Interview Que: Debug an AI Agent that's only sometimes Wrong

The hardest bugs in production AI never throw an error. The request returns 200 OK, the dashboard stays green, and the answer is quietly, confidently wrong. This is how production teams see inside a Large Language Model system, and how to answer the observability interview like someone who has actually done it.

A user says "sometimes it hallucinates." There is no stack trace, no error, no way to reproduce it. This is the full map of AI observability: why it differs from normal monitoring, how traces become the unit of debugging, how OpenTelemetry captures a Large Language Model (LLM) request, how quality is measured on live traffic, and how a real incident gets investigated end to end.