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Your ChatGPT and Claude Conversations Are Court Evidence
Greg Brockman's journal became Exhibit 161 this week. The next chapter writes itself. Someone's ChatGPT history becomes Exhibit 162. That sentence sounds like speculation. It isn't. The infrastructure is already in place. The court orders are already in place. The only thing missing is a famous enough defendant for the headline to break the way Brockman's did. The court order most people haven't read In May 2025, Magistr
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.
GPU Cloud Shopping in Canada: Three Weeks Later
Three weeks ago I wrote a post called GPU Cloud Shopping in Canada: What's Actually Available. The short version: I checked every major cloud provider with a Canadian data center, trying to rent a current-generation GPU to train AI models in this country. Google Cloud Montreal had chips from 2017. AWS listed the right hardware but wouldn't let me actually run it. OVHcloud's H100s turned out to be in France, not Quebec. DigitalOc
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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
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Why I chose Unsloth (before training a single token)
Honest note up front: I have not yet fine-tuned anything with Unsloth. I have not run a single training job. What I did is spend three weeks researching fine-tuning frameworks before writing a line of training code — and at the end of that research, I picked Unsloth and committed to it. This post is about why. I'm writing it now, before I start, for two reasons. First, so that if this decision ages badly I have to own it public
Read essayFrom the series · The AI Displacement Series
The Two Responses
This is Chapter 2 of 7 in the AI Displacement Series.
More on Policy & Economy
Three essays from the archive on a different angle.
One Company Summoned Two Central Banks
I was at my desk Tuesday when the Bloomberg alert came through. Bessent and Powell — the Treasury Secretary and the Fed Chair — had called an emergency meeting with every major bank CEO in America. Not about interest rates. Not about the war. Not about a bank run. About a single AI model. Built by a single company. "Yeah, Sovereignty, Sure" I run a project called Sovereign Cloud. The whole thesis is that governments and bus
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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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Three Kinds of Cloud (and Why Two of Them Keep Getting Confused)
I sat down with a Canadian university last week. They were trying to articulate to industry partners what their compute offering would be. They knew "sovereign" was the right word. They couldn't define it for a buyer. They couldn't tell me what a partner would actually use it for that they couldn't already do on AWS in Montreal. That's not the university's failure. The industry calls three different things "cloud" and lets two
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ReadThe Post-AI Manifesto
The five layers AI can't eat — and how to build a career inside them.
ReadOwn or Be Owned
In the AI economy, you're on one side of the split. This is how to find out which.
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A couple of older essays we think are worth a second look.
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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You Cannot Buy What Can Only Be Built
Meta spent $14.3 billion last year to buy half of a data labeling company. They made its 28-year-old CEO the head of their Superintelligence Lab. Gave him a title that didn't exist six months before. Put him above researchers who'd been doing AI before he was in high school. Nine months later, his team reports to other people. A new group controls the data pipelines. The researchers he was supposed to lead are leaving. And the
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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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