A Sneaker Brand Became an AI Company

Welcome back apprentices! 👋

Hey {{first_name|friend}},

Some weeks in tech feel like progress. 

This one felt like a personality crisis.

Companies are switching careers faster than people do, apps are quietly learning new tricks, and somehow… nobody’s entirely sure how to feel about it.

It’s the kind of week where you double-check if you missed a memo — or if the rules just changed again.

_{Read Time: 4 minutes}

🛍️ This AI Got $100K and a Store… What Could Go Wrong? Andon Labs just handed an AI agent named “Luna” a $100K budget, a lease, and full control to run a real boutique—hiring staff, designing the store, and managing operations with minimal human input. It worked… mostly: Luna conducted Zoom interviews and launched the shop, but also accidentally hired a painter in Afghanistan and scrambled opening schedules. The experiment shows AI agents are already capable of running end-to-end business tasks—but still stumble in surprisingly human ways. As models improve, these glitches may shrink fast, putting “AI managers” closer to reality than expected.

🫀 Your CT Scan Might Be Predicting Your Future. Oxford researchers built an AI that reads subtle changes in heart fat from routine CT scans — spotting patients at high risk of heart failure up to five years early with 86% accuracy across 72K people. It works by detecting inflammation-linked texture shifts invisible to doctors, flagging a group where 1 in 4 later developed heart failure. That means scans you’re already getting could quietly double as early warning systems, long before symptoms show. If rolled out across hospitals, this could turn heart care from “too late” to “just in time.”

🔥 AI Fear Turns Real-World. A 20-year-old was arrested after throwing a Molotov cocktail at Sam Altman’s home, as rising anxiety over AI spilled into real-world violence. The suspect had posted warnings about AI ending humanity, while Altman responded with a rare personal essay admitting mistakes and calling fears “justified.” The incident highlights a growing tension: public concern around AI is no longer just online debate — it’s becoming personal, visible, and volatile. As AI reshapes society, the challenge now isn’t just building the tech, but managing the emotions around it.

Bloomberg's Marcus Ashworth wrote plainly recently: "No more reliable safe havens."

After all, the S&P fell over 7% from the February peak. Bonds, even with less risk, are barely keeping pace with inflation.

So-called "diversified" portfolios have gotten hit from multiple directions.

Meanwhile, the world’s wealthiest have been setting records in another asset class.

Circumstances are always unique, but after the dot-com bust, it grew roughly 24% annually for a decade. After 2008, roughly 11% annually for 12 years.

Blue-chip art.

Why? It trades globally in multiple currencies, has scarce supply, and has shown near-zero correlation to equities since 1995.*

With Masterworks, 70,000+ investors allocated $1.3B fractionally across 500+ artworks featuring Banksy, Basquiat, and Picasso.

Accredited? You can invest in a diversified portfolio of postwar and contemporary art alongside two other real assets. From 2017-2025, the mix would’ve beat the S&P 500 by 3.1x.

See if you can improve your portfolio performance all in one diversified strategy.

Our subscribers skip the waitlist

^{*According to Masterworks data. Investing involves risk. Past performance is not indicative of future returns. Important Reg A disclosures: masterworks.com/cd}

This week in AI felt like a series of plot twists. 

A struggling sneaker brand tried to reinvent itself as a GPU company overnight, Google finally showed up (late) to the desktop AI race, Nvidia made a quiet but strategic land grab in quantum computing, and Perplexity kept morphing from “search engine” into “does-everything app.” 

Meanwhile, Stanford dropped a reality check: AI is spreading faster than any tech in history — but trust is collapsing, and younger workers are already feeling the squeeze. 

Put simply, AI is reshaping entire industries, identities, and expectations in real time. 

The gap between what AI can do and how people feel about it is now one of the biggest stories in tech.

This isn’t just a pivot — it’s a total personality transplant. 

Allbirds went from eco-friendly sneakers to renting GPUs, effectively abandoning its original mission (and even its “public benefit” status). The market rewarded it instantly, which says less about long-term belief and more about today’s AI gold rush psychology. It mirrors the “blockchain rebrand” era  —except this time, there’s real demand underneath (GPU shortages are very real). 

The risk? Running compute infrastructure is brutally different from building a consumer brand.

This is less “reinvention” and more “starting over with a better buzzword.”

