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About Codex by OpenAI
An AI coding agent by OpenAI for writing, reviewing, and automating software engineering tasks.
Codex by OpenAI is an AI-powered software engineering agent designed to help developers write, review, test, and ship code faster, more securely, and with better assistance. Built into ChatGPT and via native tools like the Codex CLI and IDE extensions (VS Code, Cursor, etc.), Codex lets users delegate tasks—such as implementing new features, fixing bugs, generating tests, refactoring code—and it can run many tasks in parallel. The agent is context-aware: it can read your repository, suggest edits, run commands, execute tests, and interact with related files. Codex also offers a cloud mode and local/IDE integration so you can stay in your development flow. The recent upgrade (GPT‑5‑Codex) improves performance especially in real-world engineering tasks, enhances code review capabilities (detecting bugs before shipping), speeds up response times (e.g. via caching infrastructure), and adds features like being able to use images (e.g. spec screenshots or UI bug visualizations) to inform tasks. Security and safety are woven in: sandboxing, restricted network access by default, permission prompts for dangerous actions, ability to run in a “read-only” or “approval” mode, etc. Codex is particularly powerful for teams as well as individual devs, with seamless integration into common workflows (GitHub PRs, tests, file editing), enabling both rapid prototyping and maintenance of large codebases. Its strengths lie in its versatility, depth of integration, and ability to automate repetitive engineering tasks, while its downsides include learning the right prompts or workflows, potential cost for heavy usage, and dependency on internet/cloud availability when not using local modes.
Key Features
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Example Prompts
Fix the failing tests in this repo and create missing unit tests.Refactor this legacy function into smaller composable units.Generate a CI-pipeline script for this project with testing and linting.Review pull request changes for code quality and potential edge case bugs.