Production systems
Use Codex to navigate real codebases, make controlled changes, codify repeatable work, and keep production quality high.
The use cases in this collection are useful when Codex is working in a repo that already has history, tests, owners, and production constraints. Codex is particularly good at navigating complex codebases, including sprawling monorepos with lots of different services and dependencies. If you're working on a production system, get familiar with these use cases to understand how Codex can help you.
Start with a codebase tour
Use Codex to get familiar with a complex codebase, which is especially useful when onboarding onto a repo for production software.
Modernize the codebase
Leverage Codex to plan tech stack migrations, upgrade your integration to the latest models if applicable, and refactor the codebase to improve readability and maintainability.
- https://developers.openai.com/codex/use-cases/api-integration-migrations
- https://developers.openai.com/codex/use-cases/refactor-your-codebase
- https://developers.openai.com/codex/use-cases/code-migrations
Codify repeatable work
Ask Codex to turn repo-specific workflows or checklists into a skill, so that all repo contributors can benefit from a standardized process.
Keep documentation current
Ask Codex to compare source changes with existing docs, update the smallest useful docs surface, and verify the changes.
Maintain system health
Let Codex pick up feature requests and bug fixes automatically by using it from Slack and connecting it to your alerting, issue tracking, and daily bug sweeps.
- https://developers.openai.com/codex/use-cases/slack-coding-tasks
- https://developers.openai.com/codex/use-cases/automation-bug-triage
Avoid the review bottleneck
Use Codex to automatically review PRs and run focused QA passes on critical flows, so you can catch issues quickly and ship updates confidently.