Evaluating and Monitoring LLM Applications

Introduction to Evaluating and Monitoring LLM Applications

Evaluating an LLM application asks whether its responses satisfy the product’s requirements. Monitoring checks whether that quality and the supporting service remain healthy after the application is released.

Suppose a support assistant answers in 800 milliseconds, but cites a policy that does not exist. The service is healthy; the answer is not. Latency and error rates tell us whether the software ran, while evaluation tells us whether the response was useful and correct.

Quality is not one property. We may need to check instruction following, factual support, reasoning, robustness to harmless prompt changes, harmful output, and unnecessary refusals.

These measurements can move in different directions. A stricter safeguard may reduce harmful answers while blocking more legitimate requests. A prompt change may improve one task and weaken another.

For each product behavior, name what success means, collect examples that can reveal failure, and choose a measurement that matches that behavior. The later sections show how to do this for prompts, judges, retrieval, guardrails, and long contexts.