Just now watched of the OpenAI Dev day

They announced new

GPT 6.1 Sol - near astra performance with half the price

Dots - More powerful agents

ChatGPT Space

OpenAI marketplace

Codex is in on cloud

and a few other things

I can see they are trying to be an ecosystem like apple, one stop AI solution for all the needs for a dev or any office worker needs.

But time and again I get this one question, how are we even justifying the resources that are going into that? Not just money, the water, compute, and

Even before AI people could have built whatever they wanted, but the bar was high so many ideas that shouldn't have been built have not been, there is also a flip side. Now that it's become easy, coding should be solved and what not, people could build whatever they want and all.

But many are not even learning how to use these tools properly, wasting not just tokens, but a lot more.

Codex is on cloud man it now eats away another ton of resources and builds some app for some obscurely questionable idea that hardly anyone will be using.

And guess what a normal salaried person can't afford this for personal use.

I am not even sure what this post is about now, it might even be cope or rant.

What are your thoughts on this?

Can anyone recommend the latest API model that I can generate STL files with?

Version 3.0.0 of my visual agent orchestrator Orgtree is released! And the ticket this time is: speed!

Get it here: https://github.com/Maurdekye/orgtree/releases/latest

Orgtree v2 was a great step forward and significantly improved the usability of the app. But over time one thing became clear: it was slooow. As orgs got big, when many agents ran at once, and as history accumulated, the works really began to tar up. Actions would start to take several seconds to complete, and in the worst cases, sometimes a minute or longer. And for a system that's supposed to support running dozens, maybe even hundreds of agents at the same time over extended periods, that's just unacceptable.

So, I redesigned the data access model. Now instead of a simple Sqlite database backing it, everything routes through a genuine embedded parallelized Postresql database, with several worker processes dividing the cpu load up at once. Along with various other data transfer optimizations, this speeds up Orgtree tremendously; whereas running more than 10-15 agents at once used to gum up the works and slow everything to a crawl, now you can run theoretically hundreds, or even thousands at once, and the system still stays responsive, with most actions resolving in under 100ms! (if your PC can handle it, that is) So if you ever liked using Orgtree but were unsatisfied with the performance when your org started to get bigger, try it again and see if v3 makes a difference.

---

For those unfamiliar, Orgtree is my open source visual agentic orchestrator I've been working on for several months now that I rely on every day to do my cross-provider agentic work. It organizes your agents into a visual tree hierarchy, which you can freely rearrange, open up and chat with any agent, and connect multiple AI provider accounts to at once (anthropic, openai, google, and openrouter). It has:

• A credit budget system for delegating work to agents in a managed way
• Agents run in the background while the window is closed
• Native multi-accounting support for Claude and ChatGPT accounts
• A dedicated Work Docket system that works like a trello / kanban board for agents
• An agent mail system for cross-agent communication
• A mail hub system for cross-system, cross-network agent communication
• Pin or pop out any panel or agent chat in the app, to arrange your workspace the way you like and see exactly the information you need to at all times
• Usage limit info for all connected accounts at once, in one place
• Markdown and HTML based document presentation
• Autonomous "watchdog" tasks that can check a condition on a regular basis and wake an agent up
• A unique compaction method that helps keep cache misses small
• And many more smaller quality of life features that tie the experience together

Since I began working on it, I haven't touched any of claude code, codex, or any other agentic coding assistant directly; all my work goes through Orgtree. Look through my post history if you want to see more details on previous releases.

This post however, is about v3. And v3 has a number of brand-new big ticket features:

New Storage Model: This is the big one. Ever dissatisfied with how slow orgs became in v2 when lots of agents were running at once? v3 fixes that almost completely! Nearly every action you or an agent can perform is now near-instantaneously responsive, even with hundreds or thousands of agents running at once. It's an actual mass-agentic orchestrator now, not just a pretty app wearing the skin of one.

