• Autonomous Task Execution:
 Codex operates as a fully autonomous coding agent capable of handling a wide spectrum of software engineering tasks, including writing features, fixing bugs, refactoring, and running tests. It can process multiple tasks in parallel, each within its own isolated environment, minimizing context-switching and manual oversight. • Deep Codebase Integration:
 The agent is designed to understand and manipulate complex codebases. It can read, edit, and execute code, leveraging project-specific context and documentation. Developers can guide Codex using AGENTS.md files, specifying project conventions, test commands, and navigation tips, which increases alignment with team standards. • Transparent and Verifiable Workflow:
Every action Codex takes is logged and cited with terminal outputs and test results. This traceability allows for easy auditing and review, fostering trust in the agent’s autonomous decisions. The system provides clear code diffs and concise summaries after each task, simplifying code review and integration. • Flexible Deployment Models:
 Codex is available both as a cloud-based agent (integrated into ChatGPT and GitHub workflows) and as a local CLI tool. The CLI version runs entirely on the developer’s machine, supporting multimodal inputs (text, screenshots, diagrams) and offering granular control over read, write, and execute permissions. • Security and Privacy by Design:
 The cloud agent runs in a sandboxed, network-disabled environment with access limited to the provided codebase and dependencies, reducing risk of data leakage or unauthorized actions. The CLI tool keeps all code local unless explicitly shared, addressing common privacy concerns. • Open Source and Extensible:
 The CLI version is fully open source, enabling community contributions and transparency into its operation. Developers can customize workflows, integrate with CI/CD pipelines, and extend the agent’s capabilities as needed. • Real-Time Monitoring and Control:
 Developers can monitor Codex’s progress in real time, intervene as needed, and adjust approval modes to suit their workflow—from suggest-only to full autonomous execution. • Optimized for Professional Engineering Workflows:
Codex is trained with reinforcement learning on real-world coding tasks, focusing on producing human-like code, high-quality pull requests, and effective test-driven development. It is engineered to work effectively even in large, messy codebases without extensive setup.