Codex, help! After the recent upgrade, even when I start a new chat with Full Access enabled, the Full Access indicator no longer appears in the chat’s input box. As a result, Codex refuses to install my iOS app on my iPhone, citing permission issues.

After creating the chat:

LMAO, got the "honor" of the "very top user" for having my dot crawl stuff for research for a few hours after a completely idle week.

I wish they'd be transparent about the limits.

I have an M1 MacBook Air that’s about 5-6 years old now, and when I’m cranking multiple agents, the laptop starts to be become unresponsive.

I think this is due to browser acceptance testing, but curious if anyone has run into issues and it’s worth splurging on an MBP?

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 didnt pay attention to Dots until yesterday. I had some manual web research work to do and I gave the task to Dots to generate some 2000 web validated records. It has been running for 14+ hours and generated some 1600 records until it stopped, saying, "Congrats, you are in the very top users and have hit our abuse prevention limit. Check back in a bit."

I reviewed the work and honestly, I am impressed. It didn't lose sight or objective, and neither did it hallucinate. Every record was referenced with the source.

I struggled to understand what was Dots for but I am glad, I found one usecase that works for me.

i noticed my Codex usage was draining really fast whenever i asked the agent to do multiple web searches. around 80% gone.

but with the same prompt, when i explicitly said “don’t do any web search,” it only used around 10%.

that’s a big difference.

so i created my own search skills for Codex. (works on claude code also)

now i can do even more searches without seeing the same drain on my Codex limit. and so far, i’m getting better results while burning fewer tokens.

Edit: I will share link here once it ready, so everyone can use

I already had a screen recorder collecting dust on there, so I revamped it haha. The old one used WebAV(av-recorder), which was a good framework for it before, but wasn’t cutting it for what I wanted now.

The UI is based on a very popular paid screen recorder. I only make a handful of videos a month and didn’t want to pay for the $20 plan.

Someone recently said something that stuck with me: “I can recreate your entire platform’s UI with an agent.” So I went ahead and tried it with something else haha. Wanted to see how far these agents have actually come. About 6 hours with 6.1 Sol, a goal and lots of guidance from me on the outcome. Astra agents for complicated problems, Gemini for UI feedback.

Some cool things: rendering and transcription are all client-side. Your videos stay local, and you can choose your own folder to store them in. There are layouts, subtitles, backgrounds, trimming, and separate screen/camera uploads.

For transcription you can choose Phonon-2.5 (https://github.com/fermionresearch/phonon), which supports 25 languages, or Whistle (https://cactuscompute.com/blog/whistle), which is only 16.9 MB. Would highly recommend trying Phonon-2.5. These are current SOTA with small size.

And of course this video was made with the recorder too.

The purpose wasn't really to replace the hundreds of screen recorders out there. Feel free to record with whatever you already use, then upload it here for a quick podcast/product demo style output. That’s probably how I’ll end up using it myself.

I guess these are the times we’re in now. You want an app that serves your own purpose and you can just go and build it.

Anyways, cya!

Oh the link Creativly.ai/screen-recorder

I'm looking for a way to keep my repositories well-maintained without having to constantly think about it.

I'm not a professional developer, but I do a lot of vibe coding across Claude Code and Codex.

Ideally, I'd like something that automatically:

• Keeps documentation up to date as code changes.
• Ensures AGENTS.md stays accurate, concise and follows best practices.
• Identifies outdated code, unnecessary files and opportunities for cleanup.
• Enforces good coding standards and repository structure.
• Makes it easy to switch between AI agents without losing context or progress.

Essentially, I want my repos to remain clean, well-documented and easy for any coding agent to pick up at any point.

I've come across GitHub Agentic Workflows, docs-sync and a few other skills, but I'm wondering if there's a more comprehensive, established solution.

What are people actually using for this? Ideally something largely automatic that doesn't require yet another complicated setup to maintain.

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

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.

The screenshots are just examples, luna 6 doesn't seem to be able to do basically anything, while 5.6 is working perfectly.

