OpenAI Codex

Codex is OpenAI's agentic coding system, an umbrella for a family of surfaces that share one underlying model and a single account context. Relaunched in 2025 and substantially rebuilt since, it is designed not to autocomplete lines but to act as an agent: it reads a codebase, plans an approach, edits files across the project, runs shell commands and tests, and proposes finished pull requests, sustaining long autonomous sessions across many sequential tool calls.

Developers can reach Codex wherever they work. The Codex CLI is a terminal-native agent, open source and built in Rust, that runs locally, edits and runs code in a chosen directory, and ships with structured plan, execute, and review commands plus sandboxed execution and approval modes you control. An IDE extension brings the same agent into editors like VS Code, Cursor, and Windsurf, and a cloud agent, reachable through ChatGPT, runs tasks asynchronously in isolated sandboxed containers preloaded with your repository, so many tasks proceed in parallel. A macOS desktop app acts as a command center for running agent threads side by side, and a remote mode lets you kick off and approve work from a phone.

Around the core loop, Codex adds higher-level workflows. Skills extend it beyond code into tasks like code understanding, prototyping, and documentation aligned to a team's standards; Automations let it pick up routine work such as issue triage, alert monitoring, and CI without being asked; and a separate review agent can check changes before they are committed. An AGENTS.md file in a repository tells Codex how to navigate the code, run tests, and follow project conventions, much like a README for the agent.

Codex is powered by OpenAI's frontier GPT models, trained with an agentic focus so the model handles multi-step tool use and self-checks its work before submitting. It supports the Model Context Protocol for connecting external tools, including parallel tool calls, and runs work inside sandboxed environments while letting users verify output through citations, logs, and test results. It is included with paid ChatGPT plans rather than sold as a separate product, and is used by individual developers and large engineering organizations alike.