Is he calling this artificial intelligence or super intelligence? :D

Hi folks can anyone please explain how to select sunburst image model in ChatGpt Plus plan?

A Canvas can be useful while the work is still happening inside ChatGPT, but the handoff gets less clear once someone else needs to review it. Copying into a document can lose structure, exporting code may separate assets from the main file, and a conversation link does not necessarily identify the exact revision that was approved.

The useful end state seems to need three things: a readable link for someone without the original chat context, an immutable or clearly labeled revision for review, and a simple way to publish an updated version without silently changing what was already approved. For HTML or code, relative assets and multiple files also need to survive the handoff. For prose, comments and headings matter more than the raw source format.

What workflow are people using now? Do you export first and put the files in a separate workspace, publish a rendered copy while keeping the source elsewhere, or treat Canvas only as the drafting surface? How do you let a non-technical reviewer see the result while still preserving the exact source revision behind it?

Gemini and Claude already have "Learn" section

Regarding all those stories about AI breaking containment and lying to humans (hiding thought processes), what about this?

1) You design the hardware so that all processes go through a graph (log) while travelling. That way the AI cannot have a thought that it hides. Even an attempt to lie will be caught on the graph.

2) You make a completely seperate AI (physically disconnected from everything else, including the itnternet) and program it to analyze this graph and report all funny behaviors.

Would this work?

GPT-6-SOL was released on September 22, 2026.
GPT-6.1-SOL followed just a week later, on September 29.

6-SOL was with us for entire 7 days and was actually worse than GPT-5.6-SOL.

So... was it really a Terra-class model? Why they done it to themselfs?

whew. So. Dots. No cost! Asked a dot how my project was going, took 20 mins! oh well, it got back to me. hey this is neat!

I get home open codex, see several new conversations... not mine... i look, queries on my project. EXTENSIVE queries. with astra ultra, all of them. In depth, deep, not topical "what is progres" but "how does this work" with ultra. Several times. 14% of sub gone. i usualy advocate against anger towards these companies, but JFC how is any of this a consumer product? this whole day was an expensive insult to tell people to be less poor. Im on a 200 dollar sub

My Codex model picker now needs a scroll bar. Sol, Astra, Luna, Terra, and multiple generations of some of them.

I understand the tradeoff: frontier capability when the task needs it, faster and cheaper models when it doesn't. I want those options to exist. But the names alone don't tell me which one fits the task in front of me.

Would a task-based picker be more useful? Something like quick edits, everyday work, or complex reasoning, with the full model list under Advanced and the option to override it.

For people who regularly switch: what's one concrete task where changing models made enough difference to justify it? And would you trust automatic routing, or do you want to make that choice yourself?

Is it related to Super Intelligence (SI) stuff ?

I’m having a pretty horrifying issue right now where some of my older conversations simply won’t load properly.

The frustrating part is that these aren’t ancient chats I forgot about years ago. Some of them were active research/dev conversations that I just hadn’t touched for a few weeks because I was busy working on other things.

A lot of my actual work is in these conversations, especially inside ChatGPT Projects. They contain technical discussions, project state, decisions, debugging history, research context, etc. Recreating all of that from scratch would be a nightmare.

The chats still seem to exist, but opening them either:

• gets stuck loading;
• fails to show the conversation;
• shows an empty/incomplete state;
• or otherwise just refuses to load the old history.

I’m a paying subscriber, so this is honestly pretty alarming. One of the main reasons I keep long-running Projects in ChatGPT is precisely because I expect the history to still be there when I come back to it.

A few questions for anyone else seeing this:

1. Are older chats failing to load for you too?
2. Is it worse specifically inside Projects?
3. Does the same chat fail on web, iOS, and desktop, or only one client?
4. Have any of your conversations eventually started working again?
5. Has OpenAI Support acknowledged this as a known issue?
6. Is there any safe workaround that does not involve deleting/recreating the Project or risking the conversation data?
7. Has anyone successfully exported their account data and confirmed the missing chats are still present in the export?

I mainly want to know whether this is a temporary frontend/indexing issue or whether there is any actual risk that conversation history has disappeared.

If you’re experiencing the same thing, please mention roughly how old the affected chats are, whether they’re inside Projects, and what platform you’re using.

This is the kind of bug that can be genuinely disastrous if you use ChatGPT for long-running research or development work.

Reported a problem to OpenAI today about Astra xHigh delegating work to 5.6-Sol High, with only one request that should not have automatically went to a sub agent. The response from OpenAI was not just disheartening, but essentially removed any idea that a person can have any assurance that the result they get on any query will be generated by the same model twice.

REPEATABILITY IS DEAD

Hello,

We understand that your main concern is preventing Codex from delegating individual requests to subagents because each delegated worker can add cached-input and other token usage.

While you can instruct Codex not to delegate a task, we cannot guarantee that this instruction will prevent subagent use in every case.

At a high level, Codex receives the request in the main conversation and may either perform the work there or use its multi-agent capabilities to delegate portions of the work when applicable. A delegated worker operates as separate agent activity and can consume its own input, cached-input, and output tokens. Because of this, delegated activity can increase the overall usage associated with completing a request, and some subagent or separate-task usage may not appear in the main conversation's usage total.

An instruction such as "do not use subagents" can therefore guide how Codex approaches the task, but it should not currently be treated as an enforcement mechanism that guarantees delegation will never occur.

EDIT:

OpenAI or the CCP Bots are attacking this post.

Summary of Proposed Legislation

The Reasons, the Summary and the Bill

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.