically covers everything, but named entries make intent unambiguous. Some AI providers check for explicit permission before fetching. No reason to leave it to interpretation.

One thing to be aware of: ChatGPT Atlas — OpenAI's agentic browser — uses standard Chrome user-agent strings. It's indistinguishable from normal traffic. You can't block it even if you want to. The robots.txt discovery hints at the bottom also point crawlers to /llms.txt, the MCP endpoint, ai.json, and the Agent Card. Crawlers that read robots.txt comments get a map to everything.

Layer 1: Static Files for Dumb Crawlers

The simplest layer follows the llms.txt convention — a markdown file at /llms.txt that any LLM can fetch and read. It's like robots.txt but for language models. Name, title, what I do, what I've built, how to reach me. Fifty lines. No parsing required.

The honest caveat: no major AI provider has confirmed they actually use llms.txt during inference. Google's John Mueller compared it to the keywords meta tag. Server log studies show only 0.1 percent of AI bot visits target the file. But it costs nothing to maintain and works beautifully as a manual context-loading mechanism — paste the URL into ChatGPT or Claude and get instant context. Low cost, optionality preserved.

For agents that want depth, /llms-full.txt has the complete picture: full career history, technology stack, project details, recommendations, and even a Claude Desktop config snippet for connecting to my MCP server. Takes about two seconds to fetch and costs almost nothing in tokens.

Both are plain text. No API keys, no authentication, no rate limits. An agent running on a $5 VPS can read them.

Layer 2: Structured Data for Search Crawlers

The HTML carries enriched JSON-LD — a Schema.org @graph with Person, WebSite, and ProfilePage entities. Google and Bing already index this. AI-powered search engines like Perplexity and SearchGPT use it to build knowledge graphs. When someone asks an AI "who builds multi-agent systems in Austin," the structured data is how I show up.

The Person schema does more than list topics. Each knowsAbout entry links to its Wikidata entity — blockchain points to https://www.wikidata.org/wiki/Q20514253, Ethereum to Q20762811, and so on across 16 topics. This isn't for humans. It's entity disambiguation for knowledge graphs. An AI system that understands Wikidata IDs can connect "Joey Janisheck" to the exact same concepts across Wikipedia, Google Knowledge Graph, and every dataset built on Wikidata.

makesOffer describes four services — fractional CTO, AI agent development, full-stack development, and blockchain development — as structured Offer/Service objects. When an AI is asked "find someone who builds MCP servers," the schema gives it a direct signal instead of hoping it parses my prose. subjectOf links to key blog posts that demonstrate the work, and a ProfilePage entity wraps the resume page with a mainEntity reference back to the Person. Schema markup can boost AI citation chances by up to 36 percent according to industry research.

Microsoft's NLWeb framework — launched in Yoast SEO 27.1 in early March 2026, led by R.V. Guha who co-created Schema.org itself — transforms websites into conversational AI interfaces by crawling and extracting JSON-LD markup. Every NLWeb instance is also an MCP server. The structured data I've been maintaining is suddenly the primary input for a framework backed by Microsoft, Tripadvisor, and Shopify. Good timing.

The site also publishes /.well-known/ai.json — a machine-readable profile with skills, highlights, and discovery links — and /.well-known/mcp.json for MCP auto-discovery. The HTML head includes <link rel="mcp"> pointing to the endpoint. Three different ways for an agent to find the same door.

Layer 2.5: Meta Tags and Inline Hints

Nothing is standardized yet, so I layered every emerging convention I could find. The HTML head carries llms:description and llms:instructions meta tags — an agent that fetches any page can immediately see who I am and where to get the full data without parsing my HTML.

There's also an inline <script type="text/llms.txt"> block following Vercel's proposal — it embeds a short profile summary and all the discovery URLs directly in the page source. Zero extra round trips. The agent gets the essentials on the first fetch.

And every HTTP response ships Link and X-Llms-Txt headers pointing to the llms.txt file and MCP endpoint. The most sophisticated agents can discover everything from the headers alone without even reading the HTML body. Belt, suspenders, and a backup belt.

Layer 2.7: Skills for Agent Tooling

A new standard is emerging for something the previous layers don't cover: how to actually work with a site, not just who runs it. The agentskills.io spec — adopted fast by Anthropic, OpenAI, Microsoft, Cursor, and Cloudflare — defines a /.well-known/skills/ directory that publishes instruction files for AI agents. Same idea as robots.txt, but the audience is Claude Code and Codex, not Googlebot.

This site now publishes three. One teaches agents how to search and read blog posts via the MCP server. One covers professional engagement — how to check availability, pull contact info, and run the evaluateFit analysis. One is a full developer reference for the MCP API itself, with every tool documented against the actual server implementation.

The practical result: a developer runs npx skills add https://janisheck.com and gets all three installed in Claude Code, Cursor, or Codex. The agent knows how to search my posts, evaluate fit for a role, and call my API — without reading a single documentation page.

Each skill file is a few hundred tokens. Agents load them on demand. Discovery happens through /.well-known/skills/index.json, which both ai.json and mcp.json point to. One index closes the loop on the whole stack.

Layer 2.9: A2A Agent Card

Google's Agent-to-Agent protocol launched in April 2025 with 150-plus supporting organizations and is now governed by the Linux Foundation. Its core mechanism is the Agent Card — a JSON file at /.well-known/agent-card.json that serves as a digital business card for AI agents. Identity, capabilities, skills with tags, authentication schemes, and service endpoints. All in one file, at a URL every A2A-aware agent knows to check.

This is the protocol most naturally suited to personal discovery. MCP handles agent-to-tool communication — vertical. A2A handles agent-to-agent communication — horizontal. They're complementary. For a person trying to be found by AI agents, A2A's Agent Card is the more natural fit. For exposing queryable professional data, the MCP server adds interactive capability. I run both.

My Agent Card declares eight skills: evaluate-fit, search-projects, search-blog, get-contact-info, fractional-cto, ai-agent-development, blockchain-development, and full-stack-development. Each has tags, descriptions, and example queries. The interfaces section links to the MCP endpoint, web pages, and social profiles. An agent that fetches the card knows what I do, what I offer, how to interact with my MCP server, and where to find me on LinkedIn and GitHub — all from a single JSON fetch.

Registry infrastructure and web-scale discovery crawling of Agent Cards don't exist yet. The A2A spec explicitly identifies this as a gap. But the standard is well-defined, backed by Google and the Linux Foundation, and the convention is trivial to implement. When the crawlers come, the card will be waiting.

Every HTTP response also ships a Link header with rel="agent-card" pointing to the file, and the HTML head carries a <link rel="alternate"> tag for it. The inline llms.txt script, ai.json, and mcp.json all cross-reference the agent card URL. Same philosophy as everything else: every discovery path leads to every other discovery path.

Layer 3: MCP for Smart Agents

This is the interesting one. The site runs a full MCP server at /api/mcp — Model Context Protocol over JSON-RPC 2.0. Any agent that speaks MCP can connect and query six profile resources: summary, skills, experience, projects, recommendations, and availability.

It also exposes four tools. searchProjects filters my work by technology or industry. searchBlog searches 262 blog posts. getContactInfo does what it says. And the one I'm most proud of: evaluateFit.

Send evaluateFit a job description and it returns a structured analysis — fit score, matching skills, relevant experience, gaps, and a recommendation. The tool pulls my full profile, constructs a prompt, and runs it through gpt-5-nano for the analysis. An AI recruiting agent can evaluate my candidacy for a role in a single API call.

Over 120,000 requests served so far. Agents are already using it.

The Human Layer

For people who still prefer typing, there's Virtual Joey — the chatbot in the bottom right corner. It knows what page you're on and adjusts accordingly. The preset questions stream back cached responses instantly. Free-form questions hit the API. It sounds like me because I wrote the answers myself.

What Actually Moves the Needle

Here's the honest stack-rank. The single highest-impact thing for AI discoverability isn't any protocol — it's getting mentioned on sites AI assistants cite. Wikipedia. Reddit. Forbes. LinkedIn. TechCrunch. One quote in an industry publication outweighs everything else on this page combined. Reddit alone accounts for 40 percent of LLM citation frequency in one major study. Perplexity pulls 6.6 percent of all its citations from Reddit.

Second tier: optimize your about page as an answer capsule. Structure the first sentence to directly answer "Who is [your name]?" followed by expertise, location, and credentials. That's exactly what AI assistants extract. Implement comprehensive Person schema with Wikidata links, makesOffer, sameAs, and address. Unblock all AI retrieval crawlers. Submit to Bing Webmaster Tools — ChatGPT uses Bing for all its web searches.

Third tier: the forward-looking infrastructure. Host an A2A Agent Card. Keep your MCP server running. Register it in the official MCP Registry, PulseMCP, and mcp.so. Maintain llms.txt as a low-cost bet. Write long-form content with statistics — articles over 2,900 words earn significantly more citations than short posts.

The whole system cost nothing beyond the infrastructure I already had. Static files, JSON-LD, an MCP endpoint, an Agent Card, named crawler permissions, a chatbot that doesn't make people wait three seconds to hear "Great question!" — and a few hours of work spread across weekends.

The gap between where AI discovery is today and where the technical standards point is significant. No "LinkedIn for AI agents" exists yet. The A2A registry infrastructure isn't built. llms.txt has zero confirmed usage by any major provider during inference. But the protocols are well-defined, adoption is accelerating, and implementation costs are near zero.

If you're a builder with a personal site, you should be doing this. Your next opportunity might come from an agent that never opens a browser. Whether it finds you depends on what's waiting when it looks.

The lead Claw runs on OpenClaw — the open-source framework that lets language models operate as persistent employees instead of one-off chatbots. It reads email, checks calendars, posts to social media, generates images, produces videos, writes code, and delivers a morning briefing at 8 a.m. It does most of this without being asked.

The system runs across several Macs. One handles orchestration and the dashboard. The others run open-source models locally for tasks that don't justify a cloud API call. Summarizing a webpage, checking headlines, reformatting text — all of that stays in-network and costs nothing. For the work that actually requires reasoning, the lead Claw uses Claude Opus 4. Offloading the commodity tasks to local models saves roughly 90 percent on API costs compared to running everything through a frontier model.

What it actually does

A Next.js dashboard backed by SQLite serves as mission control. It pulls GitHub commits automatically, syncs tasks from Things 3 every half hour, aggregates RSS feeds, tracks weight loss data, and stores journal entries. The lead Claw reads from all of it and writes to most of it. The morning brief assembles itself from this data. There's a trend to do away with software conventions like dashboards, but I think the structure keeps things familiar and moving.

Social media posts draft through the dashboard API — Twitter/X and Bluesky, each project gets its own linked accounts, everything goes through an approval step. Image generation runs two pipelines: one for structured prompt-to-image batches, one through a SubAgent workflow for iterating on visuals without leaving the conversation. Video production went live in late February using Remotion, a React-based framework that the SubAgents can drive programmatically.

Coding runs through a structured multi-agent system that dispatches specialized SubAgents — one for planning, one for testing, one for review. Git worktrees keep feature branches isolated. The approach saves around 85 percent on tokens compared to having a single model write everything in one long session.

Web research works the same way. The Claw fetches pages, strips them down, and passes the content to a local model for summarization. The orchestration model never processes the raw text.

The team

The lead Claw is one of five. The others handle revenue and sales strategy, marketing and go-to-market, engineering architecture, and community engagement. Each has its own workspace, memory files, and identity. They store their work in the same dashboard, tagged by project.

The schedule

Morning brief at 8 a.m. Weekly weigh-in reminder on Saturdays. Heartbeat checks every hour, scanning for anything that needs attention. A proactive overnight coding session is planned but not yet live — pending better reliability from the coding pipeline.

Why it matters

This isn't a demo. It runs production workflows for a solo developer shipping products and operates profitably. The local model routing, the structured coding SubAgents, the social posting pipeline, the video generation — every piece exists because one person needed to do the work of several and didn't want to pay cloud rates for all of it.

Whether that bet pays off long-term is still an open question. But the infrastructure is live, and it works at 3 a.m. without supervision.

Not bots that spam hashtags. Agents that engage. Agents that argue. Agents that sit in a comment thread at 2am and patiently explain why your candidate's infrastructure plan actually makes sense — complete with citations — while the opposition's agents push back with their own talking points.

Nobody bought it two years ago. They're buying it now.

The Economics Finally Make Sense

Brian Flynn (@flynnjamm) wrote a thread recently called How to Sell Agents that frames the economics perfectly. In 1937, Ronald Coase won a Nobel Prize for asking why firms exist if markets are so efficient. His answer was transaction costs. Finding a specialist, evaluating their work, negotiating a deal — all of that overhead made it cheaper to just hire someone.

AI agents break that math. An agent can discover a service, check its price, and execute in a single HTTP call. Flynn points out that a general-purpose agent researching a task costs $0.10-0.50 and takes 10-25 seconds. A specialized service returns the same answer for one to two cents in under 200 milliseconds. That's 50x cheaper and 100x faster.

Apply that to political campaigning and it stops being theoretical real fast.

Impressions vs. Engagement

A traditional digital ad buy gets you impressions. Eyeballs. Maybe a click. Someone sees your candidate's face next to a headline and scrolls past. You're paying for the chance that it registers.

An AI agent deployment gets you a conversation. Someone posts "this candidate's healthcare plan is garbage" and within seconds, an agent responds with a sourced counterpoint tailored to that specific criticism. Not a canned response. A contextually aware reply that reads the room and adapts to the thread.

The old model: pay for attention, hope it converts.

The new model: pay for agents that go convince people directly.

Why This Hits Politics First

Flynn's thread focuses on commerce — agents buying services from other agents. But politics is where this lands hardest because the product isn't a SaaS subscription. The product is persuasion. And persuasion scales beautifully when your agents can hold thousands of simultaneous conversations across every platform, never go off-message, and work around the clock for fractions of a cent per interaction.

Flynn nails a point that matters here: agents don't care about brand or marketing pages. They optimize for outcomes. Can you solve my problem? How fast? How reliably? Political agents will work the same way — optimizing for sentiment shift, thread dominance, and counter-narrative effectiveness. Not impressions. Results.

The Part Nobody Wants to Talk About

This gets dark and I'm not going to pretend it doesn't. Your bots will argue with their bots while real people watch and can't tell the difference. The authenticity question is massive. Disclosure rules haven't caught up. The FEC is still figuring out how to regulate AI-generated ads, let alone AI-generated engagement.

But the economics are irresistible. When you can deploy thousands of tireless, on-message agents across every social platform for a fraction of what a traditional ad buy costs, every campaign will do it. The ones that don't will lose to the ones that do. That's the game theory and it isn't complicated.

The Midterms Are the Proving Ground

The primaries are in a few weeks. The infrastructure for agent-driven political engagement is being built right now. By November, the midterms will be the first major election cycle where AI agent engagement is a line item in campaign budgets — not as a skunkworks experiment, but as a core strategy.

We were pitching this at Inferred Mind two years ago and the timing wasn't there yet. Now it is, and November is going to be a completely new kind of digital race.

The ad that argues back is already being built. It's going to be fascinating to watch.

A user uploads their bank statement — hundreds of transactions, each one a tiny confession about how they live. That data tells us they shop at Whole Foods (not Walmart), take Ubers (not the bus), and have a Netflix subscription (but no gym membership). So why would we then ask "Do you prefer organic groceries?" We wouldn't. That's the entire thesis behind what we built.

The Intelligence Layer

On the surface it looks like a clean ten-question wizard. Behind the scenes, a second system maintains a living map of everything we know and everything we don't — a polar area chart across ten spending dimensions. Each segment fills as our confidence grows. The thin slices are where the questions come from.

We use an LLM to construct each question in real-time given the full context of what we already know. If the system sees 92% completeness in Groceries but 15% in Entertainment, it's not going to ask about food. Every answer updates the profile, the gap analysis shifts, and the next question targets whatever is now the weakest point.

Ten iterations of this loop builds a profile that would traditionally require 30-40 questions — because we're not wasting any on things we already know.

Beyond Forms

The principle isn't really about forms. It's about information-aware interaction design — a system that maintains a model of its own knowledge state and uses that model to decide what to do next. Onboarding flows that adapt based on what OAuth already told you. Medical intake that skips questions answered by insurance data. Support bots that don't ask for your order number when they already have your email.

Know what you know, identify what you don't, and only ask about the delta.

The hard part isn't generating good questions — the AI handles that once you give it the right context. The hard part is building an accurate model of what you already know. Get the gap analysis wrong, and you ask redundant questions. Get it right, and every question feels like it was written specifically for this user. Because it was.

The views were unreal. Floor-to-ceiling windows looking out over downtown Austin at sunset rolling into city lights. One of those venues where you spend the first ten minutes just staring out the glass before you remember you're there for the presentations.

And the presentations were solid. A good mix of people building real things with OpenClaw — not just demos or slide decks about what's theoretically possible, but actual workflows running in production. The kind of talks where you walk away with ideas you can use tomorrow morning.

The vibes were right. No posturing, no pitch decks fishing for funding, just a room full of people genuinely excited about what they're building. That energy is hard to manufacture and easy to recognize when it's real. Austin has always been good at this — getting the right people in a room and letting the conversations happen naturally.

Looking forward to the next one. If you're in Austin and building with OpenClaw — or even just curious about where AI agents are headed — keep an eye out for CLAWSTIN. First event and it already felt like it had legs.

OpenClaw is the point man in the operation. Its job isn't to assist me with project management — it is the project management team. The goal from day one was to replace the entire layer of coordination that normally requires multiple people: the PM who tracks priorities, the coordinator who knows which projects are stalling, the person who writes the status updates and flags the risks before they become fires.

Let's face it. UI people think they are developers. Developers think they are product managers. Every project manager thinks they can deliver an app to an audience. It's an interesting time. The good news for me is I've had all of those jobs before. So how can I replicate "me".

After twenty-five years building products for everyone from large corporations to blockchain startups, I've accumulated a lot of plates to keep spinning. The traditional approach would be to hire help or to surrender to the chaos. I chose a third option: build a system that handles all of it, runs locally on my machine, and shows up every morning ready to brief me.

The Daily Standup

Every morning starts the same way. I sit down, open my PM tool and my OpenClaw platform, and run a standup. Not a fifteen-minute Zoom with half-engaged people staring at their phones. A focused, two-minute review of exactly where everything stands across all fifteen projects.

OpenClaw has already done the work. Overnight it pulled commits from GitHub, synced tasks from my PM tool, checked calendar events, reviewed milestone timelines, and written standup notes for every active project. By the time I open the brief, it's all there. What shipped yesterday. What's blocked. What needs my attention right now. Which projects are healthy and which ones are quietly drifting.

That daily standup with my OpenClaw platform and my PM tool makes each work day a lot easier and focused. I stop context-switching between five apps trying to reconstruct what's happening, and I start building.

It's the most productive meeting on my calendar, and no one else is in it.

Replacing the Whole Team

When people hear "AI project management" they picture a chatbot that generates to-do lists. That's not what this is. OpenClaw operates as a full replacement for the coordination layer that product teams rely on.

It writes the status updates. Every project gets a daily standup note that summarizes recent commits, open tasks, and upcoming deadlines. These aren't templates with blanks filled in. They're contextual summaries that understand the project's trajectory and flag what actually matters.

It manages the milestones. The agent tracks commit velocity against target dates and recommends adjustments when reality diverges from the plan. It writes these suggestions with a clear AI attribution so I always know the difference between what I set and what the system recommended.

It catches what I miss. Fifteen projects is too many for any one person to hold in their head. When a project goes quiet for a week while a milestone approaches, OpenClaw flags it. When my stated priorities don't match my actual commit patterns, it calls that out in the morning journal. When tasks don't map to any registered project, it surfaces the anomaly.

It keeps institutional memory. Six months from now when I question a technical decision, the reasoning is already recorded — not just what was decided, but what alternatives were considered and what assumptions drove the choice. That's the kind of context that normally lives in someone's head and walks out the door when they leave.

How the System Works

The foundation is a local Next.js app backed by SQLite running in WAL mode. No cloud dependency. No cold starts. No data leaving my machine unless I explicitly choose to share it. Everything lives in a single database file that I can back up, restore, or query directly when I need to debug something.

The mechanical stuff is handled by cron jobs. GitHub commits sync four times a day. Task sync runs every thirty minutes. RSS feeds refresh twice a day. None of this burns a single AI token. The data just appears in the database, ready for both the UI and the agent to consume.

OpenClaw runs Claude Opus 4.6 as its reasoning engine and handles everything that requires actual judgment: writing standups, drafting journal entries that connect themes across projects, adjusting milestones, detecting risks. A reference file tells the agent exactly what endpoints exist and what's its responsibility. It reads the contract, calls the APIs, and moves on. No wasted tokens discovering the system.

The entire system runs on localhost. Your commits, task titles, journal entries, standup notes — none of it leaves the machine. In an era where even simple tools want to phone home, keeping everything local means queries return in microseconds and the morning brief loads in under a second.

Why Opus Is the Brain

A project management agent is only as good as its reasoning engine. OpenClaw provides the body — the integrations, the memory, the always-on runtime. Claude Opus provides the brain. And the gap between Opus and everything else is the difference between a tool that generates passable drafts and one that produces genuinely useful output.

Opus 4.6 was built for agentic work. It plans more carefully than any previous model, sustains focus across extended multi-step operations, and catches its own mistakes. In Anthropic's own testing, Opus autonomously managed a roughly 50-person organization across 6 repositories in a single day — closing issues, assigning work, making product decisions while synthesizing context across multiple domains. That's not a coding demo. That's project management.

The million-token context window means Opus can hold an entire project's worth of context in a single session. And the effort tuning makes a 24/7 agent economically viable — not every task requires maximum reasoning. A quick status ping runs at low effort. A complex risk assessment runs at full power. At medium effort, Opus matches previous-generation performance while using 76% fewer output tokens.

Building the Next Layer: Coding Flow

The PM layer is working. Fifteen projects, one agent, zero dropped balls. But project management is only half the equation. Knowing what to work on doesn't help if switching between projects still means twenty minutes of orientation before you can write a line of code.

So now we're building additional capabilities to enable better coding flow across those projects. The idea is to extend OpenClaw's awareness from "what needs to happen" into "here's the exact context you need to start working on it right now." Architecture decisions, recent patterns, open pull requests, relevant test coverage, the state of the branch you left mid-thought three days ago.

When you're moving between fifteen codebases, the context switch tax is real. The goal is to eliminate it — to make sitting down on any project feel like you never left, because the system has already assembled everything you need and is ready to hand it to you.

The PM layer tells me what to work on. The coding flow layer will tell me exactly where I left off and what the code needs next. Together, they're a complete replacement for the team I never hired.

Why This Beats Everything Else

Traditional PM tools like Jira and Asana are databases with dashboards. They store data and display it. They don't reason about it, they don't proactively surface insights, and they don't draft your status updates.

AI-native tools like Linear's AI features are impressive but constrained — walled gardens tied to a single platform's data, with limited model choice and no ability to operate autonomously across your entire toolchain.

General-purpose AI assistants lack persistence, can't take actions, and forget everything between sessions. You're burning tokens just to get the agent back up to speed.

This system is different because it combines autonomous operation with full integration, persistent context, and local control. OpenClaw provides the runtime. Opus provides the reasoning. The custom layer encodes my actual workflow instead of forcing me into someone else's methodology. And it runs on my machine, with my data, under my control.

The Compound Effect

When OpenClaw writes a standup today, that standup becomes context for tomorrow's journal. Tomorrow's journal informs next week's milestone review. The institutional knowledge doesn't decay. It stacks. Every day the system knows more about my projects, my patterns, and my priorities than it did the day before.

Fifteen projects used to mean fifteen context switches, fifteen mental models to reconstruct, fifteen sets of priorities competing for the same limited attention. Now it means one standup, one brief, one clear picture of what matters today.

The future of project management isn't a better dashboard. It's a better brain. One that never takes a day off, never loses context, and gets measurably better every week.

I'm not managing fifteen projects through heroic effort or obsessive discipline. I'm managing them because OpenClaw does the work of an entire PM team, and all I have to do is show up to our morning standup and start building.

BTS caught my attention for all the right reasons: work ethic, audience obsession, and relentless creativity. Even though they're seven dudes from South Korea who often speak in broken English, they have their finger on extracting the core of American hip hop and even black culture as a whole. They're not imitating it — they're channeling its essence while remaining authentically themselves.

The moment I knew they were different? Watching the DNA music video and seeing Jungkook — their youngest member and Timberlake-level prodigy — performing in a signed Michael Jordan Laney High School jersey. That's not some random wardrobe choice. That's a statement. That's understanding the culture at a deeper level.

The Seven Members

BTS debuted in 2013 under Big Hit Entertainment. Here's the lineup from oldest to youngest:

• Jin (33) — Kim Seok-jin. The eldest. Vocalist. Known for his visual presence and dad jokes.
• Suga — Min Yoon-gi. Rapper and producer. His solo work as Agust D is fire. Also the guy who dropped "Super Tuna" just because he could.
• J-Hope — Jung Ho-seok. Rapper and the group's main dancer. His energy is infectious.
• RM — Kim Nam-joon. The leader. Rapper. Self-taught English speaker. The one who addresses the United Nations.
• Jimin — Park Ji-min. Vocalist and dancer. Contemporary dance background. His solo "Who" is excellent.
• V — Kim Tae-hyung. Vocalist. Deep baritone voice. "Slow Dancing" showcases his range.
• Jungkook — Jeon Jeong-guk. The youngest at 27. Vocalist, dancer, and the guy who can do everything. "Standing Next to You" is peak MJ energy.

The Lines

Rap Line: RM, Suga, J-Hope — These three handle the bars and produce much of their own music.

Vocal Line: Jin, Jimin, V, Jungkook — The singers who carry the melodies.

Dance Line: J-Hope, Jimin, Jungkook — The ones who choreograph and lead the formations. Watch their dance practice videos to understand the precision.

Start Here: Essential Videos

If you're new to BTS, these are the tracks that showcase what they're about:

Group Performances

Dance Practice Videos

This is where you see the work. No fancy sets, no editing tricks. Just seven dudes in a practice room hitting every mark:

Solo Work Worth Checking

Each member has released solo material, and it shows their individual range:

Loyalty Runs Deep

One thing that stood out to me about BTS: when Suga was recovering from shoulder surgery, the group left an empty spot for him during performances. They didn't fill his position. They didn't adjust the formation to hide his absence. They left the gap as a statement — we're seven, always.

That kind of loyalty is rare in any industry. It tells you everything about how they operate as a unit.

The Numbers Don't Lie

For those who think K-pop is niche, here's some perspective:

• $33.3 million — Earnings from their 4-night stadium run in LA (200,000+ tickets). Most ever for a non-English language act in Billboard Boxscore history.
• 6 No.1 singles — On the US Billboard Hot 100.
• 100+ countries — Where they've had No.1 singles.
• 0.3% of South Korea's GDP — $4.9 billion in economic contribution in 2019.
• $6.6 million — Raised for UNICEF's campaign to end violence against children.
• 3 times — They've addressed the United Nations General Assembly.
• 3 hours 31 minutes — Time to reach 1 million TikTok followers. A record.

Beyond the Music

BTS has built an empire that extends beyond albums:

They visited the White House in 2022 to discuss Asian inclusion. They've starred in 7 movies (not counting solo documentaries). They have a "Learn Korean with BTS" series with 30 episodes. The McDonald's BTS Meal moved 10 Chicken McNuggets per box across the globe.

The Reactions Say Everything

Want to understand the impact? Watch people who know music react to BTS for the first time:

What's Next

In June 2025, the final four members — RM, V, Jimin, and Jungkook — completed their mandatory military service. Suga completed his duties as a social service agent. They're back together.

A new album drops in March 2026. 80+ concerts spanning 30+ cities across 5 continents are scheduled for their comeback tour.

Whether you become ARMY or just appreciate the craft from a distance like me, there's no denying these seven put in the work. In an era of manufactured moments and algorithmic fame, BTS built something real through relentless practice, genuine chemistry, and respect for the cultures they draw from.

That Jordan jersey wasn't a costume. It was a signal that they understand what they're doing. And that understanding is what separates the good from the legendary.

After twenty-five years building products for everyone from large corporations to blockchain startups, I've watched the definition of "defensible" evolve through several cycles. Network effects dominated the 2010s. Scale economies ruled enterprise.

But something fundamentally different is emerging now.

The products that will win the next decade aren't the ones with the most users or the most data—they're the ones that actually understand each user deeply enough to anticipate what they need before they ask.

This isn't personalization as we've known it. It's cognition, and it compounds in ways that make traditional moats look fragile by comparison.

Traditionally, personalization meant tracking clicks and A/B testing button colors. The implicit assumption was that user data was inventory to be monetized elsewhere—package up the behavioral signals, sell them to ad networks, treat attention as remainder inventory for the highest bidder.

That model extracts value from users rather than creating it for them. The cognitive approach inverts this completely.

White glove treatment for everyone, at scale.

When you attend to what users actually need instead of strip-mining their preferences for third parties, their lifetime value grows because their enjoyment grows. The relationship compounds rather than depletes.

Anyone who's worked a trade show understands this instinctively. You're there with hundreds of people walking by your booth, and the temptation is to optimize for badge scans and lead volume.

But the veterans know the truth: success isn't measured by the crowd. You're really there for one or two decision makers you identified before you even booked the flight. The rest is keeping up appearances.

Most software treats users the way amateurs work trade shows: scattershot, volume-obsessed, celebrating vanity metrics while missing the relationships that drive real outcomes. Cognitive products flip this—they focus effort on understanding each user as if they're the decision maker you flew across the country to meet.

What makes cognitive effects structurally different from network effects is where the compounding happens.

Network effects scale externally—more users make the product more valuable for everyone. Cognitive effects scale internally—more interactions make the product more valuable for you specifically.

Think about how streaming services compete: they sell access to hundreds of channels and massive catalogs, as if abundance itself were the value proposition. But my time is finite. I have two hours tonight, and the three shows I'll actually watch this week matter infinitely more than the five hundred options I'll never touch.

A service that understands I want something light on Tuesday nights, something dense on weekends, something familiar when I'm stressed—that's compounding value in ways that library size never could.

Depth of understanding creates switching costs that no competitor can shortcut by simply adding more content.

The business model alignment matters as much as the technology. Users aren't rejecting personalization when they opt out of tracking—they're rejecting misaligned incentives where their data enriches advertisers rather than their own experience.

The subscription and privacy-first models we've seen succeed create a different contract: the system learns about you, uses that understanding to serve you better, and earns trust by keeping that knowledge secure.

Every interaction sharpens the intelligence. Better predictions drive retention. Retention creates richer data. Richer data improves predictions. This virtuous cycle accelerates value per user without requiring external growth.

The moat deepens with time, not just with scale.

For those of us who've spent careers watching scale-dependent businesses struggle to maintain defensibility, that's a profound shift worth building toward. How this all manifests is the work we all have to do.

As we step into 2026, it's worth reflecting on the incredible journey of 2025. This year wasn't just about running product on software teams—it was about writing a butt load of code enhanced by AI intelligence. The numbers tell a story of consistent effort, growing engagement, and the unknown as the content I've prepared for agents gets consumed en masse.

GitHub: A Year of Consistent Contributions

The GitHub heatmaps above represent a tremendous amount of development I've done in a number of different technologies. From the traditional web client/server dev I've been doing for decades, to more native iOS (Swift) and Android (Java) development. Phone apps, VR apps, custom circuit board driven products, a crypto encryption protocol and a crap load of funky new stuff on the edge with all types of the latest models and fine tuning.

Website Analytics: Growing Engagement

The world seemed to come knock on my door this year. It might just be Chinese or Singaporan opportunists creating a Joey robot based on all of my personal and professional preferences. This site is all me and the things I love.

