On 16 May, OpenAI announced the release of Codex, a cloud-based software development model built to assist developers in writing efficient code. Apart from Codex, OpenAI has introduced many other modern coding models. OpenAI Codex acts as an experienced coworker for software engineers, allowing them to write clean code and fix bugs. Today in this blog, we will be talking about what is OpenAI codex, how to use Codex, and OpenAI Codex examples.     

What is OpenAI Codex?

OpenAI Codex is far more than just writing code, this is one of the powerful OpenAI tools enabling developers to detect and fix bugs, analyze code, and improve the existing code with its refactoring feature. It can handle several tasks at the same time, minimizing the burden on developers’ shoulders. Things OpenAI Codex can manage include producing optimized code, finding and solving errors, and responding to inquiries about software projects.

The Evolution of Codex

OpenAI began exploring vibe coding in 2021. At the time, it mainly acted as an advanced autocomplete tool for developers. A lot has changed since then. With major improvements in reinforcement learning, Codex has become significantly more powerful.

Today, in an era where “vibe coding”—describing what you want in plain language—is the norm, Codex can take natural language instructions and turn them into working code. The recent version of Codex‑1 doesn’t just write code—it follows development best practices like linting, testing, and maintaining consistent style, making it a valuable tool for serious software development.

Key Takeaways: How to Use Codex

1. Access Codex via the ChatGPT Sidebar

Navigate to the sidebar in ChatGPT to launch Codex.

2. Assign a Coding Task

Define the task by typing a clear instruction or request, then click on the ‘Code’ button to begin.

3. Offline Execution Environment

Codex runs in a secure, internet-free environment, relying solely on the code and files you provide, such as those from GitHub repositories.

4. Transparent Output with Logs

After completing a task, Codex provides terminal log citations to verify its actions and ensure full traceability.

5. Clear Communication of Issues

If Codex encounters uncertainties or test failures, it explicitly reports them, enabling you to make informed decisions.

6. Connect Your GitHub Account

To connect Codex with your GitHub Repo, you only need to grant two permissions from the app:

a) To clone repositories

b) To create pull requests

Codex will never make changes to your repositories without your approval.

Each team member must sign in with their own GitHub account before using Codex. Once connected, GitHub access is managed at the ChatGPT workspace level. This means if one teammate gives access to a repo, others in the same workspace can also run Codex tasks in that repo.

The Technology Behind Codex

Codex runs on codex-1, OpenAI’s model that’s built particularly for coding.

It was trained using real-world programming tasks to learn how to:

a) Write code that looks and feels like what real developers create

b) Follow instructions carefully

c) Test and fix its code until it works

d) Codex performs well on coding challenges, regardless of extra setup or custom tools.

Getting Started with Codex in ChatGPT

Unlock the power of Codex in ChatGPT by following these streamlined steps:

1. Access Codex via ChatGPT Interface

Launch ChatGPT, and on the left side, you will see the Codex (beta) icon. This opens up the Codex dashboard, your control center for all coding tasks.

2. Enable Multi-Factor Authentication (MFA)

To secure your access, click “Set up MFA”. Use an authentication app like Google Authenticator or Authy to scan the QR code. Afterwards, fill in the code to confirm.

3. Link Your GitHub Account (First-Time Only)

Permit Codex to interact with your Git repositories using a one-click OAuth flow. You can choose to limit access to selected organizations or repositories.

4. Select a Repository and Branch

Choose which repository and branch you want Codex to operate on. Codex will then create a sandboxed clone of that branch for safe experimentation.

5. Optional: Configure Your Development Environment

You can add secrets, environment variables, or custom setup commands, much like you would in a CI/CD pipeline. Built-in tools like linters and formatters are ready out of the box, and you can customize tool versions as needed.

6. Choose or Create a Task

Select a predefined task template or create your own.

Example Commands:

a) “Explain the project structure.”

b) “Fix the broken test in auth_tests.py.”

c) “Scan the repo for unused code.”

You can also describe a task in your own words—Codex understands natural language instructions.

7. Launch Jobs and Work in Parallel

Click “Launch” to initiate a task. Each task runs in an isolated micro-VM, allowing you to launch multiple jobs simultaneously while continuing your ChatGPT conversations.

8. Monitor and Review Outcomes

Passing tests are marked with green check marks.

9. Deploy or Refine

Ready to ship? Click “Open PR” to make modifications directly to your GitHub repo. 

Completed tasks display with status indicators. Click any task to inspect the code diff, read Codex’s explanation, and browse the detailed activity log.

OpenAI Codex Examples

Here are a few OpenAI Codex examples showing how it simplifies your life:  

Speed Up the Development Process

Nacho Soto, an Airline captain and software engineer, demonstrates how Codex streamlines the early stages of development by automatically generating a project framework or basic structure. With just a few natural language prompts, he quickly delegates the initial setup to Codex, allowing him to concentrate on feature development while the tool manages the background work.

Fixing Bugs

Codex enables developers to build smart and efficient code by helping them fix issues and bugs without letting them break their focus. These tasks can be easily handled by Codex, allowing them to focus more on key features and saving a lot of time.     

Analyse Workflow

Apart from supporting developers to build code, Codex enables them to thoroughly analyze the overall workflow. Developers review AI-generated pull requests, identify issues, and guide Codex to apply the necessary corrections. 

Conclusion

Codex has proven its ability to elevate the developer experience by not only fixing bugs and applying feature enhancements but also by clearly explaining code logic. It handles routine tasks like generating pull requests, running automated tests, and logging its actions with clarity through terminal outputs and code diffs.

As Codex continues to mature, we can expect even deeper integrations with popular development environments, CI/CD systems, and task management tools, positioning it as an essential part of the modern engineering toolkit. 

Codex marks a fundamental shift in the way engineers collaborate with AI. While live coding assistance is now a common practice, OpenAI is pioneering a new paradigm: asynchronous, multi-agent workflows. This approach allows developers to assign tasks to Codex while continuing to work independently, enabling faster, more scalable software production.