Writing
Field Notes.
What I'm learning while putting AI to work: strategy, governance, agents, MCP, and the messy institutional reality in between.
Jev, and the cost of a decision
TypeSafe's Jev returns typed decisions instead of text for $0.042 per million input tokens. What matters for agents is what becomes affordable to ask once a judgment costs almost nothing.
The model is part of the product
AI companies have good reasons to route work to cheaper models. Paying customers still deserve to know when the product underneath their subscription changes.
Responsible AI governance should create safe paths to yes
Good AI governance does more than say no to risky tools. It gives people a safe way to do the work they were going to do anyway.
What the CPR Summit taught me about AI and compliance
A room full of compliance professionals. A show of hands. And a gap between what AI can do and what's actually being used.
Why this site exists
A place to show the work, write down what building it taught me, and prove that 'AI Strategist' is a real job and not just a LinkedIn title.
What the Microsoft Foundry Claude question actually taught us
Data governance at a university isn't one problem. It's legal risk, technical residency, and trust, all wearing the same trench coat.