OpenAI Codex disabled an Astra context-management experiment affecting approximately 4,000–5,000 users, and removed misconfigured engines causing quality degradation.

OpenAI Codex product lead Tibo reported several fixes following collaboration with users experiencing Astra quality problems. One issue involved skills written for earlier models triggering too frequently or preventing the model from checking its own work.

The team disabled an optional context-management experiment that could cause premature stopping or responses to older messages. Approximately 4,000–5,000 users were affected by that experiment, according to a rough estimate; this is not a disclosed count covering every reported Astra defect.

Separately, the team removed misconfigured engines that caused measurable quality degradation in the tail traffic routed through them. The source does not quantify that traffic share or the size of the quality decline, and it does not identify those engines as specific hardware devices.

Tibo also announced smaller improvements and a planned reset before local midnight, identified in the message as noon Beijing time. More consistent execution, better tracking of the latest user message, and improved checking of intermediate results were stated expected benefits, not independently measured post-fix outcomes.