OpenAI Codex in ChatGPT in 5 Minutes

Summary

In this video, the presenter discusses OpenAI's newly released cloud-based software engineering agent, Codex. Unlike tools like Cursor or Windsurf, Codex is designed to assist with tasks such as writing features, answering questions about code, and fixing bugs. Codex, powered by the advanced Codex 1 model, integrates with GitHub repositories, allowing users to work with code in natural language. It can autonomously run tests, edit files, and even propose pull requests. The video also highlights the agent’s capabilities, benchmarks, and practical applications, with a focus on enhancing code review and software development workflows.

Takeaways

• 😀 OpenAI's Codex is a new cloud-based software engineering agent, offering different features than tools like Cursor and Windsurf.
• 😀 Codex can assist with writing features, answering questions about codebases, fixing bugs, and proposing pull requests.
• 😀 Users can integrate a GitHub repository with Codex, select branches, and work with it using natural language.
• 😀 Codex is powered by Codex 1, a version of OpenAI's 03 model, optimized for software engineering tasks.
• 😀 The model was trained using reinforcement learning on real-world coding tasks to mirror human coding styles and PR preferences.
• 😀 Initially, Codex is available to ChatGPT Pro, enterprise, and team users, with support for Plus and education users coming soon.
• 😀 Codex works in isolated environments for each task, allowing users to work with their codebase in parallel on multiple tasks.
• 😀 The tool has access to environment variables, can read/edit files, run terminal commands, and execute test suites.
• 😀 Task completion time ranges from 1 to 30 minutes, depending on the task, and users can run multiple tasks concurrently.
• 😀 Codex provides verifiable evidence of its actions by citing terminal logs and test outputs, ensuring trust in its code changes.
• 😀 Once tasks are complete, Codex can open a pull request directly, streamlining the process of reviewing AI-generated code.
• 😀 Codex includes an 'agents MD' feature, allowing users to guide the agent's behavior based on project standards and specific commands.
• 😀 Codex 1 performs well on the SweetBench verified benchmarks, showing efficiency with fewer attempts, and converges with OpenAI’s 03 model at higher attempt ranges.
• 😀 Codex will be accessible through the ChatGPT app, enabling quick checks of repos and troubleshooting code during calls.

Q & A

What is the main purpose of Codex as described in the video?

Codex is a cloud-based software engineering agent that helps with writing code, answering questions about codebases, fixing bugs, and proposing pull requests. It is designed to assist developers by automating tasks and integrating with GitHub repositories.

How does Codex differ from tools like Cursor or Windsurf?

Codex is not intended to replace tools like Cursor or Windsurf. While those tools provide an agentic IDE experience, Codex operates in a more isolated environment, where tasks are processed independently, and it handles tasks with varying durations (from 1 to 30 minutes). It is more focused on backend codebase management and task automation.

What is the underlying model powering Codex?

Codex is powered by Codex 1, a version of OpenAI's 03 model. This model is optimized for software engineering tasks and was trained using reinforcement learning on real-world coding tasks.

Who can access Codex initially, and when will it be available for others?

Initially, Codex is available for ChatGPT Pro members, enterprise users, and team users. Support for Plus and education users will be rolled out soon.

What types of tasks can Codex assist with?

Codex can assist with tasks such as writing features, answering questions about codebases, fixing bugs, and proposing pull requests. It can also help manage repositories and automate tasks within a codebase.

How does Codex interact with GitHub repositories?

Codex allows users to integrate GitHub repositories, select branches to work on, and interact with the repository using natural language. It can display open and merged pull requests, and show diffs and changes related to each request.

How does Codex process tasks and what environment does it use?

Codex processes tasks independently in a separate, preloaded environment that includes the user's codebase. It has access to environment variables, files, the terminal, and test suites. This isolation allows for more secure and focused task processing.

What happens after Codex completes a task?

Once Codex completes a task, it commits the changes to the environment and provides evidence of its actions, such as terminal logs and test outputs. This ensures verifiable results, similar to the agent modes in Cursor or Windsurf.

What is a significant feature Codex offers for team-based projects?

Codex allows teams to guide agents within an 'agents MD' file placed in the repository root. This file helps agents navigate the codebase and adhere to project standards, similar to how Cursor uses cursor rules.

What are the benchmarks for Codex 1, and how does it compare to other models?

Codex 1 performs well in the SweetBench verified benchmarks, especially with fewer attempts. It starts to converge with the performance of the 03 model after several attempts. Both Codex 1 and 03 are state-of-the-art models for coding tasks.