如何用好 Codex？OpenAI 内部实践指南：7 个最佳应用场景，6 个使用 Tips

Core Insights - OpenAI has released the GPT-5-Codex model, which is designed for programming tasks and can collaborate with developers in real-time while also completing complex tasks independently over extended periods [2][4] - Codex has been fully integrated into OpenAI's internal development processes, providing a methodology for transforming AI coding tools from simple code completion aids into essential components of professional development workflows [4][7] Application Scenarios - Understanding Code: Codex assists team members in quickly familiarizing themselves with unfamiliar parts of the codebase, locating core logic, and tracing data flows during debugging [8] - Refactoring and Migration: Codex is utilized for making consistent changes across multiple files, ensuring that updates are applied uniformly, especially in complex code structures [13] - Performance Optimization: Engineers use Codex to identify and resolve performance bottlenecks, offering suggestions that can significantly enhance efficiency and reliability [17] - Enhancing Test Coverage: Codex helps engineers write tests more quickly, particularly in areas with low coverage, by generating unit and integration tests based on function signatures and context [20] - Accelerating Development Speed: Codex aids in scaffolding new features and automating mundane tasks, allowing engineers to focus on more critical aspects of development [25] - Maintaining Flow: Codex helps engineers manage their workload by recording unfinished tasks and turning notes into runnable prototypes, facilitating a smoother workflow [28] - Exploration and Ideation: Codex is useful for exploring alternative solutions and validating design decisions, helping teams weigh pros and cons effectively [31] Best Practices - Starting with Ask Mode: For large changes, using Ask Mode to generate an implementation plan before switching to Code Mode can clarify Codex's output [38] - Organizing Prompts Like GitHub Issues: Providing detailed prompts similar to PR or issue descriptions improves Codex's performance [39] - Iterative Development Environment: Codex is best suited for well-defined tasks, and setting up a conducive environment can reduce error rates [41] - Using a Task Queue: Treating Codex's task queue as a lightweight to-do list allows for flexible management of ideas and tasks [42] - Maintaining Persistent Context: Keeping an AGENTS.md file helps Codex understand project specifics better, enhancing its efficiency [43] - Leveraging Best of N: Utilizing the Best of N feature allows for generating multiple responses to a task, facilitating the selection of the best solution [44] Future Outlook - Codex is still in the research preview stage but has already transformed development practices, accelerating coding speed and improving code quality [45] - As the model evolves, it is expected to integrate more deeply into workflows, unlocking new software development capabilities [45]