AI can give you a great result once and a mediocre one five minutes later. The input changes slightly. The context shifts. The model makes a different choice. Suddenly the prompt, skill, or workflow that felt reliable breaks, and you cannot explain why.
An eval gives you a way to test it. You define the task, collect examples that reflect the real work, write down what good looks like, and grade the results against that standard. It turns “this seems good” into a test you can run again.
Once you turn a prompt into a skill, workflow, or agent, you have built a software system. Nobody ships you its quality bar. You have to create it.
