Your PM wants to ship an AI feature with a 15% hallucination rate on edge cases. How do you communicate the risk?
Both of the obvious moves cost you credibility: block the launch on principle, or ship quietly and hope. The answer that scores turns a scary percentage into a number of bad outputs per week and then changes what the argument is about.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Both of the obvious moves cost you credibility: block the launch on principle, or ship quietly and hope. The answer that scores turns a scary percentage into a number of bad outputs per week and then changes what the argument is about.
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.
