OpenAI has launched Codex, a research preview of a cloud-based software engineering agent designed to automate common development tasks such as writing code, debugging, testing, and generating pull requests. Integrated into ChatGPT for Pro, Team, and Enterprise users, Codex runs each assignment in a secure sandbox environment preloaded with the user’s codebase and configured to reflect their development setup.
Codex is powered by codex-1, a version of OpenAI’s o3 model optimized for programming tasks. It was trained using reinforcement learning on real-world examples and is capable of generating code aligned with human conventions. The model iteratively runs code and tests until a correct solution is reached. Once a task is completed, Codex commits its changes within the sandbox and provides test outputs and terminal logs for transparency.
The Codex sidebar in ChatGPT enables users to assign tasks or ask questions about their codebase through a text prompt. The model can edit files, run commands, and execute tests, with typical completion times ranging from one to thirty minutes. Codex supports AGENTS.md files—repository-level instructions that help guide the agent through project-specific practices and testing procedures.
Codex CLI, a command-line companion interface, is open source and uses API credits. However, as clarified by Fouad Matin, a member of technical staff at OpenAI, Codex access within ChatGPT is included with Pro, Team, and Enterprise subscriptions:
Codex is included in ChatGPT (Pro, Team, Enterprise) pricing with generous access for the next two weeks.
The system, however, does not yet support full application testing with live user interfaces. As one Reddit user pointed out:
Most software engineering is web development these days. How does it handle that, where you have separate layers for certain things, environment variables, and UI interfaces? Does it actually run the app so the user can test it, or do they need to push the change and then pull down a copy to test locally? That would be very annoying. Ideally, in the future, the agents can just test it themselves, but I guess they are not good enough yet.
Codex runs in an isolated container without internet access or UI execution capabilities. While it can handle test suites, linters, and type checkers, final verification and integration remain in the hands of human developers.
OpenAI has also introduced Codex mini, a lighter model designed for faster interactions and lower latency, now the default engine in Codex CLI and available via API as codex-mini-latest. It is priced at $1.50 per million input tokens and $6 per million output tokens, with a 75% prompt caching discount.
The release reflects OpenAI’s broader strategy to eventually support both real-time AI coding assistants and asynchronous agent workflows. While Codex currently connects with GitHub and is accessible from ChatGPT, OpenAI envisions deeper integrations in the future, including support for assigning tasks from Codex CLI, ChatGPT Desktop, and tools such as issue trackers or CI systems.