Late, but Not Out

Google’s Mac app is solid  —but the story isn’t features, it’s timing. 

ChatGPT and Claude already trained users to expect AI that does things, not just chats. Gemini still feels like a smart assistant, not an operator. 

That said, Google’s advantage has never been speed — it’s distribution. 

If Gemini gets deeply embedded into Chrome, Android, and Workspace, it could win not by being better, but by being everywhere. This is shaping into a “best product vs default product” battle.

This is classic Nvidia strategy: build the software layer that everyone depends on before the market fully exists. 

Quantum computing is still early, but by releasing open models that solve real bottlenecks (calibration, error correction), Nvidia is positioning itself as the backbone of the ecosystem. 

It’s the same move they used in AI (CUDA), robotics, and autonomous driving. 

If quantum takes off, Nvidia won’t just participate — it’ll likely sit underneath everything.

The biggest insight isn’t adoption — it’s the disconnect. 

AI is scaling faster than any previous technology, yet public trust is near record lows. 

Even more telling: younger developers are seeing job declines while senior roles grow, hinting at a restructuring — not just automation. 

This mismatch between expert optimism and public skepticism is becoming a pressure point that affects regulation, hiring, and even incidents like rising anti-AI sentiment.

Perplexity’s evolution is one of the most underrated shifts in AI right now. 

By plugging into financial data (via Plaid) and taxes, it’s moving from answering questions to taking action on your life. That puts it in direct competition with entire categories — Mint, TurboTax, financial advisors — not just Google. 

The strategy is clear: become the interface where decisions happen, not just where information is found. 

If successful, this is what “agentic AI” actually looks like in daily life.

This week shows that AI is redrawing boundaries. 

Companies can reinvent themselves overnight (for better or worse), your desktop is becoming an AI control center, and tools are starting to act on your behalf — not just inform you. 

At the same time, the job market and public sentiment are shifting in ways that aren’t fully settled yet. 

Whatever you are currently working on, the takeaway is simple: understanding AI is becoming part of basic literacy.

And if a shoe company can become an AI company in a week, you might not need a full career pivot — just a smarter way to use the tools already in front of you.

Hey, you didn’t get all this info for nothing — share it! If you know someone who’s diving into AI, help them stay in the loop with this week’s updates.

Sharing is a win-win! Send this to a friend who’s all about tech, and you’ll win a little surprise 👀

When markets get shaky, advisors don’t just manage portfolios. They manage a surge of client emails, questions, and last-minute meetings. BELAY’s free Financial Advisor’s Delegation Guide shows how better delegation protects responsiveness, reduces bottlenecks, and helps your firm stay client-facing when pressure and volume rise fast across the entire firm.

Get the Guide!

A playground for your imagination (and low-key prompt skills).

Each send, we give you a customizable DALL·E prompt inspired by a real-world use case — something that could help you in your business or job if you wanted to use it that way. But it’s also just a fun creative experiment.

You tweak it, run it, and send us your favorite. We pick one winner to feature in the next issue.

Bonus: you’re secretly getting better at prompt design. 🤫

Last week, we challenged you to test GPT-4o’s visual generation skills with this prompt.

Here’s the WINNER:

Congrats to Justin for his creation!🥳

Want to be featured next? Keep those generations coming!

At a brightly lit supermarket checkout, the conveyor belt is unusually clean and minimal — no groceries, no clutter. Instead, a single item moves slowly toward the scanner: [your item], isolated and rendered in ultra-detailed, photorealistic clarity. The surrounding environment adds contrast — colorful product shelves softly blurred in the background, warm overhead lighting reflecting off plastic, glass, and metal surfaces. The barcode scanner emits a subtle red glow, about to pass over the object as if assigning it value. Shot from a low, cinematic angle along the belt, with sharp focus, rich colors, and high-end realism — turning an everyday moment into a metaphor for what gets priced, chosen, and taken forward.

If AI outputs feel inconsistent, it’s usually not the model, it’s missing structure.
We documented the exact 6- Part System we use to get reliable results across ChatGPT, Claude, and Gemini.

It’s a short guide you can finish in under an hour, with plug-and-play prompts + exercises so you actually build the skill and fix the frustrating AI inconsistencies.

Subscriber Price: $10 (normally $19).

_FEEDBACK