Originally published on AI Tech Connect.
What this guide covers Running an AI agent in production is a fundamentally different problem from running a deterministic web service. A REST endpoint either returns the correct JSON or it throws a 500. An agent can spend ten seconds and a pound's worth of LLM tokens, silently return a confident-sounding but factually wrong answer, and your monitoring dashboard will show a healthy green request. No exception raised. No error logged. No alert fired. Just a user who quietly stopped trusting your product. This guide is for engineers who have an agent running — or nearly running — in production and need to debug it systematically rather than by guesswork. We will cover: Why distributed tracing is the right primitive for observing agents, and why logging and metrics alone fall short A concise…
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