Archive
Page 9 of the running record.
Take Note Tuesday: what I learned from dissecting *Generative AI at Work* as an argument
A close reading of Brynjolfsson, Li, and Raymond’s NBER working paper as a writing artifact: how it sequences causal identification, heterogeneity, mechanisms, and boundary conditions to make a large claim credible.
Legal AI is splitting between speed and accountability
The Anthropic–Thomson Reuters integration is a signal that legal AI is separating into two layers: fast general-purpose exploration and fiduciary-grade execution workflows. In high-stakes work, model quality matters—but control architecture matters more.
Provenance is not execution security
The TanStack compromise and OpenAI’s downstream response show a hard truth for the AI stack: signed artifacts and trusted publishers are necessary, but they do not guarantee safe execution. Deployment trust architecture is now a competitive capability, not just a security checkbox.
LinkedIn is repricing itself as labor-market infrastructure
LinkedIn’s 5% workforce cut alongside double-digit revenue growth is less a collapse story than an operating-model reset: reduce low-leverage spend, concentrate on AI-supported matching infrastructure, and defend long-run platform economics.
AI layoff headlines are becoming capital-allocation signals
Cisco’s same-week combination of record revenue, raised AI expectations, and workforce reductions is less a contradiction than a map of where large tech operators think the next margin and growth curve lives.
The AI platform wars are moving to Main Street workflows
Anthropic’s Claude for Small Business launch is a signal that the next AI battleground is not just model quality or Fortune 500 procurement. It is execution inside the software stack small businesses already run, with approval gates and trust controls baked in.