← All IntelClip / OtherAuto-compaction for long-running agents
From Codex, Behind the Harness — Dominik Kundel, OpenAI · ≈18:52
“If we have these agents run for hours or days at a time, you don't want to stand there and actually approve everything all the time.”
“the way this works is you can either trigger this manually or automatically and it will turn your transcription into or your your previous context window into a new one that you're going to use instead on subsequent turns and it contains a compaction item that has all of the necessary information in it that you need.”
What’s in it
- Explains auto-compaction that lets coding agents run for hours unattended
- Details how Codex trims context windows without losing performance
- Shows the mechanism behind long-running agent memory management
Clip transcript
when things are done. The last thing I want to talk about is compaction. If we have these agents run for hours or days at a time, you don't want to stand there and actually approve everything all the time. Um and because of that we introduced uh end end of last year auto compaction, and this has been uh used by Codex since then to automatically trigger compaction on the server side in a way that the model got trained with so that the performance stays the same. Um the way this works is you can either trigger this manually or automatically and it will turn your transcription into or your your previous context window into a new one that you're going to use instead on subsequent turns and it contains a compaction item that has all of the necessary information in it that you need.
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