Stop struggling with IDEs. The standalone OpenAI Codex app is now available, with multi - agents writing code for you.
The competition in the AI programming track is intensifying, and the form of tools is also changing significantly.
On February 2nd, OpenAI officially released the standalone desktop app for Codex and opened it to ChatGPT users on all Apple devices for a limited time. This application is no longer just a "code - writing assistant"; instead, it aims to push AI programming into a new stage of multi - agent collaboration.
Compared with web - based or command - line tools, the Codex App provides a more focused workspace for unified management of multiple AI agents and supports their parallel task execution.
OpenAI describes it as a "command center for agents": developers can assign multiple coding tasks simultaneously, allowing agents to run independently in the background, automatically complete repetitive work, and review the results at key nodes.
According to the official introduction, each Codex agent can work continuously for up to 30 minutes and finally return a complete code result. Currently, this system runs on the GPT - 5.2 - Codex model, ranking first in the TerminalBench benchmark test. However, it is closely chased by strong competitors such as Google Gemini 3 and Anthropic Claude Opus.
The release of the Codex App is also generally regarded by the outside world as a "defensive counter - attack" by OpenAI in the field of coding tools.
01 From "Code Completion" to "Multi - Agent Collaboration"
In fact, in the past few years, the main battlefield of AI programming tools has been mainly within IDEs. Products represented by GitHub Copilot have the core ability of real - time code line completion to improve development efficiency. However, the Codex App has chosen another path: it focuses on "simultaneously managing multiple agents".
In the Codex App, each agent runs in an independent thread and is organized by project. Developers can freely switch between different tasks without losing context. You can not only directly review the changes submitted by agents, comment on diffs, but also open the code in the local editor with one click for manual fine - tuning.
This application also has built - in support for git worktree, enabling multiple agents to work in parallel in the same repository without conflicts. Each agent runs in an isolated copy of the code, allowing developers to explore different implementation paths simultaneously without worrying about affecting the stability of the main branch.
Whether checking out changes locally at any time or letting agents continue to advance tasks, it will not interfere with the current git status.
For users who are already using the Codex CLI or IDE plugins, the migration cost is deliberately kept low. The Codex App will automatically inherit existing session histories and configurations, allowing developers to continue working on existing projects directly.
02 Beyond Code Writing: Codex Starts to "Get Things Done"
Another key change brought about by the launch of the Codex App is that OpenAI is deliberately expanding the boundaries of AI coding, making it no longer limited to the dimension of "generating code".
The most core mechanism among them is Skills.
OpenAI packages instructions, resources, and scripts into reusable skills, enabling Codex to stably call external tools, execute complete workflows, and follow the established development specifications of the team.
The Codex App provides a dedicated interface for skill creation and management. Developers can either explicitly call a certain skill or let the system automatically select based on the task context.
Currently, OpenAI introduced on its official blog that it has provided a set of commonly used skill libraries covering multiple aspects from design to deployment. For example, obtaining design context from Figma, managing projects in Linear, deploying web applications to Cloudflare or Vercel, even including generating images using GPT Image, and creating PDF, table, and Word documents with typesetting specifications.
To demonstrate the upper limit of this system, OpenAI also let Codex independently complete the development of a racing game. This game includes multiple characters, 8 maps, and a prop system triggered by the space bar. During the whole process, Codex called the image generation skill and web game development skill. With just an initial prompt, it completed the entire process from design to implementation, consuming more than 7 million tokens in total.
During this process, Codex played the roles of designer, developer, and QA tester simultaneously, and even "played the game itself" to finally verify the correctness of its implementation.
03 Automation: Let Agents Work Continuously in the Background
In addition to Skills, the Codex App also introduces the Automations mechanism, allowing developers to set scheduled tasks for Codex and let agents run continuously in the background.
When an automated task is completed, the result will enter the review queue, and developers can come back to continue processing at any time.
Regarding this, Thibault Sottiaux, the head of the Codex team, revealed that this mechanism has been widely used within OpenAI to handle a large amount of "repetitive but important" work, including daily issue triage, summarizing CI failure reasons, generating release briefings, and regular bug checks.
04 Security - First Agent Design
While the capabilities of agents are continuously expanding, OpenAI also emphasizes the "security - first" design principle in the Codex system. Like the Codex CLI, the Codex App uses a native, open - source, and configurable system - level sandbox mechanism.
By default, Codex agents can only access files in the current working directory or branch and use cached web search results. When a task requires higher permissions (such as direct network access or execution of sensitive commands), the system will first request authorization from the user. Developers can also configure rules for projects or teams to allow specific operations to be automatically executed within a controlled scope.
05 AI Takes Over Technical Debt, the "Most Painful Point" for Engineers
In actual use, Codex brings an unexpected but important value: handling technical debt.
Sam Altman, the CEO of OpenAI, once said bluntly that AI is particularly good at doing things that human engineers are most reluctant to do, such as refactoring code, cleaning up historical legacy issues, and completing test coverage.
In some infrastructure teams at OpenAI, the long - standing technical debt once made people almost lose confidence. Now, the model can work continuously in the background, advancing refactoring and testing as planned, making "paying off the debt slowly" an executable task.
As Altman quoted a colleague as saying: "Unlike humans, AI coding colleagues won't run out of dopamine. It won't stop due to boredom or frustration; it will just keep trying until the problem is solved."
06 Cost, Availability, and Next Steps
Currently, the Codex App has been officially launched on macOS and is available to ChatGPT Plus, Pro, Business, Enterprise, and Edu users. Usage is included in the subscription. Additionally, Free and Go users can also experience it within a limited time. Meanwhile, the rate limits for all paid plans will be doubled.
OpenAI's goal is quite clear: before competitors further expand their influence, make Codex the default tool in the field of AI programming. Data shows that more than 1 million developers have used Codex in the past month, and its usage has almost doubled since the release of GPT - 5.2.
Next, OpenAI also plans to launch a Windows version, support cloud - triggered Automations, and continuously improve model capabilities and inference performance.
07 The Next Round of Competition in the Coding Tool Market
Looking back at the evolution path of Codex, OpenAI first released Codex as a command - line tool in April last year and then launched a web - based interface. However, against the backdrop of the continuous maturity of native applications such as Anthropic Claude Code and Cowork, OpenAI's long - term confinement of developers to terminals and browsers has gradually shown its shortcomings.
The release of the Codex App is regarded as a key catch - up by OpenAI in the "agent - based programming" market.
When releasing, OpenAI also emphasized again the core concept of Codex: all capabilities are centered around code. The better an agent is at understanding and generating code, the higher its upper limit of capabilities in various technical and knowledge - based work.
The current biggest challenge is not the model capabilities themselves, but the huge usage threshold still exists between cutting - edge models and real - world work scenarios. The Codex App is designed to bridge this gap - making it easier for developers to command, supervise, and truly implement the full intelligence of the model in real - world work.
For more content, refer to: https://openai.com/index/introducing-the-codex-app/
This article is from the WeChat official account "CSDN", compiled by Su Mi, and published by 36Kr with authorization.