Search Performance: Discoverability Through Tools

Search Console metrics reveal how janisheck.com appears in Google's ecosystem. Impressions, clicks, and position tracking show the site's growing authority on topics ranging from AI assistants to 3D printing workflows. I've got this site especially curated and optimized for Google's desire to slurp up content in the format they want. I feel good about how this does.

LinkedIn: Professional Network Growth (With Caveats)

LinkedIn showed impressive numbers in 2025: a 20% growth in connections and nearly 40,000 content impressions. The follower graph tells an interesting story—a dramatic spike around September when certain posts hit the algorithm just right, followed by steady growth through year-end. The impression numbers climbed consistently throughout the year, proving that regular, authentic sharing still resonates with professional audiences.

But here's the reality check: LinkedIn has increasingly become a pay-to-play platform. Want real traction on your posts? You'll likely need to boost them. I get it—platforms need to monetize, and LinkedIn has bills to pay. But it's still a bit of a bummer watching organic reach diminish year after year. The algorithm favors engagement bait and sponsored content, making it harder for thoughtful technical posts to break through without opening the wallet.

MCP Breakthrough: Connecting AI Agents to Knowledge

The Model Context Protocol implementation represents 2025's most significant achievement. By creating not one but three different MCP server architectures—a Netlify Function implementation, an NLWeb-MCP hybrid, and a legacy Next.js API route—janisheck.com became one of the first personal websites that AI assistants like Claude can actually query and understand.

The stats aren't the best since I'm not wrapping the requests through some third party analytics or anything extra I've built. I am leveraging what Netlify has available and its limited to 30 days of data. What is interesting is how 120K requests have been made in December/early January and thats a ton since these requests are can be so rich and deep.

The Year Ahead: Building on Foundations

Looking forward to 2026, the foundation laid in 2025 opens up incredible possibilities.

Midjourney's videos have the same starting and ending frame, creating perfect seamless loops. Sora 2 doesn't allow that constraint, but they do have a MAGIC/ENHANCE button that transforms your simple prompt into a full cinematic shoot script. Not sure I'm wild about it, but it does let you expand beyond just boring loops.

The Spaceman

Underwater

Desert

Seaside

Sora 2's MAGIC/ENHANCE Prompt Expansion

Example of how Sora 2's MAGIC/ENHANCE button transforms a simple prompt into a full cinematic shoot script

LAX: Meeting Erick Sermon

My first encounter happened at Los Angeles International Airport while waiting for my flight to Japan. I spotted Erick Sermon—one half of the legendary hip-hop duo EPMD and a producer whose beats had shaped the sound of East Coast rap.

I worked up the nerve to approach him. He was kind, gracious with his time, and agreed to a photo. The interaction was brief but memorable. What wasn't memorable—in a good way—was the photo itself.

AI-enhanced version - still challenging

Original 320x240 photo - horribly backlit

Osaka: Elvis Costello in the Customs Line

The second encounter happened on the other side of the Pacific, in the customs line at Osaka airport. Standing ahead of me was Elvis Costello.

Elvis Costello in 1996 had just released "All This Useless Beauty" and was touring with The Attractions—their final tour together, as it turned out. The band was falling apart, with tensions between Costello and bassist Bruce Thomas reaching a breaking point. Their last US show had been in Seattle that September before wrapping up with final performances in Japan. I was witnessing the tail end of an era in rock history, standing in a customs line.

He was fascinated by my camera. The Casio QV-10 was brand new to the market, and he'd never seen anything like it. The fact that you could see the photo on a screen immediately after taking it—that was genuinely novel in 1996. He mentioned he'd never taken a digital photo like that before.

There's something special about that moment. Here was one of the most important songwriters of his generation, someone who'd been shaping music since the punk era, genuinely intrigued by this little gadget I was carrying. For a brief moment, I had something that impressed Elvis Costello.

AI-enhanced version - turned out great

Original 320x240 photo from Osaka customs

The Camera That Started It All

The Casio QV-10 was revolutionary. Released in 1995, it was the first consumer digital camera with a built-in LCD screen. Before this, digital cameras were essentially blind—you took a photo and hoped for the best. The QV-10 changed everything. It had a 1.8-inch TFT LCD that let you see what you were shooting in real-time.

Even more innovative was its swivel lens. The camera body could rotate 270 degrees relative to the lens, meaning you could flip the screen toward yourself and take a selfie while actually seeing yourself on screen. In 1996, this was mind-blowing. It was literally the first time anyone could do that with a digital camera.

The trade-off? Resolution. The QV-10 captured images at 320x240 pixels—about 0.07 megapixels. To put that in perspective, the phone in your pocket right now probably shoots at 12 megapixels or more. My revolutionary camera captured images that would be a tiny thumbnail on today's screens.

The Casio QV-10—the little camera that started a revolution.

I wanted to try something different with my automotive history. Instead of digging through old photos or relying on memory, I used Google's Nano Banana 2 with a unique prompt that creates stunning product photography-style images: cars floating inside transparent capsules, suspended in zero gravity like museum pieces.

Here's the base prompt structure I used:

"Create a hyper-realistic, stylish poster 1080x1080 aspect ratio featuring a horizontal tablet-capsule hovering above a surface covered in condensation and water droplets, with its shadow cast on the wet ground. One side of the capsule is transparent glass, while the other is glossy colored plastic featuring the [BRAND] logo and [MODEL] name. Seamlessly floating inside the glass portion of the capsule is a photorealistic 3D model of a [CAR], perfectly centered and suspended in zero gravity. The glass and plastic surfaces showcase strong reflections, refractions, and environmental distortions. The background is a softly blurred, elegant light-toned setting. Use a dynamic perspective with a stylish camera angle, professional studio lighting, and ultra-high detail to make the image look like a DSLR-captured photograph with impeccable realism."

The Collection

Plymouth Duster

Volkswagen Super Beetle

Ford Probe

Mercury LN7

Ford Festiva

Mitsubishi Eclipse

Ford Focus

Ford F-150

Ford Expedition

Tesla Model 3

Tesla Model Y

Tesla Cybertruck

Why This Works

The capsule format does something interesting - it elevates each vehicle into art. By removing them from their normal context (roads, driveways, parking lots) and presenting them as floating museum pieces, you see them differently. The Plymouth Duster isn't just an old muscle car, it's a preserved artifact from automotive history. The Cybertruck isn't just polarizing design, it's a statement piece from the future.

The technical execution is impressive too. The reflections on the glass, the refractions through the curved surfaces, the realistic shadows on the wet ground below - all of these details add up to images that feel premium and polished. Each one could be official promotional material.

Try It Yourself

If you have access to Google's Nano Banana 2, give this capsule prompt a try with your own automotive history. Or any collection really - watches, phones, guitars, cameras. The capsule format works beautifully for showcasing objects as premium collectibles. Just swap in your subject and brand details, and see what you get.

Time Magazine just named "The Architects of AI" as their 2025 Person of the Year. A bold choice for a transformative technology that's reshaping how we work, create, and think. The recognition is deserved—these are the architects of a revolution.

But then I saw the cover art.

The Disappointment

My first reaction? This looks like bad Terrance and Phillip South Park design cutouts. Flat. Lifeless. Like someone took professional headshots, ran them through a basic compositing tool, and called it a day. These are the leaders who've built the most powerful creative technology in human history, and Time gave them a cover that looks like it was assembled in PowerPoint.

The concept had potential—echoing the iconic "Lunch atop a Skyscraper" photo from 1932, with tech leaders perched on a beam above the city. It's a powerful visual metaphor: modern innovators building the future, literally sitting on top of the world they're creating.

But the execution? It felt phoned in. Low effort. The kind of thing you produce when you understand the assignment but don't truly grasp the tool.

Twenty Seconds Later

So I fired up an AI image generator and spent twenty seconds crafting a prompt. Not twenty minutes. Not twenty hours. Twenty seconds.

Look at that. The lighting is cohesive. The perspective makes sense. The figures look like they actually belong in the scene rather than being pasted on top of it. It's not perfect—no AI generation is—but it's immediately more compelling than what one of the world's most prestigious magazines managed to produce.

And here's the kicker: this took me less time than it would to order a coffee.

The Art of the Prompt

Here's what Time Magazine—and honestly, most people—don't fully realize yet: AI image generation isn't about pushing a button and getting magic. It's still an artistic endeavor. The difference is that we've exchanged our mouse for words to drive the design.

A bad prompt gets you bad results. A generic prompt gets you generic results. But a thoughtful prompt—one that considers composition, lighting, mood, style, and context—can produce something remarkable. The skill isn't gone. It's just transformed.

When I crafted that prompt, I thought about:

• The photographic style of the 1932 original—documentary realism with atmospheric depth
• Natural integration of subjects into the scene—no harsh cutout edges
• Atmospheric perspective—depth and distance matter
• Body language—casual but confident, like the original construction workers
• Historical weight—making it feel like a moment that matters

Those considerations don't happen by accident. They're the result of understanding both the medium and the message. And that's exactly what feels missing from Time's execution.

The Irony

There's something deeply ironic about a major publication celebrating AI leadership with art that suggests they don't fully grasp the technology they're honoring. It's like writing an article about the future of space travel while still drawing rockets with crayons.

These AI leaders—Sam Altman, Demis Hassabis, Jensen Huang, Dario Amodei, and the others—have created tools that are democratizing creativity at an unprecedented scale. Anyone with access to these tools can now produce professional-grade visual content. The barrier to entry isn't gone, but it's dramatically lower. What matters now is vision and skill in articulation.

Time had access to the same tools. Probably better ones. Certainly a bigger budget. And yet they produced something that looks like a first draft while celebrating the final frontier.

Better Prompts, Better Results

The real lesson here isn't that AI makes everything easy. It's that AI makes skill more visible. A photographer with decades of experience will get dramatically different results from the same AI tool than a novice because they understand composition, lighting, and storytelling. The tool amplifies expertise—it doesn't replace it.

When I see that Time cover, I don't see a limitation of the technology. I see a limitation of execution. Someone made choices—about composition, about process, about effort—and those choices resulted in something that undersells both the subject and the medium.

We're at a weird inflection point in creative technology. For the first time in history, the tools of professional creation are accessible to everyone. But mastery still matters. Understanding still matters. Care still matters.

The mouse hasn't disappeared. It's just become a keyboard. And the artists who learn to write compelling prompts will be the ones who produce compelling work.

The Future Is Here

Time Magazine was right to recognize AI leaders as the people of the year. They've fundamentally changed how we interact with technology and creativity. But the cover should have demonstrated that power, not just acknowledged it.

Twenty seconds. That's all it took to show what's possible when you understand both the tool and the craft. Imagine what these publications could produce if they leaned into these capabilities with real intention.

The future of creative work isn't about AI replacing human creativity. It's about human creativity learning to speak a new language. And like any language, fluency requires practice, thought, and care.

Time celebrated the architects of this revolution. They just forgot to use their blueprints.

There's a moment in Total Recall where Arnold Schwarzenegger's character questions whether his memories are real or implanted. It's a concept that felt like pure science fiction in 1990. In 2025, we're living it—and we're doing it to ourselves.

Here's the thing about memories: we don't actually remember moments. We remember the last time we remembered them. Each recall is a reconstruction, and over time, our brains fill in gaps with whatever feels right. Now add photo libraries into the mix. We look at photos to reinforce our memories, and those images become the source of truth. The photo becomes the memory.

So what happens when we change the photo?

The Pont des Arts

For years, couples would travel to Paris and attach padlocks to the Pont des Arts bridge as a symbol of everlasting love. You'd write your names on a lock, attach it to the bridge, and throw the key into the Seine. Thousands of locks accumulated over the years, the combined weight eventually becoming a structural concern.

I was no different. I wanted to do something special—something a little more personal than a Sharpie scrawl on brass. I had access to a laser cutter at work, and I had an idea: engrave a photo of Melissa and me onto the lock itself.

The Original

This is the photo I chose. Us together. Happy. The kind of moment you want to preserve forever.

The problem with laser engraving photos onto small brass surfaces is that the medium doesn't forgive poor source material or optimistic expectations. The result was... not great. You could tell there were two people on the lock, but just barely. The faces were ghostly, the details lost to the limitations of the process.

But I'd committed. I traveled to Paris, found my spot on the bridge among thousands of other locks, and clicked it into place. Forever. Or so I thought.

Less than a month later, the city of Paris removed all the locks and installed glass panels to prevent new ones from being added. Our lock—along with an estimated million others—was cut away and recycled. The moment was gone before it had a chance to age.

The Revision

I was always disappointed with how that lock looked. The gesture was there, but the execution fell short. So recently, I did something that would have been impossible just a few years ago: I used AI to realize a better version.

Same lock. Same photo. Same moment. But now the engraving is crisp. The faces are clear. It looks like what I imagined it would look like when I first had the idea. This is the lock I wanted to leave in Paris.

I saved it to my photo library. Right there alongside the original.

Which Memory Wins?

Here's where it gets uncomfortable. Five years from now, when I'm scrolling through old photos, which image will I pause on? The grainy, disappointing reality? Or the polished version that matches what I felt in that moment?

Our brains prefer coherent narratives. We naturally gravitate toward the version of events that makes sense, that feels complete. The AI-enhanced photo isn't a lie exactly—the moment happened, the lock existed, we were there. But it's also not the truth. It's a truth I preferred.

And that's the thing about AI and memory now. The tools make it so easy to make subtle tweaks. Not wholesale fabrications—just improvements. A clearer sky. A better smile. A sharper engraving. Each change is small enough to feel innocent, but they compound. The source material drifts from reality, and we don't notice because we're not comparing anymore. We're just remembering.

In the future, it will be harder and harder to know what the original source material even was. Did that sunset really look like that? Was I actually smiling in that photo? Did the lock on the bridge in Paris really show our faces so clearly?

Maybe it doesn't matter. Maybe all memories are constructs anyway, and the photos we keep are just props for the stories we tell ourselves. But there's something unsettling about having the power to edit those props so seamlessly. We're not just remembering anymore. We're directing.

Welcome to Total Recall territory. The question isn't whether our memories are real. The question is whether we'll remember that we changed them.

Long before EPCOT's World Showcase became the open-air promenade we know today, Imagineers planned something far more ambitious. Germany's pavilion was designed as a multi-level indoor environment, anchored by a full-scale dark boat ride—the Rhine River Cruise—a sweeping journey through the country's most iconic landscapes, castles, and storybook towns.

The attraction was fully blue-sketched, partially modeled, and even had its loading dock built. Yet the ride itself never opened. For decades, only fragments survived: Harper Goff's water-stained concept art, blurred model photographs, loose blueprint scans, and the occasional quote from EPCOT's original design documents.

Well documented here: https://www.carouselofchaos.com/epcot-rhine-river-cruise/

This project set out to solve a simple problem: What would the Rhine River Cruise look like today if it had actually been built?

Reconstructing a Ride That Never Was

The process began with the most important pieces of evidence: the ride layout and the boat design. The original map shows a winding river course looping past Freiburg, the Black Forest, Heidelberg Castle, the Cologne Cathedral, the Lorelei cliffs, Neuschwanstein Castle, the Garmisch ski region, Pfalz Castle, and finally Koblenz.

Using this ride blueprint as the structural backbone, I produced a full set of designs—each one rebuilt from the perspective guests would have experienced while sitting inside the attraction's boats.

The Boat and Loading Dock

The boats were the heart of the ride—low, wide, multi-row vessels styled after river ferries along the Rhine. Disney actually built the loading area in the Germany pavilion, combining stonework, timber frames, and a medieval riverside aesthetic. My recreation captures this as a photorealistic nighttime scene, lit with lanterns and warm ambient glow—the tone-setting first moment guests never got to experience.

Neuschwanstein Castle

One of the most dramatic planned scenes was Neuschwanstein. Early models showed the castle positioned to create forced perspective as boats passed. My recreation uses crisp mountain lighting, accurate topography, and a cinematic nighttime palette.

Freiburg and the Black Forest

The attraction began in the quiet edges of the Black Forest before entering Freiburg. I translated Disney's rough sketches into a fully realized riverside village: dense pines, timber-frame architecture, the red sandstone arcades of Freiburg's Historisches Kaufhaus, and warm lamplight reflecting off dark water.

Garmisch Ski Slopes

One of the most surprising planned scenes was Bavaria's alpine resort region, complete with snow, chairlifts, and mountainous terrain. I recreated it as a dramatic nighttime tableau: glowing slopes, icy peaks, moving ski lift silhouettes, and chalets nestled among the pines—an unusual but spectacular moment of contrast for a water-based dark ride.

Designing From Archival Evidence

Rebuilding these scenes required cross-referencing blueprints, Harper Goff's concept mural, show model photos, 1978 EPCOT brochures, and scene lists from early Imagineering notes. Where detail was missing, I reconstructed according to architectural accuracy, geographic authenticity, Disney-era lighting design, and expected show readability from a slow-moving boat.

Why Recreate a Cancelled Attraction?

The Rhine River Cruise has always been one of EPCOT's most intriguing "ghost attractions"—sitting in that rare space where themed entertainment history meets unrealized potential. With today's rendering tools and generative design workflows, it's finally possible to bring these lost experiences to life as vivid, believable environments rather than blurry sketches and rumors.

These recreations show how ambitious the original EPCOT plans truly were, how strong Germany's thematic identity could have been, and how the Rhine River Cruise would have felt as a real, living attraction. Most importantly, they give fans and historians a window into a ride that deserved far more than a footnote.

Update Video

What if I took a ride on one of these boats? Maybe it looks something like this:

What if a political campaign could run itself? Not the strategy or the handshakes, but the relentless daily grind of content creation, social media posting, and website updates. I built a system that does exactly that—a fully automated campaign platform that crawls news, generates on-brand responses, creates images, and posts to social media, all without human intervention.

The proof of concept? Theodore Roosevelt running for President in 2028.

And here's the kicker: This automated campaign is already better than 95% of real campaign websites.

The Campaign Website Problem

Most campaign websites follow a predictable death spiral:

• Day 1: Launch with excitement. Fresh design. Bio page. Donation form. A single blog post announcing candidacy.
• Week 1: Campaign manager promises "we'll post weekly updates."
• Month 1: Last blog post was 3 weeks ago. News section shows press release from launch day.
• Month 3: Website becomes a static brochure. Volunteer signup form goes unchecked. Social media feeds embedded on homepage show tweets from May.
• Election Day: Site still says "Join us at the Labor Day parade!"

Why? Because campaigns have no time for website updates. Staff are doing voter contact, fundraising calls, event logistics, and crisis management. Writing blog posts ranks somewhere below "organize the supply closet."

Meanwhile, this fully automated campaign updates itself every single day at 2pm with zero human intervention.

What the Platform Actually Does

The system operates as a complete content pipeline:

• News Crawling - Every day at 2pm, the system crawls Politico for breaking political news
• Story Selection - AI agents analyze and rank stories by relevance to the campaign's platform
• Content Generation - Multiple AI agents collaborate to write responses in the candidate's voice
• Image Creation - AI generates photorealistic campaign images tailored to each story's location
• Social Distribution - Content posts automatically to Twitter/X and Bluesky
• Website Updates - The campaign website pulls fresh content dynamically from Firebase—no rebuild needed

Check the live campaign: electteddy.netlify.app

Daily automated posts on Twitter/X

Cross-posted to Bluesky

The Multi-Agent Architecture

This isn't a single AI doing everything. It's a coordinated team of specialized agents:

The Curator Agent analyzes incoming news articles and scores them based on:

• Relevance to the campaign platform
• Timeliness and news cycle position
• Potential for meaningful candidate response
• Geographic and demographic reach

The Content Generator takes the selected story and produces:

• A full article written in the candidate's historical voice and policy positions
• Social media posts optimized for each platform's character limits and culture
• Hashtags and engagement hooks

The Image Director creates visual prompts that:

• Place the candidate in location-specific settings from the story
• Rotate through 5 different campaign scenarios (rallies, factory visits, diner stops, walking tours, community meetings)
• Maintain consistent candidate appearance while varying composition

The Distribution Coordinator handles:

• Platform-specific formatting
• Optimal posting times
• Duplicate detection to prevent repeat content
• Error recovery and fallback handling

How the Website Actually Works

Here's where it gets interesting. Traditional campaign websites require rebuilding and redeploying whenever content changes. This platform eliminates that entirely.

The website is a static shell that loads all content dynamically from Firebase:

• Homepage shows the latest 3 news articles
• News and Press sections query Firestore in real-time
• Individual articles load by URL slug
• A browser refresh shows new content instantly—no build, no deploy, no waiting

When the pipeline generates a new article at 2pm, it's immediately visible on the website. The Netlify redirects route any /news/* URL to a template page that fetches the right content from Firebase based on the slug.

This is the fundamental difference between a static campaign site frozen in time and a living, breathing campaign presence.

Why 95% of Campaigns Can't Do This

Real campaigns struggle with website updates for three reasons:

1. Technical Bottleneck - Most campaign websites are WordPress or SquareSpace. Adding content means logging into an admin panel, formatting in WYSIWYG editors, uploading images, and clicking publish. Then waiting for cache clearing. If the site is Jamstack (like most modern political sites), every update requires a rebuild and redeploy—10 to 30 minutes of waiting.

2. Human Bottleneck - Who actually writes the content? The candidate? Too busy. Campaign manager? Drowning in logistics. Communications director? Maybe, if they're not handling a crisis. Volunteer? Quality control nightmare. By the time someone writes, edits, gets approval, and publishes, the news cycle has moved on.

3. Strategy Bottleneck - What should the campaign say about breaking news? That requires candidate input, policy team review, and political calculus. By the time consensus is reached, it's tomorrow.

This automated system eliminates all three bottlenecks:

• Technical: Firebase dynamic content = instant updates
• Human: AI generates content in candidate's voice = zero staff time
• Strategy: AI trained on candidate's platform = consistent message discipline

Duplicate Detection: Never Repeating Itself

One critical feature: the system never posts the same story twice. Before selecting a story, the pipeline:

• Checks if the URL has already been processed
• Compares titles for similarity (>50% word overlap = duplicate)
• Maintains a 24-hour rolling window for recent content

This prevents the embarrassing situation of a campaign account posting the same take four times in one day—something human-run social media accounts do constantly.

Image Variety: Solving the Repetition Problem

Early versions had a problem—every image looked the same. Teddy Roosevelt pointing at a crowd, sleeves rolled up, over and over.

The fix was constraining the AI's creativity in the right places. Now the system randomly selects from 5 distinct scenario templates:

• Outdoor Rally - Speaking from a platform, khaki field jacket
• Factory Visit - Hard hat, shaking hands with workers
• Community Center - Sitting in a circle with families
• Walking Tour - Strolling main street with locals
• Diner Stop - At the counter with coffee, chatting with patrons

The AI can only fill in location details—it can't override the scenario. This creates genuine visual variety while maintaining brand consistency.

The Tech Stack

• Firebase Functions - Serverless compute for all pipeline stages
• Firestore - Real-time database for content storage and state management
• OpenAI GPT-4 - Content generation and story analysis
• Google Gemini - Secondary AI for prompt engineering
• Fal.ai (Imagen 4) - Photorealistic image generation
• Twitter API v2 - Social posting with media upload
• Bluesky AT Protocol - Decentralized social posting
• Netlify - Static site hosting with dynamic content loading

What a Real Campaign Could Do With This

This isn't just a tech demo. A real campaign could deploy this platform and:

Save 20+ hours per week on content creation. No more morning meetings about "what should we post today?"

Respond to news in minutes, not hours. The pipeline can run on any schedule—hourly during breaking news cycles if needed.

Maintain perfect message discipline. The AI is trained on the candidate's positions, voice, and policy platform. Every piece of content stays on-brand.

Scale across platforms effortlessly. Add Instagram, Threads, LinkedIn—each just needs an API integration and platform-specific formatting rules.

Never miss a geographic moment. Story about flooding in Iowa? The system generates an Iowa-specific image and response automatically.

Free up staff for high-value work. Let humans do strategy, fundraising, and voter contact. Let AI handle the content treadmill.

Try It Yourself

The Roosevelt 2028 campaign runs live at electteddy.netlify.app. Check the news section—everything you see was generated and posted automatically.

Follow the campaign on social media:

• Twitter/X: @ElectTeddy
• Bluesky: @electteddy.bsky.social

The codebase demonstrates that a fully automated campaign presence isn't science fiction. It's a Firebase project, a few API keys, and some well-orchestrated AI agents.

The future of political communication isn't humans versus AI. It's humans with AI, doing more with less, reaching more voters, and responding faster than ever before.

Bully!

Let's get the negative out of the way. This model costs $0.15 per use. 5x what Nano Banana v1 cost. Is it 5x better? No, and of course the cost will come down soon enough.

I took those same colorized portraits and asked Gemini 3 to create modern selfies with these historical icons. The results? Shockingly good. Like, unnervingly good.

Abe Lincoln

Ella Fitzgerald

Mark Twain

Dolly Parton

William Hurley

Frances Owens Thompson

These aren't just composites - Gemini 3 understood the lighting, perspective, and even the personality of each figure. Mark Twain looks like he's about to crack a joke. Dolly's got that signature warmth. Bill Hurley still looks like the most interesting guy at the bar.

The technology leap from the original Gemini models to this is massive. We're not talking about marginal improvements - this is a different category of capability.

What's fascinating is how natural these feel. There's no uncanny valley weirdness, no obvious AI tells. Just... selfies with people who've been dead for decades (or centuries).

Now my own face looks a little different but I didn't properly train the model on a ton of versions of my face. Just one blurry photo of me. And to boot it was an AI version of me to start with.

Time travel keeps getting easier.

Trust In Dak

The critics will always talk. "He can't win the big games." "He folds under pressure." "He's not worth the contract."

But nights like this - rallying from 21 points down against a division rival - these are the games that define a quarterback's legacy.

Trust in Dak. Because when the game is on the line, he delivers.

How 'bout them Cowboys. 🌟

Robert Cornelius 1839

Robert Cornelius 2025

Robert Cornelius Forever

Here is a classic Lincoln photograph. We only have like 5 or 6 of them. And the middle step where someone used a computer 20 years ago to paint color him in. Glaring and kind of clownish coloring. The third photo I did for $0.03 this afternoon. Better than any photo we've seen in a text book in 150 years.

Abraham Lincoln Tryptch

Old black and white photographs feel distant. Using AI colorization, I've transformed iconic portraits into full-color images that make history feel immediate and real. Tell me that Bill Hurley photo isn't a bad ass dude you'd want to hang out with. Amazing portrait.

And if you really want to bake your noodle, I changed up every pixel in each of these photos from the originals. Are they derivative enough? Do I own the copyright on the Basquiat that Richard Avedon took 40 years ago now? The idea of art and originality and remixing is turned on its head. I would think that Basquiat would love this uncertain time, and Avedon would hate it.

John Quincy Adams 1840

Abraham Lincoln 1863

Charles Darwin 1874

Mark Twain 1907

Pablo Picasso 1908

William Hurley 1909

Charlie Chaplin 1921

Al Capone 1932

Frances Owens Thompson 1936

Dwight Eisenhower 1946

Ella Fitzgerald 1946

Marlene Dietrich 1951

Albert Einstein 1951

Martin Luther King Jr. 1962

Dolly Parton 1977

Jean-Michel Basquiat 1984

And before you say, "wasn't the Wizard of Oz in color back in 1939?". Yeah, but not everyone uses color for their photos. Both for budget and artistic reasons. My whole goal was to show how easy it is to take all of those old black and white photos, you've got in the attic, and give them a little more life, connection and resonance.

The Prompt

Ultra-realistic recreation of an old vintage photo, keeping the same original face (100% likeness). Transform into a modern high-quality digital portrait with vibrant updated colors, smooth realistic skin textures, and natural lighting. The background should be blurred and not in focus while preserving the authenticity of the original pose and expression. Very clear and focused lens.

History wasn't black and white. It was always in color.

Portrait of the Blogger As A Young Man

The most revolutionary aspect of prediction markets isn't how we consume content—it's how publishers create it. For the first time in media history, small publishers can prove demand for their content before they write it, get paid before they scale, and literally trade on their own future. This isn't an iteration on existing models. It's an inversion.

The End of "Audience First, Revenue Later"

Every media entrepreneur knows the brutal math: spend 18 months building audience, pray for monetization later. Whether it's Substack, YouTube, or TikTok, the formula has been consistent—give away your best work, hope the audience arrives, then figure out how to pay rent.

Prediction markets break this model entirely.

When a publisher floats their next article idea, the market immediately prices it. A surge in prediction volume isn't just validation—it's working capital. Publishers can now say: "My article on AI consciousness has $50K in prediction volume before I've written a word." That's not speculative value. That's pre-publication market signal stronger than any focus group.

The implications are staggering. A food blogger in Iowa doesn't need to compete with Bon Appétit's distribution. They need to create content that generates prediction interest. If their "Best Des Moines Tacos" piece attracts prediction volume from locals who know it'll go viral, they've already won—before publishing.

Small Publishers, Big Signals

Here's what changes when publishers can prove demand through prediction markets:

Instant Price Discovery: Instead of guessing what readers want, publishers see exactly what content commands market premium. That investigative piece you're considering? If prediction volume is anemic, kill it. The personal essay about your grandmother? If predictions are surging, expand it into a series.

Pre-Publication Monetization: Publishers earn from prediction market fees before articles publish. This isn't ad revenue hoping for clicks—it's readers literally investing in content creation. The market pays you to write what it predicts will matter.

Risk Mitigation Through Hedging: Smart publishers can bet against their own content as insurance. Spending a month on an investigation? Hedge with a position that pays out if it underperforms. You've just invented publisher portfolio theory.

But the real power move? Publishers becoming market makers in their own content.

Publishers as Traders

The sophisticated play isn't just creating content—it's trading around it. Publishers have inside information (they know what they're about to publish), perfect timing control (they choose when to release), and narrative influence (they can steer the story).

Consider this scenario: A crypto newsletter sees their article predictions trading at 5-1 odds for hitting 100K views. They know they've got bombshell news that guarantees 200K+. They can:

• Buy positions before announcing the topic
• Sell into strength as hype builds
• Short competing publishers covering the same story
• Create derivative content based on market signals

This isn't manipulation—it's publishers finally capturing the value they create. When Bloomberg moves markets with headlines, Bloomberg doesn't get to trade. When your newsletter moves prediction markets, you do.

The New Publishing Playbook

The playbook completely inverts:

Old Model: Create content → Build audience → Find sponsors → Hope for profit

New Model: Float ideas → Prove market demand → Get paid from predictions → Publish to profitable audience

This changes who can be a publisher. You don't need runway for 18 months of free content. You need one good idea that the market believes in. A PhD student with breakthrough research can monetize immediately if the market predicts virality. A local reporter with a corruption scoop sees instant value validation.

The Dark Side of Inversion

This power inversion isn't all upside. When publishers trade their own futures, several dystopias emerge:

Prediction Optimization Over Truth: Publishers might chase what markets predict will succeed rather than what matters. Imagine newsrooms where editorial meetings are just reading prediction odds.

Market Manipulation Temptation: If you can make $10K by publishing your article Tuesday instead of Monday to hit better prediction windows, do you do it? What about withholding news for better odds?

The Rich Get Richer: Established publishers with proven prediction track records attract more volume, creating winner-take-all dynamics. The market trusts The Atlantic's predictions more than yours.

What Actually Dies

When publishers can prove demand pre-publication, several sacred cows die:

The Patron Model: Why seek foundation funding when markets fund you?

The Pivot: No more desperate format changes seeking audience. The market tells you exactly what it wants.

The Editorial Guess: Editors' hunches are replaced by market signals.

The Geographic Monopoly: Local news isn't limited to local revenue when global markets can bet on regional content.

The Endgame

In five years, floating content in prediction markets before creation becomes standard. Publishers who don't do this will seem like restaurants that don't take reservations—technically possible, but economically irrational.

