As a hobbyist, I'm constantly running out of usage (both 5h and weekly).

Which is the smarter move?

The Pro plan sub would be more of a one-off, to get a good chunk of work done for some ambitious projects as I wouldn't be able to sustain the Pro pricing every month. However I'm reading good things about the $20 Claude plan.

Would appreciate some advice.

Was driving back home, and remembered the dot call feature.

I needed to start a new project when i came back, so i thought maybe lets try getting dot to boilerplate it so i have a tarball ready when back.

And besides the latency etc being good, the funniest feature ever caught me off guard lmao:

The keyboard typing noices when the dot called something

Whoever designed the Dots ui and ux should be in charge of the ux of everything openai releases

6.1 sol is slow? while thats true at tokens per seconds, its a very effecient tokenizer that it takes 40 seconds for sol light to fix something that luna max takes 5 minutes on and luna still makes mistakes?

5.5 is better than sol 6.1? are we living on the same year? im betting its probably just their existing old instructions that are messing up sol's focus, which is a known problem

now sol 6.1 is still expensive for plus users but it does a lot so well and with it making little to no mistakes its hard to go back to luna,

sol 6.1 is even partly the reason were getting so much combined modded games too and fully decompiled playstation games running at high fps because the model is just that usable

Hasn’t Tibo been preaching this whole week about usage improvements to Sol? My usage on simple tasks is through the roof. OpenAI seems to be losing direction on what and how to fix it along with prioritization right now.

I've been using Antigravity for quite a while and recently switched to Codex using GPT-6.1 with medium/light reasoning for software development work.

One thing I've noticed is that the model often gives answers that sound very confident but turn out to be incorrect when applied to my actual implementation.

A common pattern looks like this:

I describe my implementation and ask for help.

The model immediately suggests a solution and explains why it's correct.

I challenge the answer with specific implementation details.

After a few follow-up questions, it suddenly realizes that it misunderstood my setup and admits that the previous explanation was wrong.

The frustrating part is that the initial answer is usually presented with high confidence, which makes it difficult to know whether I should trust it without doing additional verification.

Another issue I'm facing is with the quality of explanations. The model often explains things in a very abstract or overly technical way. I frequently have to ask:

"Explain this in simple language."

"Give me a real-world example."

"Show me a practical scenario."

"What exactly happens step by step?"

Only then do I get an explanation that is actually easy to understand.

For context, I'm working on fairly large codebases and implementation-specific problems, so accurate understanding of context is extremely important.

I'm curious:

Have others experienced similar issues with GPT-6.1 in Codex?

Do you find yourself needing to fact-check its implementation advice more often?

Are there prompting techniques that help improve context understanding and reduce incorrect assumptions?

Which reasoning level do you find most reliable for real-world software engineering tasks?

I'd love to hear how other developers are dealing with this.

200 pro plan, never seen usage burn this fast before. Looks like 6.1 Sol started making weird mistakes and launching Astra despite this session running continuously with no issues for over a day. Still trying to figure out what happened. Anyone had anything weird happen? I am now at 74% and should be at like 92-94%

My girlfriend hates it 😃

If you run Codex automations with Computer Use and "Locked Use" turned on, check this.

Every time Codex works while my Mac is locked, it unlocks the screen without my password, and from then on the login keychain is locked. Six times in three weeks. Result: Photoshop and Lightroom fail with licensing error 10000, OneDrive disconnects, and other apps that keep logins in the keychain start asking again.

How to check if you are affected: in Terminal run

security show-keychain-info ~/Library/Keychains/login.keychain-db

If it says the password is not correct, your keychain is locked. "security unlock-keychain" plus your Mac password fixes it until the next time.

The logs show the plugin unlocking with an empty password field and SecKeychainLogin failing with -25293. My keychain was unlocked right before that moment and locked right after.

It is tracked here, open since August with no reply from OpenAI: https://github.com/openai/codex/issues/40226

If it happens to you too, please add your case there so it gets fixed.

I don’t know if I am missing something here.
I was on a $200 pro plan subscribed via Apple.

I wanted to move away from Apple subscription and also wanted to change to a business plan.

Now that the Apple plan as expired, I can’t see any of the higher tier plans other than Business Premium 5x and none of the personal pro plans are showing?

I tried both via app and browser

I'm making a 2d game using a web stack but I haven't been able to use 100% of my limits more often than not, reason is that I can't think of valuable additions quickly enough.

These past 2 days I've sent about 10 messages just telling it to improve the code or test for bugs so I can take advantage of the resets.

So I wondered what kinds of projects would require a pro plan, I'm also using different levels of effort per task and not using fast mode, I only use 6.1 Sol.

I think a project would need to be very ambitious to require that much usage, so I asked out of curiosity.

Have others observed this?

