Every AI team I meet has the same skeleton in the closet. The demo that impressed everyone, and the production version that embarrasses them. The gap between those two is evaluation. When you build software, tests tell you if it works. When you build with AI, most teams skip tests and hope. Hope is not a strategy. What works is building an evaluation set: a hundred real inputs, with the outputs a knowledgeable human would accept. Every prompt or model change runs against that set. It sounds boring and it is. It is also the only difference between teams that ship AI that works and teams that ship vibes. Evaluate before you iterate. Your users are already evaluating you.