Data. AI. A little perspective.
AI economics, data strategy, and the realities of building with both. Independent thinking, forged through experience.
Read the latestFresh from the forge
What AGI and ASI actually mean, what Astra changes about autonomous work, and why capability, continual learning, and consciousness are different questions.
Read the essayThe latest thinking
Palantir just gave a name to the thing I've been writing about for a year: tokenmaxxing. Enterprise AI rollouts are getting paused, token budgets capped, and leadership is finally asking what the spend actually buys. The story is breaking, and the wallet is what broke it.
Frontier models are genuinely better, and they still leak at the seams the moment an app has to scale. Dwarkesh Patel just named why: sample efficiency. The takeoff story everyone is selling assumes the AI inside the box will build its own way out, which is circular. A look at the data ceiling and what it means for anyone planning around imminent ASI.
The same CEOs who sold boards on replacing people with AI are now walking it back. The receipts from Microsoft, Nvidia, Uber, and the BLS say what I've been saying all along: AI is a tool that makes talented people better, not a one-for-one swap for them.
New here?
Three ways into the ideas behind The Data Forge.
Follow the money behind the models. What does AI actually cost, and what does it buy?
Start with the economics Explore all AI essays →The platforms, decisions, and unglamorous work that make everything else possible.
Start with the foundation Explore all Data Strategy essays →Building teams, protecting judgment, and leading through the next wave of change.
Start with the team Explore all Leadership essays →Put the thinking to work
I advise leadership teams on AI spend, data strategy, and building the teams that carry both.