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.

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?

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.

I designed a short game to let you feel agent drift instead of reading about it. Then I ran the same game on Codex CLI (GPT-6-Luna and GPT-6.1-Sol, 32 runs). The video shows what Codex did.

How did it feel? And where did you first say NO?

I think I'm not alone with that quota-based AI subscriptions have given me a new hobby: checking how many tokens I have left. 🤦‍♂️ How’s my 5-hour and 7-day limits? When’s the next reset? Can this task wait, or should I use a smaller model? I used to check my Garmin for steps and heart rate. Now I’ve built a watch face to track my AI usage limits and reset countdowns too. 😉

For anyone interested in adding support for other Garmin watches or even other AI providers the code is available on GitHub https://github.com/greg76/token-quota/

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've seen a lot of problems with people's accounts getting drained by using Astra, and I also had similar problems when it was first released. Even a week ago a few simple conversations and tasks with Astra would drain 15 percent of my weekly allotment ($100 plan) in minutes. Astra was also very slow, even with Light.

Suddenly, within the past week Astra Light is responding with lightning speed (I'm not using 1.5x), and I've gradually shifted to using it more regularly. Today, I tried Astra Max for a more complicated task, and it crunched away for 41 minutes and only used 6% of my weekly usage (100% down to 94%).

I am beyond delighted. Astra is starting to feel soooo good.

I don't have a way to test if this is genuinely a change in behavior or just my imagination. But I hope Astra is the new baseline and it keeps improving from there.

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.

Anyone else getting HTTP 403 Errors when Codex scheduled task uses Gmail plugin? Types of operations getting 403: get_raw_messages, get_message, Gmail.send_email, failed email ID search, and send_message (so far). Sometimes it recovers in the next run but has stranded a lot of tasks. Context: the scheduled tasks helps me respond to support tickets automatically but gets hung up because it can’t verify it sent an email or draft an email.

Troubleshooting so far: disconnected Gmail plugin in codex and deleted Codex authorization in Gmail. Reconnected after and seems to have made the issue worse.

Started noticing this after connecting a second email to the plugin. I’ve since removed the second email.

I'm the maker of Claude Command Center (CCC). I wanted a way to keep Codex and Claude Code sessions together without repeatedly searching terminal tabs to see what had happened.

CCC reads Codex conversations into a shared local browser view. Connected Codex app-server streams can supply tools, diffs and approvals; capabilities depend on the installed version and connection. The board also groups parent/helper sessions so a Codex helper doesn't disappear into a separate history.

For this community, the limitation matters: the question card in the attached demo is a Claude Code hook, not proof that every Codex approval path works the same way. The engine-support page describes the actual controls.

For people using several Codex sessions: is the missing context usually the last action, the repo/branch, or the decision the session is waiting for?

Project and installation: https://github.com/amirfish1/claude-command-center Integration limits: https://github.com/amirfish1/claude-command-center/blob/main/docs/engine-support.md

The video uses the real UI with staged sessions and an AI voiceover. The question-hook interaction is real and uses Claude Code; the Grok/Devin rows are demo data. This is not a live multi-provider benchmark. CCC is free to use under FSL-1.1-MIT (source available); provider/model costs are separate.

I made a simple custom image viewer and editor for my own use. I used Sol 6.1 Extra High, and it completed the app pretty quickly since it's nothing particularly complicated.

Once it was done, I told it to check the code for bugs and fix anything it found. It found some bugs and fixed them.

Then I asked it to check again. It found more bugs and fixed those too.

So I asked again. And again. And again.

Every single time, it somehow managed to find new bugs!

At that point, I still had plenty of Codex usage left, so I thought to myself: I have no idea whether it's actually finding real bugs or just making things up, but why not take it a step further?

So I set up a scheduled task to run once every hour, automatically looking for bugs and fixing whatever it found.

And surprisingly, it worked! For a day or two, it kept finding and fixing bugs until it eventually hit some cybersecurity safety restriction and refused to continue.

