You fine-tuned a model and the task metric went up. How do you prove you did not break everything else?
The follow-up every interviewer holds in reserve after you say you fine-tuned something. A task-metric win proves almost nothing on its own. Here is the five-part protocol that separates a shipped model from a demo.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
The follow-up every interviewer holds in reserve after you say you fine-tuned something. A task-metric win proves almost nothing on its own. Here is the five-part protocol that separates a shipped model from a demo.
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.
