I'm joining @OpenAI to bring agents to everyone. @OpenClaw is becoming a foundation: open, independent, and just getting started.🦞 steipete.me/posts/2026/openc…

This shortage of chips is getting out of hand.

Add this shortcut to your iOS Home Screen so you can search for Codex. And use this icon raw.githubusercontent.com/lo… icloud.com/shortcuts/857005f…

Got a PayPal verification text and thought I been hacked, but it was just codex signing up for a web service it needed.

I can barely keep up with implementing/testing/landing all the Issues/PRs folks submit to github.com/openclaw/crabbox#… Codex runs INSIDE crabbox while it is building crabbox. This is becoming essential infra for my work. Codex been looping nonstop for the last 4 days in multiple trees. Since all of it is e2e verifiable it basically builds itself. Codex even signs up for the services automatically via browser/computer use. My main job is adding credit card details and closing things that I don't see as a fit.

Dario (48 hours ago): “US gov should be able to block model deployment” USG: *export controls models* Dario: “not like that”

新しいリアルタイム翻訳モデルを発表できることをうれしく思います。ぜひ本日よりAPIでお試しください。

“not consistently candid in their communications” is my fav new americanism. theinformation.com/articles/…

appshots in codex is the most useful piece of software on my Mac most of my prompts these days are: - cmd cmd investigate this - cmd cmd open a PR to fix this - cmd cmd run the eval on these set of prompts and discussion - cmd cmd set a heartbeat to keep following up with this and many more cases trust me, you’ve got to try it

codex -C ~/projects/openclaw -m gpt-5.5-cyber time

more like Fumble 5

How am I only now finding out about appshots? I was dragging screenshots into codex live a caveman.

We've updated the Artificial Analysis Coding Agent Index, replacing SWE-Bench Pro with Datacurve's DeepSWE benchmark - the swap lifts Codex with GPT-5.5 (xhigh) above Claude Code with Opus 4.8 (max), while the newly released Claude Fable 5 (max) in Claude Code debuts at the top DeepSWE, built by @datacurve, writes its tasks from scratch rather than adapting them from public GitHub issues or pull requests, so no model has seen the solutions during training. That matters because SWE-Bench Pro, the benchmark it replaces in our Coding Agent Index, had grown gameable, with some models recovering the fix from the repository's commit history instead of solving the task. The swap reorders the index: Codex with GPT-5.5 (xhigh) rises from 65 to 76, overtaking Claude Code with Opus 4.8 (max) at 73. Claude Code with Fable 5 (max), which enters directly on the refreshed index, leads at 77. SWE-Bench Pro had been flattering some combinations and penalizing others. More below.

Everyone says the latest AI agents will be "job-ready" soon, especially after the release of Fable 5 this week. But is that really the case? Over the past many months, my group and collaborators have been building Agents' Last Exam (ALE), a benchmark designed to test exactly that claim on real digital labor-market work. My group and collaborators previously have created many of the benchmarks the field runs on, including MMLU, MATH, CyberGym, and ExploitGym. Today, I'm excited to share Agents' Last Exam (ALE): a rolling benchmark that measures whether AI agents can actually perform economically valuable work across a broad range of real-world domains. With ALE, we evaluated Fable 5, GPT-5.5, Composer 2.5, and other frontier agent systems across more than 1,500 expert-sourced tasks spanning 55 occupations. The result is both impressive and sobering. Today's agents can solve a meaningful fraction of professional tasks. But when we look at the hardest tasks, the ones requiring sustained reasoning, deep domain expertise, and reliable execution over long horizons, they are still far from human-level performance. On ALE's hardest tier, every frontier agent we tested, including Fable 5, achieved a 0% success rate. The age of useful agents is here. The age of truly job-ready agents is not. We hope Agents' Last Exam (ALE) will serve as a new guidepost and north star for developing agents capable of reliably performing economically valuable work across a broad range of domains. 🧵

Fable 5 refused 200 out of 200 ProgramBench tasks lmao

IMO sth that is a bit overlooked but will become far more important in the future. GPT is 10-20x more token cost effective for ~similar outcome.

Ship of thesus Rewrite the entire codebase for each new model release

My new favorite prompt: take a step back. Wonderful results