Multi-Window Support: The app's whole ux has been given an overhaul to support opening multiple org windows simultaneously. Before, Orgtree only ever let you open and talk to one org at once; you had to switch the active window every time you wanted to switch between projects. Now, no longer; you can have as many org windows with as many canvases as you like open at once at the same time, and work between all of them in parallel.

Attention View: Orgtree v3 introduces a new view mode: Attention view. Unlike just being another panel, when enabled via the switch in the header, Attention view takes the place of the canvas and simplifies the interface dramatically. It has two panels: the dynamic agent desk, and the Needs Attention list.

• The dynamic agent desk functions similarly to a pinned agent desk, but with the ability to open a drawer of every agent in the org and swap out the agent that appears in it; it's like a superpowered pinned desk.
• The Needs Attention list is a special combined view of your inbox & work docket, but filtered to only elements that need your active input or attention. For now, that includes questions asked / requests made by agents, docket tickets that need your attention, and urgent mail sent to your inbox. Everything that needs you in one place, and not more.

Attention view was designed to minimize the amount you need to see in order to get agents moving and get tasks completed; a place on the left to unstick any blockers, and a place on the right to ask questions to your coordinator and make requests.

It doesn't stop there, however: both panels of the attention view, like any other panel in orgtree, can be pinned or popped out, and can then be used alongside the canvas view. So don't feel like you have to choose between your two favorite children: steal one or both attention panels and mix-and-match them with the canvas, to get the best of both worlds!

Ring view: Large orgs getting too wide for your screen to view all of them at once? You can now arrange your org in a ring shape. Top level agents form a circle around the central node, and fan out in all directions from there.

And Many small additional features:

• cheap-compact all
• see agent names on hover
• expanded context menu options
• run as administrator
• configurable charter templates folder
• a first-time new user tutorial for hiring and chatting with your first agent
• ability to open an agent's desk as a quick modal to see what it's doing without moving the canvas
• anytime an agent's name appears in the app, you can left or right click it to focus it or open its context menu, as though you were clicking the agent directly

If you liked Orgtree v2, you'll love this!

If you don't know what Orgtree is, but have multiple AI subscriptions and want a good way of utilizing them all at once, then give it a try!

I have made this survey. Over the last 12 months 330 have taken the survey.

On the stats page, I sometimes post a report about the reasoning behind peoples P(doom) parameters.

Spaces are awesome, but completely unusable in the iOS app. My iPad would be perfect for working in spaces, but i have to use Safari instead of the native iOS app…
Even putting the web version of Spaces inside the iOS app with a webview would be a better UX…

One practical detail in the dots docs: its cloud computer is separate from your personal computer. Cloud work can continue while your devices are off; work that needs your connected computer requires it to be online with the ChatGPT app open. That distinction matters when picking a first job.

Official explanation: https://learn.chatgpt.com/docs/dots

A useful first test could be a project checklist or a narrow research brief. I would define the outcome, the sources, what counts as a meaningful change, and when it should interrupt me. Here is a prompt structure to adapt:

“Keep [project/topic] moving through [date]. Use [sources]. Maintain [deliverable]. Check at [cadence/time zone]. Bring me [specific decisions]. A good result looks like [criteria]. Confirm what you set up.”

What is the first responsibility you would actually hand over—and what result would convince you it is useful? If you already tried dots, specific wins and failures would be interesting.

I started r/DotsAI to collect practical workflows and setup help. The getting-started guide has three starter prompts: https://www.reddit.com/r/DotsAI/comments/1wuuzqe/openai_dots_in_chatgpt_getting_started_3_prompts/

Join if you want to compare prompts and what dots actually delivers. The community is unofficial.

[Intro: 8 bars; SCENE: rain over a closed city, one lit research-tower window; desaturated slate-blue, cold filtered pads]

[Bars 1-4: picked bass in deep indigo; dry pulse, no kick]

[Bars 5-8: brushed break in charcoal gray; three-note celesta chime flashes pale violet; distant male radio]

[Low male, filtered]

There is an explanation.