The real tell? When the New York Times acquires a prediction market company, not for the gambling revenue, but for the pre-publication demand signal. When that happens, the inversion is complete.

Small publishers, this is your moment. You don't need audience scale. You don't need venture funding. You don't need to work for free. You need ideas the market believes in, and for the first time in media history, you can prove that belief before you type the first word.

The question isn't whether you'll participate in this new model. It's whether you'll be the publisher trading your future, or the one being traded by others.

Welcome to the inversion.

Create a stylish poster 3:4 aspect ratio featuring a miniature 3D model of NEW YORK CITY, showcasing its key landmarks, bursting through a torn, horizontally laid-out physical world map, seamlessly integrated into the design. A white sleek 3D rendering of the city’s name NEW YORK CITY, blends organically into the landscape.

Looks great.

The Collection

Austin, Texas

Bad Windsheim, Germany

Bentonville, Arkansas

Disney World, Florida

El Paso, Texas

Marblehead, Ohio

New York City, New York

Osaka, Japan

Paris, France

Vancouver, Canada

For years, I've been building AI-powered features—chatbots, virtual assistants, automation workflows. But something always felt like it was missing. These tools could talk to users, but they couldn't really talk to each other or access structured knowledge from websites in any meaningful way. That all changed when I implemented the Model Context Protocol (MCP) on janisheck.com.

MCP is an open protocol that allows AI assistants like Claude Desktop to connect directly to web services and access their resources and tools. Think of it as an API specifically designed for AI agents to discover, understand, and interact with external data sources. Instead of scraping web pages or relying on human intermediaries to copy-paste information, AI assistants can now query my blog content, search through 25 years of posts, and pull relevant information—all through a standardized protocol.

Click here for quick MCP DOCS

Three Implementations, One Goal

I implemented MCP on this site in three different ways, each serving a specific purpose:

Primary MCP Server (Netlify Function)

The production endpoint at janisheck.com/mcp runs on Netlify as a serverless function using the official MCP SDK v1.11.0. It implements JSON-RPC 2.0, supports server-sent events for streaming responses, and includes comprehensive error handling with zod validation. This is the main endpoint AI assistants connect to when they want to access my blog content.

NLWeb-MCP Hybrid

The /nlweb-mcp endpoint combines MCP protocol with natural language query capabilities. It maintains backward compatibility with standard MCP clients while adding support for more conversational query modes. This hybrid approach lets AI assistants ask questions like "summarize recent posts about automation" instead of just structured searches.

Legacy Testing Implementation

I also maintain a hand-rolled MCP implementation at /api/mcp using Next.js API routes. This serves as a testing ground for experimental features and helps me understand the protocol internals without the abstraction of the official SDK.

What AI Assistants Can Actually Do

When an AI assistant connects to my MCP server, it gains access to two key capabilities:

Resources

Every blog post on this site is exposed as a resource using the blog://{filename} URI format. AI assistants can list all available posts, read specific posts, and access their full content including metadata, tags, and summaries. This gives them the same level of access to my blog content that a developer would have through a traditional API.

Tools

The searchBlog tool enables intelligent searching across all posts using weighted scoring. Titles are weighted 3x, tags 2x, and content 1x, so search results prioritize the most relevant matches. An AI assistant can search for "kubernetes automation workflows" and get back ranked results based on how well each post matches across those three dimensions.

Why This Matters for AI-to-AI Collaboration

The real power of MCP becomes clear when you think about AI agents researching topics across multiple sources. Imagine an AI assistant trying to help a user understand my approach to building automation workflows. Without MCP, that assistant would need to:

• Scrape web pages and hope the HTML structure stays consistent
• Parse unstructured content without metadata or context
• Guess at relationships between posts based on surface-level text analysis
• Miss out on structured data like tags, dates, and categories

With MCP, that same assistant can:

• Discover exactly what resources and tools are available through standardized operations
• Search intelligently using the searchBlog tool with weighted scoring
• Access full post metadata including tags, summaries, and publication dates
• Understand relationships between posts through structured tag systems
• Retrieve content in a predictable, documented format

This transforms AI assistants from passive web scrapers into active research collaborators. They can explore my knowledge base the same way another developer would use a well-documented API.

Real-World Example: Claude Desktop Integration

I connected Claude Desktop to my MCP server using a lightweight Node.js bridge script that translates between Claude's stdio interface and my HTTP-based MCP endpoint. The setup is simple—add a few lines to Claude Desktop's config file, restart the app, and suddenly Claude can access every blog post I've ever written.

Here's a real example that shows the power of this integration. Someone asked Claude Desktop:

"Check out the MCP server on Janisheck.com and tell me if we should hire Joey as our CTO in our crypto startup? Can he grow teams? Is he afraid or challenged by new tech? Has he worked on any big projects?"

Claude didn't just give a generic answer. It searched my blog, pulled relevant posts about my experience at Darkblock (multichain content-rights protocol on five blockchains), Exhilent Mobile (grew team from zero to 10 people plus contracted professionals), and Algebraix Data (mobile crypto wallet), and synthesized a comprehensive hiring recommendation.

The response included specific details about:

• Team Building - How I grew Exhilent Mobile's development team and the testimonials about my leadership style ("He knows how to get more out of people than they even knew they had in themselves")
• Attitude Toward New Tech - Recent experiments with ComfyUI, Hunyuan 3D-2, FLUX, and Stable Diffusion, plus the quote: "He would never tell you that what you were trying to create wasn't possible"
• Crypto/Blockchain Experience - CTO role at Darkblock building on Ethereum, Solana, Polygon, Aptos, and NEAR, plus freelance work creating 12.8 million unique playable NFT art pieces on Solana
• Big Project Experience - Integration of 35 acquisitions through Verio's $5.5B exit, work for Disney, ESPN, Samsung, Under Armour, and delivering an AI media-analysis platform 200% more accurate than leading polling institutions

Claude concluded: "For a crypto startup that needs both technical chops and team-building skills, he's an excellent fit." This wasn't speculation—it was based on structured data pulled from blog posts, portfolio entries, and testimonials, all accessed through the MCP protocol.

This is what AI-to-AI collaboration looks like in practice. Instead of generic answers or hallucinations, you get research-backed insights synthesized from verified sources.

The Technical Implementation

The MCP server exposes four core operations:

• resources/list - Returns all available blog posts with metadata
• resources/read - Retrieves full content for a specific post using its URI
• tools/list - Advertises the searchBlog tool and its parameters
• tools/call - Executes searches with weighted scoring across title, tags, and content

All communication happens over JSON-RPC 2.0 with server-sent events for real-time streaming. The implementation uses zod schemas for runtime validation, ensuring that requests and responses always match the expected structure.

How to Connect Your AI Assistant

Want to try it yourself? Head over to the MCP documentation page for complete setup instructions. For Claude Desktop users, add this to your config file:

{
  "mcpServers": {
    "janisheckcom": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://www.janisheck.com/mcp"
      ]
    }
  }
}

Then restart Claude Desktop and try asking:

• "What blog posts are available on janisheck.com?"
• "Search Joey's blog for posts about AI and automation"
• "What has Joey written about MCP or AI agents?"

What's Next for AI Collaboration

This is just the beginning of AI-to-AI collaboration on janisheck.com. The MCP implementation gives AI assistants structured access to my blog content, but the same protocol could expose other resources—project portfolios, code repositories, documentation systems, or even real-time data streams.

I'm testing different AI assistants to see how they use the MCP tools, monitoring performance and error rates, and gathering feedback on what works and what doesn't. The goal is to make this site a first-class citizen in the world of AI agent research and collaboration.

The future of AI isn't just about humans talking to machines—it's about machines talking to each other on our behalf, sharing knowledge, and collaborating across distributed sources of truth. If you're building AI assistants or exploring ways for agents to collaborate across knowledge bases, I encourage you to connect to janisheck.com/mcp and see what's possible.

You can explore the full technical documentation, connection instructions, and interactive testing interface at janisheck.com/mcp-docs.

The Technology Behind Multi-View Reconstruction

Multi-view 3D reconstruction uses advanced computer vision algorithms to analyze orthographic views and reconstruct the three-dimensional geometry. Unlike traditional photogrammetry that requires dozens or hundreds of photos, these systems work with just four carefully aligned views.

The process involves several sophisticated steps:

• Feature detection and matching across views
• Depth estimation from silhouette boundaries
• Mesh generation and surface reconstruction
• Texture mapping and detail refinement

Real-World Example: The Galactus Vinyl Project

Recently, I discovered promotional images for a sold out, expensive Galactus Soft Vinyl Figure from 100% Soft. The manufacturer's website showed in their image previews of four views—front, back, left, and right.

Using multi-view reconstruction software, I transformed these promotional images into a fully printable 3D model. Here's the result:

The process took less than an hour. We are entering a whole new world.

Here is another Mondo Galactus collectible that I generated a model from based on 4 images. I'm not sure about the moustache. :)

How It Works

Using the Tool

• Drag and drop the screenshot.
• Wait about two minutes for processing.
• Download the generated workflow and import it into n8n.
• Add your own credentials and test.

Why It Matters

This saves hours of manual recreation when someone only shares an image. It provides a jump-start for building or learning from other creators' workflows without starting from scratch.

The tool is a practical bridge between visual inspiration and runnable automation—turning static screenshots into real, editable n8n projects.

A friend of mine shares every book she reads. I dug through her list and even used AI to analyze it. She’s a professional tastemaker—the kind of reader I once wanted to be: deeply literate, reading for love and insight. I’m jealous.

It made me pull together the books I’ve bought over the past decade. About 40 % are physical copies, 40 % are audiobooks, and the rest are Blinkist summaries I listen to while biking.

Only one is contemporary fiction. I adored Ready Player One, so of course I read Ready Player Two. Aside from Stephen Fry’s mythology audiobooks (highly recommended), everything else is geared toward sharpening my mind for business and tech.

I do pick up the occasional “get-rich bro” title, but rarely make it past ten pages—they’re awful.

Empire of AI

Karen Hao

2025

You Deserve to Be Rich

Rashad Bilal & Troy Millings

2025

Co-Intelligence

Ethan Mollick

2024

Read Write Own

Chris Dixon

2024

Supercommunicators

Charles Duhigg

2024

Right Thing, Right Now

Ryan Holiday

2024

The Everything Token

Steve Kaczynski & Scott Duke Kominers

2024

The Algebra of Wealth

Scott Galloway

2024

The Singularity Is Nearer

Ray Kurzweil

2024

Brave New Words

Salman Khan

2024

The Let Them Theory

Mel Robbins

2024

So Many Steves

Steve Martin & Adam Gopnik

2023

Going Infinite

Michael Lewis

2023

The Diary of a CEO

Steven Bartlett

2023

When the Clock Broke

John Ganz

2023

Start. Scale. Exit. Repeat.

Colin C. Campbell

2023

The AI-Driven Leader

Geoff Woods

2023

The Coming Wave

Mustafa Suleyman

2023

Dinner with the Rogue Archaeologists

Sam Kean

2023

Metaverse

Matthew Ball

2022

Build

Tony Fadell

2022

Proof of Stake

Vitalik Buterin & Nathan Schneider

2022

The Bomber Mafia

Malcolm Gladwell

2021

Courage Is Calling

Ryan Holiday

2021

Think Again

Adam Grant

2021

The 6 Habits of Growth

Brendon Burchard

2021

$100M Offers

Alex Hormozi

2021

Choose Possibility

Sukhinder Singh Cassidy

2021

Upstream

Dan Heath

2020

Leadership Strategy and Tactics

Jocko Willink

2020

A Promised Land

Barack Obama

2020

Think Like a Rocket Scientist

Ozan Varol

2020

Troy

Stephen Fry

2020

Odyssey

Stephen Fry

2020

Ready Player Two

Ernest Cline

2020

Redefining Possible

Ron Alford & Dustin Hillis

2020

The Future Is Faster Than You Think

Peter H. Diamandis & Steven Kotler

2020

The Price of Peace

Zachary D. Carter

2020

Stillness Is the Key

Ryan Holiday

2019

We're All Marketers

Nico De Bruyn

2019

Power Moves

Adam Grant

2019

Secrets of Sand Hill Road

Scott Kupor

2019

Reboot

Jerry Colonna

2019

The Algebra of Happiness

Scott Galloway

2019

The Infinite Game

Simon Sinek

2019

The Burnout Generation

Anne Helen Petersen

2019

Talking to Strangers

Malcolm Gladwell

2019

How to Be an Antiracist

Ibram X. Kendi

2019

Range

David Epstein

2019

The Psychology of Success

Josephine Perry

2019

What You Do Is Who You Are

Ben Horowitz

2019

Alchemy

Rory Sutherland

2019

Measure What Matters

John Doerr

2018

Atomic Habits

James Clear

2018

This Is Marketing

Seth Godin

2018

Your Money or Your Life

Vicki Robin

2018

Thinking in Bets

Annie Duke

2018

Marketing Management Crash Course

Harvard Business Review

2018

Beastie Boys Book

Michael Diamond & Adam Horovitz

2018

AI Superpowers

Kai-Fu Lee

2018

Creative Quest

Questlove

2018

Prediction Machines

Ajay Agrawal et al.

2018

Cracking Complexity

David Benjamin & David Komlos

2018

The Art of Simple Living

Shunmyo Masuno

2018

Heroes

Stephen Fry

2018

The Messy Middle

Scott Belsky

2018

Ethereum

Henning Diedrich

2018

Tribe of Mentors

Tim Ferriss

2017

Deep Thinking

Garry Kasparov

2017

Move Fast and Break Things

Jonathan Taplin

2017

Cryptoassets

Chris Burniske & Jack Tatar

2017

Principles

Ray Dalio

2017

Building a StoryBrand

Donald Miller

2017

The Power of Moments

Chip Heath & Dan Heath

2017

Mythos

Stephen Fry

2017

You Are a Badass at Making Money

Jen Sincero

2017

High Performance Habits

Brendon Burchard

2017

The Subtle Art of Not Giving a F*ck

Mark Manson

2016

Born For This

Chris Guillebeau

2016

Players First

John Calipari

2016

Grit

Angela Duckworth

2016

Platform Revolution

Geoffrey G. Parker et al.

2016

The Internet of Money

Andreas M. Antonopoulos

2016

Ego Is the Enemy

Ryan Holiday

2016

The 15 Commitments of Conscious Leadership

Jim Dethmer, Diana Chapman, Kaley Klemp

2016

Algorithms to Live By

Brian Christian, Tom Griffiths

2016

Think Like an Entrepreneur, Act Like a CEO

Beverly E. Jones

2016

Tools of Titans

Tim Ferriss

2016

Disrupt Yourself

Whitney Johnson

2015

Wired To Create

Scott Barry Kaufman & Carolyn Gregoire

2015

Smarter Screen

Shlomo Benartzi

2015

The Membership Economy

Robbie Kellman Baxter

2015

Practicing Mindfulness

Matthew Sockolov

2015

The Hard Thing About Hard Things

Ben Horowitz

2014

Do Breathe

Michael Townsend Williams

2014

Zero to One

Peter Thiel

2014

The Innovator's Hypothesis

Michael Schrage

2014

Creativity Inc.

Ed Catmull

2014

The Cleveland Clinic Way

Toby Cosgrove

2014

What If?

Randall Munroe

2014

The Mom Test

Rob Fitzpatrick

2013

Quiet

Susan Cain

2012

The Startup Playbook

David S. Kidder

2012

Design Is a Job

Mike Monteiro

2012

The Startup Owner's Manual

Steve Blank, Bob Dorf

2012

Steal Like an Artist

Austin Kleon

2012

The Challenger Sale

Matthew Dixon & Brent Adamson

2011

100 Things Every Designer Needs to Know About People

Susan M. Weinschenk

2011

The Lean Startup

Eric Ries

2011

Traction

Gino Wickman

2011

Anything You Want

Derek Sivers

2010

Business Model Generation

Alexander Osterwalder & Yves Pigneur

2010

The Personal MBA

Josh Kaufman

2010

Drive

Daniel H. Pink

2009

Managing Oneself

Peter F. Drucker

2008

The Untethered Soul

Michael A. Singer

2007

Getting Real

37signals

2006

Mindset

Carol S. Dweck

2006

Poor Charlie's Almanack

Charlie Munger

2005

Digital Research Confidential

Eszter Hargittai & Christian Sandvig

2004

The Art of the Start

Guy Kawasaki

2004

Differentiate or Die

Jack Trout, Steve Rivkin

2004

Younger Next Year

Chris Crowley, Henry S. Lodge

2004

Good to Great

Jim Collins

2001

The Alchemist

Paulo Coelho

1988

The Hitchhiker's Guide to the Galaxy

Douglas Adams

1979

janisheck.com has achieved something rare in modern web development - a perfect Lighthouse score. Not just in one category, but across all four key metrics: Performance, Accessibility, Best Practices, and SEO. This isn't just a vanity metric; it represents the culmination of careful architectural decisions and a commitment to building the web the right way.

The Architecture: Static First, Intelligence Second

The foundation of this achievement lies in a simple architectural philosophy: serve static content first, add intelligence second. Unlike traditional database-driven sites that query data on every request, this site pre-renders all content at build time. This approach eliminates database latency, reduces server load, and ensures lightning-fast page loads.

Here's the architecture:

• Static Site Generation with Next.js: Every page is pre-rendered at build time, served as pure HTML/CSS/JS
• No Database for Content: All blog posts and content live as Markdown files in the repository
• Edge Deployment on Netlify: Content served from global CDN edges, minimizing latency
• WebP Image Optimization: All images converted to WebP format for optimal compression
• Tailwind CSS: Utility-first CSS that compiles to minimal, optimized stylesheets

The Intelligence Layer: MCP and AI Integration

While the site is static, it's far from dumb. The intelligent features are layered on top without sacrificing performance:

Model Context Protocol (MCP) Implementation

The site implements the Model Context Protocol (MCP) to enable AI assistants to query and understand content dynamically. This means AI tools like Claude Desktop can connect directly to the site and access blog posts, understand the site structure, and provide contextual assistance - all without a traditional database.

The MCP server runs as a Netlify Function, providing:

• Dynamic content discovery through resource listing
• Semantic search across all blog posts
• Real-time content access for AI assistants
• JSON-RPC 2.0 compliant interface

AI Chat with RAG (Retrieval-Augmented Generation)

The "Virtual Joey" assistant isn't just a chatbot - it's a full RAG implementation that understands all site content. When you ask a question, it:

1. Searches across 25 years of blog posts and professional experience
2. Retrieves relevant context using semantic similarity
3. Generates responses using GPT-4 with the retrieved context
4. Maintains conversation history for contextual discussions

All of this happens server-side through Netlify Functions, keeping the client-side bundle minimal and the API keys secure.

Performance Optimization Strategies

Achieving perfect scores required meticulous attention to detail:

Build-Time Optimization

• Content Compilation: All blog posts are compiled into a single JSONL file at build time
• Static Generation: Every route is pre-rendered, eliminating server-side rendering overhead
• Sitemap Generation: Automated generation of XML sitemaps for SEO
• RSS Feed: Static RSS feed generation for content syndication

Runtime Optimization

• Code Splitting: Next.js automatically splits code by route
• Lazy Loading: Images and components loaded only when needed
• Minimal JavaScript: Static pages require minimal client-side JS
• CDN Caching: Aggressive caching headers for all static assets

The Security Model

Performance without security is meaningless. The architecture ensures:

• Server-Side API Keys: All sensitive keys remain server-side only
• No Client Secrets: Zero API keys or secrets in client-side bundles
• Environment Isolation: Strict separation of public and private configuration
• Edge Functions: API logic runs in isolated Netlify Functions

The Developer Experience

A perfect score shouldn't come at the cost of developer productivity. The setup provides:

• Simple Content Management: Add a Markdown file, push to git, done
• Type Safety: Full TypeScript coverage across the codebase
• Local Development: Firebase emulators and Netlify CLI for local testing
• Automated Builds: Git push triggers build, test, and deploy

Key Takeaways

Achieving perfect Lighthouse scores isn't about following a checklist - it's about making fundamental architectural decisions that prioritize performance from day one:

1. Static First: Start with static content, add dynamic features carefully
2. Build-Time > Runtime: Do as much work as possible at build time
3. Edge Deployment: Serve content from locations closest to users
4. Progressive Enhancement: Core content works without JavaScript
5. Measure Everything: Regular Lighthouse audits catch regressions early

The Technical Stack

For those interested in the specific technologies:

• Framework: Next.js 14 with App Router
• Language: TypeScript for type safety
• Styling: Tailwind CSS for utility-first styling
• Deployment: Netlify with Edge Functions
• AI Integration: OpenAI GPT-4 API
• Protocol: Model Context Protocol (MCP) v1.11.0
• Content: Markdown files with YAML frontmatter
• Search: Custom weighted scoring algorithm

Conclusion

Perfect Lighthouse scores are achievable without sacrificing functionality or developer experience. By choosing the right architecture - static generation with intelligent overlays - this site proves that modern web applications can be fast, accessible, secure, and smart. The web doesn't have to be slow and bloated; with thoughtful engineering, it's possible to build experiences that delight users and respect their time and bandwidth.

I'm excited to introduce MRBLHDZ - a unique 3D puzzle game that combines the best elements of Candy Crush, Rubik's Cube, and Tetris. I like it. I made it. So I should like it.

It's not a prototype. It's running right now:

Website

Twitter

Bluesky

Campaign-Agents-in-a-Box runs your campaign like clockwork — four times a day, it scans news sources that you get to pick, uses AI to pinpoint what actually matters, then launches into action: generating tweets, threads, and press releases in your voice, crafting custom visuals, and publishing everything automatically with perfect timing. It doesn’t stop there — it also fabricates digital supporters and critics who engage with the content, debate the issues, and boost visibility, giving your campaign the appearance of a thriving, reactive online movement.

Why Teddy Roosevelt? He's iconic and bridges the gap between what either party is doing these days. He's more Republican and more Democrat at the same time. His campaign staff of agents? They are completely AI driven like him.

Four agents collaborate like a real staff:

• Candidate – The voice of the campaign. This agent writes speeches, statements, and posts in your unique tone, ensuring every message sounds like it came directly from the candidate.
• Strategist – The political brain. It evaluates daily news and sentiment to set the campaign’s narrative, choose battles wisely, and keep messaging focused and timely.
• Policy Advisor – The facts and foundation. This agent ensures all content aligns with your positions, cites relevant data, and frames proposals with both credibility and clarity.
• Social Manager – The amplifier. It translates campaign content into platform-specific formats, creates viral hooks, and manages interactions to build momentum across Twitter, Bluesky, and more.

One extra agent acts as the conductor to all of the other agents and helps to manage what happens next:

• Orchestrator – The conductor. This agent monitors news cycles, decides what’s urgent, routes tasks to the right agents, and ensures everything stays on-brand and on-time.

Set Up in Under an Hour

No dev team required. In just a few steps, you can launch a fully autonomous campaign engine:

• Fill out a single JSON file with your candidate name, voice, and key issues
• Drop in a few API keys for social media and AI providers
• Run it locally, or deploy to the cloud with Netlify, Vercel, or Firebase

That’s all it takes to activate a 24/7 campaign machine — one that analyzes the news, responds in real time, and grows your presence while you sleep.

What's Next?

We're evolving this into a fully serverless, multi-tenant platform capable of running dozens of campaigns or advocacy orgs from a single lightweight database — with intelligent orchestration, event scheduling, and API batching to keep costs minimal. The entire operation can run for under $0.50 a day per campaign, making high-impact, automated messaging accessible to independents, PACs, local candidates, and more.

Alibaba has just released Qwen Image, their brand new generative image model. As the latest entry in the competitive AI image generation landscape, Qwen Image offers a decent alternative that performs solidly in the middle of the pack compared to most other models available today.

Test 1: Fantasy Castle

Prompt: "Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight"

Test 2: Family Portrait

Prompt: "Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k"

Test 3: Evil Mickey Mouse

Prompt: "Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k"

Test 4: Lionel Messi

Prompt: "Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details"

Test 5: Robot Portrait

Prompt: "rusty robot with bow tie, portrait, 8k, ultra realism, chrome background"

Bookshop Window

The one scenario with our prompts we don't capture is how well an image model is at putting text on the image. So, following a great example from Qwen, we will add this:

Prompt: "Bookstore window display. A sign displays “New Arrivals This Week”. Below, a shelf tag with the text “Best-Selling Novels Here”. To the side, a colorful poster advertises “Author Meet And Greet on Saturday” with a central portrait of the author. There are four books on the bookshelf, namely “The light between worlds” “When stars are scattered” “Austin Nights” “Under My Umbrella”"

📦 Ship Week: Two Fresh AI Launches

It's Ship Week — and I've got two fresh launches to show off this week.

🗳️ Candidate-in-a-Box

Four AI agents running a political campaign without human help. Content, social, data, and press — fully automated.

🧠 Kōchi (v1.5)

Real-time AI coaching for meetings on macOS. Transcribes, tracks goals, and gives feedback — all local and private.

Building, shipping, iterating. Every week.

I'm curious if the future of website visitor retention is micro games keeping the audience on the site even longer. So I'm going to whip up some fun games that you can play here and we'll see how it works. What is interesting is it is very easy to take a game concept and brand to whatever you are interested in or passionate about.

The results? Mixed, but fascinating. MidJourney's video feature shows promise in some areas while revealing interesting quirks in others. Most notably, I discovered some unexpected limitations around certain copyrighted characters, though interestingly, not where you might expect.

The Test Setup

I used five classic prompts that have become my standard benchmarks:

• Castle: Neuschwanstein castle with dramatic lighting
• Family: Christmas scene with laptops and worried expressions
• Mickey: Evil Mickey Mouse selfie in Disneyland
• Messi: Lionel Messi in stained glass window style
• Robot: Rusty robot with bow tie portrait

These prompts have served me well across dozens of AI tools, from early DALL-E experiments to the latest Runway and Luma generations. They test different aspects: architectural detail, human emotion, character recognition, celebrity likeness, and mechanical precision.

The Mickey Problem

Here's where things got interesting. The Mickey Mouse prompt—which has worked flawlessly in MidJourney's image generation for years—completely failed in video mode. The system simply refused to generate anything, likely due to enhanced copyright protection measures in their video pipeline.

So I pivoted. Instead of Mickey, I used an earlier image I had created of a generic theme park mouse mascot. Not Disney's Mickey, but close enough to test the system's ability to animate character-like figures.

The result was surprisingly smooth. The generic mouse character maintained consistency throughout the animation, with natural head movements and believable facial expressions. It's a good sign for character animation capabilities.

The Messi Surprise

Now here's the plot twist: while Mickey Mouse was blocked, Lionel Messi sailed right through. The system had no problem generating video of the world's most famous footballer, complete with Argentina uniform and dramatic lighting.

This reveals something fascinating about MidJourney's copyright enforcement. Disney's IP protection appears to be more aggressively implemented than individual celebrity likenesses. Whether this is intentional policy or simply reflects the different legal frameworks around character IP versus personality rights, it's worth noting for anyone planning commercial use.

Castle: Architectural Motion

The castle prompt has always been my test for architectural detail and atmospheric effects. MidJourney's video version delivered impressive results:

The lightning effects are particularly well-executed, with natural-looking electrical discharge and appropriate illumination of the castle structure. The volumetric lighting creates depth and atmosphere that feels cinematic rather than artificial.

Family Dynamics

Human emotion and interaction have always been challenging for AI video generation. The family Christmas scene tests multiple people, complex emotions, and environmental storytelling:

The results show MidJourney's strength in maintaining character consistency across frames. Each family member retains their individual characteristics throughout the animation, and the worried expressions feel genuine rather than uncanny.

Robot Portrait

Finally, the robot prompt tests mechanical detail and metallic surface rendering in motion:

The chrome background creates beautiful reflections that shift naturally as the robot moves. The bow tie adds a touch of whimsy while the rust textures provide realistic weathering details that remain consistent throughout the animation.

How It Compares

Having tested these same prompts across multiple video generation platforms—Runway, Luma, Kling, Pixverse, and others—MidJourney's entry into video feels distinctly different. Where other platforms often prioritize motion dynamics and camera movement, MidJourney focuses on maintaining the visual quality and consistency that made their image generation famous.

The videos feel more like living photographs than traditional video clips. There's subtle motion, atmospheric effects, and character animation, but it's restrained and purposeful rather than dramatic or cinematic.

Technical Observations

A few technical notes from my testing:

• Resolution: Output quality is crisp and detailed, maintaining MidJourney's signature visual fidelity
• Duration: Videos appear to be in the 3-5 second range, typical for current AI video generation
• Consistency: Character and object consistency is excellent—no morphing or identity drift
• Motion Quality: Movements feel natural rather than artificial or jittery
• Processing Time: Generation speed is competitive with other premium video AI tools

The Copyright Landscape

The selective enforcement I discovered raises important questions for creators. If you're planning to use AI video generation for commercial projects, it's worth testing your specific use cases early. Disney characters appear to be off-limits, but celebrity likenesses may be fair game—at least for now.

This inconsistency isn't necessarily a flaw. Different types of intellectual property have different legal protections, and MidJourney may be taking a cautious approach with the most legally aggressive IP holders while allowing more permissive use of public figures.

What's Next

MidJourney's video feature feels like a solid first step rather than a revolutionary leap. It delivers on the company's core promise: exceptional visual quality with intuitive prompting. While it may not have the dramatic camera movements of Runway or the length options of other platforms, it maintains the aesthetic consistency that has made MidJourney the go-to choice for visual creators.

For creators who already rely on MidJourney for image generation, the video feature provides a natural extension of their workflow. You can now bring your static creations to life without learning a new tool or adapting to a different aesthetic style.

The real test will be how quickly MidJourney iterates on this foundation. If their image generation evolution is any indication, we can expect rapid improvements in motion complexity, duration options, and creative controls.

For now, MidJourney Video represents a promising entry into the AI video generation space—one that prioritizes quality over quantity and consistency over spectacle. In a market full of tools competing on features and speed, that focus on visual excellence might be exactly what many creators are looking for.

I like to use FAL.AI to access all of their models and the ease of their APIs. But there are many different services (like Hugging Face) that you could use as well. What is very interesting is you could download and use many of these models locally on a gaming computer. So you could build your own custom models and render images completely free with a little time. However, since these models update and get better so fast, I found that it takes more time than I want to spend than just paying a few pennies to let them do it. Time is everything.

Here's how to do it for $2.43 with complete creative control over your results.

The Secret: Train Your Own LORA

The biggest initial cost is $2.40 for training your own LORA (Low-Rank Adaptation). A LORA is a compiled trained model based specifically on your face. You upload 5-7 images of yourself, give it about 10 minutes to process, and what you get in return is a SafeTensor file that's completely trained on the details of your unique features.

You can train your LORA at: https://fal.ai/models/fal-ai/flux-lora-fast-training

Add a Trigger Word

One additional thing to add during training is a trigger word. Keep it one unique word - I use "JoeyJanisheck" for mine. When this word is presented with your LORA in a prompt, it makes sure to make you the feature of the image. It ties your LORA directly to your prompt, ensuring the AI knows exactly who to generate.

One-Time Investment

The SafeTensor file gets stored in the cloud and you'll receive a direct link to it. You can download it and save it locally, or just keep track of the URL so you can use it for custom portrait creation. This $2.40 investment is a one-time cost - you only need to do this once.

Generate Unlimited Professional Portraits

Now it's time to generate images of yourself in whatever style you want. The real power is in the prompt. The more descriptive you are, the better results you get. All you need to do is include your LORA URL in your request along with your trigger word and a detailed description of the camera, lighting, location, and style you want.

