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Three Astra Ultra Dots ran all night

@tachichocolate

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dot讚讚 三個 Astra Ultra 跑整晚

@tachichocolate (Oct 2 2026, Traditional Chinese): first-hand follow-up — ran THREE Astra Ultra Dots overnight ("三個 Astra Ultra 跑整晚"). Continuation of his already-documented overnight Astra implementation projects (see his DeAia4kk6P1 card); real caption, image attached.

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I stayed on a 30-minute call with my Dot — it already knew the context

I stayed on a 30-minute call with my Dot — it already knew the context

I thought Dot calls were basically ChatGPT Voice with a cute avatar and a VM. Then I somehow stayed on one for 30 minutes 😳 It already knows the context, what we’re working on, and how I like things done. You just call and continue. This feels less like “voice mode” and more like having an AI coworker on speed dial. 🤯 the thing is i have bad temper, i curse it and yell alot and it just acts so calm wtf😂😂
@AbdoKerdawy
My Dot checked on my Claude Code benchmark running on my Mac

My Dot checked on my Claude Code benchmark running on my Mac

Very cool, using my Dot to check on my benchmark running on Claude Code, on my Computer, totally seamless. I could quickly see my Dot becoming a core way I interface with everything on my computer. The more I use it, the more I feel like the differentiator is going to be both the model, and just how darn good OpenAI is at Computer Use, it really can just do it all right out of the box. So far very impressed, congrats to the whole team at OpenAI, and with unlimited usage in chat rn, I don't even have to bug @thsottiaux for resets 😅
@morganlinton
OpenAI Dot stress-tested with a hiring task

OpenAI Dot stress-tested with a hiring task

I Gave an OpenAI Dot a Hiring Task, Then Tried to Trip It Up I gave an OpenAI dot 4 fake intern applications to organize. Then I changed the priority, added 2 more, and slipped in a duplicate. Could it keep it straight? Quick context: dots are OpenAI's always-on agents. Each has its own cloud computer and can work through ChatGPT Work or Codex. The test was all fictional. Rules: organize the evidence, keep gaps visible, leave decisions to me. And it got interesting fast. Applicant two claims Python, but the project was a browser interface with no Python sample. The dot kept both facts visible and marked the evidence unknown. It did not turn a claim into proof, and an absent sample just tells you what to ask for. Changed priority to project-first: it reordered the columns, changed nobody's eligibility. Added 2 more plus a duplicate: got 6 unique applicants, not 7. Asked for an interview draft: 5 project-specific questions, left as a draft. It did not pick the applicant. I did. Honest part: one staged session, fake data, no comparison to normal chat. It organized the material. The decisions stay mine. Full breakdown: https://openai.com/index/introducing-dots/
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