What is AI Evals (Evaluation)?

Because AI output can vary, you can't tell if an AI system works just by trying it a few times. Evals are a set of realistic test cases, such as typical customer questions or documents, with a clear definition of a good answer, run every time the system changes.

DeepLearning.AI's AI Engineering Skills Map highlights evaluation-driven development as one of the most important skills in building AI applications: running a disciplined loop of testing, reviewing errors and fixing the biggest problems first. Evals can be checked by code, by another AI model acting as a judge, or by people.

For a business, evals answer practical questions: does the AI receptionist book the right appointment type, recognize emergencies, quote approved prices and hand off when it should? A system without evals is a system you're hoping works.