Blog

A 15M-parameter JEPA model plans 48x faster than foundation-model alternatives, Meta open-sources a brain activity predictor trained on 1,115 hours of fMRI, and a new RAG benchmark methodology makes data leakage a structural non-issue.

How a local weekly pipeline turns 100+ AI podcast feeds into transcripts, two-pass LLM notes, a searchable vault, and a short Top N list you can actually read.

Reasoning models like DeepSeek-R1 don't think longer. They simulate internal multi-agent debate, which explains the accuracy gap.

Self-organizing AI agents outperform the hierarchical setups we design for them, and the research puts numbers on why that matters.

Agentic Operating Model Part 6: agent ownership, decision rights, RBAC vs accountability, autonomy by action class, shadow mode to full autonomy, RACI, escalation paths, and stop signals.

Agentic Operating Model Part 5: how AI-native teams scale by encoding expertise into agents, with product vision, evals, telemetry, and platform design.

AI adoption is the wrong frame. The real challenge is redesigning the company around AI — ownership, roles, data, agents, and decision rights.

The PM's priority is not to design prompts. It's to own what the agent is supposed to do, how success is measured, and how autonomy expands safely.

Not all workflows are equal candidates for agent ownership. Select by observability, repeatability, and reversibility.

An agent is not 'AI in a feature.' It is execution capacity. The right starting point is the org chart, not the model.