Field Notes.
Long-form strategic essays on AI-native companies, operating model redesign, and the structures emerging beneath the surface of "AI transformation."
The Capacity Paradox
Companies fund AI transformation by cutting the very capacity transformation needs. Two capacities, five root constraints, and a causal map from symptom to root cause.
AI Transformation as System Redesign
AI transformation is not tool adoption. It is a redesign of the company's system of activity — roles, ownership, data, decision cycles, and the protocol that makes better decisions possible.
Good Answers Don't Change What You Do
A week of measuring an expensive multi-agent setup against a single model call. Two things survived, and both are free: a list of questions, and a card the answer has to come back in.
The AI Landscape 2026
A map of the AI tooling stack — ten layers from foundation models to enterprise harness, with a clear vocabulary and a practical guide for choosing the right tool.
From Pain Points to Activity Gaps
A practical framework for breaking down product ideas by mapping customer activity, finding where it breaks, and designing the missing means that closes the loop.
Resumes Are Too Thin
Why resumes and job boards are too thin for an AI-native labor market — and why the future belongs to capability records, future work graphs, and capability-first matching.
Don't Patch the Old System
AI transformation is not tool adoption. It is operating model redesign. A field memo on AI-native twins, decision systems, and where real transformation breaks.