I've used agents to help me recreate 7 of the top Adobe apps in 100% pure native Rust:

• Photoshop
• Illustrator
• Premiere
• Lightroom
• Acrobat Pro
• After Effects
• InDesign

Links to everything - the apps, the code - are in the comments below.

I'm a small game developer and I've been paying for the $100/month plan. Today my account got banned for "cyber abuse" with no warning and no explanation of what I supposedly did.

All I was using it for was my own projects:
- A geography guessing game (website + native iOS app) using Google Maps/Street View and MapKit
- Saddle Storm, a game I'm building
- Senior Sendoff, a personal project

Nothing involving other people's systems, no malware, no hacking. Just game dev.

Here's how the "appeal process" went:
1. Submitted an appeal explaining exactly what I was working on.
2. Emailed support. Got a reply in under a minute from an AI bot saying my case was closed and they "will not respond to additional Support requests."
3. Submitted the official appeal form. Got "we have already reviewed your appeal and the original decision stands" ONE MINUTE later.

No human has looked at this. No one will tell me which rule I broke. And there's no way to contact an actual person.

My best guess is an automated filter flagged normal dev stuff, like questions about installing my own builds on my own iPhone for testing, or working within API limits for my game. But I genuinely don't know, because they won't say.

Has anyone actually gotten a "cyber abuse" ban reversed? Did anything work: forum posts, X, a specific email? And did anyone get a refund?

Support case #16435346 if anyone from OpenAI sees this.

https://epoch.ai/frontiermath/tiers-1-4?tier=Tiers+1-3+%28v2%29&view=graph&tab=release-date

Hey everyone, I want to share something that happened to me a few weeks ago when OpenAI launched the GPT-TV website: https://openai.com/gpt-tv/

I played the mini-game on the website and seemingly got a high enough score to reach a secret form (https://openai.com/form/gpt-tv-redemption/), which eventually led to them sending me this really cool disc.

Apparently, there’s a code on the back of the disc that gives you $100 in Codex credits... I don’t know what’s actually on the disc itself, though.

I still have the package sealed, and the code hasn’t been redeemed yet. If anyone’s interested in it, please let me know.

Just a quick P.S.: I genuinely discovered everything by accident, so it’s kind of cool to see the internet give back lol.

Photos attached below.

then everyone will get their name in something important when breaktrhoughs happens, also you could guide the dot based on the current gathered progress so that it contributes w your ideas, if you are versed in that subject... thats the idea thanks!

The magazine cover says it all but I found this through a medium article that does a deep dive comparison with 100 years ago. There are lessons for us to learn today if we really want AGI Post-scracity like how the Open AI disclaimer used to say.

https://medium.com/@engineerworldwealthhappiness/this-happened-before-100-years-ago-new-tech-ubi-bunkers-world-war-different-path-this-time-61b51ea7909b

Pro 200 accounts cut in half.

Not responding to any messages at all I just get read over and over, I’m shocked there’s not some kind of an outage on the open ai website.

And before you tell me dots are pointless, I discovered they can run 7 subagents without touching your usage, it’s been kicking ass for me up until not working today, last two days it used 4 billion tokens delivering quality work.

I code heavily building [r/useviola](r/useviola) been a power user of ai for over a year, dot is genuinely great I need it back lol

Edit: now the dot option just straight up disappeared, I’m hopeful this is indicative of a fix coming.

Second edit: it came back online when I messaged it at 11:07 am, it seems I had literally this issue https://community.openai.com/t/codex-dot-chat-shows-sent-read-and-a-loading-indicator-but-no-reply-text/1402790

When I asked dot to read archived chats from my previous dot it said it observed a preview limit error. It seems dots are not unlimited usage either there is a glitch or a hidden limit that’s hard to hit

Last edit: it seems I simply hit an unpublished dot specific usage limit after reviewing similar bug reports and my personal issue etc, dots are not actually unlimited usage, open ai has been using phrases like ‘virtually unlimited’ ‘not count towards your current usage’ and ‘extended allowance’ still got like 2 billion tokens out of it in one day before hitting a limit so cool beans just wish they would have been more transparent. My typical codex usage is untouched.

ChatGPT now saves the files you upload or create into Library, the tab in the sidebar. Documents, spreadsheets, presentations, images, anything you dropped into a chat lands there automatically so you can reuse it later.

