Parks staff see a deployed events agent giving wrong venue answers and need to improve it. What should they do next?

When parks staff see a deployed events agent giving wrong venue answers, the next step is to monitor the deployed agent and perform error analysis on those wrong answers. Production failures are diagnostic signal: traces, user reports, and systematic error analysis reveal whether retrieval, grounding, tool routing, or prompt issues caused the venue mistakes. That observe-then-analyze loop is how municipal agents improve after deployment, not retraining on production logs and redeploying without error analysis. Retraining the venue response model on production logs and redeploying jumps to a fix before diagnosis and leaves residents misdirected, because retraining without error analysis won't reveal whether retrieval, grounding, or routing caused the live venue failures. Adjusting the venue retrieval top-k and temperature settings to improve answer precision may change which venues surface, but blind tuning lacks the structured categorization needed to find the systematic cause behind the wrong venue answers. Collecting production venue feedback ratings into a dashboard to monitor response quality tracks scores but does not diagnose why specific venue answers are wrong or provide the failure traces needed to fix them. On the exam, monitor plus error analysis follows deployed wrong answers; distractors retrain on production logs, blindly tune retrieval and temperature for precision, or track venue feedback ratings without diagnosing the venue errors. Caveat: error analysis should segment by venue type and event source—systematic catalog mismatches need data fixes, not only prompt tweaks. Operational check: enable tracing on the parks events agent, collect wrong-venue cases, categorize failure modes, apply a targeted fix, and re-measure venue accuracy on the same fixtures before calling the issue closed.