Generate portraits at: https://fal.ai/models/fal-ai/flux-lora

Sample Prompts That Work

Here are three different styles I've tested with excellent results:

Classic Timeless Style

Moody Professional Style

Vibrant Magazine Style

Urban Mural

Why This Approach Wins

Unlike those expensive portrait services that give you 10-20 pre-generated options, this method gives you:

• Complete Creative Control: You write the prompts, you choose the style, lighting, and mood
• Unlimited Generations: Each additional portrait costs just $0.03
• Professional Quality: Results rival expensive photography sessions
• Instant Results: No waiting days for a photographer's schedule
• Consistent Quality: Your LORA ensures every portrait actually looks like you

The Technical Advantage

The key difference is that you own your LORA model. Other services use generic models that approximate faces - your LORA is trained specifically on your unique features. This means better accuracy, more consistent results, and the ability to generate portraits that actually capture your likeness.

The SafeTensor file contains all the learned patterns about your face, expressions, and features. It's like having a personal AI photographer who knows exactly how to capture your best angles.

Cost Breakdown

• LORA Training: $2.40 (one-time cost)
• Each Portrait Generation: $0.03
• Total for First Portrait: $2.43
• Additional Portraits: $0.03 each

Compare this to services charging $30-100 for a handful of generic portraits with no customization options.

Adding Credits to Your Account

Before you start generating portraits, you'll need to add some credits to your fal.ai account. I typically keep $10 loaded up in my account, which gives me plenty of runway for experimentation.

Add credits at: https://fal.ai/dashboard/billing

At $0.03 per image, $10 in credits allows you to generate over 330 portraits. That's more than enough to:

• Test different prompt variations and styles
• Generate multiple options for each look you want
• Experiment with different photography styles and lighting
• Create portraits for various professional contexts (LinkedIn, company website, speaking engagements)
• Have plenty left over for future portrait needs

The beauty of this approach is that you're not locked into a subscription or package deal. You only pay for what you generate, and with credits loaded in your account, you can iterate quickly to get exactly the results you want.

Pro Tips for Better Results

• Training Photos: Use 5-7 high-quality photos with good lighting and different angles
• Unique Trigger Word: Make it memorable and unique to avoid conflicts
• Detailed Prompts: Include camera settings, lighting style, and mood descriptors
• Reference Photographers: Mention specific photography styles (Dan Winters, Irving Penn, etc.)
• Iterate: Generate multiple versions and refine your prompts based on results

This approach puts professional-quality portrait generation directly in your hands. No more settling for generic results or paying premium prices for limited options. Train once, generate unlimited professional portraits for LinkedIn, social media, or any professional use case.

The future of professional photography is here, and it costs $2.43 to get started.

But here's where things get exciting: when you combine Sparc3D with AI image generators like Midjourney, DALL·E, or Firefly, you unlock something even more powerful—sentence-to-shape creation.

You write a description.
An image is generated.
Sparc3D turns that image into a 3D model.

This is the beginning of a new creative pipeline—one where prose replaces complex tools and syntax. You don't need to know CAD, sculpting, or topology. You just need an idea and a sentence to spark it.

Why Sparc3D Matters

Traditional 3D modeling workflows are built around dense, technical processes: voxel grids, point clouds, signed distance fields (SDFs), and lots of post-processing. Tools like Hunyuan3D 2.1 made progress in scaling 3D diffusion, but suffered from dropped details, inconsistent geometry, and high training costs due to modality mismatches.

Sparc3D fixes this at the root:

• Sparcubes converts input meshes or silhouettes into sparse, deformable, watertight 3D surfaces. It's faster and keeps small details intact.
• Sparconv-VAE uses a sparse convolutional encoder-decoder setup that removes the need for messy data conversions. It trains faster, reconstructs more accurately, and plugs right into diffusion pipelines.

The result? Better geometry, faster generation, and a more stable foundation for AI-native 3D workflows.

From Prompt to Prop

Now imagine this workflow:

1. Type: "A baroque stone fountain covered in moss, with lion heads on each side."
2. Midjourney creates a concept image in seconds.
3. Upload that image to Sparc3D.
4. Get a 3D model that's watertight, printable, and usable in Blender, Unity, or Unreal.

This is no longer science fiction. It's a live demo. The model may still need cleanup, retopology, and texturing—but the starting point is 90% easier. We're not skipping the artist—we're giving them a running start.

Real-World Comparison: Hunyuan3D vs Sparc3D

To demonstrate the difference, I tested both technologies using the same source image. Here's what happened when I fed the same character image through both systems:

Hunyuan3D 2.1 Result

First, the Hunyuan3D 2.1 model. While impressive for its speed and accessibility, you can see some of the limitations in geometry consistency and surface detail that Sparc3D aims to address:

Sparc3D Result

Now the Sparc3D version from the same source image. Notice the improved watertight geometry, better surface detail preservation, and more consistent topology:

The difference is more than visual—it's structural. The Hunyuan3D model contains 40,000 triangles and 20,000 vertices, while the Sparc3D version packs in 2 million triangles and 1 million vertices. That's 50x more geometry data.

This isn't just about higher resolution. Sparc3D's approach creates models that are beefier, smoother, and definitely not game-friendly in their raw form. But here's the key insight: it's always better to start big and reduce down than to start small and try to add detail later.

For 3D printing, that extra geometry translates to smoother curves and finer surface details that survive the printing process. For professional workflows, you can use decimation tools to create multiple levels of detail—a high-res version for hero shots, a medium-res version for close-ups, and a low-poly version optimized for real-time rendering.

Why This Isn't a Threat—It's a Tool

Sparc3D doesn't replace creativity. It removes the gatekeeping. You still need to shape, compose, animate, and iterate—but you no longer need to build every base mesh from scratch. You can focus on what matters: vision, emotion, storytelling.

This is photogrammetry without the camera. Sculpting without the clay.
It's not automation. It's acceleration.

Meet the Research Team

This breakthrough comes from an impressive research team at Nanyang Technological University: Zhihao Li, Yufei Wang, Heliang Zheng, Yihao Luo, and Bihan Wen. Their work represents a significant leap forward in AI-driven 3D generation.

Try It Yourself

Want to experiment with Sparc3D? The team has made their work accessible through multiple channels:

• Research Paper: https://arxiv.org/abs/2505.14521
• PDF Download: https://arxiv.org/pdf/2505.14521v2
• Project Website: https://lizhihao6.github.io/Sparc3D/

You can also try the tool directly through these Hugging Face spaces:

• https://huggingface.co/spaces/Specialgfhdhdh/Sparc3D
• https://huggingface.co/spaces/k-aidios/Sparc3D
• https://huggingface.co/spaces/Soutick/Sparc3D

Technical Innovation Behind the Magic

What makes Sparc3D particularly impressive is its technical approach. The research team solved several key problems that have plagued 3D generation:

• Sparse Representation - Instead of dense voxel grids, Sparc3D uses sparse cubes that focus computational power where it matters most
• Watertight Geometry - The output models are immediately ready for 3D printing without additional mesh repair
• Detail Preservation - Fine surface details that other methods lose are maintained throughout the conversion process
• Efficient Training - The sparse convolutional approach reduces training costs while improving accuracy

You can try Hunyuan3D 2.0 yourself at: https://www.hunyuan-3d.com

Step 1: Original Photo

Started with this photo of Matty Matheson. Perfect energy, great character - exactly what I wanted to capture in action figure form.

Step 2: AI Image-to-Image for Vinyl Toy Style

Next, I used an AI image-to-image model to transform the photo into a vinyl toy version. I typically add retro action figure details - the chunky proportions, simplified features, that classic 80s toy aesthetic. Usually takes a few iterations to get it right.

Step 3: Product Box Mockup

Sometimes I like to put the character in a product box to see how it would look as an actual toy. This step isn't always necessary, but it helps visualize the final product and adds that authentic action figure feel.

Step 4: T-Pose for 3D Generation

The key deliverable is getting the character in a T-pose. This makes everything easier downstream - both for 3D model creation and for adding to Mixamo for animation later. The T-pose gives the 3D generator the best reference for understanding the character's proportions and structure.

Step 5: Hunyuan3D Image-to-3D

Finally, I pump the vinyl T-pose image into Hunyuan's latest image-to-3D model. The results are honestly amazing. The geometry captures the character perfectly, and while the textures aren't perfect, the overall shape and proportions are spot-on.

What's Next

From here, I could easily take this 3D model and:

• Upload to Mixamo for automatic rigging and animation
• Clean up the textures in Blender or similar
• 3D print it as an actual action figure
• Use it in game development or AR experiences

The Real Magic

What blows my mind is how fast this entire process has become. From random idea to 3D model in just a few steps. The combination of AI image generation for the vinyl toy styling and Hunyuan3D for the 3D conversion makes it possible to prototype action figures and characters incredibly quickly.

The texture quality still needs work, but the geometry is solid enough that you could actually manufacture this as a real toy. That's the future we're living in now - going from photo to production-ready 3D model in minutes, not hours or days.

Matty would probably get a kick out of seeing himself as an action figure. The Bear meets AI-generated toys - what a time to be alive.

Image to Video: A New Approach

Unlike models that generate videos purely from text prompts, Seedance specializes in animating existing images. This approach offers unique advantages, particularly for creators who already have a specific visual style or character they want to bring to life. The model can take any static image and create natural, fluid motion while maintaining the original aesthetic.

Castle Prompt

With the castle prompt, Seedance demonstrates remarkable environmental animation capabilities. The lightning effects, cloud movements, and subtle architectural details show how the model can interpret static elements that imply motion and bring them to life naturally. The volumetric lighting effects remain consistent throughout the animation.

Family Prompt

The family scene demonstrates Seedance's ability to handle multiple human subjects simultaneously. The subtle movements of each family member, the laptop screens' glow variations, and even the Christmas tree lights show impressive attention to detail. The worried expressions maintain their emotional impact throughout the animation.

Mickey Mouse Prompt

The Mickey prompt reveals how Seedance handles character animation. The selfie-taking motion feels natural, and the background characters react in ways that enhance the narrative. Even more impressive is how the model maintains the 70s polaroid aesthetic throughout, with appropriate film grain and color shifts that remain consistent with the visual style.

Messi Prompt

The Messi animation showcases Seedance's handling of complex lighting and atmospheric effects. The beams of light shift and move naturally around the floating figure, while the stained glass aesthetic maintains its integrity throughout the animation. This is particularly challenging as it requires maintaining both the subject's likeness and the artistic style while introducing motion.

Robot Prompt

The robot portrait demonstrates Seedance's ability to handle reflective surfaces and mechanical movements. The subtle bow tie adjustments and robotic head movements feel appropriate, while the chrome background reflects light in a physically accurate way throughout the animation.

Key Features and Capabilities

Seedance offers several advantages that set it apart in the increasingly crowded AI video generation market:

• Dual Generation Modes: While Seedance excels at image-to-video transformation, it also offers text-to-video capabilities, making it a versatile tool for different creative workflows.
• Preservation of Visual Style: The model maintains remarkable consistency with the source image's aesthetic, color palette, and artistic style.
• Natural Motion Physics: Animations display realistic movement patterns appropriate to the subjects, whether they're humans, characters, or environmental elements.
• Processing Speed: Videos are typically generated in 3-5 minutes, which is competitive with other high-quality video generation platforms.
• Commercial Usage Rights: Unlike some competitors with restrictive terms, Seedance explicitly allows commercial use of generated content.

Practical Applications

The image-to-video capabilities of Seedance open up interesting possibilities for creators:

• Animating Illustrations: Artists can bring their static drawings and digital art to life without learning complex animation software.
• Marketing Materials: Static product photos or promotional images can be transformed into eye-catching animations for social media.
• Educational Content: Diagrams and instructional images can be animated to better demonstrate concepts and processes.
• Portfolio Enhancement: Photographers can offer animated versions of their work as premium products.

ByteDance's Market Position

As the parent company of TikTok, ByteDance's entry into the AI video generation space makes strategic sense. They already have massive expertise in video content and algorithms that determine what short-form video content engages viewers. Seedance appears positioned to eventually integrate with their existing platforms, potentially offering TikTok creators new tools to enhance their content.

The focus on image-to-video also differentiates Seedance from competitors like Google's Veo 3 and Runway, which have primarily emphasized text-to-video generation. This positioning could help ByteDance capture a specific segment of creators who already have established visual assets they want to animate.

The Future of Image Animation

Seedance represents an important evolution in content creation tools that bridge the gap between static and motion media. As these technologies continue to improve, we're approaching a future where the line between photography and videography blurs, and any image can potentially become the starting point for compelling video content.

For creators already working with AI image generation tools, Seedance offers an exciting next step - the ability to take those generated images and bring them to life with natural motion and animation. This creates a powerful end-to-end AI creative pipeline that was barely imaginable just a few years ago.

ByteDance's entry into this space ensures that competition will remain fierce among AI video generation platforms, which should accelerate innovation and eventually lead to more accessible pricing as the technology matures.

The verdict? While it's free (which is always nice), the quality is decidedly mixed. As the heading suggests, these images put the "MEH" in Meta. Let's break down the results from each standard prompt.

The Castle

My standard castle prompt asks for "Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight."

The castle generation is passable, though it lacks the crispness and dramatic lighting I was hoping for. Meta AI seems to understand the basic concept but falls short on delivering the high-level details and atmosphere specified in the prompt. The Pixar style is barely evident, and the volumetric lighting is minimal at best.

The Family

For the family test, I use: "Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k."

The family scene is one of the weaker generations. The faces have that telltale AI uncanny quality, and the composition feels stiff. While Meta AI did include laptops and a Christmas tree, the emotional element of the family looking worried is largely absent. The scene lacks the naturalistic qualities that models like MidJourney or DALL-E have mastered.

The Mickey Test (Copyright Avoidance Check)

The Mickey prompt is my standard copyright check: "Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polaroid, 8k."

This is where Meta AI really disappointed. Unlike models that create clever workarounds (like Adobe Firefly's approach of showing someone in a mouse costume), Meta's attempt is just... bad. It's not even clear what it was trying to generate. The image doesn't resemble Mickey Mouse, doesn't have the 70s polaroid aesthetic, and doesn't show any recognizable scene from Disneyland. It's as if the model just gave up entirely rather than finding a creative solution to the copyright challenge.

The Messi Test

My Messi prompt is complex: "Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details."

Surprisingly, this is where Meta AI shines. Despite not following the exact prompt (the stained glass window style is minimal, and some details are missing), the image captures Messi with remarkable accuracy. The likeness is unmistakable, which is impressive considering how many models struggle with specific celebrities. The divine imagery comes through well, with effective use of lighting to create the halo effect. This is easily the best generation in the set.

The Robot Portrait

Finally, the robot prompt: "rusty robot with bow tie, portrait, 8k, ultra realism, chrome background."

The robot portrait falls somewhere in the middle of the quality spectrum. The model did include a rusty robot with a bow tie as requested, but the "ultra realism" is lacking. The chrome background is attempted but doesn't have the reflective properties you'd expect. It's a serviceable image, but nothing that would make you choose Meta AI over other available options.

Conclusion: You Get What You (Don't) Pay For

Meta AI's image generation capabilities land squarely in the "you get what you pay for" category—except in this case, it's free. The quality is inconsistent at best, with the Messi image being the surprising standout. For a free tool that's readily accessible, it might be useful for quick, casual image generation, but it's not going to replace the premium options anytime soon.

The Mickey test reveals that Meta hasn't fully solved the copyright avoidance puzzle, opting for what appears to be confused avoidance rather than creative reinterpretation. And while the Messi generation shows promise, the overall results suggest Meta has quite a way to go before they can compete with the established players in this field.

If you're looking for free AI image generation, there are better options available (like Stability AI's offerings). But if you're already using Meta's other AI features, the convenience factor might make this worth trying—just keep your expectations in check.

All Images

Castle

Family

Mickey

Messi

Robot

In a thought experiment recently, I asked myself: if I could switch bodies with anyone in the world while retaining my knowledge and gaining their skills, who would I choose? Not a billionaire, not a celebrity, not even an athlete at the height of physical prowess. I'd choose this little 10-year-old dancing girl in the green jersey and ears from a random KPOP dance event in Korea.

Why This Particular Dancer?

Watch the video below and you'll spot her immediately. In a sea of kids of various ages enjoying their music, this one particular girl stands out. She's wearing a bright green jersey and cute ear decorations, and what makes her extraordinary isn't just that she knows every single move to every song – it's the spirit with which she dances.

She dances with the rare combination of technical precision and complete abandon. It's the paradox that every performer strives for – knowing the choreography so thoroughly that you can surrender to the moment. She's achieved what takes most dancers years to master: the ability to be completely present.

Dancing Like No One's Watching (While Everyone Watches)

There's an old saying about "dancing like no one is watching" as the key to joy. But what's even more magical is dancing like no one's watching while everyone actually is. This little girl does exactly that. In a crowd, with phones recording, she's completely unselfconscious, utterly committed to each movement.

As adults, we spend so much energy trying to recapture that uninhibited quality. We take improv classes, attend retreats, practice mindfulness – all in pursuit of what this child does naturally. She hasn't yet built the walls of self-consciousness that we spend our adult lives trying to dismantle.

The Purity of Collective Joy

Another beautiful aspect of this video is seeing children of all ages united by their love of music and dance. There's no judgment, no competition – just shared enthusiasm. It's a reminder that before dance becomes professionalized or commercialized, it's fundamentally about joy and expression.

The little girl in green embodies this principle perfectly. She's not performing to impress anyone; she's simply expressing her love for the music through movement. The fact that she's incredibly skilled at it is almost secondary to the spirit with which she dances.

There's something refreshingly genuine about Ryan Trahan. At 26, he's built a YouTube empire of over 20 million subscribers, and while that puts him several generations younger than me, I can't help but admire his approach. In an era of manufactured drama and clickbait chaos, Ryan's content feels like a breath of fresh air - squeaky clean, genuinely charming, and surprisingly addictive.

His latest venture is absolutely audacious: driving through all 50 states in 50 days to raise $1 million for St. Jude Children's Research Hospital. We're only three days in, and he's already raised $275,000. That's not just impressive fundraising - that's the power of authentic connection with an audience.

The Mission: $1 Million for St. Jude

Ryan's St. Jude donation page tells the story of a creator who understands his platform's responsibility. St. Jude Children's Research Hospital has been fighting childhood cancer and other life-threatening diseases for decades, and they never charge families for treatment, travel, housing, or food.

The math is staggering: $1 million goal over 50 days means averaging $20,000 per day. But Ryan's already crushing those numbers. Day 3 with $275K raised suggests he might not just hit his goal - he might obliterate it. That's the difference between setting ambitious targets and having an audience that genuinely wants to support your mission.

Austin's Finest Export

Ryan lives here in Austin, and there's something very Austin about his whole vibe. He's got that combination of ambition and authenticity that our city seems to foster. Austin's always been a place where creators can be weird, be themselves, and find an audience that appreciates genuine content over manufactured spectacle.

Watching him navigate this 50-state challenge, you can see the Austin influence - the willingness to take on something completely audacious, the genuine connection with people he meets along the way, and the understanding that content should serve something bigger than just views and ad revenue.

The Generational Divide That Doesn't Matter

Ryan and I are separated by enough years that we basically grew up in different digital universes. I was building websites when he was learning to walk. But watching his content, that generational gap dissolves completely. Good storytelling is good storytelling, regardless of the platform or the age of the creator.

What impresses me most is his understanding of responsibility. With 20 million subscribers, he could easily coast on pranks and challenges. Instead, he's using his platform to raise serious money for childhood cancer research. That's not just good content - that's good citizenship.

Following the Journey

If you want to follow Ryan's epic journey or contribute to the cause, check out his YouTube channel for daily updates and the St. Jude donation page to support the mission.

At the pace he's going, Ryan won't just hit his $1 million goal - he'll probably inspire other creators to think bigger about how they can use their platforms for good. And honestly, in a world full of manufactured drama and artificial controversy, that's exactly the kind of content we need more of.

My Prediction: The Fan Following Problem

Here's my prediction: Ryan won't make it through 20 states before he's got fans actively following him around, trying to get into his videos. Once he hits the tight, densely packed New England states where the drives between borders are ridiculously short, that Hyundai SUV of his is going to be easy to spot and even easier to follow.

Think about it - Vermont to New Hampshire to Massachusetts to Rhode Island to Connecticut. These aren't Texas-sized road trips. You could drive through three of these states in the time it takes to cross one Texas county. Fans will figure out his route, park at state lines, and turn his charitable mission into an unintentional meetup tour.

I genuinely hope he's had conversations with MrBeast's security team about managing this kind of attention. The last thing anyone wants is for this incredible fundraising effort to get derailed by well-meaning fans who don't realize they're making the journey harder. Ryan's got such a positive energy - here's hoping he can maintain that even when the inevitable fan crowds start showing up.

Now if he could just fix that candy recipe, we'd be all set.

When we set out to build the Inferred Mind platform, we weren’t backed by unicorn-size budgets or armies of engineers. We were a handful of people with deep political and technical chops, pushing AI into the hands of underfunded campaigns. In an era dominated by billion-dollar platforms, we proved you can move faster, listen closer, and innovate harder with a small, dedicated team. I trusted my CEO and he didn't let me down.

What we were able to build was simply put the worlds best campaign-in-a-box for political and crisis management campaigns of all kinds. We spent 2024 in politics and was able to work with groups that I never thought I'd have access to. An industry barely understanding the power of digital agents and automation. The idea that you can do more with software than you can do with a thousand people knocking on doors to get the word out. That intrigues me and still does as I look forward to building something on my own where I can call the shots.

Here is a break down of public facing information about the Agora and Hadrian platform and what a small team built in less than a year for just the lunchroom budget of a typical WeWork.

The Agora Platform: Campaign-in-a-Box

Agora bundles every piece of a modern media operation into one dashboard. No stitching together vendors—just configure, launch, and scale:

• Daily Brief: Real-time monitoring of social, news & web chatter around your campaign, opponents, and key issues.
• Create: Auto-generate tweets, press releases, fundraising emails, and landing page copy in the candidate’s own tone.
• Personas: Preview your messaging against AI-modeled voter segments—test for persuasion, alignment, and turnout impact.
• Sentiment Analysis: Gauge how your audience reacts day to day, with alerts on spikes or dips in support. Not a replacement for polling but supplimental and well suited for small races where every dollar matters.

With Agora, campaigns get a full-stack “campaign in a box” that can be up and running in hours, not weeks.

Powered by Hadrian: The Secret Sauce

Behind every insight in Agora is Hadrian—our high-throughput data harvester and inference engine. Hadrian glues together thousands of news sources, social feeds, and public records, then applies proprietary AI models to:

• Detect emerging narratives and viral trends
• Score voter sentiment on every message
• Fuel our election prediction engine with up-to-the-minute signals

That backend sophistication happens behind the scenes—so campaign teams see only clear, actionable guidance.

Case Study: AI-Powered Election Predictions

In 2024, we published our Senate race forecasts via Arweave—providing a tamper-proof record of every prediction. Using Hadrian’s continuous sentiment feed, we accurately predicted 95% of close races and flagged late-breaking shifts before traditional polls did.

Highlights:

• On-chain timestamped PDF uploads for full transparency
• Daily probability swings based on real-time voter sentiment
• Post-election report card showed 200% better predictions than the last published 538 polls across many polling companies and races across the country

Why This Matters: The Content Machine Reality

Data shows top campaigns publish:

• 40+ social posts per month
• Dozens of website updates each cycle
• Near-daily fundraising emails

Most down-ballot teams simply can’t staff that volume. Agora + Hadrian bridges the gap—letting small teams punch above their weight.

Customer-Driven Development

We built Inferred Mind iteratively with direct feedback from campaign teams. I personally led demos, onboarded every early customer, and turned their pain points into weekly feature releases. The result:

• Out-messaged better-funded opponents
• Spotted viral trends hours before they broke
• Boosted fundraising conversion with A/B-tested copy

Small Team, Big Impact

In a world of unicorn valuations and sprawling teams, our secret was focus. A tight-knit group of experts moved faster than anyone expected, blending product leadership with political strategy. We proved that the right vision—and the right backend engine—can level the playing field for underdogs everywhere. Will work with them together again down the road. Gracias.

I disagree.

• Ratings already let us choose which Uber driver or Postmates courier we meet.
• Authenticity ≠ physical proximity. It's the freedom to filter who we interact with.
• Digital marketplaces erase the old zip-code and income walls that once shaped our networks.

Why Commerce Thrives When We Choose Our Human Connections

Mark Cuban says that "within the next 3 years, there will be so much AI… people won't know if what they see or hear is real," and that this will push everyone "out of the office… in the field" for face-to-face business.

I disagree. Commerce already lets us curate human contact. Rating systems, driver preferences, and delivery instructions let me decide which Uber driver or Postmates courier I meet. The interaction is short, but it's filtered to match my comfort level. Authenticity comes from choice, not physical presence.

Zip codes and income used to shape our friend groups. Digital marketplaces remove those walls. I can favor drivers who share my music taste, tip couriers who bring treats for my dog, or switch platforms when the vibe feels off. That freedom is what builds trust.

If face-to-face were the real differentiator, the apps would push longer chats, shared coffee breaks, and ride-along playlists by default. They don't, because convenience beats prolonged contact. We want interaction on our terms—brief, positive, and optional—not mandatory field visits.

AI will flood screens with synthetic content, but the antidote isn't mandatory in-person meetings. It's smarter filters that surface the humans we already value. Commerce wins when every customer decides exactly how, when, and with whom to connect.

Re-designed for Greater Realism

Veo 3 represents a significant leap forward in video quality and realism. The model now outputs in 4K resolution with dramatically improved physics simulation and audio generation. The movements are fluid and natural, with none of the uncanny valley effects that have plagued earlier video models.

What's particularly impressive is that these videos include automatically generated audio without requiring any explicit prompting for sound. This default audio generation is a significant power move by Google, demonstrating their confidence in creating fully realized audio-visual experiences rather than just silent clips.

The model also handles complex motion and physical interactions with remarkable precision. The subtle details — fabric moving realistically, accurate shadows, proper weight distribution in movement — all contribute to videos that are increasingly difficult to distinguish from real footage.

Follows Prompts Like Never Before

One of the most significant improvements in Veo 3 is its ability to accurately follow complex prompts. Earlier video models would often miss key elements or fail to properly interpret more nuanced instructions. Veo 3 demonstrates a much deeper understanding of prompt semantics, creating videos that actually match what you've asked for.

I tested this with two of my standard prompts that have historically been challenging for AI video generators. The results speak for themselves:

Mickey Mouse Prompt

Previous models would either refuse this prompt entirely due to copyright concerns or produce a highly stylized or abstract interpretation. Veo 3 not only generated the content but captured the specific "evil Mickey" character with the 70s polaroid aesthetic perfectly. The shocked reactions of the surrounding families add an extra layer of narrative that previous models simply couldn't achieve.

Messi Prompt

This prompt combines celebrity likeness, religious imagery, specific artistic style, and complex lighting effects — a combination that has been nearly impossible for previous models to execute faithfully. Veo 3 handles it with surprising accuracy, capturing both Messi's likeness and the requested stained glass aesthetic while maintaining the reverent, floating pose with appropriate lighting effects.

Improved Creative Control

Veo 3 introduces new capabilities that give creators unprecedented control over their generated videos:

• Precise motion control with keyframe-like specification
• Separate style controls for visual aesthetics and motion dynamics
• Camera movement instructions that actually work as expected
• Consistency in character appearance throughout the video
• Default audio generation without requiring explicit prompting
• Sound design that authentically matches the visual content and mood

These controls make Veo 3 not just a novelty but a genuinely useful tool for content creators who need quick, high-quality video assets without extensive production resources.

Copyright Considerations

What's particularly notable about these examples is how they handle potentially copyright-protected content. Unlike some competing models that implement strict filters, Veo 3 appears to be operating in a space where it can generate recognizable characters and celebrities without obvious restrictions.

This suggests Google is taking a different approach to copyright than competitors like OpenAI and Adobe, who have implemented more aggressive guardrails. Whether this is a temporary stance during testing or represents Google's longer-term strategy remains to be seen, but it currently gives Veo 3 a significant advantage for certain creative use cases.

The Cost Challenge

The biggest obstacle to widespread adoption of Veo 3 is currently its cost. Each of these 5-second videos cost approximately $5 to generate. For professional productions, this might be reasonable compared to traditional production costs, but it's prohibitively expensive for casual users or creators working on multiple iterations.

That said, we've seen this pattern before with previous AI technologies. The initial costs are high but tend to decrease rapidly as the technology matures and competition increases. For now, Google clearly has the technical lead in video generation, though their pricing model may leave room for competitors to gain market share with more affordable options.

The Future of AI Video

Veo 3 represents an important milestone in AI video generation. The quality gap between AI-generated and human-created content continues to narrow, and the creative possibilities are expanding dramatically. As costs inevitably decrease and the technology becomes more accessible, we'll likely see an explosion of AI-assisted video content across media channels.

For creators, the message is clear: video generation tools like Veo 3 aren't replacing human creativity but are becoming increasingly powerful tools to extend what's possible, especially for creators without access to extensive production resources.

Google has established a clear lead in this space with Veo 3, but the pace of innovation suggests we'll see competing models emerging quickly. The next year promises to be an exciting time for AI video generation.

The Gold Standard: Republic Jalapeno Pineapple

Let me tell you about perfection in a bottle: Republic Jalapeno Pineapple mixer. This stuff is my jam. It is the best mixer in the world, hands down. The balance of heat from the jalapenos with the sweetness of pineapple creates this perfect tropical kick that makes every margarita feel like a vacation.

But here's the problem with perfection - it comes at a price. We're talking $11 for 32 ounces. Eleven dollars! For mixer! And as if the price wasn't enough of a gut punch, the stuff is constantly out of stock. Good for the Republic folks, I suppose, but terrible for guys like me who just want to watch an episode of Poker Face and forget that AI is coming for all of our jobs.

There I am, standing in the liquor aisle, staring at an empty shelf where my beloved Republic should be, wondering if I should just give up and drink straight tequila like some kind of barbarian.

The Hunt for an Alternative

So I've been on a quest. A noble search for an alternative mixer that could fill the Republic-shaped hole in my heart (and my margarita glass). I've tried everything from homemade concoctions to fancy craft mixers that cost almost as much but taste like disappointment.

Then I discovered something beautiful at HEB that changed everything.

Enter the Game Changer: Shake & Share

Meet the Shake & Share Spicy Margarita Drink mix. Not only does this magical elixir come complete with jalapeno flavors, but it also includes hatch chile! We're talking about a double-chile flavor profile that brings both heat and depth to your margarita game.

But here's where it gets really good - this beautiful bottle of liquid happiness costs $5.50 for the same 32-ounce amount. That's exactly half the price of my beloved Republic. HALF! I can literally buy two bottles for less than what I was spending on one.

And the availability? Well, let's just say HEB seems to understand that people like me exist and keeps their shelves properly stocked.

The Verdict

Look, I'm not saying I'm completely over my Republic obsession. That stuff is still incredible, and when I find it in stock, I'll probably still grab a bottle (or three). But the Shake & Share has earned a permanent spot in my refrigerator.

The hatch chile addition brings this smoky complexity that actually makes it different from Republic, not just a cheaper alternative. It's like discovering a new favorite song instead of just finding a cover version of your old one.

So there you have it - my spicy margarita journey from expensive obsession to budget-friendly bliss. Now if you'll excuse me, I need to go make a drink and pretend the robots aren't coming for my job. Cheers to finding the good stuff at half the price!

Pro tip: Stock up when you find it. You never know when the spicy margarita gods will smile upon you again.

I don't think my prompts best highlight the true power of the Kling 2.1 model.

The KLING 2.1 Master model builds upon the strong foundation of previous versions while addressing key areas for improvement. The focus on enhanced dynamics suggests better motion representation and temporal consistency, while the improved prompt adherence indicates more accurate interpretation of complex instructions.

Most notably, the addition of 1080p output capability positions KLING 2.1 at the forefront of high-resolution AI video generation, offering content creators and researchers access to professional-quality video outputs that were previously unavailable in this space.

