Replay / Time-Travel
Load any past agent trace, jump to a specific step, swap in a different prompt or model, and re-run forward — debug production incidents in minutes instead of hours.
Intent & Description
🎯 Intent
Re-run a past agent trace from any step with modified inputs, prompts, or tools to debug or branch.
📋 Context
Production agents hit hard-to-reproduce behavior: strange replies, unexpected tool calls, wrong answers on inputs that worked yesterday. Engineers need to load the exact past run, jump to a specific step, swap in a different prompt or model, and see whether the alternative would have done better — without affecting users.
💡 Solution
Capture per-step inputs, outputs, prompts, model id, and tool calls in a trace store. Provide a replay tool that loads a trace at step N and re-runs forward with optional modifications (different model, different prompt, different tool result). Store branches for comparison.
Real-world Use Case
- Agent runs are non-deterministic and incidents need reproducible debugging.
- Engineers need to branch from a past step to test fixes or alternative prompts.
- Per-step inputs, outputs, and tool calls can be captured durably.
Source
📌 TL;DR
Give engineers a DVR for agent runs — load any past trace, jump to the failing step, swap in a fix, and see if it resolves it, without touching production.
Advantages
- Debugging cycle drops from hours to minutes — load the exact failing trace and iterate.
- A/B comparison of prompt or model fixes becomes trivial.
Disadvantages
- Trace storage adds significant overhead at production traffic volumes.
- Non-deterministic external dependencies (live network calls) limit replay fidelity.