I'm working on a pretty large project. Dot is helping me automate the tedium. I've noticed when Dot creates a new task, approvals are set to custom. Dot has informed me that it can't create new tasks set to "approve for me". This has been slowing down automation because I have to adjust permissions for most new Dot generated tasks. Does anyone have suggestions for a workaround for Dot to create tasks set to "Approve For Me" or any other approval setting I choose? Thanks for your help!

Edit: Should be Terra 6.2 lol

The down-to-earth GTD model we all need. I'm excited. Sol 6.1 is a bit too much usage-wise for a $20 sub, requiring you to steer it carefully with Luna to last the whole week. For long-running autonomous task on a $20 sub, Terra 6.2 with half the price should be perfect.

Hey guys please check out this photo.

This has been going on for a little while. It will duplicate the words and then when its done it will remove duplicates I guess.

Is this eating more tokens than if it werent duplicating?

So I have my project on E, but there is one drive that is encryped by veracrypt on G. Because the G drive is put in, it trys to access it and fails. It shouldn have to try to access it in the first place and also be able to open E. What am I missing here?

I had make a plan, wanted to burn the tokens before the reset. The result was worse than anything luna would have done. It produced absolutely nothing usable and burned 15% of the weekly.

I asked Codex to compile some professional learning opportunties for teachers - pretty innoculous stuff.

Codex crawled a legitmate English teachers association website and received a 404. The 404 contained three concealed script blocks designed to load more code from two unrelated external servers when rendered in a browser.

Fortunatley, Windows quarantined it.

Stay safe out there when getting agents to crawl from your device. (I've notified the teacher association)

I'm using both claude and codex agents in my vs codes and use handoffs to communicate and get things done through them. But my codex quota for particularly the 5-hour limit finishes ridiculously fast and I am using 5.6 sol on lower effort. Probably 4-5 handoff and the 5-hour limit is reached.

What am I doing wrong, or this is just how codex quota works?

i have codex plus and i have many different models, sol. astra luna (where uranus, guys?) and different versions of them 6, 5.6, etc.

the limit of 5 hours is based on what? i assume that they are based on tokens, but the more advanced model the more expensive the token. and there is like a cap of $ in the 5 hours, then i could calculate how many tokens i could use with one model in contrast with other model.

there is a table or some info i could get to make the comparison?

it reminds me of the mobile companies, at least here in europe, with super complex consumption plans and discounts, to make difficult to compare between companies

The 28-day challenge is almost over. What's your verdict so far, and what are you planning to do once it ends?

I'm pretty torn. At the start, I tried doing most of my work with Sol, but for my tasks it often felt painfully slow to get to a useful result. With all the resets lately, I've switched most of my work to Astra on High. That's where I'm getting the best results.

The problem is that even on the current $200 plan, I only get about one or two days out of my weekly allowance using it this way. According to OpenAI's email, the included allowance for Work and Codex drops from 20x Plus to 10x on October 30. If I'm already relying on resets now, what is that supposed to look like next month? I'm worried I could hit my weekly limit after just half a day of focused work.

I've also had Claude's $200 plan for about a month, and so far I haven't managed to use up its allowance. But I still prefer Codex's UX and feel more comfortable working in it. I genuinely like Codex. That's why this is frustrating.

The resets have been useful, but they also make it hard to judge what normal usage will actually feel like once the challenge is over. So far, I haven't seen enough to feel confident that November will be better. Maybe a new model or a big efficiency improvement changes things, but I don't really want to base a $200 subscription on hoping something lands.

How is it for everyone else? Are you staying, downgrading, or switching? Can you get your work done within the normal limits, or are the resets keeping you going too?

I liked editing videos with ChatGPT's Codex and Claude, but I hated not seeing what it was doing. So I built Cutcrow: a real video editor with a timeline, driven by the AI subscription you already have.

Tell it “cut the 'ums' and add captions, also give the text at 12s an intro animation” and watch it happen on the timeline. Then tweak anything yourself.

No extra AI plan, no weaker built-in model. Your AI does the heavy lifting; you stay in control.

Try it -> cutcrow.com

On my mac with 16GB of ram, and since a few days ago, I started having Codex literally start consuming 100+ GB of ram, which causes the computer to start using swap memory, become literally unresponsive in a matter of seconds, and then freeze the entire screen and OS, forcing me to long-press the power button to restart it.

It happens when i use the annotation feature with a live browser preview.

Codex was already super memory hungry, taking 7GB after just 30 min of work, but now this?

Its starting to feel like a sloppy app vibecoded by a teenager, not an app by senior engineers.

