Essays on displacement, economic restructuring, sovereign compute, and what happens when the models get good enough to matter.
I'm George Pu. I've built businesses without venture capital, and I've spent the last two years writing about what AI is actually doing to the economy — not what conference panels say it's doing.
This page collects my essays on the questions that matter most for governments and policymakers: How many jobs are actually at risk? What does sovereign compute mean in practice? Where does the displacement hit first, and what does restructuring look like?
These aren't policy papers. They're observations from someone who builds with AI every day and sees the gap between what founders know and what governments are planning for. I'm not selling consulting. I just think the people making decisions should have better inputs.
If you work in policy and want to discuss any of this, reach out.
There's a growing disconnect between what's happening in AI labs and what reaches policy desks.
“The gap between what AI can do today and what most governments think it can do is the most dangerous information asymmetry of our time.”
— The premise behind every essay on this page
Each theme represents a category of essays — a different angle on the same transition.
Who loses work, how fast, and what the second-order effects look like.
Not hypothetical. Companies are already cutting headcount and citing AI. The question isn't if — it's which roles, in what order, and how fast the cascade moves through the economy.
Revenue concentration, wage compression, and what GDP stops measuring.
When 10 people do what 100 did, GDP might hold steady while employment craters. Traditional economic indicators will mislead. New frameworks are needed.
Why compute access is the new geopolitical resource — and who controls it.
Three countries control the AI stack. Everyone else rents access. For nations, this is the new oil — except the supply chains are even more concentrated.
What the trajectory looks like at 12, 24, and 60 months from now.
Extrapolating from current capability curves, cost reductions, and adoption rates. Not predictions — projections based on what's already measurable.
Data points from real research, not conference optimism.
Individual roles eliminated. Hiring freezes disguised as “efficiency.” Companies building internal AI but not announcing headcount impact. The data doesn't show it yet — but the decisions are already made.
Entire departments restructured. Mid-career professionals displaced at scale. Tax revenue from knowledge work begins declining. The public narrative catches up to what builders already see.
New economic structures emerge — or don't. Countries that invested in sovereign compute and workforce transition frameworks pull ahead. Everyone else imports capability and exports dependence.
Long-form thinking on displacement, restructuring, and what governments should actually be planning for. No policy jargon. Just observations from the build side.
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Vinci ships August 8 with the methodology published in full - so competitors can copy it. The thing they can't copy is whether the model actually does what its constitution says, in public, under tests anyone can run.
On June 12 a government letter reached past Anthropic and switched off the best coding model I'd ever used. The shutdown wasn't the lesson - what it revealed about renting intelligence was.
Over the past two years, Canada quietly rebuilt the question of who controls its artificial intelligence. Not in one announcement. That's the point. There was never a single moment loud enough to make you look up. The decisions arrived in fragments — a Christmas Eve letter, a contribution agreement with a file number, a press release at a university most people don't follow, an MOU with the important parts blacked out. Each fragment was, on its own, small enough to ignore. Together they red
In the last piece I wrote about the anchor: Canada designated Cohere as its national champion at the foundation model layer — $240 million, a 24-year term, an MOU that called the company "the only sovereign, cloud-agnostic large language model operating in Canada," and a fund Cohere itself proposed. That designation is settled for a generation. This piece is the opposite kind of writing. The last one was analysis of public records, and I tried to stay out of it. This one carries a point of
On Christmas Eve 2024, the Government of Canada issued a Letter of Intent to Cohere for a Strategic Innovation Fund contribution of $240 million. The timing is the first thing worth noticing. Christmas Eve is when governments send letters they want done quickly and quietly. The Trudeau government was already wobbling. Chrystia Freeland had resigned on December 16, eight days earlier, in a public letter that called out the Prime Minister's "costly political gimmicks." Less than two weeks lat
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
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
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
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
The Umbrella Closed on a Monday I tweeted something Monday morning about France and nuclear weapons. Felt strange typing it. I help founders figure out where to build their lives. I'm not a foreign policy guy. I don't have a PhD in international relations. I'm a 27-year-old in Toronto who runs a small business and posts on the internet. But I've been saying for two years that the world is about to test who actually owns their
Two days ago, the President of the United States stood in the House chamber and said: "More Americans are working today than at any time in the history of our country. The economy is roaring like never before." The next day, Jack Dorsey cut 4,000 people from Block (formerly Square) — 40% of the company — because AI made their jobs unnecessary. The stock went up 22%. Dorsey said he was late. Weeks before that, the Premier of Onta
Everyone is talking about Canada cutting immigration. Nobody is talking about Canada changing who runs it. That's the actual story. And it's a bigger deal than the cuts. How I See This I need to tell you where I'm coming from. Because it shapes everything. I moved to Canada from China when I was 18. Showed up at the University of Waterloo with a suitcase and no plan beyond getting a degree and figuring it out. I went throug