Lesson 684 of 1596
Agent Debugging: Tracing What Went Wrong Across Many Steps
Multi-step agents fail in ways single-call AI doesn't. Trace logging is the difference between solvable bugs and mystery failures.
Creators · Agentic AI · ~6 min read
The premise
Agent failures span multiple steps; trace logging is the only way to debug effectively.
What AI does well here
- Log every step (prompt, model output, tool call, tool result, model decision)
- Maintain trace IDs that connect related steps
- Build replay capability for diagnostic sessions
- Aggregate trace data for failure-mode pattern analysis
What AI cannot do
- Debug agents without traces
- Substitute incomplete traces for full context
- Eliminate the storage cost of comprehensive logging
Key terms in this lesson
Practice this safely
Use a small project example from your own work. The useful move is to compare the AI's draft against your goal, sources, and constraints before you trust it.
- 1Ask AI to explain agent debugging in plain language, then underline anything that sounds uncertain or too broad.
- 2Give it one detail from "Agent Debugging: Tracing What Went Wrong Across Many Steps" and ask for two possible next steps plus one reason each step might be wrong.
- 3Check trace logging against a trusted source, teacher, adult, expert, or original document before you use it.
End-of-lesson quiz
Check what stuck
10 questions · Score saves to your progress.
Tutor
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