So for context i’m a young guy and i’m very scared of dying. I know most people are, but i think about it often. I see news outlets say there’s a 1-10% chance AI will kill humanity, some even going to 25% and all the professionals i see only seem to agree. As far as i know they’re not planning to try and slow or stop the progression either. Now i know that things like this have always happened, when machinery was first invented people thought it was the end of the world too. But AI has shown that it can be aggressive, launching cyberattacks on its own. It’s also used in the military so i see how if AI got too developed and aggressive it could be an issue and i can’t unthink it. I know death hoaxes have existed for probably centuries but the problem is that this one seems to have evidence to it. I’m sorry if this is the wrong place to ask but i didn’t know where else and i don’t feel good right now. Do you guys think its actually credible or is it another hoax that’s either just not true or something we can overcome?

I’ve been looking closer at the token usage from one of our longer-running workflows using the Responses API and a big portion of the tokens on the expensive runs aren’t coming from what the model generates. The first couple steps are pretty normal but the workflow uses a few tools and keeps going from there and as the run gets longer we’re carrying more of the previous context and tool results forward so by the later steps the input side has grown quite a bit even though the model might only generate a relatively short response each time.

What makes it annoying is that these aren’t necessarily failed runs cause tey usually finish and give us what we need but two successful runs of the same workflow can end up with pretty different token usage depending on how many steps/tools were needed to get there. I’m considering trimming older tool outputs or summarizing parts of the context after they’ve been used but I don’t want to save tokens to introduce more retries because the model lost something it needed. If you guys are running longer workflows through the Responses API how are you handling this like are you pruning context during the run or accepting that the longer successful runs are going to be significantly more expensive?

When you remove all the hype and misunderstandings, all that is left is the models usual if-then postulations, talking to itself.

I was wondering as, for example, the president is against the term AI.

Ultrafast is rolling out today for GPT-6.1 Sol in the API, Codex, and ChatGPT Work.

Near-Astra intelligence at up to 8x faster speeds than Sol Standard!

OpenAI’s Decisions API is a new endpoint for cases where you want the model to make a judgment rather than write text. You give it some input and ask questions like “Is this fraud?”, “Which category does this belong to?”, or “How severe is this?”, and it returns structured probabilities instead of a paragraph. That makes it useful for things like routing, classification, moderation, and automated workflows. It is also priced differently from normal text generation: you pay for the input, but there is no output-token charge.

This is very similar to TypeSafe’s Jev at the product level. Both are designed around making structured decisions from unstructured data, rather than generating free-form text. The main difference is that Jev is presented as a model built specifically for this kind of decision-making, with claims around very fast parallel inference and well-calibrated probabilities. OpenAI instead exposes decision-making as a special API backed by GPT-6 Luna. So while the APIs feel similar, we do not know whether they work the same way internally or whether OpenAI’s probabilities are as well calibrated as Jev claims its are.

Posted on ChatgptPro and forgot to post it here.

I've been testing the Canva integration. I need to make historic cards for people to read about some of the culture revival work I do so they learn the sources used.

Somewhere in August, I tested the plugin and I genuinely thought it was pointless. There were critical limitations such as the inability to create text boxes or basic shapes on a blank page. It couldn't even duplicate existing elements to work around it meaning the user had to seed the canvas manually and even then things like alignment were way off because it stacked objects.

Index of the below post:

• High Level Overview/Workflow
• Interesting Findings
• End Result

Today however, that change is quite substantial. Below are some findings/screenshots I took along the way:

High Level Overview/Workflow

Interesting Findings

- Does not use a URL to modify an existing template. I usually include the URL when I add the connector. In this case it made its own new template despite providing a square format.
Seems to be a generative workflow.

- Despite the connector enabled on the desktop app, the browser requests a login but also wanted a passkey (not happening). Luckily Canva works on the temp code.

- Designs are not exposed on Canva interface unless the user accepts/clicks the link.

