Core answer
Start here. This is the direct spoken answer to practice first.
Overview
AI features still need normal tests, but generated language introduces quality questions that exact assertions cannot answer alone.
An AI evaluation is a repeatable test of whether an AI feature behaves well on representative inputs and defined success criteria. Normal unit tests still verify code paths, schemas, permissions, and deterministic rules, but they cannot fully judge whether an open-ended response is useful, supported, or appropriately cautious. I use both: conventional tests protect software contracts, while evals measure the variable behavior of the model and the application around it.