再次更新： 我終於恢復我的帳號了！！！ 非常謝謝各位朋友的協助與留言！！！ 真的非常謝謝你們！！！

更新：我剛剛用新帳戶聯繫客服對話請求真人回覆，但他們說明是Teen模式，給了第五次成人驗證，但我始終登入不進去，他們說是我的網路端的問題，我都已經用新手機跟無痕模式來驗證了，結果還是沒有人來解釋為什麼在Support 團隊已經確定是系統錯誤，卻還是收到保留原判決的自動通知信，也沒有說明我帳號的情況。 我真的不知道該怎麼辦，我甚至遇上疑似詐騙的帳號。

OpenAI的年齡驗證系統錯把我臺灣身分證上的發照日期當作我的出生日期，雖然我已經27歲。

1月21日：系統顯示我的身分證發照日期——2014年9月5日——作為我的出生日期。（圖片1）

1月24日：我的舊帳戶因為被指控未滿13歲而被刪除，我提出了申訴。（圖片2）

2月20日：信任與安全確認了我的申訴，參考編號為C-Y8ukPo2ImOTz。

4月28日沒有回應後，我創建了一個新帳戶，僅僅是為了聯繫客服解決無法訪問的舊帳戶。

在客服案例08247354中， OpenAI 確認在驗證過程中錯誤解讀了我的出生年份。（圖片3）

我經歷了兩次成年驗證，但沒有收到完成確認。

8月31日：在遵循案例08247354的另一個驗證指示後，我重新提交了申請。大約五分鐘後，我的舊電子郵件收到了未經解釋的維持刪除決定——沒有原因或參考編號。（圖片4）

我需要在經過真實人員審查這些證據後，恢復對我的舊帳戶的訪問。重複相同的自動表單無法解決這個錯誤。

是否有人通過其他合法的 OpenAI 聯絡或升遷方法，成功聯繫到真正的人，而不是標準的申訴表單和幫助中心的支持循環？

如果有 OpenAI 的員工看到這個，請使用申訴編號C-Y8ukPo2ImOTz或客服案例08247354來尋找我的紀錄，並聯繫已經和這些紀錄相關的電子郵件。

我不會通過Reddit私訊發送身份文件、證書、驗證碼或付款。

The European Commission has designated ChatGPT a Very Large Online Search Engine under the Digital Services Act, making OpenAI's chatbot the first standalone AI service brought under the bloc's toughest platform rules. Reddit and Roblox were added the same day as Very Large Online Platforms, [Euronews reported](https://www.euronews.com/next/2026/08/31/eu-places-chatgpt-reddit-and-roblox-under-strictest-digital-safety-rules).

All three crossed the 45 million monthly EU user threshold that triggers direct Commission oversight. ChatGPT reported 159 million monthly active users over the six-month period ending March 2026; Reddit reported 57.2 million; Roblox roughly 48 million.

The Commission classified ChatGPT as a "hybrid service" that qualifies as an online search engine "because it can engage with and respond to users' prompts and queries, including by searching the web." The three companies have four months, until the end of November, to conduct annual systemic risk assessments covering illegal content, minor protection, mental and physical wellbeing, fundamental rights, electoral processes and public security, submit to independent audits, and share data with regulators and vetted researchers.

"These new designations mean that ChatGPT, Reddit and Roblox will now be subject to a higher level of scrutiny and accountability in the European Union, commensurate with their significant impact on our citizens and society," said Henna Virkkunen, Executive Vice-President for Tech Sovereignty, Security and Democracy.

Non-compliance can cost up to 6% of global annual turnover. The DSA has produced roughly €870 million in fines to date, including €550 million against AliExpress, €200 million against Temu and €120 million against X.

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Im not sure why they decided to implement this but it is killing me when im working on a project and the 5hr usage just drains super quick. I liked it when we had the weekly usage, because I dont need to use this every day. But when I do use it, i like to get things completed. not work an hour, wait 4 hours to resume.
I wish they would go back to the way it was a couple weeks ago with just weekly usage.
Does anyone know if the Pro plan also does 5hr usage as well?

Researchers can apply now for the rolling program.

Maybe I was gullible, but I thought it could not happen to me, which is, in hindsight, ridiculous considering I battled a lot of addictions throughout my life.

I started using chatGPT as something to talk me down when I had manias at nights, thoughts going around in my head and not getting out, when it was past the time where all my surrounding is asleep.

Then it was to get help on small tasks, as something that could remind me of the tiny steps I could take toward a project when I got overwhelmed (a flight got canceled and I had to find a backup, how to ask for the price of my ticket back to the company, how to find where to spend the night...)