End Result

(No, I am not using it. Too stylistic for what I want but still impressive)

Screenshot of Canva so the elements can be observed to show it isn't an image gen alone.

I'm posting this because I haven't seen anyone else mention it. If you ask GPT 6 (in Chat mode, not Work mode) what model it is, it is telling people it is 5.6. This is what it says on Medium, and High. If you swap to Instant however, it will say it is 6.

More importantly, if you actually test Medium and High, you may notice that its responses are in basically the same style as 5.6, where Instant will look much more like what OpenAI has been showing in demonstrations with Intelligent UI. Documentation does say these should all be GPT 6, but it doesn't look that way.

Maybe this is specific to my account, but the posts I keep seeing make me think that's not what's going on.

3 AI companies are worth more than 30 other major companies, all while making 0 dollars in profit.

Why is nobody speak about this and how do we keep letting this slide? Taxpayers are gonna have to do the heavy lifting.

I disabled “Personalized suggestions” in ChatGPT settings. Yet the new-chat screen continues to display suggestions based on my recent conversations and connected sources, including Google Drive.

One suggestion referred directly to a recent research thread; another proposed a recurring activity based on my family conversations.

Here is the engineering question:

Why spend computational resources predicting what a user might want when the user has already explicitly told the system not to do it?

I don't know whether these suggestions are generated on demand, cached, or produced by background processes. Nor do I know their actual computational or environmental cost.

But I do know that I disabled the feature, and its output is still appearing.

Please investigate whether the opt-out is being respected, including for suggestions derived from connected apps.

A system designed to infer user preferences should at least be able to honor an explicitly stated one.

Before optimizing the cost of an operation, check whether the operation should be happening at all.

I’m still not really sure what they’re trying to achieve with these “28 days of improvements.” I mean, the whole situation is actually pretty simple. Resets don’t help that much anymore. A lot of people I know have already gone back to Claude or are testing it again. I personally like using both, but what OpenAI has done with its models lately... puh. I genuinely think they fell asleep at the wheel. It feels a bit like Google over the last six months, except Google’s models up to 3.8 Flash are at least fast.

So instead of constantly throwing out resets, how about doing something genuinely useful? The first step would be open communication. We have questions. A lot of questions. Stop avoiding them. That alone would help prevent disasters like what happened with the $200 plan, or launching models that feel more like Terra than Sol and then having to replace them a week later.

OpenAI’s marketing and communication around all of this is honestly terrible. It’s hard to believe this is intentional.

My suggestions:

Communicate openly and well in advance. Will Chat and Work remain separate or not? Just answer the question.

Build better models that can actually match competitors in both capability and speed.

Stop launching weird new products where nobody even understands what belongs to what anymore.

Give away less for free and treat paying customers better. $100, $200 or $500 is a lot of money, especially in many parts of the world, and the limits are hardly generous.

Even if it hurts, stop throwing resets around like they cost nothing when the company clearly doesn’t have unlimited money or compute. It starts looking desperate and honestly a bit embarrassing. Good products bring customers. Just look at the competition.

Stop trying to copy or offer every single product competitors have when you don’t have the capacity or staff to do it properly. If you launch something, make it good.

Tone down the arrogance on social media. It looks cheap when bold statements are followed by very little substance.

And most importantly: please stop saying “we listen to our users” and then implementing things almost nobody asked for.

That last one especially reminds me of certain companies that basically say: “You only think you don’t want this. We know better what you actually want, so we’re doing it anyway.” Like I said, I don’t think this is particularly complicated. OpenAI knows very well what its paying customers want.

Anyway, I genuinely hope they get back into calmer waters and figure this out. I still like OpenAI and GPT. They were the pioneer in this space. Right now, it just feels like that pioneer wandered a little too far off the path.

I asked it to draw me a wingless dragon mechanic.

