It’s the practice of starting implementation from a written, testable specification that states expected behavior, machine-checkable acceptance criteria, relevant architecture and coding-standard constraints, and the edge cases the feature has to handle. Both AI agents and human reviewers work from the same specification, which makes it possible to verify that generated output satisfies the requirement.