agrepl framework achieves 98.3% median latency reduction for AI agent replay
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The open-source Go CLI tool agrepl guarantees 100% agent replay fidelity (F = 1.0) with a 98.3% median reduction in per-step latency by intercepting all external transport-layer interactions via a local MITM proxy. This allows production engineering teams to deterministically reproduce, diff, and debug complex agent failures offline without incurring LLM API costs or triggering side-effects in external systems.
agrepl records every external agent interaction at the transport layer via a MITM proxy and replays it in a network-isolated sandbox, achieving perfect replay fidelity (F=1.0) with a 98.3% median per-step latency cut by serving cached responses instead of live LLM/API calls. This gives you deterministic, offline reproduction of a specific agent run for debugging and regression testing—no more chasing non-reproducible failures caused by sampling variance or API state—and it ships as a single MIT-licensed Go binary you can drop into a pipeline today.