codex - 💡(How to fix) Fix Reduce user-visible latency from context compaction with pre/background compaction [2 comments, 3 participants]

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openai/codex#19485Fetched 2026-04-26 05:16:29
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Root Cause

A one-minute-plus compact step is noticeable enough to interrupt the development flow. Even if total compute time is unchanged, moving part of the work off the critical path would make Codex feel much more responsive.

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Problem

In Codex desktop, automatic context compaction can block the user-visible turn for a long time. In one recent session, the UI showed:

  • Context compacted
  • Worked for 1m 17s

During that period, the user cannot distinguish useful agent work from context maintenance, so the compact step feels like a visible stall.

Proposal

Could Codex reduce perceived latency by preparing compaction before it becomes blocking, or by doing it in the background?

Possible approaches:

  • Start preemptive/incremental compaction once the conversation crosses a soft threshold, before the hard context limit is reached.
  • Maintain a background compacted checkpoint while normal interaction continues.
  • Run compaction while the session is idle or after a discrete task phase completes.
  • If compaction must block, show progress that makes it clear the delay is context maintenance rather than task execution.

Why this matters

A one-minute-plus compact step is noticeable enough to interrupt the development flow. Even if total compute time is unchanged, moving part of the work off the critical path would make Codex feel much more responsive.

Environment

  • Product: Codex desktop app
  • Observed compact duration: 1m 17s
  • Date observed: 2026-04-25

extent analysis

TL;DR

Implementing preemptive or incremental context compaction can reduce perceived latency in the Codex desktop app.

Guidance

  • Consider starting compaction before the hard context limit is reached by implementing a soft threshold that triggers preemptive compaction.
  • Run compaction in the background while normal interaction continues to minimize user-visible delays.
  • Display progress updates during compaction to distinguish it from task execution and reduce perceived stalls.
  • Evaluate running compaction during idle sessions or after discrete task phases to further optimize performance.

Example

No code snippet is provided as the issue focuses on high-level approaches to optimizing context compaction.

Notes

The effectiveness of these suggestions may depend on the specific implementation details of the Codex desktop app and its context compaction mechanism.

Recommendation

Apply workaround: Implementing a preemptive or incremental compaction approach can help reduce perceived latency without requiring significant changes to the underlying app architecture.

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