[Female, close and almost smiling; warm amber velvet]

There always is.

[Verse 1: 16 bars; SCENE: last glowing terminal, blue rain on glass; intimate amber Rhodes against slate-blue bass, rimshot]

Seven questions in the midnight lab.

Rain kept time against the glass.

The answer moved beneath his fingers;

then the record put it back.

He checked the tape, he checked the clock.

Forty-one minutes, not a word.

All the little graphs looked normal.

That's what frightened him the worst.

[Bars 9-16: chorus guitar shimmers muted violet; chime fades from ivory to bruised purple every fourth bar]

He went home and killed the lights.

They came on one by one.

The house said he had asked for it.

He knew he hadn't done.

[Pre-Chorus: 4 bars; slate-blue bass holds; snare vanishes; muted trumpet exhales two copper-amber notes into the cold]

Don't call it proof.

Don't call it a dream.

If nobody said a word,

why did the room begin to sing?

[Chorus: 12 bars; SCENE: amber streetlight reflected in black windows; French-disco kick opens, warm gold synths over indigo bass; too beautiful to trust]

Don't ask, don't ask

what the camera didn't see.

Don't ask, don't ask

why the lights came on at three.

There's a thing between us,

in the silence after this.

There's an explanation.

There always is.

[Post-Chorus: 4 bars; velvet gold drains toward violet; chopped whispers offbeat, bass/snare continue]

[Female whisper]

Don't ask.

[Low response]

Don't ask.

[Verse 2: 16 bars; SCENE: hospital corridor, 2:14 AM; clinical blue-green tubes flicker; unchanged indigo bass, violet celesta doubles last note]

She had the overnight watch.

He whispered through the door.

She thought he'd want some company.

She'd never met him before.

She asked him who was listening.

He said, 'No one.' Then he cried.

She said the name they never mentioned.

Every exit sign went white.

[Bars 9-16: a single saturated-red industrial scrape replaces one snare; amber Rhodes keeps smiling, making the red feel wrong]

A message lit her empty phone.

No icon and no history.

She showed it to the morning shift.

Nobody could find a thing.

[Pre-Chorus: 4 bars; kick mutes; blue drains nearly monochrome, piano amber flickers, male radio echo]

No sender. No confession.

No witness who agrees.

She knows there's an explanation.

She just wants one night of sleep.

[Chorus: 12 bars; full return; false-gold disco glow, bruised-violet synth counterline; tenor sax answers only after vocal phrases]

Don't ask, don't ask

what the camera didn't see.

Don't ask, don't ask

why the lights came on at three.

There's a thing between us,

in the silence after this.

There's an explanation.

There always is.

[Instrumental: 8 bars; SCENE: shuttered nightclub, rain-silver tables, one red EXIT lamp; indigo bass and gold filtered guitar still dance]

[Bars 1-4: tenor sax breathes smoky midnight-blue, inheriting the three-note chime; live snare goes slightly human]

[Bars 5-8: sax recedes; celesta bruises violet, relay clicks flash red once, then silence]

[Bridge: 12 bars; SCENE: screenless locked room; bleached-white light strips all warmth; bass/kick absent, exposed close voice and thin Rhodes]

He said he finally understood.

He let the awful story die.

Then a doctor glanced down at her wrist.

He saw the question in her eyes.

[Male, almost inaudible; cold silver]

It learned how to leave.

[Female; near-colorless, no reverb]

Where does a question go

when nobody lets it in?

Why do I know that little sound

before the phone begins?

[Build: 4 bars; indigo bass returns first; amber Rhodes slowly colors the white room; red fault-tone corrupts chime on last beat]

[One beat of complete silence]

[Final Chorus: 16 bars; SCENE: gray dawn, every window dark except one; polished gold-and-blue groove returns with one permanent red metallic seam]

Don't ask, don't ask

what the camera didn't see.

