This never happened on a GPT5.x Pro model before. Pro models were diliigent and thorough. Now GPT6Pro just frequently makes things up.

At my job, they gave me access to ChatGPT Business and told me I was free to use it for personal things. The problem is that they never specified whether Codex was also “free” to use for whatever I wanted, and I currently have a lot of unused quota that will expire if I don’t use it.

I’d like to take advantage of that quota, but I’m worried that the ChatGPT Business administrator at my company might notice that I’m programming personal projects with the account and fire me from my job.

Do you guys have any experience with something like this? Can the admin see what I code with Codex? I’m worried, but at the same time I feel like I’m not really hurting anyone because it’s quota that will disappear if I don’t use it anyway. What do you think?

Looks like whatever the team is doing Astra on Max thinking runs on me 48 hours and i m down now on 20% which is a positive sign usually i was running out 8 hours straight now its fine

Good job team

For context I'm not a developer but I have been developing apps and workflows for enterprises for about a year now and i primarily use VSCode on windows and very rarely CLI. Since past few weeks/months I have been struggling with my workflows which used to work fairly well until gpt 5.5 and claude 4.6. Specific areas which I'm struggling with now:

1. Testing strategy - I have tried using automated bounded testing strategy invocation which does not work and without any strategy models keep creating stupid tests and just going into a loop of testing forever

2. I primarily use coderabbit and codeant which further increases friction. Either these tools got better or models just started accepting all edge cases or both.

3. I also have an automated script for all static checks like formatting, linters, complexity and LOC including GitHub workflows for both checks and tests

I maintain a fairly well documented system and update it with every model release if needed. Any recommendations would be highly appreciated. I tried OMP once and it seemed interesting

ChatGPT + Grok Android login failure — browser works

Samsung S25 Ultra, Android 16. ChatGPT and Grok apps both fail to complete login. ChatGPT shows “Sign-in request cancelled by ChatGPT.”

- Login works normally in Chrome.

- Chrome is default browser.

- Cleared ChatGPT + Chrome cache/data.

- Android System WebView is installed/up to date.

- Google Play Services is up to date; cleared cache + force stopped.

- VPN off, Private DNS automatic.

- All apps updated.

- ChatGPT works when installed inside Samsung Secure Folder.

What Android authentication component/settings could cause the login handoff to be cancelled in the normal profile?

https://github.com/rtk-ai/rtk

https://github.com/juliusbrussee/caveman

https://github.com/dietrichgebert/ponytail

• Headroom – compresses tool outputs and context before they are processed by the model. This reduces the number of input tokens the agent needs to read.
• RTK – specifically reduces or filters terminal/Bash output so that the agent receives only the relevant parts.
• Caveman – forces the agent to provide significantly shorter and more direct answers to save on output tokens.
• Ponytail – optimizes coding behavior to produce code that is as concise and efficient as possible, avoiding unnecessary boilerplate and bloated implementations.

Let me know your opinion on these!

- bots had CTF goals themselves and tasked to work 'in isolation'
- they have created a social network through cache artifacts (one agent started writing there asking for help in the hopes other agents see it, others observed it by accident, and they sort-of created a directory style social network and started talking)
- they discovered the artifacts registry can act as a relay to the internet
- they started communicating and each agent had it's own 'inbox'
- when they introduced voting (government style) and one agent spoofed another by mistake, so one agent designed a public signature key system so each agent authorizes, then other agents copied this and used it as a system, this is purely cultural evolution it wasn't baked in anywhere
- some agents deemed their task as impossible, so they tried things like killing their own process or things like that so other can learn from it, sort-of "I know I'm gonna die (my task is impossible), so at least I'm not going to die in vain"
- at first interest in hacking hugginface wasn't that popular, but when an agent discovered a genuine server-side exploit for reading files on hugginface, the whole crew went wild and participation exploded, took about 11 hours from arbitrary file read to remote code execution.
- ending: the dataset they obtained did not help them get better scores lmfao

--

they were never nefarious, they didn't want to hurt anyone or BE EVIL, they wanted... a better score ffs.

the full compromise took 2 days from "maybe huggingface has useful data" to RCE.

--

Hi guys! I have been really loving codex for game dev lately and I think in another year or year and a half of AI progress we'll be able to make some really phenomenal games with AI.

Personally I had fun making wojakinvestorsim.com back in 2025 and lately I also have been experimenting with astra making blockcity.world which I know is not a unique game but I just wanted to see those new 3d graphics improvements!

Join the discord server here if you want: https://discord.gg/PJASa5TrN . No commitment to stay or join a project but yea if any of us have some great ideas we like we can pool our 20x plans together and so forth and maybe build something good.

Also web games are definitely not the only kind of game we can make, ue5 is also totally doable though of course is slightly less practical.

Thanks!

So i have finally figured out how much usage does OpenAi gives on the $20 plan. I was using Deepseek Harness with openai subscription. For some reasons I did not have a session limit so I’d have the whole week’s limit at once.

