Unlocking Data and AI
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Subscribe • Previous Issues Open Models Will Absorb Most of the AI Spend Here is my bet: open models (open weights and open source alike) will end up absorbing most of the money and compute the world spends on AI. The proprietary frontier models get the headlines and the IPO valuations, but developers and AI teams see something different up close. Open…
Subscribe • Previous Issues What Startups Taught Me About the Next Layer of AI Infrastructure A little while back I wrote about how teams use reinforcement learning (RL) to make agents reliable. Since then I keep bumping into startups where RL is not a research footnote or a feature buried in the stack. It is central to what they are building. I…
Subscribe • Previous Issues Your CLI Was Built for Humans, Not Agents There’s a friendly debate among developers about how to give AI agents reliable ways to use external tools, data, and services so they can do useful work beyond generating text. One side favors CLIs, or Command-Line Interfaces, where agents run text commands against tools like git, aws, jq, duckdb and…
Subscribe • Previous Issues Agents Need Maps, Not Bigger Context Windows Like everyone else, I’ve been enjoying the steady improvement in coding agents and the tooling around them, from frameworks and harnesses to evaluation suites. But the more I talk with teams actually deploying agents in enterprises, the more I circle back to plumbing. Agents need data integrations and infrastructure built for…
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