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The Barrier to Building AI Isn't Talent. It's Capital.
Startups in San Francisco raise $18 million just to afford the compute. We did the same work bootstrapped. The real gate on who gets to build AI isn't ability - it's who can afford to be in the room.
Read storyFounder Reality is written by George Pu — $10M+ portfolio built by 27, no investors, no co-founders.
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What I'm thinking about right now.
We Are No Longer Building a Canadian Legal AI Model
Yesterday I published the post-mortem: we asked flash-1-mini ten questions any Canadian lawyer would consider basic, and it invented seven citations. That post was about what broke. This one is about what it changed. Because two weeks ago I was telling people we were building a Canadian legal AI model - and today we decided we're not. I want to walk through why, because the answer changed how I think about what "building AI" actually means. The original scope The original scope made sense
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We Asked Our 4B Legal AI 10 Questions. It Invented 7 Cases.
An honest post-mortem on our own model — and what anyone building or buying AI should take from it.
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Open Weights, Closed System
Google shipped local AI on the Mac this week. The weights are Apache 2.0. The experience is a walled garden. That's not a contradiction. That's the playbook.
Read essayFrom the series · 90-Day Action Plan to Surviving AI
The Money Question
When I was deciding whether to kill SimpleDirect, the biggest thing holding me back wasn't the identity stuff. It was money.
More on Inside the Machine
Three essays from the archive on a different angle.
Why I'm Open-Sourcing My Portfolio
What active thesis investing actually looks like — and why I'll publish every bet I make.
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Why I Sold My Index Funds in February
Why the index gospel was built for a world that no longer exists.
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The Lie Every $997 Trading Course Sells You
What two years of quant trading taught me before I shut it down.
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You might not have read this
A couple of older essays we think are worth a second look.
I Almost Told a Lawyer to Build His Own AI
A lawyer friend — call him Mark — called me this week. He and another friend had spent the weekend trying to run an 8 billion parameter language model on a 16 gigabyte laptop. Mark thought he was going to show his friend something impressive. The output was gibberish. Incoherent strings of text that no junior associate would have signed off on. He'd come to me because he wanted to know what hardware to buy next. On the call, I didn't know. What I did know was NVIDIA's software stack. I'd
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Hardware Sovereignty Is the New Data Sovereignty
After I wrote about trying to buy a Mac Studio and failing, the replies kept circling the same question. "If I can't buy the hardware and I don't trust the cloud, what am I supposed to do?" That question led me somewhere I didn't expect. I Checked What GPUs You Can Actually Get in Canada Not the marketing pages. Not the pricing calculators either. The actual hardware you can spin up today in a Canadian data center. I went t
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Recent threads
The latest from @TheGeorgePu.
Canada's AI hardware reality check — what's actually available vs. what founders think they can buy.
GPU shipping is the tell. If you can't physically own the compute, you don't own your AI stack.
I only write code when it's 10/10 important. Slowing down is the real productivity move in 2026.
Mac Studio supply is crunched. Apple's quietly rationing M3 Ultra — AI builders feel it first.
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