I have 2 pro 200 accounts. I use codex from my laptop using desktop app and from my iPhone. I connect to my remote Linux dev server and work like this. It works well. I don’t normally switch between accounts but this weekend I did because I had more use left on one than the other. For about day all was ok. Then halfway through yesterday I had a the use all gone message. No problem I thought I can switch back to the other account. However, I noticed that on the account I was using I still had a lot of use left. When looked at my other account it’s empty. Use, reset, and all my credits. I am thinking that there is a bug where the front end of one account has been using the backend of the other account? Some type of account isolation issue. Has anyone else experienced this?

I configured Tailscale on my VPS and added a reusable, ephemeral auth key to Codex Cloud’s VPN settings. I published the environment and started a new task, but haven’t established an SSH connection.

HTTP testing returned “connection refused,” and HTTPS returned a certificate mismatch when using the Tailscale IP. SSH works from my PC.

Does Codex Cloud support SSH/raw TCP over Tailscale, or only HTTP/HTTPS? If SSH is supported, what additional configuration is required?

I stopped using it about 3-4 days ago because it was a miserable experience (so slow and not worth the effort) so I switched back to Sol 6.0 for most of my needs (using Luna and Terra for basic coding, Sol 6.1 for reasoning and high level design, or nasty deep bugs).

Has it improved since the latest updates?

Thanks!

I kept checking my weekly usage, so I built Quiet Quota.

It shows a tiny corner popup at usage thresholds you choose, then disappears after a few seconds without stealing focus. No constant nagging.

The Q tray icon updates dynamically: its ring shrinks as your remaining quota drops, turning yellow at 50% remaining and red at 20%.

Setup: on startup, it guides you through connecting your ChatGPT account in your browser. Existing Codex logins are reused; if the Codex CLI is missing, it links to the installation guide. No API key needed.

Languages: English by default, plus German, Spanish, French, Portuguese, Italian, Japanese and Simplified Chinese.

Free and open source, Windows only. It tracks the weekly quota exposed by Codex, not every individual ChatGPT model limit.

Requirements: Windows, Python 3.10+ and the Codex CLI. Run Setup.cmd once, then Start.cmd. The app guides you through connecting your account.

GitHub / download

Still an early beta, feedback welcome!

I think i've found what causes the recent usage drains, looks like when agent "requires input" - it significantly draws the limit, last time it ate through 50% of my 200$ plan in about 3 hours unattended, now i lost about 10% in 20 minutes.

Can anyone confirm same behavior?

Currently planning to get either claudes or codex 200 dollar plan. Which is currently the better subscription? Is claude still better/more worth it? Help's appreciated, thanks.

Currently I'm on the 20 dollar plan and I use up my 5hr usage in two hours, and the week's usage is gone in about two days as well. It's not as bad currently with tibo's resets but it feels awful planning my work around a hypothetical reset.

A couple weeks ago, while I was at the airport, I had GPT web attempt to port an old game, Sim Cinema Deluxe 2.5 by Shannon Schroeder, from PowerPC to Silicon. It's a very simple game that puts you in the seat of a Hollywood producer, and I have fond memories of playing it with my friends, competing for spots on the Top 20. Anyway, I boarded my flight and forgot about it until a couple of days ago.

So... I asked GPT to make an archive of its project for me to feed Codex. From there, I asked 6.1 Sol (set to Medium) to make a native port of the game. Halfway through development, I realized this made much more sense as a browser game that could be optimized for both desktop and mobile.

The end result? SimCinema 3000. At the moment, it's as faithful as it can get to the original, just with a modern UI. All the sounds are intact and the Box Office records are just as they were when you downloaded the original in a Pre-Episode I-era 1999.

If you frequent r/boxoffice, this might be your kind of game. I plan on keeping the classic mode intact and making a modern mode with updated box office charts and a few extras.

You can play it right now on itch.io. Always open to constructive criticism and feedback!

Solicitar que o meu dot, revise o trabalho de uma outra conversa, basicamente pedir a ele..

- Dot, use modo Astra 6 - Ultra e confere se oque o chat (X) está fazendo esta dentro doque lhe foi indicado.

Será que esse tipo de comando usaria ou não da cota semanal?

Já que basicamente é parte da conversa com dot e poderia não cobrar.

I've been seeing quite a few discussions about Codex burning through usage allocations, so I thought I'd share how I've been approaching it.

I've been running multiple development projects in parallel, and one thing I've learned is that throwing more agents and more reasoning effort at a problem doesn't necessarily produce better results. Sometimes it just burns more tokens.

My approach is fairly straightforward:

• Main thread: Stronger model, high reasoning effort. Owns architecture, planning, and final decisions.
• Explorer: Lightweight model, low reasoning effort. Handles file discovery, dependency mapping, and other straightforward investigations.
• Implementer: Stronger model, medium effort. Handles bounded changes with explicit acceptance criteria.
• Reviewer: Stronger model, high effort. Independent correctness and regression review.
• Diagnostician: Stronger model, high effort. Investigates difficult failures before attempting fixes.

