What's the difference between evaluating a model and evaluating the product around it, and why do you need both?
A model that scores 92% on your eval can still ship a product users hate, because the model is one component in a system. Teams that run only model evals get blindsided. Here is the distinction that matters.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
A model that scores 92% on your eval can still ship a product users hate, because the model is one component in a system. Teams that run only model evals get blindsided. Here is the distinction that matters.
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.
