Codex AppTranslation site

What is the Codex App?

Codex App is OpenAI Launched in February 2026 macOS Proprietary Desktop AppsPositioned as “Command Center for AI Agents.”The core goal is to upgrade from a single code generation tool to a single code generation tool. Its core goal is to upgrade from a single code generation tool to a Full-process development platform supporting multi-agent parallel collaboration，重新定义开发者与 AI 的协作模式。用户可同时创建多个smart (phone, system, bomb etc)代理，每个代理独立执行长达数小时的任务（如代码生成、测试、部署），并通过工作树隔离技术避免冲突，实现复杂项目并行开发。其内置“技能系统”封装了数百个预置工具（如 Figma 转代码、AWS 部署），支持自定义技能扩展，开发者可通过自然语言一键调用全流程能力。

The product combines a 100,000 token context window with AGENTS.md persistent documentation to ensure agents understand project logic with an output accuracy of over 90%. Asynchronous interactions are designed so that developers don't have to wait for a task to complete, and can review code changes or manually intervene at any time. Whether it's efficient collaboration with professional teams, rapid prototyping for non-technical staff, or automated O&M scenarios, the Codex App integrates CLI, IDE, and cloud services through a single desktop application, making it the “AI Command Center” for the entire software engineering process.

Core Features of the Codex App

1. Multi-agent workflow management
   • parallel task processingAI agent threads can be created at the same time, with each agent running independently for up to 30 minutes (e.g., code generation, testing, debugging), grouped by project, and switching seamlessly between tasks without losing context.
   • Long-term collaboration: Agents can work for hours or even days in the background on complex tasks (e.g., cross-file refactoring, performance optimization), and developers can step in at any time to review or manually modify them.
   • work tree isolationGit Worktree: Built-in Git Worktree support allows multiple agents to collaborate on the same code repository without interfering with each other, avoiding conflicts, and allowing developers to freely explore different scenario paths.
2. Skills system
   • functional encapsulation: Users can package commands, resources, and scripts as skills (e.g., “Generate Unit Tests”, “Deploy to Cloud Server”), and agents can automatically invoke or manually specify skills based on the task.
   • skills inventory: Built-in hundreds of pre-built skills (such as Figma design to code, Jupyter data analysis), covering the whole process of development, design, operation and maintenance, supporting one-click installation and custom creation.
3. Asynchronous Interaction and Automated Scheduling
   • non-blocking operation: While the agent is running, the developer can continue with other tasks and view the results via notifications or Diff stats when the task is complete.
   • Repetitive Task Delegation: e.g., automatically handling pull requests, monitoring logs, generating documents, etc., reducing the frequency of manual intervention.
4. Cross-platform integration
   • Seamless synchronization with CLI/IDE: Session history, configuration, and active threads in App are automatically synchronized to the Codex CLI and IDE plug-ins such as VS Code, supporting multi-environment switching.
   • Support for mainstream development tools: Integration with Docker, Kubernetes, GitHub Actions, etc., with the ability to call external services directly.

Codex App's Core Technology

1. multitasking architecture
   • on the basis of Tokio Asynchronous RuntimeIt is built to achieve efficient collaboration through three major components: task generator, scheduling center, and result aggregator.
   • Lightweight task model: Each agent runs as a separate Tokio task, consumes few resources (just a few KB of stack space), and supports tens of thousands of concurrencies.
   • Intelligent synchronization mechanism: Triple-guaranteed data security using mutex locks, atomic variables, and channel communication to avoid lock contention and shared memory conflicts.
2. Contextual perception and long memory
   • 100,000 token context window: Support for reading the code structure of large projects (such as microservices cross-service call logic) , the generated code directly into the existing project .
   • AGENTS.md file: Users can maintain project contextual documentation (e.g., naming conventions, business logic), significantly improving the accuracy and relevance of agent output.
3. Skills Execution Engine
   • Documentation system organizational capacity: Define skill dependencies through a directory structure rather than cramming all the tools into a context for modular invocation.
   • Dynamic resource allocation: Optimize resource utilization by automatically adjusting batch policies based on task type and system load.