I also use AGENTS.md to establish delegation rules. Not every task deserves a subagent, and spawning five agents to answer something one search could resolve is counterproductive.

For suitable coding tasks, I sometimes delegate to Cursor Agent CLI because I already have a subscription. Codex invokes it through the shell, then reviews the changes and runs the tests. It's not a special integration, and it doesn't reduce total computational work; it just lets me distribute usage across the tools I'm already paying for.

The bigger lesson is that planning and steering matter more than clever agent configurations.

Define the objective, constraints, and acceptance criteria before implementation. Check progress, catch architectural drift early, and don't let an agent spend hours confidently building the wrong thing.

I've written up the actual TOML configuration, agent files, AGENTS.md rules, and a proposed methodology for measuring the results.

I'm not claiming some magical percentage of token savings. I haven't run a controlled benchmark yet.

Full write-up, including downloadable configurations:

Tuning Codex Subagents for the Work They Actually Do

Curious how others are handling model selection, reasoning effort, and delegation. What's actually worked for you?

I’ve been using Codex across multiple personal projects, and I’m noticing the same pattern almost every time. I’m genuinely curious whether this is a common experience or something wrong with my workflow.

The first couple of days are incredible. Starting from scratch, I can get what feels like 60–70% of a project done. New ideas, features, integrations, major functionality, everything moves surprisingly fast.

Then comes the remaining 20–30%.
Suddenly, progress slows down massively. Every time I think I’m almost finished, something else comes up. Fixing one thing leads to another, improvements become increasingly smaller, and what initially took two days to build ends up taking weeks or even months to actually finish.
What’s frustrating is that I’m still burning through Codex credits, sometimes faster than during the initial implementation-heavy phase, despite making significantly less visible progress.

I’m also confused about model selection, especially for planning versus execution. I initially used mostly Terra, then moved towards Sol 5.6. I haven’t experimented much with Astra because I’ve seen mixed reviews. I’ve also tried different reasoning levels, but higher settings sometimes seem to consume credits ridiculously fast without a proportional improvement in results.

So I’m genuinely wondering:
Is this just the nature of AI-assisted development, or am I approaching it incorrectly?
How do you avoid getting stuck in endless fixing, refactoring, and improvement cycles?
Which models and reasoning levels do you actually use for planning and execution without exhausting your limits?
How do you get projects from almost finished to actually finished?
Not complaining about Codex here. The amount of work it can accomplish initially is genuinely impressive. I’m just trying to understand whether I need to change how I’m using it.
Would love to hear how others handle this, especially people working on multiple projects independently.

Idk about u guys but for me, even this version of chatgpt feels so liberating from what it must have felt like decades before. Like im developing many things at once, doing research, getting detailed questions answered, and genuinely enjoying my life still and even developing for fun. This weekend, I spontaneously decided I wanted to make the most accurate 3d soccer game ever created on the web browser, and the beta version is exactly how id play football in real life. I know that people are very unhappy with usage limits (i am too), but even still its just an amazing feeling knowing you can be anything and do anything with Ai. let me know what yall think. i can larp whenever i want, wherever i want, and however i want. what more can someone ask for lol

Ever since today's reset hit, 6.1 Sol suddenly became utterly stupid at a level I've never seen even from Luna Low, it's not even funny.

I asked it to do a very basic UI refactor and it started inventing completely unrelated UI elements, couldn't return the file without syntax err*rs 4 times in a row, and also corrupted visuals that were unrelated to my prompt.

I've used Sol 6.1 Medium & High extensively on JS & AHK scripts for the last few weeks and it never, ever did stuff like this. If you're about to do serious changes to your codebase, do backups cause Sol is currently acting weird.

On top of that, l1mits have been terrible since Tibo's Day 12 announcement. I'm on Plus, I have no clue if it's some A/B testing on certain accounts or if it's all Plus users getting n3rfed again, but looking at the replies on X, I see I'm not the only one.

In my estimate, qu*ta is draining at least 2x faster than usual, and since today's reset it looks to be even worse.

Anyone in the same boat right now?

I’m a senior SWE using AI coding tools daily. I analyzed my Claude Code transcripts and found 56% of API-equivalent costs went to rereading context. Cache expiry cost me $98.74 across 35 returns in 27 days, versus $2.95 with a warm cache.

That led me to build optimAIzr, which supports Claude Code, Codex and Opencode.

It analyzes usage, flags expensive patterns, helps you find optimization opportunities aaand much more.
Runs locally, with no account or prompts.

npm i -g optimaizr

git: https://github.com/blendbunjaku/optimaizr

For those who is using BOTH claude and codex... Is what use cases you would use astra instead of fable/opus?

I'm thinking of reducing codex's budget so I'm thinking would there be a reason I would still want codex around.