The Fat Wallet Thesis
It's Not Just Crypto Anymore
Forget the core tech. Distribution is destiny. I wrote about this last year as it applied to crypto. A year later, I think it's the single most important framework for understanding where value lands in AI too. Maybe in every technology cycle, period. The short version: the most valuable layer in any technology stack is the one closest to the user. The layer with the lowest switching costs and the most direct distribution channel. In crypto, that layer is wallets. In AI, it's the assistant. The principle is the same.
The stack, simplified
Think about it like floors in a building:
Ground floor: Infrastructure
Blockchains. Data centers. GPU clusters. Essential, invisible, and increasingly commodity. Nobody brags about their ISP at parties. Nobody's going to brag about which foundation model powers their assistant, either. Not for long.
Middle floor: Protocols
AWS, DeFi protocols, model APIs. Important middleware. But users don't care which protocol handles their swap any more than you care which CDN serves your Netflix stream. Or which model answered your question.
Penthouse: The interface
Chrome. MetaMask. ChatGPT. This is where people actually live. This is where attention sits. And attention is the only currency that doesn't inflate.
The crypto version (still true)
Robbie Petersen laid this out well: as blockchains commoditize, wallets become the value capture layer. They own the user relationship. They see every transaction. They can route flow wherever earns the best kickback. The wallet doesn't care if you're on Ethereum or Solana. It cares that you're using their wallet. It's the Google playbook. Chrome doesn't care which server your website runs on. It cares that you're searching through Google.
The AI version (and why it might be bigger)
Now watch the same pattern play out in AI, except faster and with higher stakes. Models are the new L1s. GPT-4, Claude, Gemini, Llama, DeepSeek - they’re all converging. Performance gaps shrink every quarter. Open source is nipping at closed source. Sound familiar? It should. It’s the L1 wars all over again. And just like L1s, models are becoming plumbing. The AI “wallet” is the assistant. Whoever’s chat interface you talk to first thing in the morning owns your decisions. Not your model provider. Not your cloud host. The assistant layer sees everything: your calendar, your emails, your preferences, your purchase intent. It routes your attention the same way a wallet routes your transactions. The switching cost is trust, not technology. You don’t switch assistants because a new model scores 2% higher on a benchmark. You switch when you lose trust. Your assistant knows your schedule, your writing style, your kid’s school pickup time. That’s a moat no benchmark can measure. Here’s the thing about the AI version that makes it scarier than crypto: the interface layer doesn’t just route transactions. It routes thinking. When your assistant summarizes your email, picks which meetings matter, drafts your responses - it’s not just capturing value. It’s shaping decisions. The fat wallet thesis in crypto is about capturing transaction flow. In AI, it’s about capturing cognitive flow.
The pattern, zoomed out
Every tech cycle, same movie:
Web: Hosting was commodity. Browsers won.
Mobile: Carriers became pipes. IOS and Android captured the value.
Cloud: Compute is commodity. Slack, Notion, Figma - the apps on top took the margins.
Crypto: Blockchains commoditize. Wallets win.
AI: Models commoditize. Assistants win. In each cycle, smart money bet on infrastructure early. But the long game always favored whoever owned the last mile to the user’s eyeballs. Or in AI’s case, the user’s thought process.
Where are your bets?
Most people right now are betting on models. New architectures, new training runs, new benchmarks. Some of those will do fine. But the asymmetric bet is the same as it's always been: the interface layer. He who controls the front-end controls the future. The real question in crypto was "which wallet do 100 million people open every morning?" The real question in AI is "which assistant do 100 million people think through every morning?" If the answer is the same product, god help us all.
Originally published 2025. Updated Feb 2026 with the AI parallel. Inspired by @robbiepetersen_'s Fat Wallet Thesis