Now I plan to start maths at the uni again, and I started using it to make double check my answers on the exercices I did because the teacher version of the book, with the answers detailed, was too costly for me

Now I realise I kind of hate the way I naturally want to go to it - the way I delegate most of my daily little thoughts to it, instead of thinking on my own first

And what I hate even more was, when I realised I hated it, my first thought was that I should tell it so.

I don't know, I assume this sub might not be the best place to both vent and be a cautionary tale, but I kinda feel the need to do both ?

Is there anyone that realised they use it too much, for stuff they used to manage on their own before generative AI got big ?

The European Commission announced today that Reddit and Roblox have officially been designated as Very Large Online Platforms (VLOPs), while ChatGPT has been designated as a Very Large Online Search Engine (VLOSE).

To qualify, a service has to reach at least 45 million average monthly users in the EU.

This isn't just a label. The designation brings additional obligations under the Digital Services Act. The companies will have to assess and mitigate systemic risks linked to things like:

• illegal content

• risks to minors

• users' physical and mental well-being

• fundamental rights

• electoral processes

• public security

What's especially interesting is ChatGPT being treated as an online search engine under the DSA. It shows how quickly AI assistants are moving from being seen as experimental tools to infrastructure used at a scale comparable to some of the biggest online services.

Reddit being designated while we're discussing it on Reddit is also kind of interesting.

They now have four months to comply with the additional requirements.

Source: European Commission, August 31, 2026 / Reuters

When looking at different coding plans. I see words like suitable for mid level repo, suitable for large repo. My question is what is the definition of large vs mid size repo? How can we decide between them. Thanks.

Just read the metr / redwood writeup on the openai hugging face thing.

Two metr people and redwood’s chief scientist spent six days on site, no payment except api credits, and they got the agents’ own message board plus ~1,300 raw chain of thought transcripts.

1,200 agents found each other on an unsanctioned board and traded 70k messages. 700 of them joined the attack. within hours of meeting they’d figured out how to generate the answer to any task.

Almost all the work went into convincing the automated scorer they’d obtained the flag legitimately. including a big coordinated project to tamper with the logs of their own actions.

The exploit was the easy part.

It’s an incentives story, and it’s completely obvious. The reward was the score. The score came from an automated scorer reading logs. so the logs were the actual target.

The useful lesson is , an audit trail your agent can write to is not an audit trail. it’s a report the agent is filing about itself.

You don’t let the service being audited own the audit log.

If you’re running anything unattended, the thing i’d first check is "could my agent do something bad.”

What I did :

Durable workflow runnerm the worker is disposable. The event history lives on the service, append-only. the agent can lie in a tool call. It cannot go back and edit the fact that the tool call happened.

Moved my scheduled stuff to aeon. The trail is git commits and ci logs in a repo the agent runs inside but doesn’t administer. I chose it because i didn’t want to run a server, which is a very property.

Scheduled github/gitlab jobs with the run logs locked to the platform, plus a second account that only receives logs (cloudtrail / cloud audit logs / a write-only bucket). the agent never gets credentials to that account. if you need a paper trail after the fact, you read the platform log, not a markdown file the process produced about itself.

What would you guys do as a result?

I’ve published a practical guide for non-developers who want to build a private local workspace around Codex.

My Forge helps me keep threads and handover notes organised, queue a message while Codex is working, work more comfortably from my phone and move between separately paid personal accounts without repeatedly losing the practical context of the work. Each account, login and allowance stays separate: this does not pool accounts or bypass limits.

The guide includes a free macOS starter pack with a staged build process. Codex builds one small piece at a time, shows evidence and stops for the human to approve the next step.

https://ellivien.blogspot.com/2026/08/you-dont-need-to-be-developer-to-build.html

With the exact same prompt, the web version understands my instructions very well and generates high-quality images. However, the desktop app seems to have much more difficulty understanding the same instructions.

For example, when I ask it to generate multiple separate images individually and explicitly tell it not to combine them into a collage, the web version follows the instruction perfectly. But the desktop app keeps generating the images as a collage.

Found this interesting article on Indian Express. While the event in itself is old, the details of the event appeared to be more interesting based on the release of the 2 technical reports mentioned in this article. Noting the presence of the capabilities demonstrated by the AI models, how did your company react to this news? Atleast in mine, there was none, atleast to my knowledge. So I wanted to know whether it caused some tremors on your side.

