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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 only do model evals get blindsided. Here is the distinction that matters.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

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These lessons teach the material this question tests, in order and from the beginning.

Applied AI Engineering·EvaluationSign in13mWhy measuring this is genuinely hardEvaluation is not testing with extra steps. Three properties of generative output break the assumptions ordinary testing rests on, and understanding which one you are up against tells you which technique to reach for.Applied AI Engineering·EvaluationSign in13mWhy your offline score and reality disagreeA system that scores well and disappoints users is the most common outcome in this field. Five specific reasons the two diverge, and the small number of production signals worth wiring up to catch it.

UP NEXT ON YOUR JOURNEY

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