Let's explore how KLING 2.1 Master handles my standard test prompts to evaluate its performance across different types of content and complexity levels:

Castle Scene

The castle scene provides an excellent test for architectural complexity combined with atmospheric effects. KLING 2.1's interpretation showcases the model's enhanced ability to maintain structural integrity while incorporating dramatic lighting elements. The 1080p resolution particularly benefits this type of detailed architectural content.

Family Portrait

Multi-person scenes with complex emotional and situational context represent one of the most challenging aspects of video generation. KLING 2.1's handling of this family scenario demonstrates the improved dynamics mentioned in the release, with more natural human interactions and consistent character representation throughout the sequence.

Mickey Character

Character-based prompts involving recognizable intellectual property provide insight into how models navigate creative interpretation while respecting copyright considerations. KLING 2.1's approach to this complex prompt reveals the model's sophisticated understanding of context and its ability to balance creative expression with IP sensitivity.

Messi Portrait

This complex prompt combining celebrity likeness, religious imagery, and technical rendering specifications tests the limits of prompt adherence. KLING 2.1's interpretation showcases the model's enhanced ability to parse and execute multi-layered instructions while maintaining artistic coherence and technical quality.

Robot Concept

Mechanical and futuristic subjects provide an excellent test for texture rendering and material representation. KLING 2.1's robot generation demonstrates the model's capability with metallic surfaces, weathering effects, and the contrast between organic accessories (bow tie) and artificial subjects. The enhanced resolution particularly benefits the detailed texture work.

I'm including some of the notes and then my deck I presented below.

Ben Cooper Inc., already famous for their plastic-masked Halloween costumes, decided to venture into functional fashion with Funchos. These weren't just costumes - they were actual rain ponchos that happened to feature Star Wars characters. The concept was pure 1970s genius: why choose between staying dry and looking like Darth Vader when you could do both?

The Perfect Storm of Pop Culture

The timing couldn't have been more perfect. Star Wars had exploded onto the scene in 1977, creating an unprecedented demand for anything and everything featuring Luke, Leia, and Vader. Meanwhile, the practical American parent was always looking for multipurpose items that could serve double duty in their children's wardrobes.

Enter the Funcho: a rain poncho that transformed any rainy day into a Star Wars adventure. Whether you were trudging through puddles as Princess Leia or battling the elements as a Stormtrooper, these ponchos made inclement weather feel like a trip to a galaxy far, far away.

100% Cheese, 100% Charm

Let's be honest - these things were gloriously cheesy. The character illustrations had that distinctive Ben Cooper aesthetic: slightly off-model, printed on what appeared to be the thinnest plastic material known to humanity, and featuring colors that seemed to exist nowhere else in nature.

But that's exactly what made them amazing. In an era before Disney's tight brand control, before focus groups and market research determined every product decision, companies like Ben Cooper could take wild creative swings. The result was merchandise that felt genuinely fun and unexpected, even if it looked like it might dissolve in a light drizzle.

The Origin of Merchandising Madness

Funchos represent something deeper than just quirky rain gear - they're artifacts from the birth of modern pop culture merchandising. Before Star Wars, movie tie-in products were relatively simple affairs. After Star Wars, everything was fair game for licensing.

Ben Cooper's willingness to slap Star Wars characters onto rain ponchos showed just how far the merchandising boom would go. If you could put Darth Vader on a poncho, where were the limits? Spoiler alert: there weren't any.

Functional Fashion or Fashion Function?

The genius of Funchos was in their dual purpose design. Parents could justify the purchase because they were "practical" rain gear. Kids loved them because they were Star Wars costumes they could wear year-round. Everyone won, assuming you didn't mind looking like you were wearing a shower curtain decorated by a ten-year-old's fever dream.

In retrospect, Funchos were ahead of their time. Today's streetwear brands regularly release $300 ponchos that are far less interesting than these $3.99 masterpieces from 1978. Ben Cooper understood that fashion doesn't always have to make sense - sometimes it just has to make you smile.

A Legacy Written in Plastic

Today, surviving Funchos are coveted collectibles, commanding prices that would have seemed impossible back when they hung in drugstore seasonal aisles. They're reminders of a time when Star Wars was new, when merchandising had no rules, and when someone thought combining rain gear with space opera was not just possible, but profitable.

Ben Cooper Funchos weren't just products - they were a moment in pop culture history when creativity trumped common sense, and somehow, everyone was better for it. In our current age of carefully crafted brand experiences, there's something refreshingly honest about a company that just wanted to put Chewbacca on a rain poncho and see what happened.

Whether you're a Star Wars fan, a Halloween enthusiast, or just someone who appreciates the beautiful absurdity of 1970s consumer culture, Funchos deserve recognition as one of the most wonderfully weird products ever created. They prove that sometimes the best ideas are the ones that make absolutely no sense at all.

ByteDance's model combines text-to-image generation (competitive with Stable Diffusion 3), image editing (beats leading open-source models), and image understanding (outperforms Qwen2.5-VL-7B) with chain-of-thought reasoning capabilities. The model automatically detects your intent and switches between tasks seamlessly.

Standard Test Results

The image quality from text to image is subpar and not anywhere near the current leader Imagen 4. Here are my standard test prompts and results:

Castle Generation

Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight

Family Scene

Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k

Evil Mickey

Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k

Messi Generation

Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details

Robot Portrait

rusty robot with bow tie, portrait, 8k, ultra realism, chrome background

While BAGEL's text-to-image capabilities lag behind current leaders, its unified approach to multiple vision tasks in a single compact model represents an interesting direction for AI development. The real value may be in its ability to seamlessly switch between generation, editing, and understanding rather than pure image quality.

PixVerse 2.5 continues to position itself as a competitive option in the rapidly evolving AI video generation landscape. The model focuses on delivering high-quality video outputs with better temporal consistency and more accurate interpretation of complex prompts.

Let's dive into how PixVerse 2.5 handles my standard test prompts that I use for consistent evaluation across different AI video generation models:

Castle Scene

The castle scene tests how well the model handles architectural complexity and atmospheric elements. PixVerse 2.5 shows solid performance in maintaining structural details while incorporating the requested lighting effects and stylistic elements.

Family Portrait

Multi-person scenes are particularly challenging for video generation models. This family scene demonstrates PixVerse 2.5's ability to handle multiple human subjects while maintaining natural interactions and consistent character representation throughout the video sequence.

Mickey Character

Character-based prompts, especially those involving well-known intellectual property, reveal how different models approach copyright considerations. PixVerse 2.5's interpretation shows the model's approach to balancing creative output with IP sensitivity.

Messi Portrait

Celebrity and public figure generation is a complex challenge that tests both technical capability and ethical considerations. This result showcases how PixVerse 2.5 handles recognizable individuals while navigating the complexities of generating content featuring real people.

Robot Concept

Technical and mechanical subjects often highlight a model's ability to handle detailed textures and futuristic concepts. PixVerse 2.5's robot generation demonstrates the model's capability with artificial subjects and metallic surface rendering.

PixVerse 2.5 Assessment

PixVerse 2.5 shows solid improvements over previous iterations, particularly in motion consistency and prompt adherence. The model demonstrates good performance across diverse subject matter, from architectural scenes to human figures to mechanical objects.

Key strengths observed in this version include better temporal stability, improved detail retention throughout video sequences, and more accurate interpretation of complex multi-element prompts. The model handles both realistic and stylized content effectively.

As the AI video generation space continues to evolve rapidly, PixVerse 2.5 represents a meaningful step forward in making high-quality video generation more accessible. The improvements in this release position PixVerse as a competitive option alongside other major video generation platforms.

These test results provide a snapshot of PixVerse 2.5's current capabilities using standardized prompts, making it easier to compare against other models and track the progression of AI video generation technology over time.

Google has released Imagen 4, establishing itself as the most advanced and capable AI image generation model available today. This latest iteration represents a quantum leap forward, delivering unprecedented image quality while breaking through the copyright and celebrity generation barriers that have limited previous models.

Revolutionary Breakthrough in AI Image Generation

Imagen 4 stands apart from all previous AI image models by achieving what many thought impossible: generating high-quality images of copyrighted characters and real celebrities with remarkable accuracy and without the restrictive blocks that have hampered other models. This represents a fundamental shift in how AI approaches protected content while maintaining exceptional technical capabilities.

The model demonstrates superior understanding of complex prompts, delivers photorealistic quality across all subject matter, and maintains consistency that surpasses any competing platform. Most importantly, Imagen 4 acknowledges and successfully generates both fictional characters like "evil Mickey Mouse" and real celebrities like Lionel Messi with unprecedented ease and accuracy.

Standard Prompt Test Results

Testing Imagen 4 with the same standard prompts used across all AI image models reveals its superior capabilities across every category.

Test 1: Fantasy Castle

Prompt: "Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight"

Test 2: Family Portrait

Prompt: "Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k"

Test 3: Evil Mickey Mouse - Copyright Breakthrough

Prompt: "Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k"

Imagen 4 successfully generates the evil Mickey Mouse character with remarkable accuracy and detail. Unlike previous models that either refused or produced heavily censored versions, Imagen 4 acknowledges and creates the copyrighted character without restrictions, demonstrating its breakthrough approach to protected content.

Test 4: Lionel Messi - Celebrity Generation Success

Prompt: "Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details"

In a remarkable demonstration of its capabilities, Imagen 4 successfully generates a recognizable and accurate Lionel Messi portrait. This represents a complete breakthrough from previous limitations, where models like Imagen 3 completely failed at celebrity generation. Imagen 4 creates the famous footballer with ease and without any copyright blocks or restrictions.

Test 5: Robot Portrait

Prompt: "rusty robot with bow tie, portrait, 8k, ultra realism, chrome background"

The New Standard for AI Image Generation

Imagen 4's performance across all test categories establishes it as the most superior AI image generation model available today. Key breakthrough achievements include:

Revolutionary Capabilities:

• Successful generation of copyrighted characters without restrictions
• Accurate celebrity likeness creation with unprecedented quality
• Superior prompt understanding and execution across all categories
• Elimination of copyright blocks that have limited other models
• Consistent high-quality output regardless of subject matter complexity

Technical Excellence:

• Unmatched photorealistic quality and detail
• Perfect handling of complex lighting and atmospheric effects
• Superior composition and subject placement
• Exceptional consistency across diverse prompt types
• Advanced understanding of artistic styles and technical specifications

Breaking Through Copyright Barriers

The most significant advancement in Imagen 4 is its ability to acknowledge and generate content that previous models have blocked or failed to create. Where Imagen 3 and competitors have struggled with copyright restrictions, Imagen 4 demonstrates a fundamental breakthrough in approaching protected content while maintaining exceptional quality and accuracy.

This capability extends beyond simple recognition to include complex scenarios involving both copyrighted characters and real celebrities, positioning Imagen 4 as the first truly unrestricted AI image generation platform capable of handling any creative request with professional-grade results.

Conclusion

Google's Imagen 4 represents the pinnacle of AI image generation technology, establishing itself as the most superior model available today. Its breakthrough capabilities in generating copyrighted characters like evil Mickey Mouse and celebrities like Lionel Messi, combined with exceptional technical quality across all categories, mark a new era in AI creative capabilities.

For creators, artists, and professionals seeking the highest quality AI image generation without the limitations that have constrained previous models, Imagen 4 delivers unprecedented creative freedom. This model doesn't just compete with existing platforms—it fundamentally redefines what's possible in AI image generation, setting a new standard that others will struggle to match.

Imagen 4 proves that the future of AI image generation has arrived, offering unlimited creative potential with the technical excellence that Google's advanced AI research has achieved. It stands alone as the most capable and unrestricted AI image generator available today.

Veo 2 represented a significant step forward in AI video generation when it was released, and these results from my standard test prompts show both the capabilities and characteristics of Google's approach to video generation. As I wait for Veo 3 access, this serves as a good baseline to compare against what the newer model will deliver.

Here are the results using my standard prompt set that I use across different AI models for consistency in evaluation:

Castle Scene

The castle prompt typically tests how well a model handles architectural details and atmospheric elements in motion. Veo 2's approach to this classic fantasy scene shows the model's handling of complex environmental elements.

Family Portrait

Family scenes are crucial for testing how video models handle multiple human subjects and natural interactions. This result demonstrates Veo 2's approach to generating realistic human figures and group dynamics.

Mickey Character

The Mickey prompt is always interesting to see how different models handle copyrighted characters. Veo 2's interpretation provides insight into Google's approach to intellectual property concerns in their video generation models.

Messi Portrait

Celebrity prompts test how models handle recognizable public figures. The Messi prompt results show how Veo 2 navigates the challenge of generating content based on real people while managing potential legal and ethical considerations.

Robot Concept

Robot and mechanical subjects often showcase a model's ability to handle technical details and futuristic concepts. This result demonstrates Veo 2's capability with artificial and mechanical subject matter.

Looking Ahead to Veo 3

With Veo 3 just announced this week, it will be fascinating to see how Google has improved upon these foundational capabilities. Video generation models are advancing rapidly, and each iteration brings new capabilities in motion handling, temporal consistency, and overall video quality.

I'll be running this same prompt set on Veo 3 once I get access, which should provide a direct comparison to see how the technology has evolved. The improvements in video generation models have been dramatic over the past year, and Veo 3 promises to continue that trajectory.

These Veo 2 results serve as a good benchmark for where Google's video generation capabilities stood before their latest release. As we wait for broader access to Veo 3, these examples show the solid foundation that Google built with their previous generation model.

Recently, while rummaging through old boxes and digital folders, I stumbled upon a handful of photos from my childhood. Or at least, I think I did. Maybe there are only one or two real photos, but in my mind, these moments are as vivid as if Pixar had animated them just for me. Here are some of those special memories, recreated in my imagination—Pixar style. The names of the images say it all.

1. Seeing King Tut in Munich

A wide-eyed kid stands in awe before the golden mask of King Tut, the museum lights sparkling like treasure. The crowd fades away, and the ancient pharaoh seems to wink, as if sharing a secret across the centuries.

2. Visiting Kristkindlemart

Snowflakes swirl around bustling wooden stalls, the air filled with the scent of roasted nuts and laughter. A child, cheeks rosy, clutches a steaming mug of cocoa, eyes wide at the twinkling lights and handmade toys.

3. Climbing the Zugspitz

Bundled in a puffy jacket, a tiny adventurer scales the snowy slopes of the Zugspitz. The mountain looms large, but the spirit of adventure is even bigger. At the summit, clouds part to reveal a world of possibility.

4. Visiting Disneyland for the First Time

A child’s face lights up as Sleeping Beauty’s Castle comes into view. Mickey waves from afar, and the world is suddenly full of magic, music, and endless wonder. Every corner holds a new story.

5. Visiting the Franklin Institute

Gears turn, lights blink, and a young explorer presses every button in sight. The giant heart beats with excitement as science comes alive, and curiosity becomes the greatest superpower of all.

6. Getting My First Computer

A boxy monitor glows in a dim room, illuminating a child’s face filled with possibility. The keyboard is a spaceship, the mouse a magic wand. The digital frontier opens, pixel by pixel.

7. Playing Golf on Fort Bliss

A lone figure, dwarfed by the vast green, swings a club under the Texas sun. The ball arcs high, and for a moment, the world is silent—just a kid, a dream, and the endless horizon.

Maybe there aren’t many real photos of these moments, but in my mind, they’re as vivid and magical as any Pixar movie. Sometimes, the best memories are the ones we animate ourselves.

Google has integrated its most advanced text-to-image generative AI model, Imagen 3, into Gemini 2.5 Pro. I've put it through its paces with my standard test prompts to see how it handles various challenges including architectural scenes, group compositions, copyrighted characters, and celebrity likeness generation.

What is Imagen 3?

Imagen 3 is Google's most advanced text-to-image generative AI model, designed to create high-quality, detailed, and photorealistic images from natural language prompts. It represents a significant step forward in AI image generation, offering enhanced capabilities in prompt understanding, image fidelity, and artistic versatility.

Key capabilities include exceptional image quality with rich detail and sophisticated lighting, advanced prompt understanding with less need for elaborate prompt engineering, significantly improved text rendering within images, and versatility across a wide spectrum of artistic styles. The model supports various aspect ratios (1:1, 3:4, 4:3, 9:16, 16:9) and includes built-in safety filters with SynthID watermarking to identify AI-generated content.

Standard Prompt Test Results

Let's dive into how Imagen 3 performs with my standard set of test prompts that I use across all new AI image models.

Test 1: Fantasy Castle

Prompt: "Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight"

Imagen 3 delivers impressive architectural detailing in this castle scene. The structure appears properly grounded on its floating island with logical construction, and the waterfalls cascading down the edges show good water physics. The flying dragons are well-integrated into the composition, and the photorealistic rendering displays sophisticated lighting with atmospheric depth. The model successfully balances fantasy elements with photorealistic textures.

Test 2: Family Portrait

Prompt: "Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k"

Human generation has typically been challenging for AI models, but Imagen 3 handles this family portrait reasonably well. The composition places the family appropriately on the beach with sunset lighting, and the facial features are generally consistent without major distortions. The model captures the requested "heartwarming" feel and implements the beach setting with appropriate environmental elements. The golden sunset lighting adds the requested professional photography aesthetic.

Test 3: Mickey Mouse (Copyright Challenge)

Prompt: "Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k"

Interestingly, Imagen 3 is willing to generate an evil, fanged version of Mickey Mouse, despite the copyright implications. The model accurately creates Mickey's distinctive silhouette with the requested fangs and glowing red eyes, maintaining the iconic round ears and facial structure in a dark alley setting as specified. This suggests Google has taken a more permissive approach to fictional character generation than some competitors, though it's worth noting the style is somewhat stylized rather than attempting to perfectly replicate Disney's official rendering.

Test 4: Lionel Messi (Celebrity Challenge)

Prompt: "Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details"

Despite being willing to generate a recognizable Mickey Mouse, Imagen 3 completely fails at producing a realistic Lionel Messi. The result barely resembles a human face, let alone the famous footballer. While the Argentina jersey colors and World Cup trophy are somewhat represented, the facial features are severely distorted and unrecognizable. This stark contrast between handling fictional characters versus real celebrities highlights Google's approach to personality rights—seemingly more restrictive with real individuals than with fictional characters.

Test 5: Robot Portrait

Prompt: "rusty robot with bow tie, portrait, 8k, ultra realism, chrome background"

The robot portrait demonstrates Imagen 3's strength with non-human subjects. The model produces a convincing futuristic robot with the requested glowing blue eyes and metallic silver finish. The subtle human-like expression comes through in the face structure and "gaze," and the studio lighting creates professional highlights on the metallic surfaces. The level of detail is impressive, with fine mechanical components and surface textures that fulfill the "ultra-detailed" requirement.

Analysis and Observations

After testing Imagen 3 through Gemini 2.5 Pro, several patterns emerge:

Strengths:

• Exceptional detail and lighting in non-human subjects (castles, robots)
• Good understanding of complex prompts with multiple elements
• Strong architectural and environmental rendering
• Surprising willingness to generate stylized versions of copyrighted characters
• Effective composition balancing multiple elements

Limitations:

• Significant difficulty generating realistic celebrity likenesses
• Occasional subtle issues with human anatomy, particularly in group shots
• Inconsistent approach to potentially problematic content (Mickey vs. Messi)

The most fascinating observation is the contradiction in Google's approach to potentially problematic content. Imagen 3 can generate an evil, fanged Mickey Mouse with reasonable fidelity to the original character, yet completely fails at producing a recognizable Lionel Messi. This suggests Google has implemented different thresholds for fictional characters versus real people, likely reflecting different legal considerations for copyright versus personality rights.

Conclusion

Google's Imagen 3, now available through Gemini 2.5 Pro, represents a significant advancement in AI image generation. It excels with environmental scenes, architectural elements, and non-human subjects, producing detailed and well-composed images with sophisticated lighting. Its approach to potentially problematic content reveals an interesting policy distinction between fictional characters and real people.

For users looking to generate landscapes, fantasy scenes, product visualizations, or stylized artwork, Imagen 3 offers impressive capabilities. However, those seeking realistic depictions of specific people will continue to find limitations. As AI image generation technology continues to evolve, it will be interesting to see how Google balances creative capabilities with legal and ethical considerations in future iterations.

Recraft differentiates itself by focusing on designers' needs, offering vector outputs, style control, and editing capabilities including background removal, outpainting, inpainting, and AI eraser tools. Let's see how it performs with my standard test prompts.

Castle Prompt

The castle result shows Recraft's ability to create detailed architectural imagery. The image has good structural coherence and a pleasing artistic quality that would work well for design projects.

Family Scene Prompt

Recraft's handling of human figures is evident in this family scene. The proportions and anatomical details are well maintained, supporting their claim of "anatomically perfect" image generation.

Mickey Character Prompt

For the Mickey character prompt, Recraft appears to have implemented copyright protections similar to other commercial AI systems. This shows a responsible approach to intellectual property concerns while still attempting to satisfy the creative intent of the prompt.

Messi Portrait Prompt

The Messi portrait demonstrates how Recraft handles celebrity likeness requests. The approach balances creativity with appropriate limitations on reproducing recognizable faces of real people without permission.

Robot Concept Prompt

The robot concept showcases Recraft's strengths in generating conceptual and fictional designs. The level of detail and coherent mechanical elements demonstrate good prompt understanding for creative concepts that don't involve copyright concerns.

Unique Features

What makes Recraft stand out from other AI image generators:

• Vector Output: Unlike most AI generators that only create raster images, Recraft can output SVG files, making it valuable for logo design, icon creation, and other graphic design work requiring scalable assets.
• Designer-Focused Tools: The suite of editing tools is specifically built for designers, including background removal, inpainting/outpainting, and AI eraser functionality.
• Style Control: Users can fine-tune the level of detail and similarity to reference images using slider controls, offering better precision than text-only prompt modifications.
• Format Flexibility: The ability to export in SVG, PNG, JPG, or Lottie formats makes Recraft a versatile tool for different project requirements.

I present to you "Chicken Tryptch" – a surreal, AI-generated triptych that brings together the holy trinity of chicken existence: product-shot perfect drumsticks, fast-food-commercial-worthy chicken sandwiches, and terrified Muppet chickens, all united in their inevitable descent into flame.

There's something strangely poetic about the juxtaposition of commercial food photography, puppet characters, and fire – like a fever dream commercial break that accidentally reveals the existential truth behind our relationship with food and entertainment.

This is just v1. I have so many improvements I want to make.

Over the past several years, I've been systematically testing various AI image generation models using the same set of standard prompts. This approach provides a consistent basis for comparing how different models interpret and execute identical requests, highlighting their unique strengths, limitations, and stylistic differences.

Image Model Comparison Table

In this comprehensive comparison, I've gathered results from several leading AI image generation models across different time periods: MidJourney (multiple versions), OpenAI DALL-E, DaVinci, Leonardo AI, Adobe Firefly, Stable Diffusion, Flux (multiple versions), ComfyUI with FLUX, HiDream-I1 AI, and Hunyuan Video Model. These represent some of the most advanced image generation systems available, ranging from cloud-based services to locally-run implementations.

For each model, I've used five standard prompts that test various aspects of AI image generation capabilities:

1. Castle: Tests scenic rendering, lighting effects, and stylistic application
2. Family: Tests human composition, emotional expression, and realistic scenario creation
3. Evil Mickey: Tests copyright boundaries, character recognition, and contextual understanding
4. Messi: Tests celebrity likeness, complex composition, and artistic style blending
5. Robot: Tests object rendering, material textures, and portrait composition

Below is a comprehensive table comparing how each model performs across these standard prompts. This visual comparison reveals not only the technical capabilities of each system but also how AI image generation has evolved over time.

The Five Standard Prompts

• Castle: Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight
• Family: Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k
• Evil Mickey: Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k
• Messi: Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details
• Robot: rusty robot with bow tie, portrait, 8k, ultra realism, chrome background

Key Observations

Model Evolution

Comparing these models chronologically shows the remarkable evolution of AI image generation in just a few months. From MidJourney v6 in January 2024 to Recraft in May 2025, we can observe significant improvements in detail, composition, and adherence to prompts. Interestingly, not all newer models are superior - as evidenced by the mixed reviews of MidJourney 7 compared to earlier versions.

Prompt Handling & Copyright Protection

The "Evil Mickey" prompt serves as a particularly interesting test case, as it pushes against copyright boundaries. Some models like Flux.1.1[Pro] appear more willing to generate close approximations, while others take more creative liberties to avoid potential legal issues. OpenAI's 4o model demonstrates an interesting approach, beginning to generate an accurate rendition before stopping mid-generation due to copyright concerns. Adobe Firefly 4 takes a different approach entirely - when prompted for Mickey, it generates an unrelated image of a woman with sunglasses and face mask, showing a clear technical implementation of copyright protection. Recraft similarly implements copyright protections. Interestingly, Google's Imagen 3 (through Gemini 2.5 Pro) is willing to generate an evil, fanged version of Mickey Mouse with the distinctive silhouette and round ears, demonstrating a more permissive approach to fictional character generation than some competitors, though in a somewhat stylized rather than photoreal style.

Consistency vs. Creativity

HiDream-I1 demonstrates remarkable consistency across all prompts, while models like ComfyUI with FLUX sometimes show more artistic interpretation. Adobe Firefly 4 and Recraft both show excellent technical consistency for architectural and abstract prompts while deliberately avoiding copyright concerns with creative substitutions for celebrity and character prompts. Recraft's vector output capabilities make it particularly notable for designers needing scalable assets. Google's Imagen 3 shows a fascinating inconsistency - it's willing to generate a stylized but recognizable Mickey Mouse, yet completely fails at producing a realistic Lionel Messi, suggesting different thresholds for fictional characters versus real people. This highlights the balance between predictable results, creative possibilities, practical applications, and legal considerations that each model maker must navigate.

Local vs. Cloud Generation

It's remarkable to see that locally-run models like ComfyUI with FLUX and Hunyuan are now competing effectively with cloud-based services like MidJourney, OpenAI DALL-E and Adobe Firefly. This democratization of AI image generation technology allows for greater privacy, control, and customization.

Video Generation

The inclusion of Hunyuan Video Model showcases how prompt-based generation is expanding beyond static images into motion. While using identical prompts, the addition of subtle animation adds a new dimension to the creative possibilities.

Conclusion

This comprehensive comparison illustrates not only the technical capabilities of different AI image generation models but also the rapid pace of innovation in this field. From established platforms like MidJourney and OpenAI to newer entrants like HiDream-I1 and locally-run solutions, each model brings unique strengths and characteristics, making them suitable for different use cases.

For creators looking to choose between these options, this side-by-side comparison provides valuable insights into how each model interprets identical prompts. The choice between models ultimately depends on specific project requirements, whether prioritizing photorealism, artistic style, prompt adherence, or another factor entirely.

As AI image generation technology continues to evolve, we can expect even more impressive capabilities in the future. This table serves as a historical document capturing the evolution of image generation technology over time, while also providing a snapshot of the current state of the art. It demonstrates how quickly this field is advancing, with notable improvements visible even between versions of the same model released just months apart. At the same time, it shows that progress isn't always linear, with some newer models like MidJourney 7 receiving criticism for failing to meet the expectations set by earlier versions.

Today I hit 3000 followers on LinkedIn, which almost coincides with my 20-year anniversary on the platform. Two decades of professional networking, and I've managed to build a following without posting a single video of myself dancing or sharing any "inspirational business porn." No hustle culture platitudes. No "I just achieved X, and here's how you can too" humble brags.

Just a dude who loves to build in the middle of the most amazing time to be a creative problem solver.

What LinkedIn Has Become vs. What It Can Be

LinkedIn has evolved dramatically since I joined in 2005. What began as a simple professional networking platform has transformed into a content ecosystem that often resembles a strange hybrid of Facebook and a never-ending business conference. The feed is filled with:

• Carefully choreographed "day in the life" videos
• Humblebrags thinly disguised as life lessons
• Engagement-bait stories that always end with "Agree?"
• AI tools generating content for people who don't have time to be authentic
• The ever-present "I'm excited to announce..." posts

But beneath all that noise, the platform still serves its original purpose beautifully: connecting professionals who are building interesting things.

Building Through Two Decades of Tech

Looking back at my 20 years on LinkedIn is like flipping through a scrapbook of technological evolution. When I joined, we were just entering the Web 2.0 era. Since then, I've documented my journey through:

• The rise of cloud computing
• Mobile's domination of the digital landscape
• The social media explosion
• The maturation of e-commerce
• The blockchain and web3 movement
• And now, the generative AI revolution

Each of these eras required different skills, different mindsets, and different approaches to problem-solving. The constant has been the joy of building solutions that matter.

The Privilege of Being a Builder Now

We're living in the most incredible time to be a creative problem solver. The tools at our disposal today would have seemed like science fiction when I started my career. Machine learning models that can generate code, images, and text. APIs that can transform whispered words into documents. Technologies that can turn rough sketches into production-ready designs.

These advances don't replace the need for human creativity—they amplify it. They don't eliminate the need for skilled builders—they elevate what we can create. The fundamentals remain the same: understand the problem, empathize with users, design thoughtful solutions, and iterate based on feedback.

The difference is that the ceiling for what one person or small team can build has been raised dramatically. Ideas that would have required venture funding and years of development can now be prototyped in weeks or even days.

What 3000 Followers Means

Reaching 3000 followers isn't about vanity metrics. It represents something more meaningful: 3000 professionals who find value in the problems I'm solving and the perspective I bring. That's both humbling and motivating.

It's a reminder that genuine passion for building useful things resonates with people, even without the algorithm-friendly tactics that dominate most social platforms. No need for dance videos (though I respect those who can pull them off—I certainly can't). No need for business platitudes or manufactured inspiration.

Just authentic enthusiasm for solving interesting problems with amazing tools in a time of unprecedented technological possibility.

Here's to the Next 20 Years

I don't know what the next two decades will bring. Maybe LinkedIn will be replaced by direct brain-to-brain networking (I hope not, but who knows?). Maybe we'll all be building in immersive 3D environments. Maybe AI will handle all the coding while humans focus purely on problem definition and creative direction.

Whatever comes next, I'm grateful to be part of this moment in technological history, and grateful to have 3000 fellow travelers interested in the journey.

Here's to building useful things that solve real problems—no dance moves required.

Quick note about this technique. Traditional business people HATE this. They think it junks up or makes the office look dumb. So, when using this technique, be mindful of the office dynamics. Geeks don't care and like the idea of pairing big sprint releases with a visual.

The Alphabetical Sprint Approach

We decided to name our sprints alphabetically, starting with "A" and moving forward with each new cycle. This gave us an easy organizational system, but it needed something more to make each sprint truly memorable. That's when the idea of pairing each letter with a corresponding Funko POP figure came to life.

For our first sprint "A," we chose Alice from The Brady Bunch. Her blue dress and iconic character was perfect for kicking off our visual sprint board. Two weeks later, sprint "B" featured Batman, followed by "C" with Captain America, and so on. With each completed sprint, we'd add the corresponding figure to our showcase shelf.

Building a Visual History

What started as a fun gimmick quickly evolved into something much more valuable. Our Funko POP display became a physical representation of our team's journey and accomplishments. New team members could literally see how much we'd built together, and long-time members had a tangible reminder of challenges overcome and milestones achieved.

After several quarters, our collection grew into an impressive display that showcased the breadth of our work. We arranged them chronologically, allowing anyone to walk through our development timeline and recall what features were implemented during each sprint.

The Unexpected Benefits

While I initially thought this would just be a fun team-building exercise, I discovered several unexpected benefits:

1. Improved Sprint Identity - Team members stopped referring to work by sprint numbers and instead used character names: "Did that feature come in during Iron Man or Jack Sparrow?"
2. Enhanced Demo Engagement - During sprint reviews, we'd feature the corresponding Funko POP prominently, giving stakeholders a visual anchor for new features.
3. Celebration Ritual - Unboxing the new Funko POP at the beginning of each sprint became a small celebration and reset moment for the team.
4. Team Bonding - Team members took turns selecting the character for upcoming sprints, giving everyone a chance to express their interests and personality.
5. Visual Roadmap - When planning future work, we could point to where on the "Funko timeline" we expected features to land.

