Compaction is the summary step that lets a long AI session keep going after its context window gets crowded. It’s compression: helpful, but lossy. The tool summarizes what happened and continues from the smaller version, so the work survives while some detail quietly disappears. The model may keep the goal but lose the exact wording of an instruction, or remember there was a bug but forget the edge case behind it.
A five-hour meeting is the familiar version. When you come back from a break, you don’t remember every sentence. You remember the important points, the decisions, and the next step. That’s enough to keep going, but some detail is gone.
Why you care
Important context shouldn’t live only in the chat. Put durable facts into files, notes, or project memory, and ask the agent for a handoff note before a big transition. When the stakes are high, treat compaction like meeting notes rather than a perfect recording: wrap up the phase, save the important state, and start the next session with a clear brief. The work keeps moving after compaction. It just may not carry every detail with it.