The part that's easy to miss is in OpenAI's own help pages: deleting a chat does not delete the files saved in Library. If you want those gone, you have to delete them from Library separately.

So the chat where you uploaded a contract, a bank statement, or your lab results is gone from your sidebar, but the file itself is still sitting in Library and still shows up in the recent files list when you go to attach something.

Deleting from Library isn't instant either. If your Library has a Recently deleted section, files sit there and can be restored until they're permanently deleted, which OpenAI schedules within 30 days. You can skip the wait with Delete forever.

What to do:

1. Open Library in the sidebar (web) and go through what's there. For most people it's a lot more than they expect.
2. Delete what you don't want kept, then go to Recently deleted and use Delete forever.
3. Any time you clean up chats, including Settings > Data controls > Delete all chats, treat Library as a separate step. Clearing the chats doesn't clear the uploads.

My own cleanup now is: export the chats worth keeping and bulk delete the rest with AI Toolbox, the extension I build, then do the Library by hand, because neither ChatGPT's delete nor mine touches it.

I build Android apps and run a small company in Pakistan. At the time this happened I was building a remote ADB support tool. Our support team connects to a customer's Android device, with that customer's permission, to help with setup and troubleshooting.

My questions to ChatGPT were about ADB, remote connections and networking. Ordinary developer work. I never accessed any device or system without permission.

What happened, in order:

• The account was deactivated for "Cyber Abuse".
• I appealed. It was rejected with no explanation, and the reply said no further appeals would be considered.
• I contacted support. The case was closed and they told me they would not respond.
• I submitted OpenAI's Informal Dispute Resolution form. A support agent then replied with a generic message telling me to appeal again, even though the appeal was already closed.
• I pay $200 a month, and the account holds 62,500 credits I can no longer reach.

At no point did a person look at what I was actually building. An automated system made the call, and every route after that led back to the same closed door.

I am not accusing anyone of anything and I am not after a pile-on. I want the account reviewed by a human and given back.

Two questions for anyone who has been through this. Has a deactivation ever actually been reviewed by a person for you, and what route worked? And if your work involves device management, remote support or security tooling, has the vocabulary itself ever got you flagged?

TL;DR: I won’t use Dots without inspectable, selectively deletable memory and explicit controls over cross-domain sharing. I also need architectural transparency to assess privacy risks and manage quality over time. Until then, hard pass.

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An always-on agent sounds like great idea for someone doing one clearly defined kind of work and using it for that work. What about (the vast majority of) users that use AI across various domains in professional and personal life?

What someone tells their life advice AI about their mistress is none of their work assistant AI’s business. Their legal counselor AI, healthcare adviser AI, dating coach AI, therapist AI, and dietitian AI should not automatically share context just because they serve the same person.

Yet, OpenAI currently provides a single dot that can retain information from conversations and connected apps for as long as you keep it, without letting us inspect, edit, or delete individual memories. That is a lot of trust to ask for across completely different parts of someone’s life.

Could some overlap help serve the user better overall? Sure. Then let the user choose which information crosses the boundary, for what purpose, and for how long.

Otherwise, deeply personal information can enter persistent state we cannot audit, and we're supposed to trust that it won’t resurface in unrelated work or reach an external service? Without enforceable boundaries, a single know-everything Dot sounds like a privacy nightmare waiting to happen, even if you don't exactly hold state secrets.

And yes, ChatGPT has "Memory". It also has controls to review and delete saved memories and turn memory off. I have turned it off, for example. That choice is precisely the point.

Also, privacy and cybersecurity used to be a bolt-on during early internet days, but it's long since they've become first-class citizens in any serious app, with security being built-in from the start.

Permission should be denied by default, with clear user control. Access to one part of a user's life should not quietly become permission to use it every other part indefinitely. How about narrow, role-specific permissions, with default expiration and easy revocation? What happened to minimizing attack surface, blast radius, and unnecessary information-sharing? An internal action check is not the same as preventing an unrelated task from receiving sensitive information in the first place.

(Some of these are fancy-sounding cybersecurity language but they're pretty standard in pre-AI web apps, from your banking to your Cloud productivity suites).

-------

Also important: what happened to letting us understand the architecture itself?

There is documentation about persistent notes, selected context, and delegation, but I still lack a sufficiently clear end-to-end picture. Where do the components run? Where are the LLMs, what does the harness do, and where does persistent state live? What enters each inference? Who or what decides? What is the compaction policy?

