AI Agent Trace Replay: Turn Production Failures Into Safe Regression Tests

Description and use

<p>Your agent failed once in production. The tempting fix is to patch the prompt, glance at the next successful run, and move on. That is how the same failure returns after a model, tool, or routing change.</p> <p>The more useful response is to turn the failed run into a replayable regression test. Not a full rerun against live customer data. Not a screen recording. A small, scrubbed fixture that preserves the decisions and tool boundary that mattered, then proves the fix without sending another email, creating another ticket, or charging another card.</p> <p>This guide shows how to build that

Problem

<p>Your agent failed once in production. The tempting fix is to patch the prompt, glance at the next successful run, and move on. That is how the same failure returns after a model, tool, or routing change.</p> <p>The more useful response is to turn the failed run into a replayable regression test. Not a full rerun against live customer data. Not a screen recording. A small, scrubbed fixture that preserves the decisions and tool boundary that mattered, then proves the fix without sending another email, creating another ticket, or charging another card.</p> <p>This guide shows how to build that

Outcome

<p>Your agent failed once in production. The tempting fix is to patch the prompt, glance at the next successful run, and move on. That is how the same failure returns after a model, tool, or routing change.</p> <p>The more useful response is to turn the failed run into a replayable regression test. Not a full rerun against live customer data. Not a screen recording. A small, scrubbed fixture that preserves the decisions and tool boundary that mattered, then proves the fix without sending another email, creating another ticket, or charging another card.</p> <p>This guide shows how to build that

Evidence

AI Agent Trace Replay: Turn Production Failures Into Safe Regression Tests

Source