Checkpoints and restore is an AI interface design pattern that captures named snapshots of state before an agent performs a significant action, then exposes a visible restore button that lets users roll back to any checkpoint with a single click. This UX pattern treats reversibility as infrastructure: whether state lives in the app, a codebase, a design file, or an external API with a supported undo window, each checkpoint is a durable, addressable recovery point. Unlike blanket version history, checkpoints are explicitly tied to agent steps and labeled with the change they represent, so users know which point to return to when something goes wrong. The pattern is the practical realization of designing the undo before you design the action, giving users the confidence to approve ambitious agent operations because they always have a known-good state to return to.
Essential for AI coding agents, design tools, and automation platforms where agents make multi-step changes and users need a reliable, labeled rollback path when something goes wrong.
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