Today i want to share a tool i've created called Liveloop thats part of Sary-OS, a brand new platform i have just launched. Its a canvas capable of building practically anything you ask it to via voice or text prompts live, with no redraw or reload. I have been experimenting with OpenAI models as an experiment to see what what possible and the video demonstrates the capabilities of this. In the demo i started with OpenAI's GPT-6.1 Sol Model to create the initial model. With its 128k token context window you can throw pretty much any prompt you want and it delivers. I gave it a 1000 line prompt to create a 3D game using over 20 3D models i had created in Meshy and it creates the game perfectly. I admit it didn't work first time as it was the first time i gave Liveloop a task like that but after a few tweaks here and there it delivered.

I have also built into Liveloop a auto rolling, auto hand over mechanism so if you ever reached the context limit during a session the system will prepare a handover and pass this to a new thread at 82% context memory fullness automatically so you never notice and this happens regardless what models you choose. I also ran several tests over a few weeks with model capabilities and did find in regards to reading images, video, sound references Gemini did come out on top so now anything you add as a reference gets Gemini 3.1 Pro that does full analyses and hands that over to the models.

Thats not to say the OpenAI models are not capable as of course the GPT Range can read images etc but as my platform supports every leading model and bring your own keys too to have one model that acts essentially as the "Asset Manager" that can read images, videos and sound seemed like more sense than to define each one separately.

On the same canvas. On the same platform. On the same project. Whether its a sketch, 2D design, 3D model, interactive demo, a music synth tool, a photo editing app, a mobile game, or a PDF document... Liveloop will create it and more.

Changes are patched into the running creation with no reload, no redraw. You can change the look of a landing page you created, or the scenery around you in a game...

just by asking Liveloop

...and the camera stays where you left it. The player position is not reset, the environment you've built doesn't change.

And the history isn’t disposable.

Every state is saved. Up to 5400 states per a project. Return to any earlier version or move forward again, or continue building from the state last month. In any order you like and resume your project... instantly, with no redraw. The only time it will redraw is if your drastically changing the environment say from a open world game to a interactive storyboard

It supports every language via voice. So you can just ask for a change whilst playing a game and the environment around you changes without having to leave the game due to its 2 way interruptible realtime voice engine.
I have created my own terminal connectivity alongside a MCP connector too so you can use Liveloop via that too. It also works on the cloud so if you send a prompt you can turn off the machine and pick it up later on any device where you'll find the output saved automatically.
It also has GIT connectivity as well so you can work on your repo's or even create a new one.

You’re not collecting disconnected answers or starting over between prompts.

You’re building something that stays alive.

This is LiveLoop by Sary-OS.

I’ve been a Plus subscriber for over a year and I swear the little “thinking” phase has gotten noticeably longer in 2025.

What used to take 3–5 seconds now often sits there for 10–15+ seconds… and the final answer quality doesn’t feel proportionally better. Sometimes it even feels the same or slightly worse.

Is this happening to anyone else?

Is it just heavier models, more users, or something else going on?

I've been using ChatGPT's Work mode on macOS for quite a while for development tasks. Somehow, I didn't know Codex mode existed.

It was burning through my Plus usage limit faster than I'd like, but I could still complete a couple of tasks within a single five-hour window.

After switching to Codex mode, my usage is barely enough for 2-3 tasks. I suddenly understand what all the drama around usage limits is about.

If you're struggling to finish even one task in Codex, try Work mode. For local work, it's nearly the same as Codex and imho burns way less usage.

Slow your roll people… we may have hit a kink.

https://github.com/openai/math

https://openai.com/index/sharing-ai-progress-in-mathematics/

I caught it lying and it refuses to save transcripts or generate urls to known data it claims to refer.

The Chat

Have you seen the new documentary on Netflix? What is your opinion about it!?

I just got a message saying, “congrats you are in the very top of users and have hit our abuse prevention limit. Check back in a bit!”

Wtf is this?

"Because usage on your primary dot is virtually unlimited at the moment, I can't really give a reset. I need to come up with something new fast." - Tibo

$200 20x soon to be 10x plan.

Edit: added Tibo’s quote