We research, invest in, and build long-term ownership in the companies powering intelligence — across digital intelligence and the emerging frontier of physical intelligence.
Every position starts as research. Research sharpens into an investment thesis. The thesis becomes long-term ownership in the companies building the infrastructure of the intelligent economy.
Public writing on the economics of compute, models, and machines.
Where the infrastructure layer of the intelligent economy will form.
Long-term ownership in the companies building it — starting with Watt.
Intelligence is scaling in two layers — digital and physical. Each needs an infrastructure and economic layer underneath it. Compute Notes researches, invests in, and builds across both.
The optimization layer for enterprise AI adoption — managing AI workloads, cost, and performance across complex model ecosystems.
Autonomous machines, robotics, and industrial automation — AI infrastructure extending into the physical world.
Intelligence delivered as software. The bottleneck becomes cost and control — the consumption layer of the agent economy. Watt is our first venture here.
Intelligence delivered through machines. As robots and autonomous systems scale, they need their own perception, control, and unit economics — the next infrastructure layer.
We research, invest in, and build long-term ownership in the companies shaping the intelligent economy — approaching AI as a unit-economics problem, informed by a background in M&A and financial due diligence. Not a service provider, and not a fund with a fixed clock: an operator-investor building conviction positions over a long horizon.
The financial and consumption layer of the agent economy.
Intelligence meeting the physical world — perception and control.
The next interface between humans, machines, and space.
Watt is not the whole story — it is the first proof point. Each venture tests the thesis in a real market before the next frontier is funded.
An AI co-pilot for audit professionals — the optimization thesis applied to a real, paying workflow.
An agent for M&A and transaction-services work, built from years inside diligence rooms.
The second frontier, already in development — a real pilot in a real market, not a slide.
Our first pilot applies Physical AI to agriculture, using intelligent systems to transform existing industrial workflows. Agriculture is a compelling entry point: real-world environments, proprietary data generation, and clear operational economics.
The underlying technology has broader applications across industrial automation, infrastructure inspection, energy, forestry, and other complex environments.
The intellectual engine behind every thesis and venture — published openly.
The economics of compute — and what we're building underneath it.
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