Scenarios for using the Codex App

1. Complex project development
   • case (law): OpenAI's internal team used the Codex App to build and release Sora for Android in 28 days, a four-person team that would have taken ten people a month to develop.
   • workflowsThe agent is responsible for UI design, back-end logic, testing and deployment, and invokes the pre-built toolchain through the skills library, without opening a traditional IDE.
2. Cross-team collaboration
   • take: Multiple developers manage agent tasks through a shared Codex App project, viewing progress and changes in real time and avoiding communication costs.
   • dominance: Work tree isolation ensures code security, and the skills system unifies implementation standards and reduces human error.
3. Non-Professional Developer Empowerment
   • case (law): Non-technical people through natural language description of the needs (such as “generate an e-commerce site home page”), the agent automatically invoke the design to code, deployment and other skills to complete the development.
   • fig. values (ethical, cultural etc): Lower the technical threshold so that business people can participate directly in software production.
4. automated operation and maintenance (O&M)
   • mandatesAutomatically monitors server metrics, triggers alarms, performs capacity expansion or rollback, and agents are on call 24 hours a day to handle exceptions.

How do I use the Codex App?

1. Installation and Configuration
   • system requirements: macOS 12+ (Windows version coming soon).
   • Installation: Installation via Homebrew or by downloading the DMG package directly, with support for npm global installation of CLI tools.
   • Login Authorization: Sign in with your ChatGPT account or connect to a customized transit platform (like weelinking) via an API Key.
2. basic operation
   • Creating a Proxy Thread: Create a new thread in the list of projects on the left and enter a task description (e.g. “Refactor user login module to use JWT authentication”).
   • Selection of models and environments: The bottom panel toggles Local/Worktree mode, selecting the model (default GPT-5.2-Codex High) and execution environment (e.g. Docker container).
   • Monitoring and Modification: Real-time display of agent output in the center panel, Diff stats on the right side to compare code changes, and support for direct commenting or manual editing.
3. Skills management
   • installation skill: Browse the Skills library for recommended skills (e.g. “Figma to React”, “AWS Deployment”) and install them into your project with a single click.
   • Customized Skills: Create new skills through the interface, define command templates, dependency files and trigger conditions, and save them for the agent to call.
4. Advanced Techniques
   • Questioning patterns first:: Complex tasks are first implemented as plans (e.g., “Optimize a database query in three steps”), and then executed in code mode.
   • organizational context: Maintained in the project root directory AGENTS.md Documentation that provides persistent information such as naming conventions, business logic, etc.

Recommended Reasons

1. efficiency revolution
   • parallel processing: Reduce traditional linear development time by more than 60% with overlapping multi-agent tasks.
   • Automation Redundancy: Repetitive tasks (e.g., testing, deployment) are fully delegated to agents, and developers focus on creative tasks.
2. Upgrading the collaboration paradigm
   • From “pair programming” to “team management”: The shift in the developer role from coder to AI team supervisor is in line with future software engineering trends.
   • Unified workflow: Integrate CLIs, IDEs, desktop applications, and cloud services to avoid efficiency losses due to tool switching.
3. Technical depth and flexibility
   • Bottom-Level Optimization: Deeply tuned models and architectures for software engineering scenarios, with complex grammar understanding accuracy exceeding 90%.
   • open ecology: Support for customized skills and external tool integrations, adapting to different teams' technology stacks and processes.
4. Free strategy to attract users
   • Free for a limited time: ChatGPT Free and Go Edition users can use it without limitations, and Plus and other subscription users can double the rate limit to rapidly expand the user base.
   • Low migration costs: Seamless compatibility with existing Codex CLI/IDE plug-ins for a smooth transition for developers.
5. Industry benchmarking
   • Competitive differencesThe Codex App is closer to being the “software engineering brain” than the single code completion of GitHub Copilot, as it provides full-process agent collaboration.
   • future potential: With the increased mathematical power of GPT-5, multi-agent systems may be extended to non-coding domains such as design and data analysis, reshaping the AI Productivity toolsGrid.