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Agent Time Machine gives developers a rewind button for AI coding agents. An agent can fix the reported bug, pass its tests, and still break something else. Understanding which decision caused that failure is essential to building agents people can trust. The platform records an agent’s file edits, tool calls, and test results in an interactive timeline. Developers can return to a saved checkpoint, try a different action in an isolated workspace, and let the agent continue. The original attempt stays intact, making it possible to compare both paths. Independent tests check whether the change actually worked, while runtime and token usage show the resources each attempt required. A Playground also lets users compare a scripted baseline with a live Meta agent on the same coding task. Agent Time Machine turns an agent failure into an experiment developers can inspect, change, and measure.