Stratagems #19: Mark Found His AI Audit Method in a Training Manual. He Left a Trap in His Report.

This is an essay dressed as a short story, using a fictional auditor named Mark to explore the strategic logic of AI auditing: specifically, the idea that the best audit findings do not fight the system's stated strengths but instead expose the assumptions underneath them. The 'trap left in the report' framing is a hook for a broader point about how to make audit findings stick rather than get rationalized away by the team being audited. It draws loosely on classical strategy frameworks applied to AI governance contexts. The practical takeaway is thin for someone already deep in AI security or audit work, but for a technical PM or founder who has never thought structurally about how to run an AI audit, it offers a useful mental model in a readable format. Reservation: the narrative wrapper adds color but also adds length without proportional insight. -> Best for: technical PM or solo founder starting to think about AI compliance and audit processes