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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.
Latest Essays
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 Commitment
After I started running experiments and having conversations, opportunities started appearing.
More on Investing
Three essays from the archive on a different angle.
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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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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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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Straight from the inbox
The weekly newsletter — long-form, no fluff.
Latest Videos
Real talk. No script.
What you might have missed
Three things from across the site you may not have found yet.
90-Day Action Plan
A concrete week-by-week plan to get out of the line of fire.
ReadOwn or Be Owned
In the AI economy, you're on one side of the split. This is how to find out which.
ReadSovereignty
The case for building a life nobody can revoke — money, jurisdiction, identity.
ReadYou might not have read this
A couple of older essays we think are worth a second look.
What We're Building: An Open-Weight Canadian Model Series
The model is the smallest part of the story. Here's what it is, what it isn't, and what comes next. Today we shipped flash-1-mini. It's a 4-billion-parameter open-weight model, fine-tuned for Canadian context, bilingual in English and French, that runs on a laptop with no cloud dependency. You can download it, run it offline, and own it. The weights are yours. I want to write about what it is, what it isn't, and what comes after — because the model itself is the smallest part of the story.
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What fine-tuning actually costs (it's not what you think)
Training an AI model is assumed to cost millions of dollars. It's the single most common misconception in the space, and it's wrong by roughly two orders of magnitude for the activity most people actually want to do. This post is a short, concrete breakdown of what fine-tuning actually costs in 2026, what it doesn't cost, and where the real spend lives. I'm writing it now because 'how much does this cost' is the first question
Read this essayRun the numbers yourself
Free calculators and assessments. No email wall.
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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