Decode how the world's most powerful tech ecosystems are built — and who wins next

If you work at the intersection of technology, capital, or policy, you already know the frustration. Every week brings another breathless article about China's AI dominance, or Silicon Valley's latest unicorn, or Europe's startup gap — and almost none of it gives you the structural understanding to act on what you're reading. The headlines change; the underlying dynamics stay opaque.

I built this lab for the people who can't afford to stay at the headline level — because their decisions are too consequential for that. The investor who needs to assess geopolitical risk in a Southeast Asian tech bet. The policy analyst drafting an industrial strategy who needs to understand what France's Grandes Écoles system actually does, and what it doesn't. The startup founder choosing between Singapore and Warsaw for a European expansion. The graduate student who wants to understand why Shenzhen became the world's hardware capital, not just that it did.

What I've tried to do here is build the course I kept looking for and couldn't find. Not a country-by-country tour. Not an economics textbook. A working analytical toolkit — a six-dimensional framework that you apply consistently across five of the world's most structurally distinct innovation systems, so that by the time you've worked through it, you can turn that same framework on any ecosystem anywhere and know what questions to ask and where to look for the answers.

The material doesn't flinch from complexity. We go inside the mechanics of DARPA's funding model and how it differs from Horizon Europe. We examine what Made in China 2025 actually specified versus what it achieved. We interrogate the ethics of surveillance-enabled data advantage. We look hard at diaspora networks — brain drain, brain gain, brain circulation — because talent is the variable that most analysis underweights. And we spend serious time on the geopolitics/geoeconomics: US-China tech decoupling, semiconductor export controls, supply-chain interdependencies, and AI governance divergence, because these are no longer background conditions — they are the decisive strategic variables of the decade.

I expect a lot from everyone who engages with this curriculum, and I'll give a lot in return. Come with intellectual curiosity, a willingness to sit with data that complicates the simple story, and a genuine question you're trying to answer — about where to invest, where to locate, what to build, or what to recommend. That's the right starting point. I'll see you inside the lab.