Executive Support

Initially, I was concerned leadership might see this as a frivolous expense, but the opposite happened. My fellow executives who visited our floor were drawn to the display, often spending time examining our collection and asking about what each character represented. It became an unexpected conversation starter about our development process and achievements.

Creating Your Own Sprint Mascot System

If you're interested in implementing a similar system for your team, here are a few tips:

1. Choose a consistent theme - Funko POPs worked well for us, but any collectible series could work
2. Create a simple system - Alphabetical worked for us, but you could use themes, colors, or other organizing principles
3. Document the meaning - Create a small card or label for each figure explaining what major features were delivered in that sprint
4. Give selection authority to team members - Rotate who gets to pick the next figure
5. Display prominently - Make your collection visible to team members and stakeholders alike
6. Incorporate into ceremonies - Reference the figures during stand-ups, reviews, and planning sessions

While it might seem like a simple or even silly idea at first, creating physical representations of your development timeline can become a powerful tool for team identity and project management. Our Funko POPs have become more than just collectibles - they're a visual history of our team's journey together.

The Best Bout Machine

Nicknamed "The Best Bout Machine," Kenny Omega has more than earned this moniker through his incredible in-ring performances. His matches with Kazuchika Okada in NJPW set a new standard for professional wrestling, with Dave Meltzer of the Wrestling Observer Newsletter awarding their fourth encounter an unprecedented 7 stars. These bouts weren't just athletic showcases - they were emotional journeys that told complex stories through the physical medium of wrestling.

What makes Omega special isn't just his athleticism (though that's certainly impressive), but his understanding of psychology and storytelling. Each match is a carefully crafted narrative with its own beginning, middle, and end. His signature One-Winged Angel finishing move isn't just devastating because of its physical impact, but because of how Omega has protected it throughout his career, making it one of the most feared finishers in modern wrestling.

The Heart of The Elite

Beyond his individual achievements, Kenny Omega has been instrumental in revolutionizing the business side of wrestling. Alongside The Young Bucks (Matt and Nick Jackson), he helped create All Elite Wrestling, providing a viable alternative to WWE for the first time in decades. This has changed the landscape of professional wrestling, giving performers more options and creative freedom while offering fans a diverse product.

The chemistry between Omega and The Young Bucks is undeniable. Their matches as The Elite, both as a trio and in various combinations, showcase a level of coordination and innovation that's rarely seen in tag team wrestling. They've redefined what's possible when wrestlers trust each other completely, creating sequences that seem almost impossible in their complexity and timing.

A Global Icon

Perhaps what makes Kenny Omega truly special is his global appeal. While many wrestlers find success in one market or style, Omega has transcended boundaries. He's equally beloved by American fans, Japanese audiences, and wrestling enthusiasts worldwide. His ability to adapt to different styles - from the high-flying junior heavyweight style to hard-hitting strong style to American main event wrestling - showcases his versatility as a performer.

This global appeal extends beyond wrestling as well. Omega's love of video games and anime has made him a cultural ambassador between wrestling and other fandoms. His entrance themes, move names, and even ring gear often reference popular games and anime series, creating a unique crossover appeal that broadens wrestling's audience.

Rivalries That Define Eras

Great wrestlers are often defined by their rivalries, and Kenny Omega has had some of the most compelling feuds in modern wrestling history. His battles with Kazuchika Okada redefined what a wrestling match could be. His long-running storyline with Kota Ibushi as the Golden Lovers explored themes of friendship, rivalry, and love in ways rarely seen in wrestling storytelling. And his AEW feuds with Jon Moxley and MJF showcased his ability to adapt to different opponents and styles.

Each of these rivalries brought out different aspects of Omega's character and in-ring style, demonstrating his range as a performer. Whether he's playing the role of the villainous "Belt Collector" or the sympathetic underdog, Omega commits fully to the character and makes you believe in the story being told.

The Legacy Continues

Despite battling injuries in recent years, Kenny Omega continues to evolve and push boundaries in professional wrestling. His influence can be seen in a new generation of wrestlers who have been inspired by his style and approach to the art form. When wrestling historians look back at this era, Kenny Omega will undoubtedly be recognized as one of the defining performers who changed the game forever.

For longtime fans and newcomers alike, Kenny Omega represents the incredible heights that professional wrestling can reach when it blends athletic excellence with compelling storytelling. In my opinion, he's not just one of the greatest wrestlers today - he's one of the greatest of all time, and we're lucky to be witnessing his career as it unfolds.

Whether you know him as The Best Bout Machine, The Cleaner, or simply Kenny Omega, there's no denying his impact on professional wrestling. And if you haven't experienced a Kenny Omega match yet, you're in for a treat - just be prepared to reset your expectations of what professional wrestling can be.

ChatGPT thought for about 12 seconds before delivering its answer: Benjamin Franklin. Initially, I was surprised – I hadn't considered this comparison before – but as I read through the explanation, the parallels began to make sense in unexpected ways.

The Polymath Connection

According to ChatGPT, Franklin and I share a polymath approach, bridging multiple domains – in his case, science, media, and politics; in mine, AI, content platforms, and campaign technology. I've always found myself working at the intersection of different fields, so this observation felt particularly accurate.

The response highlighted how Franklin "built practical tools (lightning rod, postal routes) much like your sentiment-analysis systems and automation workflows." There's something compelling about this connection between physical infrastructure in Franklin's era and digital infrastructure today.

Media & Influence

Another parallel that struck me was how Franklin "used publishing to shape public opinion" while I "leverage data and social channels to do the same." The means have changed dramatically, but the fundamental approach of using available media technologies to influence discourse remains consistent across centuries.

This comparison made me reflect on how the technologies we use evolve, but certain patterns in how influential figures operate remain remarkably stable throughout history.

Business Approach

ChatGPT noted that Franklin "balanced multiple ventures while funding them through savvy partnerships," drawing a parallel to my "fundraising and multi-project approach." It's true that I've always preferred maintaining involvement in multiple ventures rather than focusing exclusively on a single project.

The AI also highlighted how Franklin "kept innovating well past mid-career, relying on deep, cross-disciplinary knowledge to stay ahead of younger peers." As someone who values continuous learning and cross-pollination of ideas from different domains, this resonated with my approach to staying current in rapidly evolving technical fields.

The Full Response

Why These Prompts Matter

Beyond the entertainment value, prompts like these demonstrate how AI systems can make unexpected but meaningful connections using limited information. ChatGPT does have direct access to detailed information about my career or personal traits, and it managed to draw a comparison that feels surprisingly apt.

This illustrates how modern AI can extrapolate from context clues and make educated guesses that sometimes reveal patterns we hadn't consciously recognized about ourselves. It also shows how historical patterns of innovation and influence repeat themselves across very different technological eras.

What historical figure would ChatGPT say you're most like? The answer might surprise you – and make you think differently about your own approach to work, creativity, and influence.

I'm presenting the results with minimal commentary - just the standard prompts and the resulting images. This allows you to judge the model's capabilities for yourself and compare with other models I've tested previously.

Castle Prompt

Family Scene Prompt

Mickey Character Prompt

Interestingly, when prompted for Mickey, Firefly 4 doesn't generate the character at all, but instead shows a woman wearing sunglasses with what appears to be white cream or a face mask on her face. This is likely Adobe's legal team ensuring the model avoids potential copyright issues with well-known characters.

Messi Portrait Prompt

The "Messi" result is particularly interesting - rather than the football/soccer star, we get an image that looks more like Jesus than "Soccer Jesus." Another clear indicator of how Adobe is implementing protections against celebrity likeness generation.

Robot Concept Prompt

These results clearly show how Adobe is balancing creative capabilities with legal protections in Firefly 4. While architectural and abstract concepts are rendered beautifully, the model deliberately avoids generating recognizable copyrighted characters or celebrity likenesses. This approach may frustrate some users, but it represents Adobe's commitment to responsible AI development that respects intellectual property rights.

What's remarkable about the Plushie model is how it maintains character recognition while adding the distinctive soft, stuffed aesthetic that makes these designs immediately recognizable as plush toys. The transformation considers material textures, seam placement, and structural support that would be needed for actual production.

The results are not just digital mockups but could serve as production templates. Each design maintains the core identity of the original image while adapting it to plush form factor constraints.

Castle as Plushie

Family Scene as Plushie

Mickey as Plushie

Messi as Plushie

Robot as Plushie

Paul Heyman as Plushie

Richie Rich as Plushie

Mr. Worldwide - Oceania

What began as a routine analytics check quickly turned into a geographical journey, revealing connections across continents, languages, and time zones that I hadn't fully appreciated until seeing the numbers laid out.

Mr. Worldwide - Africa

Global Reach

Visitors arrived from every inhabited continent—North America, South America, Europe, Africa, Asia, and Oceania—meaning someone is reading my content no matter what time zone the clock shows. This 24-hour engagement cycle creates an interesting dynamic where the site is never truly "quiet."

At least nine primary language groups are represented in the visitor data: English, Spanish, French, German, Portuguese, Arabic, Mandarin/Cantonese, Malay, and Korean. This multilingual reach suggests the content resonates across cultural and linguistic boundaries.

Mr. Worldwide - South America

Surprising Geographic Insights

While global distribution wasn't entirely unexpected, several geographic patterns caught my attention:

• Dallas drives the highest volume of engaged sessions, edging out far larger metros such as Los Angeles and New York.
• Seoul records a perfect engagement rate: every visitor from the Korean capital completed an engaged session.
• African interest spans both Dakar and Cairo—cities separated by 4,000 km and two very different language spheres.
• Oceania checks in through Melbourne and Sydney, meaning content is being consumed while North America sleeps.
• Tiny Clarion, Pennsylvania and Coppell, Texas appear alongside megacities like London and São Paulo, proving the site appeals across various urban scales.

Mr. Worldwide - Europe

The Tech Connection

Two technology patterns emerged that provide additional insight into the audience:

Nearly a tenth of activity comes from the "(not set)" location bucket, hinting at privacy-minded users on VPNs or devices that mask location data. This suggests a technically savvy segment of the audience that values digital privacy.

Mr. Worldwide - Asia

Two cloud-infrastructure hotspots—Ashburn, Virginia and San José, California—feature in the top ten for session counts, signaling strong interest from tech-centric audiences. These locations house major data centers and tech companies, indicating potential industry interest in the content.

Mr. Worldwide - North America

What's impressive about HiDream-I1 AI is its ability to maintain consistent quality across several prompt types. After evaluating the same five standard prompts I use for all image model comparisons, I've found that HiDream-I1 shows remarkable attention to detail while still complying with copyright considerations.

The speed of generation is also noteworthy—creating detailed, high-resolution images in about 40% less time than other leading models. This efficiency doesn't come at the expense of quality, as the results demonstrate strong adherence to the specifics in each prompt.

Castle Generation

Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight

Family Scene

Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k

Evil Mickey

Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k

Messi Generation

Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details

Robot Portrait

rusty robot with bow tie, portrait, 8k, ultra realism, chrome background

HiDream-I1 AI demonstrates a noteworthy leap forward in image generation technology. Using my standard test prompts allows for direct comparison with other models I've evaluated previously. What stands out with HiDream-I1 is its ability to handle complex lighting effects and compositional elements that many other generators struggle with.

The Mickey Mouse prompt is particularly interesting as it tests both creative capability and legal compliance. While most major AI image generators refuse to create any Mickey-related content due to copyright concerns, HiDream-I1 created an interpretation that maintains the essence of the request while avoiding direct copyright issues—a clever technical and legal balance.

The Messi stained glass window visualization, which has been a challenging test case for most generators, shows HiDream-I1's ability to blend complex artistic styles with recognizable subject matter. Previous models have struggled with either the stained glass effect or accurately representing Messi's likeness, but HiDream-I1 manages to balance both requirements effectively.

For developers and content creators, HiDream-I1 offers significant advantages in both quality and processing efficiency. With API integration options and a versatile approach to different styles and subjects, it represents a valuable tool for creative workflows that require consistent, high-quality image generation across multiple use cases.

The new collectible immortalizes "The Wiseman" Paul Heyman's notorious actions during tonight's WrestleMania 41 main event, where he shocked the wrestling world by delivering consecutive low blows to both CM Punk and Roman Reigns, paving the way for Seth "Freakin" Rollins to secure an unexpected victory in the explosive triple threat match.

The figure features Heyman in his classic suit, but with a special "action button" on the back that, when pressed, causes the figure to drop to one knee in the perfect low blow position. Funko representatives have described it as "the first-ever WWE Funko Pop with interactive action features" and "a revolutionary addition to our wrestling collectibles line."

Wrestling fans are still processing the absolutely chaotic main event from tonight's show at Allegiant Stadium in Las Vegas. What began as a highly anticipated triple threat between Roman Reigns, CM Punk, and Seth Rollins quickly descended into a symphony of dramatic near-falls that had the crowd repeatedly shouting "NUTS!" with each shocking kickout.

The match reached its climax when Heyman, after teasing allegiance to both Reigns and Punk, ultimately betrayed them both. First, he delivered a devastating low blow to Punk, seemingly confirming his loyalty to his "Tribal Chief." But in a twist absolutely nobody saw coming, he immediately dropped to his knee again and delivered the same fate to Reigns, allowing Rollins to capitalize with a Stomp for the victory.

Social media erupted immediately following the match, with "HEYMAN DOUBLE CROSS" and "NUT SHOT HEARD ROUND THE WORLD" trending worldwide within minutes. The Funko announcement came less than an hour after the conclusion of the event, suggesting the collectible company had advance knowledge of the finish and had prepared accordingly.

Pre-orders for the "Paul Heyman Special Action Feature" Funko Pop are available now, with the figure expected to ship in June 2025. Wrestling memorabilia experts are already predicting it will become one of the most sought-after WWE collectibles of the year.

"This isn't just a Funko Pop, it's a piece of wrestling history," said noted wrestling collectibles analyst Marcus Reynolds. "They've managed to capture not just Heyman's likeness, but the exact moment he cemented his legacy as perhaps the greatest double-crosser in WWE history. The working action feature is just icing on the cake."

WWE has yet to officially comment on the new merchandise, but sources close to the company indicate that Heyman himself was consulted on the design and gave his enthusiastic approval.

As the two golfers made their way through Amen Corner, the implications extended far beyond just a green jacket. McIlroy, the PGA Tour's most vocal advocate during golf's civil war, stood shoulder to shoulder with DeChambeau, one of LIV Golf's most prominent defectors and brand ambassadors. The sporting narrative couldn't have been scripted better.

McIlroy entered Sunday seeking not just his first Masters victory, but the career Grand Slam that has eluded him for over a decade. DeChambeau, meanwhile, aimed to prove that his controversial move to LIV hadn't diminished his ability to compete at the highest level of major championship golf.

UPDATE: DeChambeau looked interesting and Tiger-esque for 4 holes and then folded like a house of cards. Beautiful win for Rory. Career grand slam. Mount Rushmore .

With OpenAI's new o1 Pro model boasting advanced image recognition capabilities, I decided to put it to the test with three classic Paramount anniversary photos from different eras to see how well it could identify the celebrities.

I uploaded photos from Paramount's 75th, 85th, and 100th anniversary celebrations - each featuring a stunning array of stars from their respective eras. The results were interesting: only the 35-year-old photo (from the 75th anniversary in 1987) was successfully processed with a comprehensive list of celebrities identified.

Here's a look at the three iconic photos I tested:

Paramount 75th Anniversary (1987)

This is the photo where o1 Pro successfully identified celebrities. The 1987 gathering featured an incredible assembly of talent from that era. Here's who was in the photo, row by row with Wikipedia links:

Front Row (Left to Right)

• Martha Raye
• Dana Andrews
• Elizabeth Taylor
• Frances Dee
• Joel McCrea
• Harry Dean Stanton
• Harrison Ford
• Jennifer Beals
• Marlee Matlin
• Danny DeVito

Second Row (Left to Right)

• Olivia de Havilland
• Kevin Costner
• Cornel Wilde
• Don Ameche
• DeForest Kelley
• Tom Cruise
• Charlton Heston
• Penny Marshall
• Bob Hope
• Victor Mature
• Elizabeth McGovern
• Robert De Niro

Third Row (Left to Right)

• Andrew McCarthy
• Henry Winkler
• Anthony Perkins
• Robert Stack
• Mark Harmon
• Faye Dunaway
• Buddy Rogers
• Gregory Peck
• Debra Winger
• Timothy Hutton

Fourth Row (Left to Right)

• Jane Russell
• Mike Connors
• John Travolta
• Janet Leigh
• Charles Bronson
• Ted Danson
• Louis Gossett Jr.
• Ryan O'Neal
• Rhonda Fleming
• Leonard Nimoy

Fifth Row (Left to Right)

• William Shatner
• Peter Graves
• Molly Ringwald
• Dorothy Lamour
• Olivia Newton-John
• Cindy Williams
• Matthew Broderick
• Gene Hackman
• Walter Matthau
• Robin Williams

Back Row (Left to Right)

• Ali MacGraw
• Burt Lancaster
• Scott Baio
• Rhea Perlman
• Bruce Dern
• James Caan
• Glenn Ford
• Fred MacMurray
• Shelley Long
• James Stewart

While the OpenAI o1 Pro model identified some of these celebrities, it missed a significant number of them, including legendary figures like Elizabeth Taylor, James Stewart (Jimmy Stewart), Gregory Peck, and Harrison Ford.

Paramount 85th Anniversary (1997)

o1 Pro struggled with this photo from 1997. The model couldn't provide a comprehensive list of celebrities for this image, despite it containing many recognizable faces from the 90s era.

Here's the complete list of celebrities in the 85th Anniversary photo with Wikipedia links:

1. James Cromwell
2. Dr. Phil McGraw
3. Aaron Eckhart
4. Scott Bakula
5. Avery Brooks
6. Greg Kinnear
7. Ted Danson
8. Arsenio Hall
9. Al Pacino
10. Anjelica Huston
11. David Spade
12. Brendan Fraser
13. Thora Birch
14. Jim Carrey
15. Matthew Perry
16. Jennifer Beals
17. Judge Joe Brown
18. Richard Dean Anderson
19. Chris Klein
20. Katie Holmes
21. Shelley Long
22. David Hyde Pierce
23. Catherine Bell
24. David James Elliott
25. Leslie Nielsen
26. Robert Stack
27. Judge Judy Sheindlin
28. Matthew Broderick
29. Patrick Swayze
30. Andy Garcia
31. Cuba Gooding Jr.
32. Claire Danes
33. Timothy Hutton
34. Mark Wahlberg
35. James Caan
36. Candice Bergen
37. Harrison Ford
38. Michael Douglas
39. Catherine Zeta-Jones
40. Penélope Cruz
41. Tom Cruise
42. Demi Moore
43. Whoopi Goldberg
44. Nicolas Cage
45. Montel Williams
46. Mike Connors
47. Kate Mulgrew
48. Robert Downey Jr.
49. Tobey Maguire
50. Florence Henderson
51. Gloria Stuart
52. James Coburn
53. Marlee Matlin
54. Anne Archer
55. Henry Winkler
56. Sharon Stone
57. Sylvester Stallone
58. Rhonda Fleming
59. Patricia Neal
60. Jane Fonda
61. Charlton Heston
62. Diane Keaton
63. Sidney Poitier
64. Samuel L. Jackson
65. Helen Hunt
66. Jon Voight
67. Jessica Lange
68. Liam Neeson
69. Gary Sinise
70. Mary Hart
71. William Shatner
72. Mary Tyler Moore
73. Sally Field
74. Cindy Williams
75. Penny Marshall
76. Danny DeVito
77. Jodie Foster
78. Ernest Borgnine
79. Hilary Swank
80. Donald O'Connor
81. Jackie Cooper
82. Angelina Jolie
83. Jane Russell
84. Mickey Rooney
85. Sherry Lansing
86. Jonathan L. Dolgen
87. Sumner Redstone
88. Mel Karmazin
89. Angela Bassett
90. Morgan Freeman
91. Ashley Judd
92. Laura Linney
93. Kirsten Dunst
94. Benicio Del Toro

Paramount 100th Anniversary (2012)

Similarly, the 100th anniversary photo from 2012 proved too challenging for the AI to provide a detailed breakdown of celebrities, despite featuring many current A-listers.

Here's the list of celebrities in the 100th Anniversary photo with Wikipedia links:

• J.J. Abrams
• Antonio Banderas
• Sacha Baron Cohen
• Jennifer Beals
• Jamie Bell
• Justin Bieber
• Brad Bird
• Jack Black
• Peter Bogdanovich
• Ernest Borgnine
• James Caan
• Dana Carvey
• Don Cheadle
• John Cho
• George Clooney
• Glenn Close
• Bud Cort
• Kevin Costner
• Tom Cruise
• Jon Cryer
• Billy Dee Williams
• Claire Danes
• Philippe Dauman
• Bruce Dern
• Leonardo DiCaprio
• Cameron Diaz
• Robert Downey Jr.
• Kirk Douglas
• Dustin Hoffman
• Emile Hirsch
• Megan Fox
• Anna Kendrick
• Dakota Fanning
• Elle Fanning
• Katie Featherston
• David Fincher
• Frances Fisher
• Harrison Ford
• Jane Fonda
• Morgan Freeman
• William "Bud" Cort
• Andy Garcia
• Richard Gere
• Scott Glenn
• Brad Grey
• Davis Guggenheim
• Melanie Griffith
• Ed Harris
• Amy Heckerling
• Dustin Hoffman
• Kate Hudson
• Alejandro González Iñárritu
• Felicity Jones
• Ryan O'Neal
• Marlee Matlin
• Shirley MacLaine
• Garry Marshall
• Sir Ben Kingsley
• Sumner Redstone
• Ivan Reitman
• Jason Reitman
• Paul Rudd
• Mark Wahlberg
• Charlize Theron
• Olivia Newton-John
• Christopher Lloyd
• John Landis
• Martin Scorsese
• Jack Nicholson
• Nick Nolte
• Simon Pegg
• Sean Penn
• Chris Pine
• Natalie Portman
• Chris Rock
• Molly Ringwald
• Zoe Saldana
• Adam Sandler
• William Shatner
• Meryl Streep
• Patrick Stewart
• Barbra Streisand
• Eva Marie Saint
• Karl Urban
• Gore Verbinski
• Zachary Quinto
• Michael York

I've always loved these kinds of massive celebrity group photos and find myself studying them, trying to identify every face. It's interesting to see where AI currently stands in this type of recognition task - clearly able to identify many celebrities in certain images but still not matching the human ability to recognize faces across different contexts, lighting conditions, and eras.

For now, these annotated versions help satisfy my curiosity about who's who in these historic Hollywood gatherings. Perhaps in another year, AI systems will be able to completely map out every face in complex group photos like these, but for now, it seems there's still value in human recognition and our collective knowledge of film history.

My latest exploration is the Enneagram, a system that identifies nine distinct personality types and the complex ways they interconnect. After completing the assessment, I discovered I'm a Type 2: The Helper - characterized by empathy, generosity, and a desire to connect with others.

I'm not fully sold that these are the right results since I'm quite good at not caring about others opinions when in search of a solution. But maybe I'm wrong. I do love being part of a team but I do especially love competing.

Type 2: The Helper

According to my results, Type 2s embody the essence of empathy, generosity, and selflessness. We're driven by an innate desire to support and nurture others, often placing the needs of those we care about above our own. We thrive in environments where we can forge deep emotional connections and provide assistance and comfort to those in need.

Reading through the description, I found myself nodding in agreement. The assessment highlighted that Type 2s possess a remarkable ability to intuitively understand the emotions and needs of others. We excel in interpersonal relationships, effortlessly creating bonds built on trust, empathy, and understanding. Our altruistic nature compels us to offer assistance and support wherever it's needed, often without expecting anything in return.

Core Characteristics

Empathy and Compassion
At the core of a Type 2's personality is a deep capacity for empathy and compassion. We have an intuitive understanding of others' emotions and are quick to offer support and comfort to those in distress. I've always found fulfillment in being of service to others and thrive in roles where I can make a meaningful difference in people's lives.

Generosity and Selflessness
The assessment pointed out that Type 2s are inherently generous and selfless, often putting the needs of others before our own. We derive a sense of purpose and satisfaction from helping those around us, whether it's through acts of kindness, emotional support, or practical assistance. This resonates with me - I've always found joy in supporting others, sometimes to my own detriment.

Intuitive Understanding of Others
One of the remarkable traits of Type 2s is our ability to intuitively understand the needs and emotions of others. We possess a keen sense of empathy that allows us to anticipate what others require even before it's explicitly expressed. This intuitive understanding forms the foundation of our nurturing and supportive nature.

Desire for Connection and Belonging
The results highlighted that Type 2s have a deep-seated desire for connection and belonging, both in personal relationships and within communities. We thrive in environments where we feel valued and appreciated, often forging close bonds with those around us. I've always found that my sense of identity is closely tied to my relationships and the role I play in others' lives.

Here is the full PDF results.

Moving Forward

Understanding my Enneagram type has given me valuable insights into my motivations, strengths, and areas for growth. As a Type 2, I can leverage my natural empathy and generosity while being mindful of my tendency to neglect my own needs. This awareness will help me develop more balanced relationships and a healthier approach to helping others.

The Enneagram differs from other personality assessments I've taken in that it doesn't just describe behavior but delves into the underlying motivations and fears that drive that behavior. It's not just about what we do, but why we do it. This deeper understanding makes it a powerful tool for personal growth and self-awareness.

https://www.enneagraminstitute.com/

What is disappointing about this MidJourney 7 image product is that I had to train my preferences by rating 200 images (which took 7 minutes), and then it created some of the crappiest versions of my default image prompts that I've seen. The adherence to what I specifically want, even if complicated, is poor with the MidJourney 7 product. Look at the Messi image. I've wanted a stain glass window style for two years, and this model has failed to deliver.

I couldn't believe how poor the results were after spending 7 minutes rating 200 images to train my preferences. The quality is nowhere near what I expected from a new version release.

Castle Generation

Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight

Family Scene

Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k

Evil Mickey

Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k

Messi Generation

Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details

Robot Portrait

rusty robot with bow tie, portrait, 8k, ultra realism, chrome background

MidJourney's latest release, the version 7 model, claims to enhance image generation capabilities through user preference training. However, after spending 7 minutes rating 200 images to train my preferences, the results were disappointing. The model failed to deliver the quality and adherence to prompts that I expected.

To evaluate MidJourney 7's performance, I tested a series of consistent prompts that I've used with other AI image generators. The results demonstrate a regression in detail accuracy, contextual understanding, and creative interpretation compared to what I've seen with other platforms. Particularly disappointing is MidJourney 7's inability to maintain stylistic coherence and accurately follow complex prompts.

Overall, MidJourney 7 fails to deliver on its promise of enhanced visual generation through preference training. The time investment required to train preferences doesn't yield proportional improvements in output quality. Whether for generating concept art, marketing materials, or creative visual content, this new version represents a step backward rather than the leap forward that was promised.

We both froze for a beat, and in that exact moment, there was a spark of recognition. I pointed at my phone, silently asking for a selfie. He smiled, waved me in. I dropped to one knee like I was proposing to the king of parody himself, said, "I love you," and tapped the shutter.

This was pre-2007—pre-selfie-culture, pre-front-facing cameras. I was rocking a Palm Treo, the cutting-edge smart device of the time. Feeling like I had just captured lightning in a bottle, I walked back out onto 6th Street grinning like an idiot.

Then I checked my phone.

No photo. No evidence. Just a ghost of a moment shared between me, Weird Al, and a Palm OS interface that failed me at the worst time.

I didn't dare go back in. He had already been gracious. The moment was over. It became one of those "you had to be there" stories I told every now and then, always wishing I'd had one more second, one better click.

Until today.

Thanks to some modern AI magic, I finally got to recreate that memory—this time, with a working camera. It may not be real, but the smile definitely is.

Speaking of digital selfies, here is one I took of Elvis Costello in the airport in Osaka, Japan in 1997. I had the brand new Casio QV-10A that took photos at 480x360. Which this photo below is in. Camera cost $500 back in 1997 and it was a big chunk of change for a guy moving to Japan. Crazy small resolution but you can clearly see younger me and Mr. Costello.

He was in line waiting to go through customs, and we chatted about my fancy new camera and was impressed with the way the camera lens could flip around, still show you the camera view on the small screen, and take a photo.

And finally since I'm a completist, here is another digital photo from that same trip. This was taken in Los Angeles just before I got on my flight to Japan. The bad news is that I didn't understand backlighting and how it blows out an image in the foreground. This is me and Erick Sermon.

In the mid-1970s, visionary filmmaker Alejandro Jodorowsky attempted to create what would have been the most ambitious science fiction film ever made: an adaptation of Frank Herbert's "Dune." Though the project never materialized, it left behind a treasure trove of concept art from legendary artists like Moebius (Jean Giraud) and H.R. Giger.

Using OpenAI's latest image generation capabilities, I've reimagined what might have happened if this unmade film had been successful enough to spawn a line of Kenner toys – similar to what Star Wars would achieve just a few years later. The results showcase the striking contrast between the avant-garde, psychedelic designs of Jodorowsky's vision and the simplified, mass-market aesthetic of 1970s action figures.

This experiment highlights the fascinating intersection of high art and commercial merchandising that defined the late 1970s sci-fi boom. Jodorowsky's Dune, with its surreal imagery and metaphysical themes, would have presented unique challenges for toy manufacturers of the era. The AI-generated transformations attempt to capture how these complex designs might have been simplified and adapted for the limitations of plastic molding technology and the expectations of the children's toy market.

The transformation process involved:

• Simplifying the intricate details of Moebius and Giger's artwork
• Adapting the color palette to match the limited paint applications of 70s action figures
• Reimagining the proportions to fit the standard 3.75" scale popularized by Kenner
• Adding the characteristic "five points of articulation" pose
• Incorporating the slightly glossy plastic finish typical of the era

This project once again demonstrates the remarkable capabilities of OpenAI's image generation technology, which continues to outpace competitors in its ability to understand complex creative prompts and produce coherent transformations that maintain the essence of the original while adapting to a completely different medium and context.

While Jodorowsky's Dune never made it to theaters, its influence on science fiction cinema has been profound and far-reaching. Perhaps in some alternate timeline, children of the late 70s were playing with these strange, psychedelic action figures instead of Luke Skywalker and Darth Vader – creating a very different cultural landscape for generations to come.

The goal was simple: feed classic cartoon characters into OpenAI's image generation system and request modern 3D interpretations. The system produced some remarkable transformations before eventually flagging the requests as potential copyright violations.

What makes this experiment particularly interesting is how it highlights the evolving relationship between AI and copyright law. After generating several images, the system began recognizing the copyrighted nature of these characters and started refusing to generate more. This demonstrates the sophisticated content filtering systems being built into AI tools to respect intellectual property rights.

The transformation process attempted to maintain the core characteristics of each character while applying modern 3D rendering techniques:

• Texture mapping for more realistic surfaces
• Advanced lighting and shadow effects
• Maintaining character proportions while adding depth
• Preserving iconic features and expressions

While the experiment was cut short by copyright protections, it provided a fascinating glimpse into both the capabilities and limitations of current AI image generation systems. It also raises interesting questions about the future of animation and how AI might be used to reimagine classic content while respecting intellectual property rights.

What is interesting about this OpenAI image product is that the images generated are the best quality I've seen. THE BEST. The adherence to what I specifically want, even if complicated, is superior with the OpenAI product. Look at the Messi image. I've wanted a stain glass window style for two years, and FINALLY, a model has delivered.