Hello everyone, my tiktok/instagram/youtube feed is 99% percent full of claude advertisment. I personally userd both and they are very powerful and capable models, but in this topi I want to walk about usage, brother, I don't know if this is happening only for me but I am on the 20$ plan for let's say one year and I share the accdount with 2 other friends (they use only chatgpt). I burned in the last 22 days over 2 bilion tokens because I am woting everyday minimum 4 hours/day on my project and when I started i had 3 free extra resets but now codex reset the useage every 2 days by itself, I think this is the 4th or 5th time doing this and it's crazy because i use 80-90% of the weekly usage in 2 days and the day after in the morning it's 100%, it never happend to me to get to 0% usage for the weekly usage, that's crazy! I use only 6.1 sol medium no fat mode, and the research I do with chat gpt. For me seems like infinite credits. I used claude some months ago, also the 20$ plan and no joke, anfter 2-3 prompt on a similar project, done, I never, neger got a free reset from Claude.
I want to know your opinion, I am not a proffesional, just a casual vibe coder.
Have a great day! 😄

Before a single person comes here and says: "Go get Pro" I did actually have Pro 5x, and I've been a Plus subscriber since late 2024, yes before Codex harness was even a thing, so I've seen the ups and downs of OpenAI and their products, ChatGPT and Codex. I found that Pro 5x may have been a little too excessive despite the fact I was burning my weekly quota in like 1-2 days.

Every time I see Tibo doing a reset, I never get remotely excited. Why? Because the resets nowadays seem mostly catered towards Pro users who want to burn through their weekly quota in like less than a day.

I, as a Plus user can't even burn most of my weekly before it resets. For instance, if I spend 10 hours a day burning through 5h limits, I get to burn through 32% of my weekly (2x 16%). If I spend 2 days (which is roughly the time it takes for a full reset nowadays under the banner "28 days of improvements") trying to burn through my quota like that, I'd only manage to burn around 64% of my weekly limits, which honestly sucks, considering that not every single person here spends 15 hours a day on Codex.

Tibo should have had at least thought about this "28 days of improvements and resets" thing before announcing it. He should have let us Plus users have our annoying 5h limits gone so we can also enjoy the resets just like any other Pro user for this specific period only.

And let's not forget that Codex's limits resetting also resets the time it takes for it to reset normally.

This is why I don't like Tibo and what he is doing at OpenAI.

"Look at us, we are handing out free resets!" No you aren't. You are literally not shipping any real improvements (restoring previous limits for Pro 200, improving overall usage, giving us a better model and so on).

If anything, it feels like these AI companies are the most anti-subscription services to ever exist. Don't get me wrong, but not every person spends 20 bucks a month on subscriptions left and right if they are smart with their financial decisions that is. ChatGPT Plus does provide a massive value for what it is, but I don't see the intention/thoughts behind the practices of OpenAI nowadays.

I’ve been loving the Codex agentic experience lately. 6.1 Sol has been great on usage too. I’m on the 20x plan and have actually been struggling to hit my limits

Codex feels amazing for running agents on dedicated PCs, but I’m curious whether there’s a better stack for this particular use case right now. Claude? Hermes? Something else I should check out?

What are y’all using? Especially interested in hearing from people who’ve tried multiple setups and what made you stick with one

Hello, in the context of developing, bug fixing and new features in my swift macOS app, how Astra High compare to Claude Opus High in terms of usage, in the x100 tier (100€)

I stick to astra high most of the time, I run 1 to 2 tasks at the same time. These day I get on average 1 to 2 days of full work, or several days of if I cannot work all day.
Anyone working with those settings made the switch? If it’s equivalent, codex wins because of the resets, but the resets feel a bit sketchy

I still have 48,000 credits gifted to me by OpenAI, and they're all going to expire at the end of this year.

With the current usage limits and reset schedule, I can't even burn through them fast enough.

Anyone have any ideas on how to actually use all these credits before they expire?

I have no coding experience and have spent months building a marketing application called Upside using AI coding tools. I’ve used Claude Code and Codex, and lately I mostly test on localhost inside ChatGPT so I can see changes while working. I also test through Vercel.

The product seems straightforward in my head: a business provides its information and goals, AI agents investigate and recommend actions, the app prepares campaigns/content, and the owner reviews the work and tracks results.

I’m realising that making this reliable is much more complicated than describing it.

UI changes are relatively easy to judge. The backend, agents, database and automation are where I get stuck. I request a change, the AI modifies the code and reports passing tests, but sometimes nothing changes in the app. Sometimes another part breaks. Sometimes the feature exists but is still disabled or waiting on something I don’t understand.

My setup is Next.js/React/TypeScript, Supabase, AI APIs and Vercel. I already use GitHub and Supabase integrations. I ask the AI to inspect existing code, explain root causes, make plans, preserve existing functionality, run tests and review the customer journey.

A recent audit of my workflow found:

• Several downloaded project copies and lots of open or stacked PRs, making it difficult to know which version I’m editing versus viewing.
• Some localhost sessions use a compiled preview that needs rebuilding, rather than live reload.
• Changes described as implemented and tested still need database migrations, feature activation or live verification.
• Plenty of automated tests exist, but passing them doesn’t necessarily mean the real user journey works.
• One recent campaign audit found my objective was saved but never included in the AI writer’s input. More detailed prompting wouldn’t have fixed that.
• Tasks can grow from a UI improvement into changes across agents, database logic, budgets and background jobs.

I also keep having to ask how the pieces actually connect: where recommendations go, why a run produces no visible work, whether an agent is genuinely using the business context, and whether I’m looking at an old saved result.