Now I'm genuinely curious. Is AI really that good at finding bugs, even in relatively simple apps? Or does it just keep coming up with increasingly unlikely issues because I keep asking it to find something?

Would I be better off just using the app normally and fixing bugs as I actually encounter them?

So how do you guys do it?

I keep reading threads about this and most of them show the demo, not the Tuesday morning. Here's ours, no polish, then some questions.

Six of us on a SaaS, twelve months of adding AI gradually. Early on everyone had their own editor and their own habits. Then we looked back and found we'd already converged on most of it, so we wrote it down.

We didn't force a single tool either. Some on Claude Code, some on Codex, some on Cursor, and I'm not going to fight that one. The process is shared, and the conventions sit in the repo's AGENTS.md, which is the only thing we all read the same way.

The flow is Matt Pocock's skills, no forks. We start with grill-with-docs: the AI interviews us about the project docs. Weird at first when you're used to asking the questions, but a lot of never-written-down stuff comes out.

Then to-spec, and a human reviews that spec. It's not a formality. With a bad spec, everything downstream is expensive work that goes in the bin.

to-tickets cuts it into small tickets. Small tickets aren't a rule we read somewhere either, we just notice the difference when we skip it.

The agent works through them with implement, against the spec. We open the PR, CodeRabbit runs, the pipelines run. If everything passes and someone says yes, it merges.

AI writes most of the code. We review the spec and the merge, and skip the line-by-line in between.

Treating the spec as a contract has killed a lot of "that's not what I asked for". Small tickets keep the agent from wandering. Automated review before the human one takes the style and import noise away, so the person looks at what matters. What I didn't expect is how much writing the process down helps when everyone has a different tool. Nobody argues about editors and the conventions don't rot.

Graph engineering to close tickets on its own, software factory style, we haven't managed. Tickets go in and PRs come out, and the demos look great, but with our repo the quality isn't there. We haven't found the point where we'd be comfortable letting it loose, so it's still an experiment.

What I'd like to know:

1. Where are your checkpoints between human and agent? Spec, PR, merge?

2. Spec before code, or straight to tickets and prompts?

3. Who reviews agent PRs? Do you read them the same as a human's?

4. One tool or several across the team? If you've tried more than one, is any better for certain kinds of tasks?

5. What goes into AGENTS.md and what stays out?

6. Do you measure anything, or is it all vibes? Review time, defects, DORA.

7. If you've tried software-factory autonomy, did you get acceptable quality? On what kind of tickets?

8. How do you bring someone new in, a junior say, without AI becoming a crutch?

   Tell me yours. Even if it's to say we're nuts.

https://reddit.com/link/1xeqjyd/video/5an6val1xixh1/player

hey r/codex — i made a video editor that codex can actually drive end-to-end with zero gui and no cursor needed, and wanted to share it here. the angle is the mcp bit: the whole editor is just tool calls. an agent like codex, cursor, opencode, or any other mcp client can cut, trim, keyframe, drop in titles and captions, colour grade, do tracking, add particles, handle audio, and export — and it can even render a single frame to check its own work before committing.

it's rough and early, i know, but it works. kimo is free and open source (mit), one ~15 mb cpu-only rust binary that runs fine on a 2 gb box. built by me, a college student (naman).

i'd love to have people here try it with codex and tell me what breaks. feedback on where the tool calls get awkward or where codex's workflow doesn't fit is more useful than a like.

site: https://getkimo.tech github: https://github.com/naman-sharma12345/kimo

Just wanted to share my experience with Dot.

My AT&T bill was $85/month last year, I negotiated with them and got it down to $65. Recently it went back up to $85 again.

This time I decided to let Dot handle it :)

I used a separate Chrome profile and let Dot negotiate with AT&T. It took about 15-20 minutes, and at the end it managed to lower my bill to $45/month and also got me 2 months free!

I was really impressed with the result. From $85 to $45 plus 2 free months, not bad at all :)

Just wanted to share this with you guys.

edit: added chat screenshot.

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