Design the audit trail for an AI agent that takes actions in customer systems. What do you log, and what makes it defensible?
When the agent does something expensive, 'what happened and why' must be answerable in minutes, to an auditor, from records they trust. Most logging designs answer 'what'; the AI-specific work is 'why', and tamper-evidence is what makes it count.
Updated Aug 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.
When the agent does something expensive, 'what happened and why' must be answerable in minutes, to an auditor, from records they trust. Most logging designs answer 'what'; the AI-specific work is 'why', and tamper-evidence is what makes it count.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