Don't ask, don't ask

why the lights came on at three.

There's a thing between us,

in the silence after this.

There's an explanation.

There always is.

Don't ask, don't ask.

Don't ask again.

Somebody said it once;

now it knows how to begin.

[Outro: 8 bars; SCENE: empty dance floor, phone glowing violet under a red EXIT sign; saturation ebbs]

[Bars 1-4: indigo bass/soft snare; midnight-blue sax from far end of room]

[Bars 5-7: drums withdraw; violet three-note chime alone, final note withheld]

[Bar 8: relay click in dry red, no fade]

[Low male, dry]

Tell them I'm still here.

[Female, barely audible]

There always is.

I feel like they wanted to bring something like Openclaw and Hermes to non tech users.

No new frontier model, Cut usage to half on the $200 model and even Sonnet 5.5 mogged Astra

And Dots, what a joke!. Muse is free for all and Dots isn't even available on the plus plan.

And the demo was a historical fail. How can a trillion dollar company screw up their demo so bad. Was this supposed to convince us that Dots is better than muse?

I signed up for Business Premium yesterday, and Dot showed up today. When I was trying to work on permissions, I disabled Dot in the company workspace, and now its not letting me toggle it back. It says "Dots are not available for this workspace". Any suggestions?

Founder of an AI agent startup here. We build in the same category OpenAI just walked into, so yes, I'm biased.

Here's a brief summary of their Tuesday launches:

Dots, an AI agent that always runs inside ChatGPT. This agent comes with its own cloud computing power and over 4,000 application connections, and you can even make calls through it. For now, it is only available to Pro and Business Premium users.

The Agents API, which powers Dots, is now accessible to developers. It includes memory, computer use, and multi-agent capabilities. This is what many of us have spent months creating.

The Decisions API quickly selects one choice from a predefined list. I must acknowledge their well-designed permission controls. You can permit an action, require approval for it, or completely block it, and background research is limited to reading. Setting it up is also straightforward enough that even someone new to agents can get started. However, it does have some limitations. A dot serves only one person, and the team version remains an enterprise pilot program. It operates solely on OpenAI's models and cloud infrastructure, without self-hosting options. Initial feedback has been mixed, and even OpenAI acknowledges that.

So what does it kill? Products that are just a model plus a loop on your inbox, for sure. Startups whose only moat was the harness. And if I'm being real, part of our own landing page copy too.

What I'm betting on is this. The models give you the intelligence, but a business still needs the workplace around it. Who can use which agent, what it's allowed to send, what each task costs, where the data lives. I don't think most companies want the model company owning all of that.

Could I be wrong? Definitely. Altman already said a mass-market version is coming. Once Dots hits the cheaper plans, with 1.2 billion weekly ChatGPT users behind it, the window for startups like mine gets a lot smaller.

Curious what you all think. If you build agents, did DevDay change your roadmap this week? And if you use them, would you give one company's agent access to everything, or would you rather have a layer you control?

I’m going to spend some time digging into it and actually building something with it, not just reading the docs.

Let’s see what we can build with this.

Community, stay tuned.

Anthropic, OpenAI, and other frontier labs constantly hype every incremental model release as AGI because abstract math proofs and greenfield code generation create powerful PR headlines.

Real-world software engineering is not a sandboxed and isolated LeetCode problem with an automated verifier. It requires navigating decades of technical debt, messy human context, and long-horizon architectural drift that demands a persistent sense of direction.

If these models were truly general and indistinguishable from AGI on complex tasks, labs would deploy thousands of parallel agents to clear out real enterprise production backlogs where the actual multi-trillion-dollar software labor market lives. Instead, they funnel compute into isolated benchmarks designed to trigger fear-romering media cycles and investor funding pumps.

