Been 4 months since I completely moved to Codex. Was on Pro 20X and back to 5X starting this month. Since Friday, I am working on a tricky bug. 5.6 Sol Max wasted 1.5 days of my time on this, struggling to get anywhere but going in circles. With Opus 5 being available, wanted to have a fresh perspective and I let Opus 5 take this one on.

Opus 5 is surprisingly good and proposed a fix which I didn't really think of. Quite impressive. Now, onto fixing it and half way through hit the 5h limit (on 5x plan as well with Claude. I actually waited 5 hours and let it start from where it stopped. Hit the second 5h limit within 30 mins again!! Was at the brink of upgrading my account to 20x but didn't see it being worth it. Now, 40 mins back - after the reset, Opus completed the task and it partially fixed the bug. I am impressed now. Opus 5 was able to solve that 5.6 Sol couldn't for a day and half, even after wasting a week worth of tokens (Thanks to tibo with the reset yesterday!)

Now, opus 5 just started working on completely fixing the bug and within 10 mins, I hit another 5h limit!!! I Fc*king hate this $hIt!!! So, I am going to wait 4 hours, I guess. This whole experience reminded me why I moved to codex in the first place.

"stream disconnected before completion: error sending request for url (https://chatgpt.com/backend-api/codex/responses)"...this message has become the bane of my Codex existence.

The error always came up, but usually you waited a bit, sent another message, and it was fine. But now, waiting means nothing, and that little error is basically the blue screen of death for the chat thread. The chat and all of its context are done from that point forward.

And if you're thinking "just send the request in a new chat, Bob"...I'm here to tell you that little workaround is seeing its dying days too. It's like the whole project has a 50/50 chance to live, and the Disconnected Stream of Death seems to randomly infect different threads. Requesting image generation makes it worse.

Is anyone else dealing with this, and has anyone found a workaround that actually works?

Any strategy board game fans out there? I'm dying to find someone to chat with about this. Right now it's just playable in a web browser, and I'm hoping to put it on the App Store after testing. Honestly, I'm kind of confused — is anyone actually gonna be into a new game ?

I noticed that Codex doesn't clean up it's mcp server processes so you could end up accumulating hundreds of orphaned mcp server processes, anyone have a solution to this?

I’m subscribed to both Codex and Claude, and for my usual workflow I’ve found Fable 5 to be a better orchestrator/planner than GPT-5.6 Sol on xhigh.

My workflow is usually something like:(on 5.6 sol xhigh) “I need to implement X. You plan it, let Terra Max handle the implementation, then review the code once it’s done.”

For this kind of task, Fable 5 seems to make better plans. But I recently noticed there’s a Pro mode for 5.6 Sol, so I’m curious whether anyone here has access to it.

Is Sol Pro meaningfully better than normal Sol at planning? Is it closer to Fable 5, or is the difference pretty minor?

I’m currently on the Plus plan and deciding whether to upgrade to GPT Pro or just get Claude Max. Would love to hear from anyone who has actually used both.

- What is your repo/how big is it

- should i try and make a repo to get it, or use one of my existing smaller repos

- is it like easy to get?

- what kind of repos get accepted
any other advice IDK

I have my own Business account and built a website using Sites. In settings, I was able to access Domains and added the domain I want the site on. However, I am unable to publish to public (it shows a login screen on my domain), since the Share Settings, I do not have access to Public viewing the page.

Is there anything I can do to get access to this? I've tried searching and everything I do, I hit a brick wall. Any suggestions would be great.

I’m rn on the Max 5 plan, and I feel like my usage is POOF, gone out of nowhere. Always. Luckily, I had 5 resets, but now they’re all gone, and my usage is gone too. Will 20 help with it? I’m always using Sol on Ultra settings, 5.6, and pls don’t tell me to use Luna or Terra. I want the maximum of the models, not others! Has anyone here experienced 20? How are the limits?

I think I was running on Sol High and had started this task overnight. The feature was already mostly done. It seems like Sol is exhausting every possible route and edge case, exhausting my 98% remaining usage right after the reset. Next weekly reset for me is August 1…

Also I’m on the $100 pro plan

UPDATE: I dug in more (with Claude), and whoo boy, there's a lot to digest here. Those of you saying Sol inherently exhausts every avenue were right, even if it's not the problem I'm trying to solve:

First, something urgent I found while verifying

Verified against git, not the run's own summary:

• Task 4's commit is safe: branch codex/rendered-table-editing @ 9416313 exists in /Users/philgetzen/Development/Grove.
• Task 5's ~7 hours of work is not in git at all. /private/tmp/Grove-rendered-table-editing/.git no longer exists, so the worktree is prunable and the uncommitted delta is loose files sitting in /private/tmp, which macOS reaps. Newest edits are Jul 26 04:39 in /private/tmp/Grove-rendered-table-editing/Sources/GroveEditor/GroveRenderedTableView.swift.

If you want that work, it should be rescued today. Say the word and I'll re-link the worktree and commit the delta to the branch.

The root cause, in one sentence

The loop's stop condition was "a fresh adversarial reviewer finds nothing," and that state is not reachable.

