Generating Code With OpenAI Codex and ChatGPT

OpenAI Codex is an AI model built to turn your natural-language requests into working code. A request like "Build a calculator," written in English or any language, is translated into real programming code by the technology at the core of Codex. This family of models powers the code generation you do inside ChatGPT and OpenAI's coding-focused tools. In this guide I cover where Codex stands in 2026, step-by-step scenarios for generating code with ChatGPT, the differences between Codex CLI and the ChatGPT interface, and how Codex compares to Claude Code.

The Relationship Between Codex and ChatGPT

Many people confuse Codex with ChatGPT. To put it simply: ChatGPT is a general-purpose chat interface that can also produce code. Codex is a family of models optimized specifically for software development, along with a command-line tool built on top of it. So you can request code by chatting in ChatGPT, or work directly on your project using Codex's agent tool.

Both of these usage styles form the foundation of the vibe coding approach: instead of memorizing code, you reach the result by describing what you want.

Where OpenAI Codex Stands in 2026

The Codex name has represented more than one product over the years. The first Codex model was introduced in 2021 and powered the code-completion tools of that era. In 2023 that first model was retired. In 2025 OpenAI brought the name back with a far more ambitious product: a coding agent that can take on software tasks from start to finish. As of 2026, Codex no longer means a single model but a family of tools that complement each other.

• Codex CLI: An open-source agent tool that runs in the terminal. It reads your project files, makes edits and runs commands with your approval.
• The Codex agent inside ChatGPT: You describe the task, and Codex writes the code in an isolated cloud environment, runs tests and presents the result as a change proposal you can review. It can run several tasks in parallel and integrates with GitHub.
• The editor extension: Lets you assign tasks to Codex from inside code editors such as VS Code.

Behind these tools run OpenAI's current models trained specifically for software development. Access to Codex is included in ChatGPT's paid plans, and usage limits vary by plan. So if you already have a ChatGPT subscription, in most cases you do not need to pay anything extra to try Codex.

How to Use Codex

There are two practical ways to get started with Codex. The first is through ChatGPT: if you have a paid plan, you open the Codex section, connect your project and describe your task in natural language. The second is from the terminal: you install the Codex CLI tool on your computer, run it inside your project folder and explain what you want. The steps roughly work like this:

1. Sign in with your ChatGPT account and make sure your plan includes Codex access.
2. If you will work in the terminal, install the Codex CLI tool and log in with your account.
3. Enter your project folder and give your first task, such as "Add validation to the contact form in this project."
4. Review the changes Codex proposes and approve them.
5. Test the result and, if needed, refine it with a new request.

For your first attempt, I recommend picking a small throwaway project rather than something important. You will grasp how the tool thinks within a few tasks, and then you can move on to real work with confidence.

Can ChatGPT Write Code?

This is one of the questions I hear most often, and the answer is clear: yes, ChatGPT can write code. It can produce code from scratch in common languages such as Python, JavaScript, HTML and CSS, explain existing code, find bugs and suggest improvements. For small and medium-sized jobs, it is often enough on its own.

You should also know its limits. ChatGPT cannot see the project folder on your computer, cannot browse your files and cannot run the code it produces in your environment. You are the one who tests whether the code works. In large, multi-file projects, carrying the context into a chat becomes increasingly difficult. That is exactly where Codex CLI and similar agent tools come in.

Practical Ways to Generate Code With ChatGPT

The easiest entry point for beginners is generating code through ChatGPT. Here are a few tips for effective use:

• Be specific: Instead of "Build a website," make detailed requests like "Build a single-page promo site with a contact form, using a dark theme."
• Move step by step: Rather than requesting a large project all at once, break it into parts. Test each part, then continue.
• Share errors: Paste the error message you encounter exactly as it appears. ChatGPT can usually identify the problem and suggest a fix.
• Give context: Stating which technology you're using and your goal helps you get far more accurate code.

Step by Step: Code Generation Scenarios With ChatGPT

Let's move from theory to practice. The three scenarios below are realistic examples that even someone who has never written code can try today.

Scenario 1: A Single-Page Promo Site

1. Describe your goal: "I want a single-page promo site for a small home-cooking business, with header, about, menu and contact sections."
2. Set the technical frame: "Use a single HTML file with the CSS inside it, and no external libraries."
3. Save the generated code to a file on your computer and open it in a browser.
4. Fix what you don't like by describing it: "Make the menu section three columns and soften the colors."
5. Ask for one change per turn. That way you always know which request changed what.

Scenario 2: Automating a Repetitive Task

1. Explain the task you do by hand: "I want to rename hundreds of photos in a folder based on the date they were taken."
2. Say "Write a Python script for this and explain what each part does."
3. Also ask how to run it. ChatGPT will walk you through everything from setup to execution.
4. Try the script on a copy of your files first, and never make the first run on the original data.
5. If you hit an error, paste the message exactly as it appears and ask for a corrected version.

Scenario 3: Debugging

1. Copy and paste the full error message without summarizing it.
2. Share the piece of code that causes the error.
3. State in one sentence what you expected and what happened instead.
4. Apply the suggested fix and share the result again.
5. Once it is solved, ask "Why did this error happen?" so you know what to do when you meet a similar one.

Codex CLI or the ChatGPT Interface?

Both generate code, but they work differently. To make the choice easier, let's put them side by side:

My recommendation is simple: while you are learning and working on single-file jobs, the ChatGPT interface is more than enough. Once you start making multi-file changes in a real project folder, Codex CLI saves you a noticeable amount of time.

Codex or Claude Code?

Among terminal-based agent tools, the best-known alternative to Codex CLI is Claude Code. Both tools work with the same philosophy: they read your project, make a plan, edit files and run commands. The main differences are these:

• Model family: Codex runs on OpenAI's models, while Claude Code uses Anthropic's Claude models.
• Subscription ecosystem: Which tool suits you often comes down to which subscription you already have. If you have a ChatGPT subscription, Codex is the natural choice, and if you have a Claude subscription, Claude Code is.
• Working style: Both tools evolve quickly, and the gap between them shifts with every release. My suggestion is to try both on the same small task, such as adding a dark theme to a simple page. Continue with whichever output and working style feels more comfortable to you.

One more thing: this is not an either-or decision. Many builders, myself included, use different tools side by side for different jobs.

What to Watch Out For

Although generating code with AI is powerful, there are some points to keep in mind:

• Always review: The generated code is usually correct, but not always. Review the result especially for security and data handling.
• Test in small pieces: Running and verifying the generated code before moving to the next step prevents errors from piling up.
• Stay open to learning: Trying to understand the code the AI writes makes you a far more independent builder over time.

The Connection to Vibe Coding

Everything I've described in this article is part of a single approach: instead of memorizing code line by line, you describe what you want and steer the result. That approach is called vibe coding, and I cover it in detail in my article on what vibe coding is. Codex and ChatGPT are two of the most accessible tools for it. The lasting gain is tool-independent: as your prompting skills improve, you get better results no matter which tool you use.

Which Tool Should You Start With?

If you're just starting out, generating code through ChatGPT is the lowest-barrier path. As you get comfortable, you can move to Codex's command-line tool or similar agent tools. For those who want to learn this transition in the right order and with real projects, our vibe coding course covers building applications from scratch with AI tools, step by step. And if you want to use AI not only for code but across your whole workflow, take a look at my training programs.

In conclusion, OpenAI Codex and ChatGPT are among the most accessible ways to quickly turn your ideas into working software. As you build the habit of writing good prompts, you'll be amazed at how much you can produce.