The difference between AI output and accountable work
Why evidence, review, and acceptance criteria change what organizations can responsibly do with AI.
Field notes, methods, and leadership perspectives from the continuing work of making AI useful, reviewable, and accountable.
Why evidence, review, and acceptance criteria change what organizations can responsibly do with AI.
A practical model for directing, supervising, and evaluating AI-assisted work.
A better sequence for moving from an interesting AI capability to a durable operating practice.