OpenAI's Codex: How AI is Building Itself & Revolutionizing Development

The Rise of AI-Powered Development: A New Era

The world of software development is undergoing a seismic shift. AI coding tools are rapidly gaining traction, impacting every stage of the process. But what's truly remarkable is how these tools are now being used to improve themselves. This article dives into OpenAI's innovative use of GPT-5 Codex, its own AI coding agent, to build and refine its development tool, showcasing a fascinating example of recursive self-improvement in AI.

What is OpenAI Codex?

Codex, initially based on GPT-3 and now powered by GPT-5, operates as a cloud-based software engineering agent. It's designed to handle a wide range of tasks, including writing features, fixing bugs, and proposing code changes. It’s accessible through ChatGPT’s web interface, a command-line interface (CLI), and IDE extensions for popular platforms like VS Code and IntelliJ. The name “Codex” itself harkens back to an earlier iteration that powered GitHub Copilot's tab completion, representing a pivotal “wow” moment in AI’s ability to understand and accelerate developer workflows. Learn more at https://daic.aisoft.app?network=aisoft.

Codex's Evolution: From GitHub Copilot to Agentic Coding

The current CLI version of Codex shares similarities with Anthropic’s Claude Code, highlighting the competitive landscape in the AI coding space. OpenAI, however, emphasizes that its web-based Codex features were in development internally before the CLI release. The adoption of Codex has seen a dramatic surge, with usage jumping 20 times after the release of the interactive CLI extension alongside GPT-5 in August 2025, and further accelerated by the specialized GPT-5 Codex version in September 2025.

Internal Adoption: OpenAI Engineers Embrace Codex

It's not just external developers who are benefiting from Codex. OpenAI’s own engineers have embraced the tool, utilizing the same CLI version available to the public. This open-source approach, where the team uses and contributes to the same codebase, fosters a collaborative and iterative development process. The recursive nature of Codex development extends beyond simple code generation, with Codex monitoring its own training runs and processing user feedback to determine future development directions. Tasks are assigned to Codex through project management tools like Linear, mirroring how work would be delegated to a human colleague.

A Recursive Loop: AI Building AI

OpenAI’s approach mirrors historical trends in computing, where tools are used to build increasingly complex systems. From hand-drafted circuits to EDA software, each generation of tools enables the creation of more sophisticated technology. Codex’s self-improvement loop exemplifies this pattern, with each iteration contributing to the next.

Codex in Action: The Sora Android App

A prime example of Codex’s impact is the rapid development of OpenAI’s Sora Android app. According to OpenAI, just four engineers built the app from scratch in a remarkable 18 days, with a total development time of 28 days. Codex assisted with architecture planning, sub-plan generation, and component implementation, demonstrating its ability to significantly accelerate development timelines. See how AI can streamline your workflow at https://daic.aisoft.app?network=aisoft.

Integrating Codex into the Workflow

Designers at OpenAI are now leveraging Codex to prototype features directly, bypassing the traditional handoff to engineers. Codex integrates with project management tools like Linear and communication platforms like Slack, allowing team members to assign coding tasks directly to the AI agent. Feedback in Slack can trigger Codex to create pull requests, facilitating a seamless and collaborative development process. This integration transforms Codex into a “junior developer” that the company hopes will evolve into a senior contributor.

Challenges and Considerations

While OpenAI reports significant success with Codex internally, independent research has shown mixed results for AI coding productivity. A METR study found that experienced developers were slightly slower when using AI tools on complex codebases, highlighting the importance of considering project complexity and codebase maturity. However, AI tools like Codex may excel in simpler projects.

The Future of AI-Assisted Development

OpenAI’s use of Codex to build itself represents a significant step towards a future where AI plays an increasingly integral role in software development. The ability of AI to not only assist developers but also actively participate in the development process promises to revolutionize how software is created and maintained. Explore the possibilities at https://daic.aisoft.app?network=aisoft.