This is insane. While everyone is still talking about Claude 5, OpenAI just dropped a bomb in the middle of the night. They turned Codex into a real desktop app. Now one person can command thousands of AI agents at once. Programmers may never have to work overtime again.
The gap between Claude 5 and OpenAI is getting bigger and bigger. The competition is heating up.
Just recently, OpenAI made a surprise move. They officially launched the Codex desktop app. It is no longer just a web tool. It is a real app on your computer.
This is not just a code writing tool. It is a real command center where one person can lead an army of AI agents working together. It is the true meaning of “one person, one army.”
The most accurate way to describe Codex is “the commander of AI agents.”
Here is what makes Codex different from other coding tools:
First, you need to give it a clear mission. For example, build a photo sharing app, add a drag feature, and choose a “glass style” design. Then you just sit back and watch. Multiple AI agents work together like a real team in a tech company.
Codex does not write code like a student. It acts like a senior engineer. It breaks the whole project into smaller tasks. Each task becomes a “Skill.” Then it calls these Skills one by one to get the job done.
What is even more powerful is that when you write a comment in the code, Codex can directly use the installed Skills and fix the problem right away.
Here is a crazy example. OpenAI showed how Codex used 700,000 tokens and built a full 3D racing game in one go.
Another time, Codex built a complete cocktail recipe app. It had a beautiful glass-style design.
This is the real power of AI agents. They are not just chatbots. They are your team members.
One developer said, “Before, I was just one person. Now I feel like I have a whole team working for me.”
“AI agents are not just about speed and power. They are about collaboration. They are not here to replace us. They are here to work with us, side by side, until the problem is solved.”
OpenAI president Greg Brockman strongly recommended it.
He said he had been a hardcore terminal and Emacs user for many years. But after trying Codex, he never went back to the terminal. It was just too convenient.
He called it “a new way of coding that feels like having a real AI teammate.”
OpenAI Codex represents a brand new way of AI coding. It is not just about writing code faster. It is about changing how humans and machines work together.
Compared to Claude Cowork, Codex has a clear advantage. It is not just a coding tool. It is a real teammate.
Right now, the Codex app is only on macOS. A Windows version is coming soon.
OpenAI also announced that all ChatGPT paid users, including Plus, Pro, Business, Enterprise, and Edu plans, can use Codex right away.
The Real Killer Feature: One Person Commands an Army of Agents
The Codex app on macOS is a huge upgrade.
Imagine this. You open the app and see a list of AI agents. Each one is a teammate. They write code, test code, and work with other AI agents to fix problems in real time.
In the past, the relationship between humans and AI was “I write, you help.” Now it has become “we write together, line by line.”
The most powerful part of Codex is that it changes the way we write code forever.
We no longer give AI simple tasks. We give AI full projects. It runs through the whole process from start to finish. It plans, codes, tests, and fixes bugs all by itself.
Let us go back in time. In April 2025, Codex was still just a web tool. But the way humans work with AI has already changed a lot.
In the past, we thought of AI as a helper. We asked it to write small pieces of code. Now, with Codex, one person can lead an army of AI agents to build an entire project.
These agents can work on different tasks at the same time. They do not waste time or get tired. They can handle big projects that used to need a whole team.
The key question is: what is the difference between AI tools and AI agents?
AI tools are like hammers. They wait for you to pick them up. AI agents are like workers. They see the problem and start fixing it on their own.
The biggest change is that the old IDE and terminal are no longer enough.
This new way of working needs a new kind of workspace. It is not just a text editor. It is a real command center.
That is why OpenAI built the Codex app. It is not just a coding tool. It is a command center for AI agents.
Parallel Work: Multiple Agents Working at the Same Time
Codex gives each AI agent its own space to work.
When multiple AI agents work on the same project at the same time, they might try to change the same file. This could cause conflicts and lost work.
The app solves this by showing you the changes directly. You can see the diff, write comments, and use the editor to review and merge the changes.
It also supports Git worktree. This means different AI agents can work on different branches of the same project at the same time without conflicts.
Each AI agent works on its own copy of the code. They explore different solutions. In the end, you choose the best one. This is like having multiple teams working on the same problem, but they never get in each other’s way.
When an AI agent is done, it can check out the changes and merge them back. The whole process is safe and clean. The git status stays correct.
Users can also use the Codex CLI and IDE extensions to sync chat history, share context, and work on the same project from different places.
Skills System: Teaching Codex New Tricks
Codex is not just a coding AI. It is a platform that can learn new skills.
Through the Skills system, users can teach Codex new abilities.
For example, Codex can browse the web, collect information, connect to APIs, write documents, and more.
Skills are basically instructions, resources, and scripts. Codex can use them as reliable tools. Teams can also share Skills with each other.
The Codex app has a special Skills store and management system.
When you want Codex to use a certain Skill, you just mention it in your message. Codex will use it automatically.
OpenAI showed an example. They asked Codex to build a racing game.
The game had different cars, tracks, maps, and obstacles. Every space on the track had its own rules.
They used the GPT Image Skill to draw the game art. They used the Web Skill to let Codex search the web for game design ideas. Then Codex wrote the whole game using 700,000 tokens.
The game had multiple modes. Players could race against AI drivers. QA agents tested the game and found bugs. Then Codex fixed the bugs.
You can see that in the first version, the game was a mess. The cars were scattered everywhere. The track was broken.
In the middle, the cars started crashing into walls and getting stuck.
Sometimes the game would freeze. Nothing worked.
Another time, in the 80-token version, the game looked better but still had problems. The cars were going in circles.
The collision system was not working well. The cars just kept spinning.
In the second round, the cars were still going in circles and could not finish the race.