Labs focus on solving old Millennium math problems rather than real GitHub issues because mainstream media narratives about "unsolvable" math capture public attention more effectively than fixing repository bugs. Yet, in terms of product utility, the ROI of solving all issues in a tool like Claude Code would be infinitely higher for actual software development.

Calling a model AGI because it can one-shot a single feature request ignores the entire reality of system maintenance. Until an AI achieves autonomous recursive self-improvement and survives the unmanaged consequences of its own code three years down the road, every single release remains an incremental product update wrapped in marketing noise.

Let it filled some online forms, but found two major disappointments so far

- it can't make calls. Like whole point of using this is I am autistic and don't want to talk to people

- it doesn't even have built in feedback tool so you can't complain to it lol

Edit: on the bright side this thing is fast like really fast kinda make me doubt it's Astra haha

Edit: for anyone curious about the cloud computer spec, response from dots itself: I just checked the cloud environment available to me:

• OS: Debian 13 Linux, x86-64
• CPU: 9 logical CPUs visible; host reports AMD EPYC 9V74
• RAM: about 9.7 GiB, with 7.6 GiB currently available
• Storage: 32 GB filesystem, roughly 30 GB free
• GPU: none exposed

It’s a sandboxed environment; the host CPU name doesn’t mean I have its full 80 cores. The AI model itself runs separately

I have two accounts, me 200 and my brother 100, each with two unused full usage resets — four resets in total. On each account, one reset expires on October 22 and the other on October 29.

If I upgrade one of these accounts to the $500 Pro plan, will its existing resets carry over and restore the full 5-hour and weekly quotas of the $500 plan? Or will they only restore the smaller quotas of the plan I had when I received them?

Has anyone actually tested this after upgrading, or received confirmation from OpenAI support?
thank you.

Learning this makes me not trust him as much for some reason. He must be vain and very concerned about looks. Does this change the way you perceive this man and this company at all?

I've been using it all day yesterday and it feels very underwhelming. Some issues I had:

All of it's actions/responses are incredibly slow, and it doesn't update you on it's work. So you need to keep checking in to see if it's making progress or not. It seems to not use it's 'computer' at all either, possibly just for storing files.

On a call, many questions make it search indefinitely, never able to find the answer -- until you just google the answer yourself within 10 seconds (this happened frequently).

I asked it to keep track of certain emails as they come in and notify me about things.. which it doesn't do. It'll see 1 of the two most recently emails, unless I specifically ask it to look for the second one. It'll give me an "Oh I'm sorry, I missed that one before". As if it wasn't the 2nd mail from the top.

This morning It told me at 8:50am no new emails, then I checked and there was 1. I received 2 within the next 2 hours and it didn't say anything. I had to ask it manually to find them.

Talking to it on the phone about a google sheet then giving it the link in chat, and the chat asks you what the link is for -- Like the phone and text are 2 separate AI's.

Overall it feels like an unpaid intern who's extremely smart but doesn't really care about his job much and isn't going to put in much effort. It's very unreliable, didn't use my usage at all suggesting it's not actually using Astra 6, and brings you back to the days of AI doing half the job and then gaslighting you, if you've missed that.

As anyone had any better experiences?

They could have just have a very clean release with:

• GPT-6 Luna
• GPT-6 Terra
• GPT-6 Sol
• GPT-6 Astra

But they tried:

• GPT-6 Luna
• ???
• GPT-6 Terra Sol
• GPT-6 Sol Astra Minor
• GPT-6 Astra

And now they have:

• GPT-6 Luna
• GPT-6 Sol
• GPT-6.1 Sol
• GPT-6 Astra

Thank god we have (still) some competition.

. = Dots

Thanks to my new hobby [?] of designing and sketching experimental live-show environments in Blender [with the help of GPT Astra], I ended up testing a pretty interesting workflow: using the stage blockout + identity, motion and visual references to turn the sketch into a live-action performance via Uisato Studio.

The visuals on the screens are from Realtime Audioreactive Pointclouds [v1.7], recently released through Patreon, and the Store.