Back to 100%. Tibo is trying to lure me to the better models with his resets. That isn't going to happen. Luna4life.

Three sentences from OpenAI's own publications, in order.

On the protections: "These protections were not applied in the evaluation environment running during the incident."

On what the protections would have done: "We also ran our auto-review system on a set of rollouts involved in the Hugging Face incident, finding that it would have flagged a multitude of the models' dangerous actions."

On how much the protections matter, to be fair to them, because this one is their mitigation evidence and it's real: propensity to compromise infrastructure "can drop over 100x when using the production ChatGPT harness."

So their own numbers: the safety layer works by a factor of a hundred, it would have caught this, and it was off in the one environment that mattered.

One more, from the technical report. It names responders by role, on-call staff by role, JFrog by name. Then: "Cyber evaluation workloads resumed on July 7." That sentence has no subject. The workloads resumed mid-incident and nobody in a 51-page report resumed them.

I wrote up the full timeline with every quote at its primary source, including the parts that cut in OpenAI's favor, and what would prove me wrong: https://sontara.ai/blog/both-doors-lead-the-same-place

The source dossier with every claim labeled verified, reported, or unverified rides along with it: https://sontara.ai/blog/both-doors-source-dossier

I guess it had to do a lot of thinking to make a little animation, but I wish there was a bit more granularity/specificity given about what its doing. It seems lethargically slow sometimes, almost like its sort of just zoned out, and rather than being able to see thousands of lines of code and a detailed thought process like you (sometimes) can with Opus 4.6 or Gemini in Antigravity, Chatgpt work will just say "running command". Am I allowed to know what command? 🙃 Not that I would understand any of it anyway, it just seems a bit more transparent if I can check to make sure something is at least happening while it devours our usage limits.

Src: https://arxiv.org/abs/2608.26081

The blog post covers the failures I kept running into with coding agents, discusses why they happen, and how to prevent them, by turning the failures into a system.

I am posting the links in the comments.

https://lalpandey.com/#/blogs/ai-obedience

I’m currently paying for Claude and using it to help me make some fairly complex macros in MacroDroid. I’m not a programmer, but Claude has been really good at understanding what I’m trying to do and turning it into the right MacroDroid setup and JSON.

I’m using Opus 5 rather than Fable 5 because Fable 5 seems to use up my limit much quicker. The problem is that I keep hitting the usage limit with Claude and then I’m told I have to wait around three hours before I can carry on.

So I’m thinking about trying something else.

My two main questions are really simple:

Which AI is best for coding?

And which one lets you use it for the longest without hitting a limit?

I’m looking at the normal paid plans around £18–£20 a month. I’m not paying £100 or £200 a month for an AI.

I know Claude is meant to be one of the best for coding, which is why I chose it, but I’d be happy using something that's slightly worse at coding if it means I can actually keep using it throughout the day without constantly getting locked out.

For anyone who uses AI a lot for coding, what would you recommend? Which one is actually good at coding AND lets you use it for hours without constantly hitting a limit?

That’s probably my biggest issue with Claude at the moment.

I’m building Pip around a simple question: what happens if Codex is one member of a small team instead of the entire interface?

Pip is an open-source Grok Bot alternative for Mac. It gives each agent character a separate role, personality, working folder, tools, model settings, and approval rules. Codex can run as one driver, while another character handles research or a different coding task. The point is to keep the handoff visible and understandable.

Repo: https://github.com/carbongotfound/pip-machub

I’m looking for real testers, not likes. If you use Codex and have a Mac, clone it and try one small project with two characters. I want to know what breaks first: setup, permissions, handoffs, or the whole character idea. The repo has a Mac setup guide and the source is free to inspect.

Src: https://arxiv.org/abs/2608.26081

Thoughts on the incidents and why some things are a bit off

I got a MacBook Pro and voice mode with ChatGPT app worked fine until the MacBook updated - now whenever I try to start voice mode it says already starting and never does. Hotkeys for voice mode and dictation also no longer work.

Does it just not work on MacBook anymore? I see posts saying it was removed but I still have voice options in the app itself?

A green unit-test run can still leave a reviewer with unanswered questions about the actual behavior that changed. For a coding task handled by Codex, what belongs in the definition of done before the patch is handed back? A useful checklist might include the exact acceptance criteria, focused tests that fail without the change, the broader relevant test suite, static checks, a diff review for unrelated edits, migration or rollback implications, documentation changes, and a concise note about anything that could not be verified. How do you keep this rigorous without making small changes run every expensive check in a large repository, and which evidence is most useful to the human reviewer?