Lesson 2093 of 2116
AI Agent Observability: Tracing, Spans, and Replay Debugging
How to instrument AI agents so you can debug what actually happened in production.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2tracing
- 3spans
- 4replay
Concept cluster
Terms to connect while reading
Section 1
The premise
AI agents need OpenTelemetry-style tracing with one span per LLM call and tool call, plus full input/output capture for replay debugging in production.
What AI does well here
- Emitting structured span data when given a tracing tool
- Including correlation IDs across distributed calls
- Logging tool inputs and outputs at decision boundaries
- Producing replayable traces when prompts are deterministic
What AI cannot do
- Self-instrument without explicit tracing infrastructure
- Identify the root cause of multi-turn behavior changes alone
End-of-lesson quiz
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