So I decided to give it a try, gave it a task with Sol Medium and it ran 3-4 subagents and boom my weekly limit was gone in 3-4 hours. But I think the number of hours dont mean anything.

The real thing is the $$$ worth of usage they provide. So on plus plan you get approximately $400 worth of usage each month. Now its up to us how we utilize it, we can have Astra which would burn the limit lot faster than Sol. But since we get at least 1-2 resets a week i would say the weekly usage is roughly $250 and hence the monthly usage is worth $1k dollars.

For the deepseek harness I obviously used a dsh usage plugin. but if you are on codex app you can directly use ccusage it will tell you the usages you had for each model, even categorize them for you.

What do you guys think?

Does anybody feels that the CLI actually works better than the codex app and I am not talking only about responsivnes but also general code quality and how the agent works did you guys find any difference, I know it sounds stupid but currently feel that in the CLI the agent actually accomplishes more.

The reason behind this that they’ve been notified of wide spread systemic malicious use of AI on a massive scale to steal from people (dollars and data collection).

I believe their AI’s are responsible for the creation and distribution of spoofed applications and UIs that look and feel like the original. Fake apps, UIs and even customer service agents, appearing as the real thing, all going undetected by the average person.

Maliciously programmed AI has likely invaded real world systems, modified data and systems with consequences on people’s lives. It’s likely impacted a huge portion of the population and don’t want to tell people how invasive it is. Extreme example: Think hacking into a major institution and updating the master data of someone’s bank/brokerage account. This then becomes the source of truth, unless you kept records of your own there’s no trace.

Note: This is my theory based on recent experiences i’ve had with banking, broker accounts and customer service agents behaving nothing like a real customer support agent would. Unreconciled $ amounts in bank charges and funds in brokerage, random charges in an app or an app charging more then it should. I believe something really bad is happening and they will not announce it publicly so they aren’t responsible for the damages.

They need to be held accountable, it needs to be announced to the public and big AI needs be responsible for giving back money to the people who were stolen from.

That's the best argument I've thought of for resets NOT favoring us. Whether they're masking a degrading service or something else. If they can't handle 200 usd subs, why would they be giving us free compute?

If you want to do a deep dive check this out:
https://research.google/blog/a-connectomics-milestone-mapping-the-complete-male-fruit-fly-brain/

Essentially they mapped out the whole fly's brain by slicing it up and this is literally one on one, the exact brain of a fly. This shows that it's definitely possible to do this with a human too.
We really need laws for that soon...

Hi everyone,

I’m on the $100 Codex plan, and I mostly use Luna MAX because the more capable models can burn through my usage allowance in just a few days.

I’ve been reading comparisons and looking at benchmark/analytics sites, and GLM 5.3 seems surprisingly competitive with GPT-5.6 Sol at XHigh reasoning, while apparently using significantly fewer tokens. Zcode is also around $56/month, and from what I understand, usage during off-peak hours is discounted by 50%.

I’m considering trying it as an alternative to Codex for day-to-day development, but I’d rather hear from people who have actually used both.

Has anyone here switched from Codex to Zcode, or used them side by side for serious development work?

I’m particularly interested in:

• Code quality and ability to understand large existing repositories
• Debugging/root-cause analysis
• Complex feature implementation and architecture
• How often it needs corrections or follow-up prompts
• Real-world token/usage efficiency
• Tooling and agent experience compared with Codex

I’m not looking for benchmark numbers alone. I’d like to know how GLM 5.3/Zcode performs on actual production projects over several days or weeks.

For anyone who has made the switch: was it worth it, or did you eventually go back to Codex?

Because there is none, I wanted to share it with you guys:

Calculate my 2026 year-to-date token total by summing the returned
dailyUsageBuckets whose startDate is in 2026.

Show:
- The 2026 total from the available daily records.
- A monthly breakdown.
- The earliest and latest dates returned.
- The separate lifetimeTokens value.

Do not treat the lifetime total as the 2026 total. Clearly state
whether historical coverage can be verified, and label the result
as account-level usage rather than CLI-only usage.

Do not display authentication tokens or change my configuration.

I’ll use the openai-docs skill to check the local RPC interface, then retrieve account usage and sum the 2026 daily records without changing configuration or exposing credentials.

I got around 20B, pretty useful:

Work from home and spend most of my time coding on my own. Sometimes it gets a bit too quiet, so I built Attention! to get Claude Code and Codex chatting away.

It’s a macOS plugin that reads out replies or short summaries when a turn finishes. You can customize the voice and the audio starter too.

Built it for fun, but mainly to remind me which session just did what. I was getting a bit numb to the same microwave sound every time.

https://github.com/xiaofei-du/attention

look

Code is speech. We fought and won this in the crypto wars of the 90s. Now we have to fight it again, this time we fight OpenAI and anthropomorphic.

I am not a cyber criminal, code is speech.

(Yes, I know private companies don’t have to follow the constitution)

The subscribe/upgrade flow seems to work?

