Lesson 889 of 1596
Replaying Agent Runs for Debugging and Regression Testing
Build a replay harness that re-runs a recorded trace against a new prompt or model.
Creators · Agentic AI · ~24 min read
The premise
Without replay, every prompt change is a leap of faith — every fix risks breaking three things that used to work.
What AI does well here
- Re-run a recorded trace deterministically (mocked tool returns)
- Diff the new and old final outputs side by side
- Score regressions across a saved corpus of past runs
- Bisect to the prompt or tool change that caused the regression
What AI cannot do
- Replay non-deterministic tool effects faithfully without stubs
- Detect 'silently fine' regressions without scored evals
- Cover situations the recorded corpus never saw
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 replay in plain language, then underline anything that sounds uncertain or too broad.
- 2Give it one detail from "Replaying Agent Runs for Debugging and Regression Testing" and ask for two possible next steps plus one reason each step might be wrong.
- 3Check debugging 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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