Production AI agents need more than one-run debugging
A AI agent can hide serious problems when each run is checked one by one. A research agent built with LangGraph and a had three search channels, and one of them failed on every attempt for two days.
Each individual trace still looked successful, so the failure was not visible during normal debugging. The problem appeared only after separate scripts analyzed the span files across many runs.
Useful agent monitoring should show trends, failed tool sequences, and places where runs get stuck. Teams also need to test whether per-trace debugging is enough for real use.
Key points
- Single-run traces can miss repeated failures over time.
- One of three search channels failed 100% of the time for two days while each trace looked green.
- Analyzing span files across many runs exposed the hidden failure.
- Useful monitoring should show trends, failed tool sequences, and stuck points.