But in the 700-token version, everything changed. The game looked great. The track was clean. The cars drove smoothly. The AI opponents were smart.
This time, the game really worked.
From the very beginning, we could see the AI was like a student. It was not perfect. It would make mistakes. But it kept trying.
Then it got better and better. The cars started driving on the track. The game became playable.
Finally, the game was complete. The AI had learned from its mistakes. It fixed the bugs and made the game fun.
This is the real power of AI agents. They do not give up. They keep trying until they get it right.
OpenAI’s internal team also used Skills to build tools for their own work. They gave Codex the power to use internal tools and workflows. This made the whole team more productive.
The Codex app comes with a Skills store. It includes all the tools and workflows that OpenAI uses internally.
Using Vercel Skill to build a website
Using database Skill to create a to-do list
Using Linear Skill to manage issue backlog
When you write a Skill for your own app, Codex can use it anywhere. It works in the app, the CLI, and the IDE extension.
You can also submit Skills to the open source repo and share them with the whole team.
OpenAI open sourced Agent Skills: https://github.com/openai/skills
Automations: Let AI Work for You 24 Hours a Day
Codex also has a powerful feature called Automations. It lets AI agents work in the background automatically.
Automations means you can choose a set of Skills and set a timer. The AI will run on its own.
When the Automation starts, the AI agent wakes up, checks the project, and does what you told it to do.
Automation automatically runs Skills in the background
The OpenAI team uses Automations to handle boring tasks. For example, sorting issues, searching for answers, summarizing why CI failed, writing daily reports, and fixing bugs.
Dual Mode: Human and AI Working Together
When we talk about AI agents, we need to understand something important.
There are two ways to use them. One is fully automatic. The AI does everything on its own. The other is human-in-the-loop. The human and AI work together.
Codex supports both modes. You can choose to let the AI work alone, or you can work with it step by step. The app, CLI, and IDE extension all support this.
Default Security Settings Keep You Safe
Of course, OpenAI also put a lot of effort into security. They call it “Security by Design.” This means security is built into Codex AI from the very beginning.
The Codex app runs in a sandbox. This is a closed system. The Codex CLI also runs in a sandbox.
By default, Codex AI can only edit files in the current project. It cannot access other files on your computer. It cannot open web pages.
If you want it to access the internet or other files, you need to give it permission. It will ask you first. You are always in control.
OpenAI also lets project teams set different permission levels. This way, different AI agents can only access what they are allowed to access.
The Future of Coding Is Here
As AI tools get better and better, the gap between Codex and other tools is getting smaller.
In December, the GPT-5.2-Codex model was released. Codex can now handle more than one million tokens at a time. It can process over 100 files at once.
A research team is already expanding how Codex is used. They are building a Windows app, adding voice input, improving the model, and making it faster.
An OpenAI researcher said that in the past, fixing bugs and adding features to Prism took months. Now, with Codex, it takes just days.
Inside OpenAI, the team is already using AI agents to handle real work. They use AI to write code, test code, and fix bugs. The AI is not just a helper. It is a real team member.
They also use Automations to support mobile development. Codex works in the background, handling boring tasks while humans focus on creative work.
Codex is not just a tool. It is a new way of working.
One AI agent can do the work of many people. The stronger the model, the more knowledge it has, the more powerful it becomes.
our dream ai
OpenAI is going all in.
But there is still one big challenge. The gap between frontier models and real-world use is still huge.
Codex is just the beginning. One person, one army. This is not just a slogan. It is the future of coding.
OpenAI is making Codex stronger and turning it into a real AI teammate. It is also creating a new kind of knowledge work where AI agents are the new normal.
nude ai generatorGame Log
Here is what Codex used when it built the racing game. This is the initial prompt (summarized):
Use Three.js to build Voxel Velocity, a 3D racing game with only one mode. Players race against 3 AI opponents on 1 track with 7 CPU drivers. The game must work in browser mode. No installation needed. Players choose a car from 8 colors and 8 difficulty levels. There are standard, time trial, and endurance modes. Players can choose manual or automatic transmission. The game has a start screen with a title, start button, and exit button. There is a phone mode with tilt controls, drift controls, and brake controls. The game has a drift scoring system. Cars have collision physics. The track has walls, obstacles, and a boost system. There are speed levels (Level 1: 0.7, Level 2: 1.1, Level 3: 1.5). There is also a speed boost system. The game shows lap time, best lap, and current position. The HUD shows speed, gear, drift score, and mini-map. The game has 8 tracks with different themes. Weather effects include rain and snow. AI drivers have different skill levels. The game has a pit stop system. Tire wear affects handling. Fuel runs out at 1.2 laps. Tires wear out at 0.6 laps. The pit crew has no idle time. Damage is repaired during pit stops. The AI has a 50% chance of making a pit stop. There are 8 car colors. The game tracks statistics and AI learning. CPU difficulty is predicted based on player data. The game has a write/save system. The leaderboard shows global rankings. There is a replay system. The game has a photo mode. There is a music and sound effects system. The game has a tutorial mode. There is a challenge mode. The game has a career mode. There is a multiplayer mode. The game has a track editor. There is a car customization system. The game has a team management system. There is a sponsorship system. The game has a weather forecast system. There is a news system. The game has a fan system. There is a social media system. The game has a streaming system. There is a VR mode. The game has a mobile mode. There is a console mode. The game has a PC mode.
After reading this prompt, Codex showed 10 different attempts. Each attempt showed the game getting better and better.
Here is what one attempt looked like:
The game had basic functions. It used the original game engine. The game was stable. The game had all the basic features. It was missing some advanced features. Then it chose the missing features and built them one by one. After each round, it tested the game to make sure everything worked. It also fixed any bugs it found.