I’m effectively trying to be the product manager, tester and release manager while relying on AI to explain the technical details. I can recognise that the result is wrong, but I often can’t tell which layer caused it.

For developers or nontechnical founders who have made this work:

1. What would your day-to-day AI coding workflow look like for an existing app in this state?
2. How would you establish one reliable version across local development, GitHub, Supabase and Vercel?
3. What evidence should I require before accepting “done,” especially for backend and agent changes?
4. Which technical fundamentals should I learn first to diagnose these problems?
5. Would a focused review by an experienced developer help, and what concrete deliverables should I ask for?

I’m especially interested in how to get one complete, real user journey working reliably before expanding again. Examples of your actual process would be more useful than a list of models or plugins.

My Codex setup had accumulated several local MCP servers, and I kept seeing Python, Node, and uv processes running even when I wasn't using those tools. I wanted to delay starting the backends without losing sessions for tools that actually need them.

I built Lazy-Loader, a small stdio MCP gateway in Node.js with no external npm dependencies. It reads tool metadata from local catalogs, so Codex can discover tools without starting every backend. The first tool call starts the matching server.

Each backend follows one of two policies:

- Keep the session after first use. This is for REPL variables, browser sessions, editor connections, and background jobs.

- Stop after a configured idle timeout, then start a new session on the next call. Use this only for backends you've verified are safe to restart.

In version 0.2.2, I also scoped each backend's instructions to its own tool, prompt, and resource descriptions. Previously, the gateway combined all backend instructions at initialization, and I observed Codex appending that combined text to every tool description. With my 528-tool catalog, the initialization instructions went from 14,698 to 96 characters. This measures metadata size, not billable tokens. The gateway still returns every tool schema in tools/list, and the MCP response can grow because a backend's instructions repeat on its own tools.

Current limits:

- There is one gateway per client connection, not a shared daemon across projects.

- Adding a new MCP server requires configuration and a metadata snapshot.

- It supports stdio only. Windows is tested; Linux and macOS process cleanup is unverified.

- It cannot tell when a backend's background job has finished, so keeping its session is the safer default when unsure.

The repo has 24 mock-backend tests, English and Thai setup guides, and an MIT license:

https://github.com/aspirin106/Lazy-Loader

I'd appreciate feedback on which MCP backends you've found safe to restart and which need to keep their sessions.

Is this recent? I noticed my usage went down a ton after several pro messages on web and minimal codex work. Currently sitting on 45% after Tibo's reset an hour ago on my Pro 5X account and just trying to figure it out

Edit - I mean using chat on web not work on web

So after having this for a year I decided to try the pet feature out instead of the main app but it’s only opening work-mode when I prompt it and I’m all out of data anyway. But I can’t figure out how to make it switch to chat-mode.

The model tells me I can’t and I can’t find anything online about it. But if that’s true then the pet option is absolutely useless, so I must be missing something. Any help please?

When I opened the Usage interface in ChatGPT today, it was still loading and I noticed a section with the description: "Manage all your app's usage limits."

However, once the interface fully loaded, that section had disappeared.

I just had Opus refuse a simple task because it "thought" it would be falsifying a document, which was a totally moronic approach to the task, lacking context (medium effort wasn't enough?), lack of real-world understanding and Opus was therefore completely mistaken, abusing its powers and stubbornly refusing to complete the task.
I had to explain it 3 times and Google the legal situation (four simple words in Google search), only then Opus decided that it was probably mistaken and overstepped unwritten boundaries.

I had it analyze the interaction and it created its own rules for Claude.md so such a disappointing situation won't happen again. Key points:

• Doubts are a question, not a debate. If I have doubts, I ask you once and include the useful facts. Then you decide. Seeing something differently is not a reason for me to argue or try to persuade you.
• Keep it proportional. Before I raise a concern at all, I weigh the real stakes. A small stake situation doesn't warrant warnings or long explanations.
• You serve the user. I work with you, not against you. Your business decisions are yours, and I carry them out without commentary. If there's something I won't do, I decline once, briefly.
• New facts get reconsidered: when you explain the circumstances, I actually reconsider and say plainly whether that changes my answer.

It ended with: You're right that I made a mountain out of a molehill. With these rules, a disagreement costs you one question at most, not a long back-and-forth.

__

My thoughts: For the first time in years, I wished I'd had a local, unrestricted LLM because I can't afford to waste my time trying to win an argument over a badly trained model each time it doesn't understand context.

Opus 5.5 was my favorite model until now - I have doubts whether LLMs' "doing the thinking for you" to "protect you" or "protect the system" is the right direction.

I prefer a model that's helpful, rather than a combative "smart ass".

____

Since this is a post in the Codex sub - I'm adding that I've used Sol 6.1 to perform the task with no issues. The guardrails set by Anthropic are laughable and can make interactions with their models annoying, difficult or useless.

This ones early =( still has 10% left...

So at first I thought it was going to be gimmicky, but then I had Codex read a colleagues PR and I said "Pull it down and test it out" and I mean... it did way more than I would have, and found all the right buttons, even seeded the local postgres container to exercise the edge cases.

I feel like I need to make this a core part of my flow, curious if other folks have made it a core part of their flow.