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The Wire · Showcase

CODEX STABILIZES LEGACY CHECKPOINTS WHILE PYTHON SDK SHIFTS TO GPT-5.5

By RepoJournal · Filed · About OpenAI

Codex shipped a compatibility fix for older persisted rollouts that were breaking resume workflows, while the Python SDK quietly updated all README examples to point at the next-generation models.

The Codex team fixed a deserialization issue where legacy `input_image.detail` values from before the enum was narrowed were causing resume to skip checkpoints and reconstruct oversized suffixes [1]. This fix addresses confirmed Sentry reports and prevents compaction failures in production. In parallel, Codex continues its modularization push: slash-command logic moved out of the chat composer to prevent file bloat [2], MCP tool naming is now centralized in the manager to keep `ToolInfo` as the single source of truth [3], and goal telemetry parity was added as the `/goal` endpoint migrates into the extension system to preserve existing metric contracts [4]. The Python SDK updated all README snippets to reference `gpt-5.5` and `gpt-realtime-2` [6], signaling these are now the canonical examples developers should reference. Codex also added experimental `additionalContext` support to turn endpoints, allowing clients to pass ephemeral external state without surfacing it in prompts or triggering lifecycle behavior [5].

Action items

References

  1. [1] Restore legacy image detail values ↗ openai/codex
  2. [2] Move slash input logic out of chat composer ↗ openai/codex
  3. [3] Move MCP tool naming mode into manager (#21576) openai/codex
  4. [4] Add goal extension telemetry parity ↗ openai/codex
  5. [5] Add experimental turn additional context (#24154) openai/codex
  6. [6] Update README models to gpt-5.5 and gpt-realtime-2 ↗ openai/openai-python

FAQ

What changed in OpenAI on May 27, 2026?
Codex shipped a compatibility fix for older persisted rollouts that were breaking resume workflows, while the Python SDK quietly updated all README examples to point at the next-generation models.
What should OpenAI teams do about it?
Verify your Codex deployment includes the legacy detail values fix to prevent resume failures • Update any internal documentation or examples still pointing to older GPT models toward gpt-5.5 • Test additionalContext parameter if you're building client-side integrations with Codex turn endpoints
Which OpenAI repositories shipped on May 27, 2026?
openai/codex, openai/openai-python

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