What should you log and audit in a production AI system, and why?
Audit logging is the backbone of AI accountability, yet logging everything blindly turns your logs into the biggest privacy liability you own. The signal is what to log so any decision can be replayed, and how to do it without hoarding PII.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Audit logging is the backbone of AI accountability, yet logging everything blindly turns your logs into the biggest privacy liability you own. The signal is what to log so any decision can be replayed, and how to do it without hoarding PII.
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.