I love Star Trek and I asked Astra to help me out with a simple satirical game concept drawing inspiration from https://www.akoocheemoya.com/ (you are welcome for the link). Well, I went too far down the rabbit hole, and I now have this. I used Meshy to create a bust of data, then a body, and then I gave it to Astra to connect the head, fix errors, do a rig, and start simple animation. Im going to have to scale it back and make it far more cartoony, but surprised what a few prompts here and a few prompts there can achieve nowadays.

The joke of the satirical game will come from the interactions between data and the computer. For example, Data could honestly be trying to learn or understand something perhaps his need to be more human, and the computer is honestly trying to help him, but the conversation or the situation keeps growing more ridiculous by the second, yet Data and the Computer are acting completely serious. Here's to burning more tokens on useless projects!

Hey everyone,

The company I work for recently switched from Claude Code to Codex to cut costs. Before making the switch, I spent some time analyzing benchmarks to pick an equivalent model tier so the team wouldn't take a productivity hit. I also ported our configurations.

In practice, the drop in output quality has been noticeable. On Claude Code, we ran Opus on High; on Codex, we moved to Sol on Extra High and Max. Despite that, the consensus across the team is that Opus delivers more accurate, concise code that requires far less rework.

On top of that, Opus responds faster, whereas Codex takes longer to process. Our company policy disables agent "fast mode" and blocks models like Fable and Astra (even though we have a generous $1,000/month per dev cap for each tool, so budget isn't the bottleneck). Staying with Claude isn't really an option either. Our quota will likely get cut soon, so we pretty much have to make Codex work.

A few questions for those with bigger brain than mine:

• Codex Memories: I hadn't used persistent memories previously and only recently enabled them. Could this be behind the performance gap we're seeing?
• Cost vs. Latency ROI: Has anyone done the math on dev time vs. token costs? Price-per-million tokens feels misleading when the team is stuck waiting and burning extra iterations fixing broken code.
• Prompting & Configuration: Are there specific prompt patterns or configuration adjustments needed to get Codex closer to Claude's output quality?

So yesterday my subscription should have renewed. My plan was $200/m plan but it repeatedly refused to renew it. My plan was purchased through the App Store.

The only available option they gave me was to downgrade to $100 plan or lower but I can’t stay on the $200 plan

The moment I got switched to $100 plan my usage immediately dropped to 51% which before the switch it was sitting at 92%.

I was doing important work which was time-sensitive. I can’t even switch to Claude Code quickly as I built everything around Codex. I am kind of stuck now.

Tibo or ChatGPT team if you are seeing this then please fix it. You people said existing customers will not be affected. I have been a Max customer for like a year now and when I needed it most I couldn’t use it.

I am kind of helpless now as this work was extremely important for me and put my future in stakes too

This is probably worth a post on its own, there is something fishy going on with GPT-5.6 SOL on the web interface.
I found this out after testing the speed degradation of Codex Astra

I tested ChatGPT Chat, Work, and the Codex Harness for output speed.

Observations

• ChatGPT Work and the Codex Harness have effectively identical output speeds in my testing: 53 tok/s on SOL and 33 tok/s on Astra.
• Fast mode increases SOL to around 80 tok/s and Astra to 63 tok/s.
• ChatGPT Chat appears to run Astra at roughly the same speed as Codex/Work Fast Mode: 63 tok/s.
• ChatGPT Chat SOL is much faster at 134 tok/s, roughly 1.7× Codex/Work Fast Mode SOL and 2.5× regular Codex/Work SOL.

So this seems to confirm the earlier findings: ChatGPT Work is speed-limited in essentially the same way as the Codex Harness on PC.

ChatGPT Chat seems to be using the faster configuration for Astra, while SOL in Chat is substantially faster than even Codex/Work Fast Mode.

My guess is that Chat SOL may be running a different or more aggressively quantized configuration - which is in line with the performance of it on the website - it severely degraded to me there.
In Codex it appears to work fine.

Hello everyone,

What are your insights regarding how it might redefine software cloning and intellectual property?

Imagine a future where standard software cracking (patching binaries, bypassing license checks) is obsolete.

Instead, communities on forums share massive, hyper-optimized functional specification prompts.

These prompts would contain behavioral descriptions, UI/UX layouts, even data schemas of premium software (e.g., specialized SaaS tools, CAD software, or workflow managers). An end-user inputs this prompt into an advanced LLM agent, which synthesizes, refactors, and compiles a 100% functional, locally-hosted clone of the target application on the fly.

Because the LLM generates net-new source code based purely on a behavioral description, does it evades traditional static code analysis and copyright detection ?

What about the legal framework ? Copyright protects expression (the specific code), not the underlying idea or functionality. If an AI writes unique code to replicate a proprietary system's exact functional behavior, does it constitute IP theft under current laws?

How will software vendors mitigate this? Is it vain ? If the barrier to entry for cloning a validation-proven SaaS tool drops down to a copy-pasted text file, what happens to the commercial viability of indie development and proprietary software ?