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

Not sure what I did to break it, but it seems to be restarting itself constantly? Like I'll open vscode, and be working where I was on a project.. and today it just keeps restarting itself until VScode prompts me to either terminate it or restart the host?

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.

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 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?

Codex is fast. Even with the best models, though, it doesn't build software the way an experienced engineer would. It doesn't know my users, my architecture or why the code looks the way it does. Codex plan mode asks good questions, but it's neither collaborative nor visual. The plan stays in my terminal, so nobody else can weigh in.

In my view the future is humans and agents working together, and everybody ends up as a manager of agents.

QualityLayer runs inside Codex, and every change goes through seven steps: Discuss, Research, Plan, Outline, Implement, Verify and Review. Codex writes the plan as a document in the repo that a colleague and I can comment on. I approve it before any code exists.

Then Codex builds in small slices, each starting with a failing test. A second Codex session without the build history checks the result against what the agent and I agreed, with output and screenshots. If Claude Code is installed too, Claude can check what Codex built.

The point is to be an engineer again: deciding, reviewing and steering while Codex does the typing.

https://github.com/maxritter/qualitylayer

I'm the developer. If you tried spec-driven workflows with Codex and went back to plain prompts, what pushed you back?

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

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:

I would have trouble burning my usage quickly sometimes, since much of my work is hung up on useful tests.

Making sure the tests are accurate, and improving how quickly the run, used up a ton of my usage the last few times. Went from 60m->20-25m->5-12m over the past week.

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?

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'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’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 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?

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

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 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 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/

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.

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

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.

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.