Tag:Debugging

When a multi-step agent produces a confidently wrong answer, the step that threw the error is almost never the step that caused it. The real culprit is an earlier decision whose bad output only surfaced downstream, so you patch the symptom and the failure comes back next week. This is agent failure attribution, and here is how to find the decisive step with counterfactual replay instead of guessing.

A user sends you a screenshot of your agent doing something wrong. You have the logs, you have the trace, and you still cannot make it happen again, because the model sampled differently and a tool returned something new. You are debugging a ghost. Record every source of nondeterminism during the run and you can replay that exact failure on demand.