Openai

If you’ve read my post about worktrees in Claude Code, you know the key to parallel workflows is a simple flag: --worktree. Run it, and you get an agent working in its own isolated repo copy. Launch three, and you’ve got three agents working in parallel without clashing. Magic. Now you open Codex CLI, look for an equivalent flag… and it doesn’t exist. There’s no --worktree. No --tmux. No isolation: worktree for custom agents. Issue #12862 has been open on GitHub asking for exactly this, with community members proposing their own implementations in forks, but nothing has been merged. Native parallelism for Codex CLI doesn’t exist — not yet. ...

You install Codex CLI. You launch it with excitement and tell it to “Fix the broken tests in this repo,” and then the nightmare begins: Codex: I want to run pytest Allow? (y/n) You press y. Immediately, this pops up: Codex: I want to modify test_user.py Allow? (y/n) So, you press y. Again, and again, and again. Every file it wants to read, every command it wants to run, every line it wants to modify. Confirm, confirm, confirm. It’s like working with an intern that asks permission for everything. ...

Imagine you hire a brilliant consultant. They have two PhDs, speak seven languages, and solve problems you didn’t even know you had. You sit them in a room and say: “I need you to refactor the authentication in the project.” The consultant looks at you, nods, and asks: “What project?” You haven’t given them access to the code. You haven’t explained the architecture. They don’t know if you use JWT tokens or session cookies. They don’t know what language you’re using, how many microservices you have, or why the last migration attempt ended in disaster. ...

Two weeks ago, OpenAI introduced Codex Automations. The idea: define a trigger (a cron job, a push, a new issue), write instructions in natural language, and an agent runs it solo in an isolated worktree. No human intervention. While you sleep, the agent triages issues, summarizes CI failures, generates release briefs, and even improves its own instructions. Sounds like magic, right? And it is, a little. But there’s one catch they didn’t emphasize too much in the keynote: you need the Codex App running on your desktop. macOS or Windows only. No headless servers. No running it on a mini PC and forgetting about it. ...

Every time an article comes out about a large company’s infrastructure, half the Hacker News comments are variations of “of course they use Kubernetes with 47 microservices and a distributed database with custom consensus protocol.” And when it turns out they don’t—that they use plain PostgreSQL with a single primary and discipline—there’s an uncomfortable silence. That just happened with OpenAI. The numbers nobody expected Bohan Zhang, infrastructure engineer at OpenAI, published details about how they scale PostgreSQL for ChatGPT. The numbers: ...

The first time I used Claude Code to refactor an entire module, I had an almost mystical experience. I described what I wanted, went to grab a coffee, and when I came back there was a pull request with 14 changed files, updated tests, and a decent commit message. “This is magic,” I thought. It’s not magic. It’s a while loop. Michael Bolin from OpenAI recently published an article breaking down the internal workings of Codex CLI. And it turns out the secret behind AI coding agents isn’t some revolutionary algorithm or mysterious neural network. It’s a loop that calls an LLM, executes tools, and repeats until there’s nothing left to do. ...