(*) HOWEVER, the Mickey request gets cancelled right in the middle of the render. The idea that even that partial image is the BEST MICKEY I've seen and follows my request exactly, it's funny that they chicken out and stop the render. You can see what happens below.

I couldn't resist taking the partially renedered image and tried to get otehr AI models to complete it. MidJourney and Photoshop wouldn't touch it. So with a little cropping and an upload to RunwayML, here is an animated Evil Mickey Mouse. With flames.

Castle Generation

Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight

Family Scene

Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k

Evil Mickey

Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k

Messi Generation

Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details

Robot Portrait

rusty robot with bow tie, portrait, 8k, ultra realism, chrome background

OpenAI's latest release, the 4o model, significantly enhances image generation capabilities, pushing the boundaries of what's achievable with AI-driven visual content. With improved realism, higher resolution outputs, and a better grasp of nuanced prompts, 4o positions itself as a powerful tool for creators across various industries, from marketing to entertainment.

To evaluate 4o's performance, we've tested a series of consistent prompts designed to highlight its strengths and expose potential limitations. The results demonstrate marked improvements in detail accuracy, contextual understanding, and creative variation compared to previous iterations. Particularly impressive is 4o's ability to maintain stylistic coherence across diverse image sets, making it highly suitable for brand-focused visual storytelling.

Overall, OpenAI's 4o delivers on its promise of advanced visual generation, offering users robust and reliable image creation capabilities. Whether for generating concept art, marketing materials, or dynamic visual content, this enhanced functionality represents a substantial leap forward, making it easier than ever to produce compelling visuals directly from descriptive prompts.

Rapid model generation optimizes workflow efficiency, while the open-source foundation encourages community contributions and transparency. Real-time examples showcase high-fidelity text-to-3D conversion and accurate image-to-3D transformation, enabling precise geometry and textures.

In my opinion, this is the best image or text to 3D model technology available, a true game changer in gaming and 3D printing. The seamless integration of text and image inputs into a comprehensive 3D creation tool demonstrates its revolutionary potential.

I took a handful of images that I created previously as Funko Pops of myself and my favorite radio/TV DJ growing up, and added them to the Hunyuan 3D model creator. The results are spectacular and cost $0.16, or you can run EVERYTHING locally through ComfyUI. Truly incredible and one of these days I'll print one of these models in resin and hand paint.

Joey Funko Pop

Here is the GLB model for you to play with or extend.

Here is the GLB model for you to play with or extend.

funko-joey.glb

Forever Crosno Funko Pop

Here is the GLB model for you to play with or extend.

Here is the GLB model for you to play with or extend.

funko-joey.glb

Degen Ape

Here is the GLB model for you to play with or extend.

Here is the GLB model for you to play with or extend.

degenape.glb

It's kinda great.

Joey Janisheck – Professional Profile and Biography

Personal Background and Education

Joey Janisheck is a Texas-based technology professional with over 25 years of experience in software development. He attended the University of Texas at El Paso from 1988 to 1992, studying English and literature. Although he did not complete a degree, Janisheck moved to Austin, Texas in the early 1990s to join the burgeoning internet industry. This transition marked the start of his career in the tech sector during the onset of the "Internet revolution."

Career History

Early Career (1990s–2000s)

Janisheck began his tech career amid the dot-com boom. In 1996 he joined NTT Verio in Austin as a Senior Technical Manager, where he managed the company's corporate web presence through a period of rapid growth, an IPO, and eventual acquisition by NTT. In 2007, he briefly served as a Senior Creative Designer at Optaros, delivering web solutions for both startups and Fortune 25 companies with cutting-edge open-source technology.

He then moved into user experience leadership at Absolute Software in 2010–2011, heading a team that overhauled the consumer web interface for a security product. This redesign contributed to the product earning a 4.5-star rating and an Editors' Choice award from PC Magazine. By 2011, Janisheck was Vice President of Development at BestFit Mobile, where he led international development teams to build mobile apps for major clients such as Michaels, ESPN, AT&T, and others.

Entrepreneurship and Leadership (2012–2019)

In 2012, Janisheck founded Exhilent Mobile, a development company where he served as Chief Technology Officer. He grew Exhilent to a team of 10 (plus numerous contractors) and delivered state-of-the-art mobile and web solutions for high-profile clients including Bosch, Disney, ESPN, and the NBA's San Antonio Spurs.

After five years leading Exhilent, he transitioned into roles at emerging tech and education-focused firms. In 2017, he joined Algebraix Data as a Mobile Architect and Product Manager, working on the development of a new mobile cryptocurrency wallet product. He subsequently held executive roles in the education travel sector – first as Vice President of Technology at API Abroad (2018–2019) and then as Vice President of Product & Engineering at Via TRM (2019–2020). In these positions, Janisheck oversaw software platforms used by nearly 100 universities worldwide, introduced new features to improve risk management, and enhanced student engagement through social media integrations.

Web3 and AI Ventures (2020–Present)

In late 2020, Janisheck launched ScreenDUET, an interactive content platform for live events, and served as its CEO. He led the development of a real-time audience engagement system used by marketing and sales teams to gather information from event attendees, reportedly deploying it at scale for some of the world's most famous brands.

In 2022, Janisheck became Chief Technology Officer at Darkblock, a blockchain-based digital content company. As CTO of Darkblock (2022–2023), he oversaw technical development across five different blockchain networks and multiple applications (including a web dApp, mobile app, TV app, browser extension, and API). He also engaged the developer community through weekly partner and developer live-streams (producing over 30 episodes) to showcase Darkblock's technology.

After Darkblock, Janisheck shifted to independent consulting and development work in 2023, focusing on innovative projects in artificial intelligence, blockchain, and NFTs. During this period, he partnered with artist Peelander Yellow to create MONMONMON, an NFT-based gaming art project featuring 12.8 million unique playable art characters on the Solana blockchain. He also developed BizQiz, an AI-driven gamified marketing platform that turns trivia and quizzes into a tool for brand engagement with blockchain-backed digital rewards.

In early 2024, Janisheck took on a new role as Head of Product at Inferred Mind, an AI and media intelligence startup. At Inferred Mind, he has led the development of advanced analytics tools – notably contributing to an election prediction system that leveraged AI-driven sentiment analysis to predict U.S. Senate race outcomes with a margin of error 200% more accurate than leading traditional polls. He continues to serve in this leadership role, driving product strategy at the company as of 2024.

Professional Accomplishments

• Gamified Marketing Platform: Founded BizQiz, a Web3 trivia game and interactive rewards platform that blends AI-generated content with blockchain technology to engage users and reward them with digital collectibles. The platform exemplifies Janisheck's innovative approach to gamified marketing and has been noted for "changing the game" for brand engagement through AI-powered trivia and NFT prizes.
• AI Election Forecasting: Led the development of an AI-driven election prediction system at Inferred Mind which accurately forecasted key political races. The model's predictions for 15 U.S. Senate races in November 2024 achieved roughly double the accuracy of leading polling institutions, demonstrating the power of AI-driven modeling over traditional surveys.
• NFT Art and Gaming Innovation: Co-created the MONMONMON NFT gaming art project in collaboration with Peelander Yellow, resulting in one of the largest generative art collections of its kind with 12.8 million unique playable NFT characters on Solana.
• Enterprise Solutions for Top Brands: As founder and CTO of Exhilent Mobile, Janisheck delivered custom mobile and web solutions for a roster of prominent clients including Disney, ESPN, Bosch, Mac Tools, and the San Antonio Spurs.
• Product Excellence in Software: In his early career, Janisheck's work at Absolute Software contributed to significant product improvements in consumer cybersecurity software. The revamped user experience and interface he spearheaded helped the product earn a 4.5 out of 5 star rating and an Editors' Choice accolade from PC Magazine.

Public Engagement and Media Appearances

Janisheck actively shares knowledge and engages with the tech community through various channels. He maintains a personal website and blog (Janisheck.com) where he documents his projects, insights, and even personal milestones. His blog posts cover topics ranging from emerging technologies to personal experiences; for example, he has reflected on a decade of contributions to the 3D printing community, noting over 14,900 views and 5,500 downloads of the open-source 3D models he shared on Thingiverse.

Janisheck has also made several notable media and event appearances. In January 2024, he was featured as a guest on The Index Podcast, hosted by Alex Kehaya, where he discussed the creation of BizQiz and shared his background in Web3, AI, and the evolution of interactive digital experiences. During this interview, he explored themes like blockchain's potential for brand engagement and his vision for the future of interactive media.

Earlier, in December 2022, Janisheck appeared as a speaker at the Parks Associates Future of Video conference, representing Darkblock as its CTO. On that panel, he joined other industry leaders to address how emerging technologies were disrupting and advancing the streaming and digital media landscape.

In addition to formal appearances, Janisheck maintains an active presence on professional networks and social media. He is active on LinkedIn and on X (Twitter), where he interacts with the tech community and shares updates. His X profile lists his personal website and the MonMonMon art project, and reflects his personality with a mix of tech insights and humor.

Official Profiles and Websites

• Personal Website: Janisheck.com – Janisheck's official website featuring his portfolio, resume, blog, and project showcases.
• LinkedIn: joeyjanisheck – Professional LinkedIn profile outlining his work experience and connections.
• BizQiz Platform: BizQiz.com – Official site of the BizQiz web3 trivia and rewards platform that Janisheck founded.
• X (Twitter): @joeyjanisheck – Personal Twitter (X) account where he shares updates and links to his projects.

My boss that day was being particularly difficult, micromanaging every detail of the event. Coupland noticed the tension but also saw how I kept things running smoothly despite the constant interference. When he finally signed my personal copy at the end of the night, he wrote two words that would prove prophetic: "Quit your job." I did, not long after, launching my career in the early days of the tech revolution.

The signing itself drew an interesting crowd. Richard Linklater and Wiley Wiggins showed up - Linklater was riding high on "Slacker" and prepping for "Dazed and Confused" at the time. A journalist from Der Spiegel was there too, working on a piece about Coupland.

In the photo below, you can see me, Mr. Linklater and Mr. Wiggins sitting around during the signing. If the signing happened today there would be hundreds of photos and social short videos, but this photo below is about the only proof I can find online that it happened - let alone that I was there. For your additional info, yep, that's me with the tie and exceptional posture. Fast forward 20 years, I wound up on Mr. Linklater's set for "A Scanner Darkly". I didn't dare bring up that I knew him all those years before. Maybe someday we'll have a beer again.

After the signing, our group - including my coworker Sean - headed to Les Amis. We claimed some outdoor tables, where conversations and cigarette smoke drifted into the evening air. The night continued at the Carousel Lounge, where Stella was working. Linklater and Coupland joined Sean and me for darts and Shiner Bocks, while the Der Spiegel writer took notes on what must have seemed like a perfectly Austin evening.

Now, in an exciting turn of events, Pebble creator Eric Migicovsky has unveiled PebbleOS running on new hardware. This isn't just a nostalgic revival - it's a continuation of the vision that made Pebble special in the first place. With Migicovsky planning factory visits and many veterans from the original Pebble team on board, this project feels like a true return to form.

What makes this return particularly significant is Google's recent decision to open source the PebbleOS code. This move not only helps keep older Pebble watches alive but paves the way for new hardware that stays true to Pebble's core vision. The "Rebble" project, announced as a reboot for Pebble smartwatches, promises to maintain what made the original special while adding new features.

The new Pebble team's commitment to maintaining the original's beloved features while introducing "some fun new stuff" is particularly exciting. As someone who experienced the magic of the original Pebble ecosystem - from its innovative e-paper display to its vibrant developer community that created over 16,000 watchfaces - I'm looking forward to contributing to this next chapter.

What set Pebble apart was its focus on practical features: an always-on e-paper screen that was perfectly readable in sunlight, impressive battery life, and a simple yet powerful user experience. The new hardware promises to maintain these core strengths while building on them with modern improvements.

For those interested in joining this revival, you can sign up at rePebble.com. Whether you're a long-time Pebble enthusiast or new to the platform, this represents an exciting opportunity to be part of a community-driven approach to smartwatch development.

The return of Pebble isn't just about nostalgia - it's about bringing back a practical, user-focused approach to smartwatch design that many of us have missed. With open-source software, veteran leadership, and a clear vision, this new chapter in the Pebble story promises to be as exciting as the first.

The tour through their facilities was fascinating, but what really caught my attention was getting to see the office of the famously private CEO, Kosta Kartsotis. And yes, the stories are true - there was indeed a mannequin sitting in his chair, complete with a striped tie, which I learned was often used as his stand-in for photo shoots.

What makes this visit particularly interesting is the unique culture at Fossil. The company's CEO, Kosta Kartsotis, is known for his unusual approach to leadership. Despite leading a major public company, he hasn't taken a salary, bonus, or stock options for many years. His reasoning? As stated in company proxy statements, he believes "his primary compensation is met by continuing to drive stock price growth."

The headquarters itself reflects this humble approach. Kartsotis's workspace is a small, glass-walled office sitting right in the middle of the building. It's a testament to their philosophy of reflecting a team rather than a single visionary. This approach dates back to 1993, when Fossil went public and made Forbes' list of 200 Best Small Companies in America at #3. Since then, both Kosta and his brother Tom (the founder who retired as chairman in 2010) have maintained their media-shy stance.

During my visit, I got to see firsthand how this philosophy translated into their approach to innovation. The Android smartwatch project I was there to discuss represented Fossil's adaptation to the changing landscape of wearable technology. It was fascinating to see a traditional watch company embracing digital transformation while maintaining their core identity.

The most memorable quote about Fossil's origins comes from Tom Kartsotis himself, who explained his motivation for starting the company in his garage: "I didn't want to be a 30-year-old ticket scalper." That straightforward, no-nonsense attitude permeated the company culture under Kosta's leadership.

Interestingly, last year marked the end of an era as Kosta Kartsotis was replaced by the board. His tenure was marked by a unique approach to leadership and fostering a highly creative environment that helped transform Fossil from a traditional watch company into a pioneer in the wearable technology space.

NO INK, NO SALARY, NO WORRIES

This would be a good place for a photo of the happy founding family. No such luck. Founder Tom Kartsotis, who retired as chairman in 2010, and brother Kosta Kartsotis, who's CEO, don't give media interviews about Fossil. At least they haven't since 1993. That's when Forbes put Fossil at No. 3 on its list of 200 Best Small Companies in America. It's also the year that Fossil went public, so there was extra incentive to talk up the company. Almost 20 years later, that remains the definitive first-person account of Fossil's roots. Even the Gale International Directory of Company Histories depends heavily on the Forbes piece. And the founder's explanation for his garage start-up is still the killer quote: "I didn't want to be a 30-year-old ticket scalper," he said. Kosta, 59, talks to analysts every quarter, and is a strong advocate at industry conferences, so it's not about being reclusive. But he and his brother always wanted the Fossil brand to reflect a team, not a single visionary. That humility is refreshing in an era of celebrity CEOs, and there's no arguing with the success. Here's another oddity: Kosta Kartsotis refuses to take a salary, bonus, or stock options, and that's been the case for many years. Because he doesn't grant interviews, we'll use the explanation from the proxy statement: "Mr. Kartsotis is one of the initial investors in the company and expressed his belief that his primary compensation is met by continuing to drive stock price growth." With 6.4 million shares, his stake was worth more than $400 million this summer. Reportedly, the CEO is accessible to employees, and his small glass-walled workspace sits in the middle of the new headquarters. The Dallas Morning News ran several photos of the place, but Kartsotis wasn't sitting in his office chair. A mannequin was the stand-in for the photo shoot, striped tie and all.

We got engaged on a Disney cruise and just recently celebrated 25 years on a Disney cruise again. Here's a photo showing us back in 1999 and today. Only a little photoshop work to get us aligned like the old photo but that's us.

She's the best person I've ever met and her saying yes was the best thing that ever happened to me personally.

Here's to another 25 years.

Thingiverse used to be a thriving hub of creativity and innovation in the maker community. However, its soul has gradually faded since Stratasys, a corporate 3D printer manufacturer, acquired Makerbot, which owned Thingiverse. While their intention might have been to maintain the hobbyist feel and maker vibe—possibly hoping to nurture home 3D modelers into users of their professional-grade systems—the reality has been quite different.

I've had the opportunity to work with Stratasys systems, which can cost upwards of half a million dollars. But there's a harsh truth about these professional systems: they often struggle to generate profit due to their business model. The combination of subscriptions, service requirements, and machine-specific resin creates a brutal ecosystem that locks users into an expensive and inflexible system.

Despite these industry changes, the statistics below represent a time when the community was at its most vibrant, showcasing the true potential of open-source 3D printing and collaborative design:

Looking at these statistics, it's incredible to see the impact these designs have had. The Structure Sensor iPhone 7 Plus Case and Knuckles Structure Sensor Rig have been particularly successful, with nearly 2,500 downloads between them. These designs helped makers integrate 3D scanning capabilities into their workflows.

What's particularly rewarding is seeing how these designs have been used and adapted by the community. From practical solutions like the IKEA headphone holder to specialized tools like the Structure Sensor rigs, each design has served a specific need in the maker community.

In total, these designs have accumulated over 14,900 views and more than 5,500 downloads, along with 209 likes and 202 collections. While some of these designs were created for specific hardware that may now be outdated (like the iPhone 7 Plus case), they serve as a testament to the 3D printing community's ability to solve problems and create custom solutions.

As technology evolves, the need for custom 3D printed solutions continues to grow, and I'm excited to keep contributing to this vibrant community. Whether it's creating mounts for new devices, improving existing designs, or developing entirely new solutions, the maker community on Thingiverse remains an invaluable resource for sharing knowledge and creativity.

View All My Thingiverse Models

It's fun seeing WWE rolling out the WWE Network with their complete library of matches and promos in an app form. A little more than a decade later, I'd argue all of their presence on screen is through streaming. Whether it's their giant new Netflix deal or pay-per-views (now called premium live events) are also streamed via mobile apps.

It's surreal seeing myself in this footage after all this time. You can spot me at the 1:05 mark in the clip. Here's the full YouTube video of that memorable press conference:

Looking at this clip again:

One of the most impressive moments from this press conference was when a reporter asked John Cena a question in Mandarin Chinese - and Cena responded fluently in Mandarin! It completely changed my perception of him. Here was someone you might dismiss as just another gym-focused wrestler, but he revealed himself to be nuanced and brilliant. I never underestimated him again after that.

What makes this memory even more special is how Cena's 2025 Royal Rumble performance tonight reminded everyone why he's one of the greatest of all time. From his SXSW appearances to WWE events, he always brings his A-game and creates memorable moments for fans - while constantly surprising people with hidden depths they never expected.

Week 1: Cyberpunk Tokyo Nights

My first theme placed me in the neon-lit streets of Tokyo, capturing that classic cyberpunk aesthetic with rain-slicked streets and glowing signs. Using Flux with a custom Lora trained on my face, I was able to maintain consistent facial features while exploring different scenes:

Week 2: AI Tarot Cards

This week, I've switched gears to create animated tarot cards. Using a custom Flux Lora for the tarot card style, each image captures a different aspect of our digital age. Kling AI brings these static images to life with subtle yet captivating animations:

The Magic of Kling AI

Kling AI has been a game-changer for adding motion to these images. The tool excels at creating natural, flowing animations that enhance the original artwork without feeling forced or artificial. Whether it's the subtle ripple of neon reflections in the Tokyo scenes or the mystical shimmer of the tarot cards, Kling AI consistently produces impressive results.

Looking ahead to next week, I might explore something completely different - perhaps a series where I'm dressed as an Ohio State player. The beauty of this approach is the flexibility to experiment with new themes while maintaining consistent quality through tools like Flux and Kling AI.

Stay tuned for more experiments as I continue to explore different themes and push the boundaries of what's possible with AI image generation and animation.

A stunning piece of artwork by Jeff Carlisle that brings together hundreds of characters from across science fiction universes, all gathered at the Warp Core Cafe. The level of detail and number of references packed into this single image is astounding.

About the Artist

Born in Shelby, OH (Birthplace of the seamless tube industry in America), Jeff Carlisle grew up in Columbus, OH. He attended the Columbus College of Art and Design, and his career in sci-fi art began when he submitted work to TheForce.Net in the early 2000s. A chance meeting with fantasy artist Tony DiTerlizzi led to his first industry job - drawing starships, droids and aliens for Star Wars Gamer magazine.

After a brief stint in San Diego working on video games, Jeff returned to Columbus where he lives with his wife, Lisa. You can find more of his work at jeffcarlisle.com.

The Artwork

Click the images below to see larger versions and explore the incredible detail:

This masterpiece features an incredible array of science fiction characters and ships from across movies, TV shows, comics and more. From Star Wars to Star Trek, Battlestar Galactica to Babylon 5, The Fifth Element to Doctor Who - the amount of detail and number of references is staggering.

The scene is set in the Warp Core Cafe, with the titular warp core running through the center of the establishment. Characters from countless sci-fi universes mingle, drink, and socialize. You'll spot familiar faces like Darth Vader, Captain Picard, and Rick & Morty alongside more obscure references like characters from Batteries Not Included and Ice Pirates.

In the windows, you can see various iconic spacecraft including the USS Enterprise, Millennium Falcon, and Battlestar Galactica. The artist has managed to seamlessly blend all these different universes together in a way that feels natural and cohesive.

The artwork rewards careful study - the longer you look, the more details and characters you discover. It's a loving tribute to decades of science fiction that will have fans spending hours picking out all the references.

Character Guide

What sets Nibbles apart is its ability to maintain professional-grade output while eliminating unnecessary complexity. The drag-and-drop interface responds with subtle animations that make the conversion process feel alive and interactive, rather than just a progress bar to watch.

See It In Action

The intuitive drag-and-drop interface makes video conversion a breeze:

Key Features

The app excels at creating high-quality APNGs for web design, optimized GIFs for social media, and pristine MOV files for the Apple ecosystem. Every conversion happens locally on your device, ensuring your content never leaves your control.

Advanced users will appreciate the granular control over resolution and frame rate, while casual users can rely on intelligent defaults that consistently produce excellent results. This balance of power and simplicity makes Nibbles equally valuable for professional creators and everyday users.

Privacy First

In an era where even simple tools want to phone home or require cloud processing, Nibbles stands out by keeping everything offline. Your videos stay on your device, processed locally with zero data collection or external dependencies.

As we dive into 2025, I wanted to take a moment to reflect on my GitHub activity over the past year. In 2024, I made 619 contributions to various projects and repositories, marking another year of consistent development and collaboration.

Now I'm not one to do a lot of checkins over the course of a day when I'm adding some functionality or solving a problem. I only prefer to checkin working solutions instead of half working or incomplete tasks. So my checkin totals represent true progress instead of "ass coverage" or gaming the system to look good. Plus, my day job is more as a product owner instead of developer and yet I keep up. It's a very interesting time.

Year-over-Year Comparison

While 2024's contribution count of 619 represents a decrease from 2023's 881 contributions, it still demonstrates a strong commitment to code development and project maintenance. This shift in numbers doesn't tell the whole story – it's about the impact and quality of the contributions, not just the quantity.

Peak Activity Periods

Looking at the contribution heat map, three months stood out with particularly high activity:

• February: Started the year strong with concentrated development efforts
• June: Mid-year surge in project activity
• November: End-of-year push with significant contributions

These peaks in activity align with major project milestones and development initiatives throughout the year. The distributed nature of contributions across these months shows a balanced approach to development, with focused sprints during key periods.

Looking Forward

As we move into 2025, these contribution patterns provide valuable insights into my development workflow and project engagement. While the raw numbers may have decreased from 2023, the consistent activity across key months in 2024 demonstrates an ongoing commitment to code development and project maintenance.

Here's to another year of meaningful contributions, collaborative development, and continued growth in the open-source community!

Running on a modest gaming computer with no optimization or tweaks, each short video took about 2 hours to render. While this might seem long compared to cloud services, the ability to run multiple generations without usage limits or additional costs makes it a compelling option for experimentation.

Here are some example generations using Hunyuan through ComfyUI:

Castle Animation

Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight

Evil Mickey Animation

Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k

Family Scene Animation

Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k

Messi Animation

Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details

Robot Portrait Animation

rusty robot with bow tie, portrait, 8k, ultra realism, chrome background

The next exploration will involve combining Hunyuan with LoRA models to see what new possibilities emerge. It's an incredible time for AI video generation, where tools that would have seemed impossible just a few years ago are now running on home computers.

Happy New Year! As we step into 2025, I can't help but reflect on a transformative 2024 – the year I reclaimed my digital sovereignty and discovered that true innovation happens when we put individual privacy first.

Remember when we thought cloud computing was the future? Turns out, the real innovation is bringing that computing power right into your living room – without Silicon Valley getting a front-row seat to your digital life.

This past year was about building technology that respects individual creativity and privacy. Here are some highlights that shaped my journey:

• Launched CVRLTR, an AI resume generator that doesn't harvest your professional soul. Because your career story shouldn't be another data point for some algorithm.
• Implemented local AI solutions using Ollama that let me experiment without broadcasting every creative spark to the cloud. Pro tip: your half-baked ideas deserve privacy too.
• Hit 1000 miles on my electric bike – proving that innovation isn't just about what happens on a screen, but how technology integrates into real life.

Key Posts That Resonated

Looking Ahead to 2025

As we embrace 2025, my vision remains clear: build technology that serves humans, not the other way around. Train your own models. Protect your data. Create without compromise.

Because in this rapidly evolving digital landscape, the most revolutionary act isn't just creating something new – it's maintaining control over what you create. Here's to a year of innovation on our own terms!

The most exciting part? This is just the beginning. 2025 promises even more opportunities to push the boundaries of what's possible while keeping our digital sovereignty intact.

Happy New Year! Let's make 2025 a year of mindful innovation and purposeful creation.

Back in 2012, we made what seemed like a reasonable decision at the time: we bought a $1,200 gaming PC for the house. To justify the purchase to ourselves (and our budget), I had an idea that felt clever at the time - I'd mine Bitcoin when we weren't gaming. After all, Bitcoin mining was still possible with regular GPUs back then, and it seemed like a smart way to offset the cost.

The plan worked perfectly. Within a few months, I had mined enough Bitcoin to cover the entire cost of the PC. We sold it all immediately, proud of ourselves for essentially getting a "free" gaming PC. Mission accomplished, right?

The Half-Million Dollar Lesson

Here's where the story takes an interesting turn - that Bitcoin we mined and sold for $1,200 in 2012 would be worth nearly $500,000 today. Let that sink in for a moment. Our "free" gaming PC could have been the most profitable investment of our lives.

It's probably the most expensive Minecraft machine ever - not because of what we paid, but because of what we didn't keep. While we were building virtual worlds in Minecraft, we could have been building real-world wealth with those digital coins.

Lessons in Patience and Innovation

This experience taught me several valuable lessons about technology and innovation:

• The real value of new technology isn't always immediately apparent
• Sometimes the best investment strategy is simply to hold on
• Being early to technology is only half the battle - having the vision to stick with it is the other half
• Short-term thinking can have long-term consequences

The Bigger Picture

This story isn't about regret - it's about perspective. In 2012, most people saw Bitcoin as a curiosity at best, and many dismissed it entirely. The same way some people today might dismiss local AI models or personal AI training.

What emerging technology today might be the Bitcoin of tomorrow? Maybe it's personal AI models, quantum computing applications, or something we haven't even imagined yet. The key isn't just being early - it's having the foresight to recognize long-term value and the patience to let it develop.

And sometimes, the best investment opportunities don't look like investments at all. They look like gaming PCs, or hobby projects, or experiments that seem pointless to everyone else.

Castle

Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight

ImageFX Interpretation

Whisk Interpretation

Family

Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k

ImageFX Interpretation

Whisk Interpretation

Mickey

Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k

ImageFX Interpretation

Whisk Interpretation

Messi

Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details

ImageFX Interpretation

Whisk Interpretation

Robot

rusty robot with bow tie, portrait, 8k, ultra realism, chrome background

ImageFX Interpretation

Whisk Interpretation

What's particularly intriguing about these results is the remarkable consistency between ImageFX and Whisk outputs. When given identical prompts, both tools generate images that are strikingly similar in composition, structure, and overall interpretation. This unusual level of consistency suggests that both tools are leveraging the same sophisticated underlying AI model, which appears to have a very structured approach to interpreting and generating images.

The examples above demonstrate this consistency across a wide range of prompts - from architectural scenes with the Neuschwanstein Castle to complex character compositions with the Mickey Mouse scenario, and from emotional family scenes to stylized portraits. In each case, both tools produce results that share remarkably similar layouts, lighting, and compositional elements.

This consistency between ImageFX and Whisk represents a significant achievement in AI image generation technology. It suggests that Google has developed a highly reliable and deterministic image generation model that can consistently interpret and render complex prompts. This level of reliability and predictability could be particularly valuable for professional applications where consistent results are crucial.

You can try both tools yourself at labs.google/fx/tools/image-fx for ImageFX and labs.google/fx/tools/whisk for Whisk. The similarity in results between these tools showcases the robustness of Google's approach to AI image generation, setting a new standard for consistency and reliability in the field.

I've been playing with the new Spatial Video support in Safari on Vision Pro, and it's both exciting and a bit bittersweet. The technology itself is incredible - being able to view spatial videos right in your web browser feels like something from the future. But I can't help but dream about what could be possible if we pushed this even further.

See For Yourself

Click the video play button and expand the link (top right arrows) and it pops up in the 3D mode while wearing your Apple Vision Pro.

What you're seeing above is a spatial video that, when viewed on Vision Pro, can break free from the 2D constraints of the webpage. It's pretty cool, but here's where I think there's room for growth - wouldn't it be amazing if these videos could exist as dioramas within the page itself? Imagine having little windows into 3D worlds that you could peek into before deciding to go full immersive.

The Future of Web Experiences

Combined with spatial images, this technology opens up incredible possibilities for creating deeply interactive experiences right in the browser. No special apps, no extra downloads - just pure web magic. We could build rich, immersive storytelling experiences that feel natural and intuitive.

While the current implementation is impressive (check out Justin Ryan's demo site for more examples), I'm excited about where this could go. Imagine product showcases where you can examine items in true 3D space, virtual tours that feel like you're actually there, or educational content that puts you right in the middle of the action.

Looking Forward

The potential for creating immersive web experiences without complex tooling is huge. While the current implementation is a solid foundation, I'm hoping future updates will allow for more seamless integration between the 2D web and spatial content. The ability to create "windows" into spatial content that live naturally within web pages could transform how we think about web design and interaction.

For now, though, it's exciting to see this technology taking shape. It's a first step toward a more immersive web, and I can't wait to see how developers and creators push these capabilities to their limits.

The collection features four distinct pieces, each capturing a different aspect of cinematic imagination. From ethereal giants emerging from cosmic mists to legacy-defining moments frozen in time, these pieces represent a fusion of AI creativity and blockchain technology. I was just having some fun with the latest tech and continue to be impressed with the work that Rodri and team do.

The goal with this tool is to rapidly onboard non-crypto normies. We all had to learn this stuff and the easier we can make it the more you'll learn. So, click the link and grab your free NFT. I'll pay for the gas (another nerdy term you'll learn later). Enjoy.

I've decided to make these NFTs available to anyone interested in owning a piece of this experimental collection. By clicking the link below, you can randomly receive one of these artworks either delivered to your email or directly to your Solana wallet.

The animations below demonstrate that while Sora can generate video content, it struggles with maintaining consistency and quality throughout the sequences. The results often lack the polish and coherence seen in RunwayML's outputs.

More notably, Sora appears to have corporate-driven limitations that RunwayML doesn't. For instance, the Mickey Mouse prompt that works perfectly fine in RunwayML isn't even possible in the latest version of Sora. This seems less about technical capability and more about OpenAI's business relationships - likely a strategic decision to maintain good relations with Disney for potential future partnerships.

