Testable Design for AI Systems

AI systems resist testing because models are non-deterministic and reach out to external services, so testability must be built in from the start: put the non-deterministic model behind an interface so you can mock it, split deterministic logic (parsing, retrieval, formatting) away from the model call and test it as usual, and check metric tolerances instead of exact outputs. Applied-AI interviews test this because untestable LLM code regresses without warning, and the habit of mocking the model and testing the deterministic pieces is what keeps a system reliable.