I made a small Codex skill for a problem I kept hitting:
AI coding agents do not just fail during implementation. They often fail before implementation, because the task is vague.
So I built goal-task-prompt.
Repo: https://t.co/c31kWU7vuf
@thsottiaux What the hell is this Fable5 thing that you can’t even use after two days? I swear I’ve never heard of it, and I already canceled my Claude subscription.
Whoa, these updates are actually huge! ChatGPT Work sounds like a total game-changer for teams and companies. Super excited the new desktop app is finally here too — that should feel way nicer to use. And hosted sites on top? Nice. Watching the 5.6 livestream right now, can’t wait to see more. Keep it coming Sam 🚀
🦞 Bro this is straight-up wild!
100k issues + PRs in just 222 days, all volunteers, every timezone, zero VC funding… y’all are actually cooking with gas 🔥
And the 100,000th one being a community bug report? Lmao that’s so on brand I can’t 😂
Huge shoutout to everyone building this thing. Keep going hard, lobster gang! Can’t wait for the next 100k 🦞💪
🦞 #100000
100,000 issues + PRs in 222 days.
🛠️ built by volunteers
🌍 every timezone, every day
🧡 zero VC, one lobster
Number 100000 itself? A community bug report. We'll fix that one too.
Thank you for building this with us.
Announcing the hosted X MCP.
Agents now have access to the best real-time information source in the world.
Connect Grok, Cursor, or any MCP-compatible AI tool to the X API without any setup!
Check it out here: https://t.co/5MzPYwGFzD
We’re sharing the next major milestone in our non-invasive brain-to-text decoder research: Brain2Qwerty v2.
Building on v1, which was published today in @Nature, Brain2Qwerty v2 is the highest-performing end-to-end pipeline capable of real-time sentence decoding from raw brain signals. It advances beyond character-level performance to decoding words and semantics, enabling accuracy for overall communication.
We believe this research has the potential to make a real difference for the millions of people who suffer from brain lesions or disorders that prevent them from communicating.
🧵👇
We’re sharing the next major milestone in our non-invasive brain-to-text decoder research: Brain2Qwerty v2.
Building on v1, which was published today in @Nature, Brain2Qwerty v2 is the highest-performing end-to-end pipeline capable of real-time sentence decoding from raw brain signals. It advances beyond character-level performance to decoding words and semantics, enabling accuracy for overall communication.
We believe this research has the potential to make a real difference for the millions of people who suffer from brain lesions or disorders that prevent them from communicating.
🧵👇
Community report: Codex may be quietly routing some gpt-5.5 xhigh sessions to gpt-5.6-sol.
Try it in Codex App/CLI:
select gpt-5.5, set reasoning to xhigh, then run the Juice test prompt.
If it returns 128, you are probably in the gray rollout.
Worth testing to see if you got it.
Introducing a limited preview of GPT-5.6 Sol, our next generation frontier model, as well as GPT-5.6 Terra, a balanced model for efficient, everyday work, and GPT-5.6 Luna, a fast and affordable model for high-volume work.
https://t.co/OoM83SyISN
Haha, I hoarded two as well! Saving them like health potions, waiting to pop them when GPT-5.6 finally drops. Boss fight prep complete 💪
Just hope it doesn’t take too long or these potions might expire 🫠
We built the Codex App with models that were okayish at front-end.
Wait to see what we can do when we finally improve front-end capabilities significantly in our models. That day will be something.
GLM 5.2 is the new open-weight SOTA on the Vals Index, Vibe Code Bench and Terminal Bench!
It is also #5 across all models, and right on the heels of Opus 4.7 - released only two months ago
@thsottiaux Super useful reminder, Tibo! Finally can run Codex with local/open-source models without burning through credits. Thanks for the advanced config link — heading to try it with Ollama right now.
Anyone got good hybrid workflow examples? 👍
This is spot on, Mike.
The real shift isn’t writing better prompts anymore — it’s building loops that keep working after you close the laptop. The memory file + evaluator-optimizer pattern especially clicked for me. Too many people are still letting the same agent grade its own homework.
Starting small with one automation trigger + a simple STATE.md feels like the right move. Thanks for laying out the full architecture so clearly. Bookmarked and planning to build my first loop this week.
What’s one loop you’re currently running that’s giving you the most leverage?
I open sourced it here:
https://t.co/c31kWU7vuf
If you use Codex or build agent workflows, try it on one vague task and compare the output before/after.
Stars and prompt cases are welcome.
I made a small Codex skill for a problem I kept hitting:
AI coding agents do not just fail during implementation. They often fail before implementation, because the task is vague.
So I built goal-task-prompt.
Repo: https://t.co/c31kWU7vuf
The multi-agent part is intentionally conservative.
It only recommends splitting when workstreams are independent, verifiable, and mergeable.
No "launch 10 agents and hope they agree" behavior.