Find the first wrong step in a trace
The final answer shows the symptom
A recommendation exceeds the budget. Was the budget extracted incorrectly, did fees go missing, or did a filter fail? A trace records the meaningful execution steps so you can find the first divergence.
For this project, inspect the input constraints, candidate IDs, exclusions, draft version, approval, and submission status. You need observable operations and outcomes, not hidden model reasoning.
Check your understanding
A final answer is over budget. What is the most useful next step?
Log enough to debug without collecting everything
A useful event includes a request or run ID, step name, outcome, duration, and safe metadata. Avoid recording credentials, payment details, or unnecessary personal information. Redaction and retention choices belong in the design.
The Workflow Lab records in-memory events for the fixture run. It does not send telemetry. Use the sequence to explain whether a failure happened before a draft, during approval, or after simulated acceptance.
Check your understanding
Change the earliest faulty component
If the price calculation omitted delivery, changing the recommendation wording will not repair the total. Reproduce the failure, locate the earliest incorrect value, fix that component, and rerun the original case.
A useful bug report contains the request, expected outcome, relevant trace events, actual outcome, and a narrow hypothesis. That is more actionable than “the agent is bad.”
Check your understanding
Write a concise bug hypothesis for missing delivery fees.
Build checkpoint
Open the Evaluation Lab and follow the practice above. Each lab explains its inputs, its actual logic, and its limits. Save your observations below; your check-ins and reflection remain in Product Academy.
For an AI-assisted code change, download the lab bundle from the lab page. Ask your coding assistant to explain the relevant function first, change one behavior, and add one test that could fail. Compare the result with your prediction.
Save your experiment and check-in
Record your prediction, what you tried, what happened, and the evidence for your conclusion. Name one thing you can now do independently and one uncertainty to revisit.
Key takeaways
- Use traces to locate the cause behind the final symptom.
- Record useful safe metadata rather than everything.
- Fix the earliest faulty component and rerun the case.