Debugging Agent Failures¶
A bad final answer is a symptom. This subtopic is how you find the actual step that went wrong, fix the failure bucket that matters most, and stop a fix from being one-off.
flowchart LR
J["Junior: find the first wrong step"] --> M["Middle: fix the biggest bucket"]
M --> S["Senior: root-cause cascading failures"]
S --> P["Professional: aggregate failures across teams"]
Levels¶
| Level | Guide | You are done when |
|---|---|---|
| Junior | Find the first wrong step | You can read a trace and name the exact step where the run first went wrong, not just where it ended up wrong. |
| Middle | Fix the biggest bucket | You can run an error-analysis loop that finds and fixes the largest failure category instead of the loudest bug report. |
| Senior | Root-cause cascading failures | You can debug a failure that only appears across multiple steps, and tell a model regression from your own. |
| Professional | Aggregate failures across teams | You can run a shared failure taxonomy and feedback loop from prod incident to dataset to release gate. |
Practice rule¶
Before fixing anything, find the earliest step in the trace where the agent's state diverged from correct. Fixing step 5 when step 1 was the actual cause just moves where the same bug resurfaces.
Related¶
- Tracing and Observability — the spans a debugging session reads.
- Datasets and Graders — every confirmed bug becomes a new golden-set case here.
- Reliability and Recovery — the retry and gate logic a debugged failure often needs.