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240+ Essays

Essays

Deep thinking on building businesses designed to own forever. Not how-to content. Decision logs, frameworks, and pattern recognition.

George Pu
George Pu
$10M+ built. Still own everything.

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Sovereignty Is Not About Ownership
Own Your Tech

Sovereignty Is Not About Ownership

A vice-president at a Canadian university called me last month. Her president had told her the institution needed to be on sovereign AI within the year. The provincial government had announced a funding program. Other universities were already applying. She wanted to know what she should be evaluating. I asked her what sovereign meant in this context. She paused for a long time. Then she said, "I think it means the data stays in Canada." I asked what about it staying in Canada specifically

·6 min
I Almost Told a Lawyer to Build His Own AI
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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

·6 min
Fine-tuning your own AI doesn't cost $35,000. It cost us about $50.
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Fine-tuning your own AI doesn't cost $35,000. It cost us about $50.

Two A100 graphics cards. Spinning quietly in a Google datacenter. Five hours of training. About $50 in compute. That's what it cost us to fine-tune our own 4-billion-parameter AI model this week. The base model went from 30% accuracy on the tasks we care about to 98%. Read any article on fine-tuning costs and you'll see numbers between $5,000 and $35,000. One blog called it a 'CFO conversation.' Another listed 'hidden expenses' that could double your initial estimate. A third quoted team

·5 min
Your ChatGPT and Claude Conversations Are Court Evidence
George's Takes

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

·6 min
The Journal That Exposed the President
George's Takes

The Journal That Exposed the President

Greg Brockman keeps a diary. Not a metaphor. A literal, decades-long, type-into-his-laptop journal that he started in college when he was deciding what to study. He kept it through Stripe. He kept it through founding OpenAI with Musk and Altman. He kept it through the brawl for control of the company in 2017 - the fight that's now being relitigated in a San Francisco courtroom. This week, his journal became Exhibit 161. Hun

·4 min
One Rack Is a Cloud
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One Rack Is a Cloud

What colocation is, and why most AI founders have never heard of it

·10 min

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You Want Out of OpenAI. Here's Where to Actually Start.
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You Want Out of OpenAI. Here's Where to Actually Start.

A week ago, I published AI Real Estate. The framing was simple: the AI you use today is rented — like an apartment. There's a ladder above it. Most people don't know the ladder exists. The response was the part I didn't expect. Dozens of people messaged me with versions of the same question. I read it. I get it. I want out. Where do I actually start? Some were lawyers. Some were founders. Some were accountants and consultant

·16 min
Three Kinds of Cloud (and Why Two of Them Keep Getting Confused)
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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

·6 min
GPU Cloud Shopping in Canada: Three Weeks Later
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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

·6 min
What fine-tuning actually costs (it's not what you think)
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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

·6 min
Why I chose Unsloth (before training a single token)
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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

·7 min
Why I'm fine-tuning a small model (and why it runs on your laptop)
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Why I'm fine-tuning a small model (and why it runs on your laptop)

I'm training an AI model. It's going to run on a laptop. Three weeks ago I would have told you I was training a 70-billion-parameter model, the kind of thing that needs a data center to breathe. I'm not. I'm training a 4-billion-parameter model that runs on a Mac Mini. If the smaller one works, a larger companion model may follow. But the 4B is the bet. This is the first post in a series where I'll share what I'm building, why,

·5 min

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