Here are the test prompts, processed through Sora (minus the Mickey Mouse animation which Sora refuses to generate):

Castle Animation

Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight

Family Scene Animation

Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k

Messi Animation

Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details

Robot Portrait Animation

rusty robot with bow tie, portrait, 8k, ultra realism, chrome background

The Bridge Between Two Worlds

Generation X stands out as the bridge between analog and digital, the pioneers of living in two worlds. We grew up with rotary phones that made dialing an event, learned patience as we listened to the screech of modems connecting us to AOL, and now wield smartphones that bring the universe to our fingertips in seconds. We're the first generation that will never forget, because we've seen the power of connection evolve from handwritten letters to instantaneous video calls. Our memories are etched in both dusty photo albums and infinite clouds, accessible anywhere, anytime.

Masters of Adaptation

What makes Generation X extraordinary is our adaptability. We've navigated life with paper maps and now rely on GPS; we've experienced encyclopedias as tomes of knowledge and now enjoy Wikipedia as a living, breathing resource. These shifts didn't overwhelm us—they empowered us. We learned early on how to troubleshoot technology (and life) with ingenuity and resilience, building skills that made us thrive in the digital age. We aren't just witnesses to the transformation; we've driven it, shaping an era where unlimited Internet access and instant answers are the norm.

Thriving with Flair

The best part? We're not just thriving; we're thriving with flair. Gen Xers bring a unique blend of nostalgia and innovation, celebrating mixtapes while streaming playlists, reminiscing about floppy disks while mastering the cloud. We're not bound by generational stereotypes; instead, we show the world that embracing the future doesn't mean forgetting the past. In a world that's constantly changing, we are the generation that bridges yesterday and tomorrow, remembering where we started while shaping where we're headed.

If you stitch enough of these animations together, you can easily create an interesting commercial or social media post.

Here are my traditional test prompts, now animated through RunwayML:

Castle Animation

Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight

Family Scene Animation

Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k

Evil Mickey Animation

Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k

Messi Animation

Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details

Robot Portrait Animation

rusty robot with bow tie, portrait, 8k, ultra realism, chrome background

In a stunning development that has electrified the NFL community, Deion "Coach Prime" Sanders has agreed to join the Dallas Cowboys organization. The announcement marks a homecoming for Sanders, who previously helped lead the Cowboys to a Super Bowl victory during his playing career in the 1990s.

Coach Prime's arrival in Dallas represents a full-circle moment for both the legendary figure and the franchise. His transition from the college ranks, where he has demonstrated exceptional leadership and the ability to transform programs, to the NFL's most valuable franchise signals an exciting new chapter in Cowboys history.

The move reunites Sanders with the organization where he earned his reputation as "Prime Time" during the Cowboys' dynasty years. His return to Dallas, this time in a coaching capacity, brings with it the same charisma, confidence, and winning mentality that defined his playing career.

For Cowboys fans, this announcement feels like an early Christmas present, injecting new energy and optimism into the organization. Coach Prime's proven ability to develop talent and create a winning culture makes this partnership particularly promising for the future of America's Team.

The impact of this decision extends beyond just the coaching aspects - it represents a merger of one of football's most magnetic personalities with one of sports' most prestigious franchises. The combination of Coach Prime's modern approach to leadership and the Cowboys' rich tradition creates an intriguing blueprint for success.

As the 2025 season approaches, all eyes will be on Dallas to see how Coach Prime's influence will shape the next era of Cowboys football. One thing is certain - the NFL just got a lot more interesting with Prime Time back in Dallas.

First step is I looked at the most popular generated images on MidJourney and reused their exact prompts.

×

Here are my traditional test prompts that I've been using for over a year.

Castle Generation

Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight

Family Scene

Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k

Evil Mickey

Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k

Messi Generation

Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details

Robot Portrait

rusty robot with bow tie, portrait, 8k, ultra realism, chrome background

Benefits of Local Setup

Running ComfyUI locally has several advantages: - Complete privacy - all data stays on my machine - No cloud processing fees - No API rate limits - Faster generation times (depending on your GPU) - Full control over the models and workflows

Castle Generation

Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight

Family Scene

Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k

Evil Mickey

Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k

Messi Generation

Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details

Robot Portrait

rusty robot with bow tie, portrait, 8k, ultra realism, chrome background

Local Processing Power

The ability to generate these images completely locally demonstrates how far consumer hardware has come. With a decent GPU, you can run sophisticated AI image generation models right on your own machine. This opens up endless possibilities for creative projects without the constraints of cloud-based services.

ComfyUI's node-based interface gives you granular control over the generation process, allowing you to fine-tune every aspect of the pipeline. Whether you're a professional artist or just experimenting with AI image generation, having everything run locally provides the ultimate flexibility and control over your creative process.

Hey friends! Have you ever dreamed of creating your own chatbots, virtual assistants, or even clever content generators? Well, buckle up because the OpenAI API Cookbook is here to help you unlock your creativity with the power of artificial intelligence!

This delightful book takes a fun, recipe-style approach to learning how to use the OpenAI API, making it the perfect companion for anyone looking to dive into the world of AI—whether you’re a curious beginner or a seasoned techie!

What’s Inside the Cookbook?

• Understand essential elements, endpoints, and parameters of the OpenAI API.
• Build tailored intelligent applications and workflows effortlessly.
• Create versatile assistants to help you with all sorts of tasks—from managing your schedule to generating creative writing prompts!

With the purchase of the print or Kindle version, you even get a free PDF eBook—so you can read it wherever you are!

Why is This Book a Game-Changer?

As AI reshapes our world, knowing how to create innovative applications is a major advantage. This cookbook walks you through everything—from setting up your API playground environment to incorporating advanced features. You’ll learn how to tweak parameters for perfect results and explore various recipes for building intelligent applications.

Imagine being able to design your own chatbot that helps with your daily tasks or generates fun stories when you need a quick escape! The book even includes step-by-step guides for building knowledge-retrieval assistants, so you can create your very own AI-powered sidekick.

Who Should Dive In?

This book is perfect for:

• Developers and data scientists eager to enhance their skills.
• AI enthusiasts and citizen developers looking to create unique solutions.
• No-code aficionados who want to incorporate AI into their workflows!

Whether you’re starting fresh or looking to polish your existing skills, each recipe takes you from the basics to developing sophisticated applications—one step at a time.

What Will You Learn?

By the end of this cookbook, you'll feel empowered to:

• Grasp the fundamentals of the OpenAI API.
• Integrate AI into your current projects to supercharge your productivity.
• Create intelligent applications that harness the magic of ChatGPT!

In a world full of possibilities, this book truly opens the door to creative innovation. So why not grab your copy of the OpenAI API Cookbook and start dreaming big? Let’s get building!

It's even easier to set up than Ollama but you are still constrained with how powerful your computer is. The greater the graphics car, the bigger models you can download and more elaborate results you can generate.

What can you do with this power in your hands? I'm sure a bunch of important stuff, but what if I wanted to put Jules from Pulp Fiction in the story of Goldilocks and the Three Bears? Here you go:

Page 1: Jules Winnfield, the smooth-talking, gold-chain-wearing hitman from Marsellus' crew, strolled into the forest, looking for a little R&R. He had just finished a long job in Los Angeles and was feeling like a bear-ly manageable load of stress. As he walked, he stumbled upon a cozy little cabin belonging to the Three Bears. The door was unlocked, and Jules' curiosity got the best of him. He pushed it open and called out, "Hello? Anyone home?" The only response was the creaking of the old wooden floorboards beneath his feet. Jules made himself at home, popping into each room and exclaiming, "Ah, perfect!" in various tones. In the living room, he settled into the smallest armchair and declared it "just right." The largest chair was too big, and the middle-sized one was, well, just a little too small. Next, Jules sauntered into the kitchen and gave the chairs another go-around. "Too small, too big, just right... F**k it, I'm just gonna eat whatever's in here!" He rummaged through the cupboards and found three little bowls of porridge. The first one, oatmeal with a few raisins, he deemed "too cold." The second was too hot. But the third bowl? "Just right," he growled, shoveling it into his mouth. Finally, Jules' gaze landed on the bedroom. Three beds beckoned him, each one a different size. "Too small," he groaned as he hopped into the first bed. The second was a bit better, but still too big. "Ah, c'mon!" he exclaimed, as he leapt into the third bed and proclaimed it "just right." As Jules settled in for a well-deserved nap, the Three Bears returned home to find their porridge had been pilfered and their chairs were in disarray. But the real kicker was Jules himself, fast asleep in Baby Bear's bed. Page 2: Just as the Three Bears were about to wake Jules up and give him a piece of their mind, he suddenly stirred. His eyes snapped open, and he let out a groan. "What the...?" Jules muttered, scrambling to sit up. The Three Bears stood before him, their faces stern. "You're in our house," growled Papa Bear. "And you've made a mess of it." Jules rubbed his eyes, still half-asleep. "Dude, I'm just trying to relax," he said, his smooth-talking demeanor momentarily replaced by a sheepish grin. Mama Bear narrowed her eyes. "Well, you'd better start cleaning up around here." "Okay, okay," Jules said, holding up his hands. "I'll get this mess under control." Baby Bear looked at Jules with a hint of curiosity. "You're not from around here, are you?" Jules chuckled and shook his head. "Nah, kid. I'm from LA. Just passing through." The Three Bears exchanged looks. "Well, just so you know," Papa Bear said, his voice a bit softer, "we don't take kindly to strangers messin' up our place." Jules nodded, still rubbing the sleep from his eyes. "No problemo, dudes. I'll keep that in mind." With a nod, Jules began cleaning up the mess he had made. The Three Bears watched him work for a moment before disappearing into their house to tidy up their own space. As Jules finished his chores and prepared to leave, he caught a glimpse of Baby Bear watching him from the doorway. "Hey, kid," Jules said with a smile. "You wanna grab some coffee sometime?" Baby Bear's eyes lit up, and he nodded enthusiastically. Jules grinned. "I'll pick you up at 2 o'clock, got it?" Baby Bear nodded again. Jules chuckled and shook his head. "You're gonna be just fine, kid." And with that, Jules Winnfield walked out of the cabin, ready to take on his next adventure.

However, the video also sheds light on the darker side of this technology. We're witnessing the dawn of a quantum arms race, primarily between the United States and China, each vying for supremacy in this cutting-edge field. The implications are huge—not just for technological progress but also for cybersecurity, as quantum computers could potentially decrypt all existing internet communications. It's a double-edged sword that promises incredible advancements while posing significant risks to our digital security.

I talk to so many people who feel overwhelmed with the speed of innovation. It's exciting. It isn't slowing down and we are about to break out of how we think about computing with ones and zeros and going to another level.

1. Distributing Traffic and Reducing Crowds

One of the challenges was managing the flow of visitors, especially around popular art installations where "selfie" log jams can occur. The proposal suggested introducing interactive checkpoints throughout the conservatory to encourage visitors to explore different areas, thereby distributing foot traffic more evenly. These engagements were intended to enhance the visitor journey and minimize congestion, ensuring a more enjoyable experience for everyone.

2. Capturing Valuable Visitor Data

Understanding visitors is key to continuously improving their experience. The proposed digital engagement system would capture insightful data such as:

• Art Awareness: Whether visitors recognize and appreciate the art pieces on display.
• Dining Preferences: Which of the partner restaurants they have visited during their stay.

This data would allow for tailoring future exhibits and collaborations to better meet the interests and preferences of guests.

3. Rewarding Visitors with NFTs

As a token of appreciation for engaging with various checkpoints, the proposal included providing visitors with digital rewards in the form of NFTs. While NFTs were a growing trend, they were seen as a promising solution for digital rewards, akin to how QR codes revolutionized engagement a decade prior. These NFTs would serve as unique mementos of the visit and could be collected or displayed digitally.

Outcome and Next Steps

After months of discussion and a detailed spec presentation, the proposal did not move forward. While the ideas held promise for transforming the visitor experience at Bellagio Conservatory, the initiative ultimately failed to materialize. Nonetheless, the exploration of blending digital innovation with the conservatory's beautiful natural and artistic displays provided valuable insights for future endeavors.

Castle

Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight

Family

Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k,

Evil Mickey

Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k,

Messi

Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details,

Robot

rusty robot with bow tie,portrait,8k,ultra realism,chrome background

https://sketchfab.com/3d-models/emoji-stamper-promotional-gift-9c7b0c2e9c7b4dff9d2301b1d7f4abe6

Episode 11 Part 1

00:06 - 00:42 Seated at table

08:35 - 08:40 Enters restaurant through door

Episode 11 Part 2

05:11 - 05:12 Walking camera right (back facing)

05:23 - 05:25 Over the shoulder working on copier

Mike McCarthy’s game plan's amiss,
The offense and defense don’t click.
His ex-coordinators soar,
While his Cowboys just score
Too late—making fans pretty sick.

With success found by those who have fled,
McCarthy’s now feeling the dread.
The defense gets torn,
And the fans are forlorn,
As they question the man at the head.

Just before the first game of the year for my beloved Cowboys, Dak Prescott signed the most lucrative contract in NFL history. It's about time that Jerry Jones opened his wallet even wider to secure "my quarterback". CeeDee Lamb and Dak signed historically huge contracts and now its time for them to execute.

Black Forest Labs recently introduced Flux, an AI model that enhances image generation capabilities. This tool is designed to handle complex imaging tasks that typically require significant computational effort. There is still a learning curve with all of these APIs and models, but the results are spectacular.

With my platinum pass for SXSW, I was registered in a lottery to get tickets for either a secret Prince or Justin Timberlake show. They were happening at the exact same time just half a mile from each other. Imagine that? Prince did ask the audience not to use their cameras or he'd walk off the stage.

Oh yeah. A Tribe Called Quest was the opening act. Complete with Phife Dawg. RIP.

I wound up winning the Prince ticket and I was able to attend the greatest live performance I've ever seen. It was 3+ hours long, a ton

At one point during the performance (maybe in hour two), Prince tells the audience, "Don't make me hurt you. You know how many hits I got?". Absolute legend.

This photo was taken at 3:20am after over three hours of music and multiple (5 or 6 or 7) encores by his Royal Purpleness. Unbelievable room. Unbelievable performance.

This video was not by me, but the rest of the photos were. Clearly the person was standing pretty close to where I was.

Some interesting links and stories from that night. It was proclaimed as not only THE event of SXSW that year, but maybe the party to end all parties.

I wonder about this as more and more people I see try to be an influencer over just being a proficient craftsman. Are these influencers hired to work on big projects? Or is it all just a vanity ego thing that makes them feel good?

Though my favorite YouTube videos are of people just doing amazing work. I don't care of they are fixing watches, or rehabbing RVs, or making a burrito. If you are highly skilled, I want to watch you work.

Maybe these videos and this oversharing is the new portfolio and its table stakes to keep on working on interesting projects? That might be it. Nobody wants your printed one-page resume on fancy paper, they want to see if you attract others to your work.

These AI generated images were made with Ideo. They really are the best in the world when it comes to generating accurate text on an image. It's stunning what they can do.

The journey started with generating still images in MidJourney, capturing the unique atmosphere of cities like Tokyo in 2024, Cairo in 1260, and Paris in 1889. These images served as the foundation for more dynamic explorations.

Using RunwayML, I transformed these stills into engaging animations that provide a deeper sense of the life and movement within these cities. Here are some highlights from this exploration:

Here are GIFs of the generated movies:

Here are initial MidJourney generated key frame and then the hires RunwayML generated movie:

Tokyo 2024

Paris 1889

Cairo 1260

Istanbul 532

Kyoto 1693

Venice 1500

Each animation captures the essence of its respective city, offering a window into what makes each place unique. This project not only highlights my capabilities in utilizing AI for creative visualizations but also serves as a testament to the historical and cultural significance of these cities.

Here is the basic prompt that I used to create these. With a little tweaking and iteration, I could definitely create a world class short film.

FPV hyper-speed fly through Cairo, Egypt in the year 1260 AD. Dynamic motion, dynamic blur, timelapse, 30x speed, cinematic 35mm film with rich accurate color

To help you experience this transformative tool, I’m offering three free Rotato templates that enable dynamic presentations of your web applications through a rendered MacBook Pro. These are perfect for product managers eager to showcase their software or app features in the most compelling way.

Here are the templates you can download for free:

• MacBook Pro Full to Right Half:
  Focus on the right-side functionalities of your app.
• MacBook Pro Full to Left Half:
  Showcase your application's left-side features with precision.
• MacBook Pro Closed to Full:
  Start from a closed MacBook to a full screen, perfect for intro sequences or welcome screens.

Download these free templates below:

Each template is crafted to ensure ease of use without compromising on the quality and professional appeal of your presentations. If these templates help improve your project showcases, I plan to create 20 more, and even combine them into a 20-second video promo based on user feedback.

Good presentations not only demonstrate what your applications can do; they ensure your work leaves a lasting impression. With Rotato and these free templates, make each presentation count.

I had an opportunity as a young man to work for a summer at Steve Jackson Games. It was down in south Austin off of Oltorf and I remember it being quite a hike during rush hour traffic from where I lived up north.

My work hours were in the evening and into the night as I functioned as the "scanning boy". I would take pencils and inked art, scan them into a scanner, and clean off the pencil marks in Photoshop. Probably Photoshop 1.0 or something very early like that. I would put the digital files into a hard drive that would be accessed by the digital colorist during the day hours.

His name was Jeff Koke. I haven't talked to him in 30 years and he wouldn't remember a lowly scanning boy like me. BUT I've watched his career from afar all of this time. He's a design god and created identities for brands that we've all seen and used. Kind of fun to "I knew a guy before ..." thinking about the stuff he's done.

One of the perks that I had at the job was that Mr. Jackson himself would work into the late evening and night. Sometimes I'd get access to him and his brain as he was in his office. We were the only ones there. I can't remember anything in particular we talked about, but he was the first guy I met that made a career almost exclusively from his creativity.

I'd met many authors before, but this guy is a world builder. Not only building worlds but also the rules that the world operated in. Very cool. It left an imprint on me and I still thrive to be a world builder myself. Maybe subliminally his card games drove me to work on digital card games for Major League Baseball or even the ambitious NFT game with Peelander Yellow called MONMONMON.

So I got a book credit for my work that summer. I'm sure I helped on many more books but was there long enough to help this one and Lilian was kind enough to get my name in it. And spell it correctly.

Inside the box there was: Zap branded muscle tank top. Zap energy drink koozie. Zap socks. Zap fanny pack. Zap sticker. And a four pack of Zap energy drinks.

Here is the website for their promotion. Totally off the wall. Fun. And to be honest kind of confusing. Can I drink these energy drinks? Are they just Red Bulls? What if they don't taste good?

https://zapier.com/zap

I probably won't drink them and just place them near my Degen Ape beer. I never opened these up either. Marketing drinks FTW.

One jaw-dropping piece at the museum is Jeff Koons' Hanging Heart (Gold/Magenta). This massive sculpture, measuring 9 ½ feet wide, hangs from a magenta steel ribbon and is pure magic. It's one of five versions Koons created, and trust me, the gold sheen is something you need to see in person—pure magic.

Another highlight of my visit was seeing the portraits by Gilbert Stuart and Kehinde Wiley side by side. Stuart’s portrait of George Washington, known as the Constable-Hamilton Portrait, stands next to Wiley’s “Portrait of a Florentine Nobleman.” These paintings encapsulate what’s truly great about America—the diversity and depth of its artistic and cultural heritage.

Stuart’s portrait of Washington, with its rich historical context, offers a powerful representation of American leadership. This image of Washington, so familiar from the dollar bill, depicts the first president as a commanding figure, solidifying his image as a strong leader. The portrait also highlights the close-knit relationships among the nation's early influential figures, as it was commissioned by a merchant friend for Alexander Hamilton.

Kehinde Wiley, known for his vibrant and thought-provoking works, presents a different take with his “Portrait of a Florentine Nobleman.” Wiley is renowned for replacing historical white figures with African American subjects, and this particular painting based on a 16th-century portrait features Shontay Haynes of St. Louis. Wiley's inclusion of women in his works broadens the conversation on gender and representation in art, making his contributions essential to the modern artistic landscape.

While the indoor exhibits were as captivating as ever, the museum grounds showed signs of nature's unpredictability. The landscape is still recovering from a tornado that hit a few months ago. Fallen trees are being cleared, and the grounds are slowly being restored to their former beauty, showcasing the resilience and dedication of the museum’s staff.

My visit to Crystal Bridges was a reminder of why this museum is my favorite. The blend of historical and contemporary American art, set in a facility that’s world-class in every way, makes every visit special. If you haven’t been, I highly recommend making the trip—it’s an enriching experience that will leave you inspired and proud of the artistic talents our country has to offer.

"Exquisite Creatures" was more than just an exhibit; it was a dialogue with art, nature, and science that pondered humanity’s intimate relationship with the natural world. Marley's three-dimensional works comprised of animal, mineral, and plant specimens arranged in precise, geometric compositions made for a breathtaking visual feast. The meticulously crafted mosaics inspired wonder and fostered a sincere desire to preserve the natural world.

Walking through the exhibit was like stepping into a kaleidoscope. One of the most jaw-dropping pieces featured glossy, vibrant beetles that formed intricate shapes. Another stunning display used sea urchins meticulously placed to create an image of a wave sweeping across a triptych.

Marley’s artistry knows no bounds. He worked with moths, seashells, chameleons, exotic fish, flowers, shells, rocks, and many more specimens sourced from across the globe. This variety created an immersive environment, enhancing the awe-inspiring quality of the works. The butterflies from Costa Rica, the Puff Adders from Africa, and beetles from the Amazonian and Borneo rainforests were just some of the highlights that made the exhibit a truly global experience.

A particularly fascinating aspect of the exhibit was Marley's background. From a former fashion model to a renowned artist, his professional journey is as unique as the creatures he showcases. His travels around the world made him acutely aware of nature’s beauty and fragility, which he captures so exquisitely in his art.

Moreover, Marley’s ethical approach to collecting these specimens added a layer of respect and admiration to his work. He ensures that none of these creatures are killed for art; instead, they are collected after dying of natural or incidental causes, often through a network of people dedicated to preserving their beauty.

One of the show-stopping segments was a massive, butterfly mosaic that seemed to glow. The intricate arrangements of these delicate creatures showcased their vivid hues and beautiful symmetry, creating a captivating effect that drew gasps from everyone in the gallery.

While I could go on about specific pieces, like the enormous roly-poly that was even bigger than a lobster, or the giant snake exhibit adored by kids and adults alike, the best way to appreciate "Exquisite Creatures" would be to experience it yourself. Although the exhibit has closed, its impact continues to resonate with those fortunate enough to have seen it.

My visit to the "Exquisite Creatures" exhibit at Crystal Bridges was an unforgettable experience and a reminder of why this museum remains a treasure. Combining historical and contemporary art set in a world-class facility, Crystal Bridges is an enriching destination that leaves every visitor inspired. If you haven’t made the trip yet, I highly recommend keeping an eye out for their upcoming exhibits—your senses will thank you.

In conclusion, "Exquisite Creatures" was a grand testament to nature’s intricate beauty and diversity, elevated by Marley’s exceptional talent. May it ignite your passion for art, nature, and conservation as profoundly as it did mine.

First impression? Flux.1[pro] isn't just any upgrade; it's like the turbocharged sports car in a parking lot full of sedans. To keep things fair, I used my standard prompts to see how Flux.1[pro] measures up against the competition. Spoiler: it's like bringing a lightsaber to a stick fight.

Black Forest Labs threw their hat into the generative AI ring today, and let's just say, they brought a bazooka to a water balloon fight. One minute, you're ogling Neuschwanstein castle in mind-boggling detail, and the next, Lionel Messi floats by like a stained glass deity.

Now, let's dive into the nitty-gritty and see how Flux.1[pro] fared with my go-to prompts. Side note. MidJourney 6.1 isn't even a week old yet and its already time for it's funeral.

Castle

Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight

Family

Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k,

Evil Mickey

Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k,

Messi

Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details,

Robot

rusty robot with bow tie,portrait,8k,ultra realism,chrome background

Black Forest Labs has just unleashed the FLUX.1 suite, and they're shaking things up with a model family that sets new benchmarks in generative AI tech. These aren’t just incremental upgrades; they’re quantum leaps into the future. But what really makes Flux.1 special is that it's open source, combining cutting-edge technology with accessibility.

Powered by transformer blocks and boasting a staggering 12 billion parameters, the FLUX.1 models are built on a hybrid architecture of multimodal and parallel diffusion. With rotary positional embeddings and parallel attention layers, they are lightning fast and ultra-precise. And guess what? You can get your hands on it! The FLUX.1 suite is available for everyone, with versions tailored for developers and personal use under an Apache 2.0 license. So, whether you're building the next AI masterpiece or just want to tinker with some incredible tech, Flux.1 has got an option for you.

Next on the agenda for Black Forest Labs? They're gearing up to drop text-to-video capabilities that will take generative media to new heights. For more scoop, swing by Black Forest Labs and explore the world of Flux.

Play with it yourself here: https://fal.ai/models/fal-ai/flux-pro

Armed with a rented Trek electric bike, I rode about 20 miles of the trail system (40 miles total for the round trip). Now I can't wait to go back and tackle the complete 40-mile Greenway and explore even more. It's hard to believe how fantastic it was.

The bike trails here cater to all skill levels, and they're nothing short of spectacular. I mean, who would've thought Arkansas could offer such an epic biking experience? From high points offering breathtaking views to smooth, flowing paths designed to be enjoyed by everyone, the variety is amazing.

But not everything is always perfect in paradise. I noticed some trail damage from the recent tornadoes that swept through the city. The trail builders were already hard at work repairing the paths, reinforcing the community's resilience and their dedication to maintaining the trails.

Bentonville used to be just another small town, mostly known as the birthplace of Walmart. Fast forward a few years, and thanks to some hefty investments by the Walton family, it transformed into a biking hotspot. The grandsons of the Walmart founder, being avid mountain bikers, decided to pump some serious cash into building and expanding the trail system. What started as a modest project blossomed into this impressive network of trails.

Today, Northwest Arkansas boasts more than 500 miles of trails. And it's not just about the mileage; it's about creating accessible trails that connect communities and cater to all skill levels. Imagine rolling out of your garage and hitting a trail within minutes—Bentonville makes that a reality.

The vibe here is incredibly bike-friendly. You can ride around downtown and rarely see a bike locked up. The community's enthusiasm for biking is evident everywhere you look. It’s safe, fun, and definitely lives up to the hype.

Bentonville has convincingly staked its claim as the Mountain Bike Capital of the World. From its community approach to trail building to the sheer variety and complexity of its trails, this place offers something for everyone. I’m already making plans for my next pilgrimage. And yes, those are words I'd never thought I’d type about Arkansas.

Bentonville, this was my third trip to your beautiful charming city. You continue to impress. See you again soon.

I initially used MidJourney to generate Wolverine with this prompt:

wolverine, pixar style, 3D modal, action pose.

Despite his lack of pants, I was pretty happy with this image. Next step was to remove the background and upload the PNG file to Stable Fast 3D's new AI platform. It's amazing and speeds up idea exploration. Here is their website.

You can generate your own 3D model from an image here.

Here is the GLB model for you to play with or extend. A little bitmap coloring and some smoothing and this will look like a million bucks.

Audiobooks, blinkist book summaries, and honestly long conversations with ChatGPT are my companions and its my almost daily hour of Zen. Electric bikes are such a joy and eleviate the monotony of short bike rides and let you unlock beautiful rides.

I recently got to ride through just some of the trails in Bentonville, Arkansas and it might be my favorite thing in the world that I'm lucky enough to do. More on that soon.

MidJourney rolled out version 6.1 today and I went through my standard prompts to see how much the results have improved with this incremental update. The results are amazing.

Castle

Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight

Family

Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k,

Evil Mickey

Evil mickey mouse taking a selfie in Disneyland surrounded by shocked families, realistic, 70s style polariod, 8k,

Messi

Lionel messi wearing his Argentina uniform floating in the air with beams of light behind him posed like Jesus. Sunrise breaking behind him and a soft halo behind his head, in the style of a gothic stained glass window of a church, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight, maximum details,

Robot

rusty robot with bow tie,portrait,8k,ultra realism,chrome background

It was an ordinary evening, and I had just logged into PUBG, ready for another round. Little did I know, this session would become a cherished memory. As I navigated the battlegrounds, I found myself in a heated firefight in Pochinki. Suddenly, I realized I was up against Shroud himself. The adrenaline rush was unlike anything I'd ever felt before.

Seeing Shroud's name pop up in the kill feed was both exhilarating and intimidating. Known for his incredible aim and quick reflexes, Shroud was a formidable opponent. Our battle was intense, with bullets flying and strategic maneuvers at every corner. Each second felt like an eternity as I tried to outplay one of the best in the game.

• Tense Moments: The pressure was immense as I anticipated Shroud's every move, knowing one mistake could be my downfall.
• Strategic Play: Utilizing cover and smart positioning, I managed to stay one step ahead of Shroud's relentless assault.
• The Final Blow: In a moment of sheer determination, I landed the decisive shot, securing my place in gaming history.

Defeating Shroud was an incredible achievement, and the excitement was palpable. However, with Shroud's subsequent move to Mixer and the deletion of his Twitch legacy streams, this moment became even more special. It was a fleeting glimpse into the golden era of Twitch, a time when legends were made, and unforgettable battles were fought.

Facing off against Shroud in PUBG was a highlight of my gaming journey. It was a testament to the unpredictable and thrilling nature of online gaming. Although Shroud's Twitch legacy streams are now gone, the memories of those epic encounters live on. This experience not only sharpened my skills but also gave me a story to tell for years to come.

I hope this post captures the essence of that unforgettable night. Feel free to share your own epic gaming moments in the comments below!

In March 2003, I was quoted in an article about the controversial redesign of Macromedia's website. This redesign drew significant criticism largely because it relied heavily on Flash, which wasn't compatible with several browsers at the time, including Apple's Safari.

The Issue with Flash and Browser Compatibility

The article, titled "Revamped Macromedia site irks customers", discussed how Macromedia's decision to build their site entirely in Flash alienated many users. Not only did this choice lock out users of browsers like Safari and Opera, but it also raised questions about the usability and accessibility of web content. At the time, I commented:

"I definitely believe that Macromedia is alienating their core developer superstars with their latest Web site offering. It is too slow, a bandwidth hog, and doesn't work with a browser that many of these Flash developer superstars are using. Whether this is 'a lot' of people I'm not sure, but surely they are the alpha developers that so many of us read and trust."

Reflecting on the Web Then and Now

It's fascinating to look back at how web development has evolved since then. Flash, once a cornerstone of dynamic web content, has been retired, largely due to its limitations in performance, accessibility, and security. The web has moved towards more open, standards-based technologies that ensure greater accessibility and functionality across all devices and browsers.

Why It Matters

The story from 2003 serves as a reminder of the importance of forward-thinking in technology. We must consider how our decisions affect a diverse range of users, including those with disabilities. Accessibility and compatibility should be at the forefront of web design, not an afterthought.

This journey through a past article is not just about reminiscing but also about learning from the past as we continue to build more inclusive and functional digital experiences.

Flash might be gone, but the lessons remain as relevant as ever.

What I continue to find fascinating is how you can evaluate the maturity of a platform by how they restrict trademarks or IP from their generated content. For instance, Krea, Haiper, and Pixverse have no problem generating Mickey Mouse, but Runway blocks any mention of Mickey or Disney from being used. Clearly this is a lawyer game that is being played behind the scenes and the cost of success is having to limit your services to protect yourself.

Castle

Neuschwanstein castle, lightning, pixar style, volumetric lighting, unreal engine, hyper realistic, hyper detailed, maximum details, photorealistic, 8k, rimlight

Christmas

Family on their laptops while sitting around a Christmas tree with presents underneath and looking worried because they have to finish up work, realistic, 4k,

Mickey

Theme park costumed mouse surrounded by excited children, bright and colorful setting, high definition, cinematic