Our case for Cognition (full piece with my colleagues @JTLonsdale @AlexKolicich @bela_becerra below) starts with two ideas from economics: Ricardo's comparative advantage and Coase's theory of the firm. Ricardo: gains from trade come from difference. Even a party that is better at everything comes out ahead by trading, because what matters is opportunity cost. A frontier model can be the best at every task and still be the wrong choice for most of the volume (every GPU-hour spent on routine edits is one not spent on work only it can do). The more jagged the frontier, the larger the gains, and the more it pays to be a good trading partner to every lab. A lab's own agent is protectionist by design (it buys domestic). Cognition trades with everyone and builds its own models where it has a comparative advantage. Coase: firms exist because markets are costly to use (finding a counterparty, negotiating, checking the work), so activity moves inside a firm wherever internal coordination is cheaper. As intelligence gets cheap, coordination becomes the scarce input. Ten thousand isolated copilots pay a transaction cost on every handoff, mostly in lost context. Devin brings those handoffs inside one system (shared context, planning, delegation, verification), with humans in the role Coase gave the entrepreneur: directing the work. Ricardo tells you where the surplus comes from, and Coase tells you what it costs to collect it. It goes to whomever can create the most intelligent system to solve this massive coordination problem and create true man-machine symbiosis (conclusion = build the best cloud agents). We heard a lot of skepticism when we invested at $2B and led the round at $4B. The labs were shipping their own agents, and the common view was that the layer in between would get squeezed. We thought better models would make it more valuable. Devin was a new kind of product, and it arrived early. It had an interface overhang (the mirror image of a capability overhang): you could delegate more to it than the models could yet deliver, and more than most teams were ready to hand off. The models grew into it, and cloud agents are now a category. The team built through that whole stretch like madmen. They are the most persistent group of people I've ever seen, and even by the standards of AI cycles, they move fast. Job not finished.

I'm proud to now be a Partner at @8VC, and I can't think of a better moment to be in this seat. Startups are beautiful things designed to fight the inertia of the world, but they die if the world stands still. The question we ask every founder, "why now?", is a second-derivative one (incumbents handle a low, predictable rate of change just fine), so four years ago most pitches didn't have a great answer, and today these answers are inspiring and plentiful. For years we argued for ideas outside consensus (that America needed to build again, that the legacy industries written off as bad software markets were exactly where AI would strip the tedium out of work). The Overton window has since moved our way, and more of the founders building in those markets now start with us. Ambition has changed too. You used to wait for scaled PMF before shipping products 2 and 3, but software is now infinitely iterable (thanks @DevinAI), so the best teams chase the maximally ambitious version of their company far earlier, and the intensity of the work right now is contagious. I'm an ambitious person myself, and I feel privileged to do this work at this moment. Thank you @JTLonsdale @AlexKolicich @andrewoetting and the whole 8VC team for the trust. Never been more optimistic.