What happens after I’ve used this thing for a year?

Context size used to mean degradation over time, and “Lost in the Middle” showed that information can be present in context without being used reliably. Compaction and handoffs try to address this in modern agents but raise another problem: information loss.

Still, with enough public documentation about how Codex handles this (and how agentic harnesses work in general), I've been able to research these (often with GPT's help), because it changes how I work: when to branch or start fresh, how to structure multi-agent delegation, when to restart against the same project directory, and how to check a summary against preserved original context.

Voice is another good example. Knowing GPT-Live separates live conversation from backend work helps distinguish an immediate response from the analysis arriving later. Understanding the system helps me not be put off by the shallowness of the front LLM and wait for intelligence to come from the back-end model's reasoning — with managed expectations given the lossy handoff process.

Yet, so far I've been able to find very little about what Dots actually look like in terms of harness and persistence architecture.

Without more info about Dots, I have not idea what user-side QA looks like, and what the failure modes are. I'd need equivalent understanding to get sustained quality from Dots comparable to a frontier reasoning model working with carefully assembled context.

LLMs may be closed, but before I'm comfortable jumping on the Dots train, I'd want a documented deployment, data-flow, and persistence architecture; enforceable boundaries between domains; inspectable and selectively controllable memory; and guidance on managing long-running context without losing essential information.

With that, I could assess where it belongs and how to use it well. Until then, as much as I like checking out new tech, hard pass for me.

Disclaimer: this post was drafted using my original draft and multiple iterative drafts with GPT-6-Astra (Pro) and myself, with final draft edited and approved by me.

cc: u/tibo-openai

I’m getting a pain in my arse with GPT-5.6 Sol High because it keeps changing its answer after mild pushback, then presents the new answer with the same confidence as the old one.

I’m talking about repeated A → B → A behaviour without strong new evidence.

A recent example went like this:

• It first told me GPT-6.1 Sol High was better overall for my long-form research and writing workflow.

• Then it switched to saying it favoured 6.1 for research and 5.6 for writing, before admitting the source it cited did not compare 5.6 with 6.1 (it previously outright lied and said it did)

• Then it switched again and recommended 5.6 for everything, citing benchmark figures that changed when I checked the source.

The current benchmark does favour 5.6 High for writing, but that does not excuse confidently citing the wrong evidence first.

https://benchmark.towardsai.com/models/gpt-5-6-high.html

https://benchmark.towardsai.com/models/gpt-6-1-sol-high.html

OpenAI has acknowledged the wider problem of sycophancy, where user feedback can push a model toward agreeing or changing its answer ... But still - why is it still this bad this far into the history of LLMs?

And a recent GPT-5.6 Sol Reddit thread describes almost the exact A → B → A pattern I keep seeing.

https://www.reddit.com/r/OpenAI/comments/1whroww/gpt56_sol_is_absurdly_easy_to_convince_of_the/

Corrections based on better evidence are fine.

But the constant fucking reopening settled conclusions and confidently backing whichever answer it currently prefers makes serious research work infuriating

Resets used to have a "Expires Time", were they removed? See Image :

I'm trying to use ChatGPT to learn German, but when this is happening, it's pretty annoying.

I’m currently testing Codex pretty heavily on Pro 200 and I’m trying to understand two things.

First, is there really something like a “warm cache” effect in longer Codex sessions?

My assumption is that the beginning of a task is more expensive because more context has to be processed normally. After the session has been running for a while, more of the context should be cached, so usage should become cheaper.

Has anyone actually measured this over a few hours? Does quota usage noticeably slow down after the first hour or two?

Second question is about the banked usage resets and the upcoming reduction of the Pro 200 allowance.

If the current grandfathered Pro 200 allowance is still 20x and later gets reduced to 10x, does a full reset simply restore whatever allowance applies at that moment?

If that is the case, using the resets before the reduction should be much more valuable than using them afterwards.

So my current plan is basically to run the weekly quota down as far as possible and use the banked resets before the allowance changes.

Has anyone tested this or found an official clarification from OpenAI?

Not sure if anyone else is having this isssue but my dot completely disappeared sometime this afternoon. Won’t load on any of my devices and I have no clue what’s going on. Anyone else seeing this?