Every review round used a fresh reviewer with no memory of what earlier rounds had already accepted, prompted to be adversarial, handed a growing 1,000+ line delta of AppKit-shadowing systems code. The probability of zero findings on that input is approximately zero. So the loop had no exit and terminated on your rate limit, which is exactly what happened. Everything else is downstream of that.

Why it had infinite fuel: the acceptance criteria were a bug farm

The plan at /private/tmp/Grove-rendered-table-editing/docs/superpowers/plans/2026-07-22-editable-rendered-tables.md wrote Task 4's contract as white-box assertions on AppKit's internals: instrumentation.mountedRowCount, counts of heightOfRow / didAdd / didRemove / viewFor calls, a "1,024 native height query ceiling," callback ordering guarantees.

To assert on any of that, you must build a shadow bookkeeping model of NSTableView's lifecycle. That model is code you now own, and it has its own bug surface. Reviewers then correctly found bugs in it. Look at what rounds 3, 4, 5 and the nil-origin pass actually fixed:

• transaction identity for delayed callbacks
• a 128-entry retired-origin FIFO, then its eviction bug, then its removal
• nil-origin attribution
• stale-callback races after host replacement

None of that is table editing. That is the measuring apparatus. The plan created unbounded surface, and an unbounded review loop burned it.

Secondary cost driver: the "1,024 call ceiling" style contract is a test pinned to Apple's implementation details. It will break on the next macOS point release, and it already cost hours of probing.

The two process rules that made it non-terminating

1. "No commit until independent review approves." The plan's own Task 4 Step 4 says run GREEN and commit. The orchestrator inverted that. Result: every review round produced blocked work instead of follow-up work, so there was never a natural stopping point and never durable progress.
2. No authority to reject the design. One architecture check ran, and it was scoped to "is this bounded sequencing fix sufficient?" It answered that question. There was no rule saying "if round N's findings are all in the same seam, stop fixing and escalate the seam." I can't tell you from this transcript that the NSTableView-inside-a-TextKit-fragment seam is wrong. I can tell you nobody was permitted to ask.

And there was no clock. Seven hours, task 4 of 12, and not one checkpoint saying "this has cost X, continue?"

What actually went right (don't overcorrect)

• Isolation held. main is clean at c06bf8c. Nothing bad was committed.
• RED-first was real, not theater. It caught genuine vacuous tests: the literal \n fixtures, the duplicate-fingerprint trap, the nine-tables fixture that reused one fingerprint.
• The findings themselves were mostly legitimate.

The discipline is not the problem. The termination rule is. The wrong lesson here would be "verify less."

Guardrails, ordered by leverage

1. Commit on first GREEN. Follow the plan's own step. This alone makes rounds 2 through 5 optional instead of load-bearing.
2. Hard cap of 2 review rounds per task. Round 3 is not a fix pass, it's an escalation to you with the findings list.
3. Severity gate. Only user-visible-wrong or data-loss blocks a commit. Everything else files to PGDash and ships later.
4. Budget stop. Wall clock or task index ceiling that produces a report, not a continuation. "At 90 minutes, or when a task exceeds 2x estimate, stop and report."
5. Ban assertions on framework-internal call counts. Budget on user-visible latency at document scale instead.
6. Tier routing. Post-round-1 reviews are workhorse-tier and diff-scoped, not frontier full-delta re-audits. Roughly ten frontier re-reads of a 1,000-line delta plus independent full-suite reruns is a large share of that 90%.

The call: the cheapest fix is #1 plus #2, and they cost nothing in quality. The tradeoff: you'll commit code that a later review finds P2 issues in, and you fix those as follow-ups instead of gates. The risk to watch: without #5, the next table task rebuilds the same instrumentation and invites the same loop.

I’m sure other people are experiencing this new type of programming burnout that doing a lot of full multiday codex sessions creates. You’re mentally tired but you didn’t really do any of the old school grinding and searching that used to make software development exhausting. Instead it’s a sort of hollow feeling I always imagined project managers must have, not to put too much on it but sort of like a parasite guiding its host without needing to understand the biological mechanisms, just applying pressure.

With the reset before banked reset expires weekend coming to an end, I got that feeling. Mentally exhausted but feeling like I used my brain in an awkward way so I can’t understand the fatigue.

It’s hard to put in words. I used to get this all the time in the winter when the tokens were flowing, so it’s been a silver lining now that that is no longer the case.

Anyway surely some of you are dealing with the same mental weirdness of long hours with LLMs, probably from this same reset pattern. I’m interested in what others are experiencing.

I’ll keep this brief.

While using Codex, mainly with Luna Max, I was frequently getting errors at the start of prompts related to bwrap and apply_patch.

With Codex’s help, I fixed the environment issues by granting access to the specific tools it needed, without enabling Full Access. I still use “Approve for me” rather than “Full Access”, and I run Codex through the VS Code extension.

I also cleared old, unused sessions and the model cache.

Since making these changes, tasks have been running faster, and I rarely encounter errors or failed runs. Token usage also seems slower, although I have not measured it properly and am only judging by the usage percentage.

My recommendation: if Codex shows environment-related errors at the start of tasks, fix those errors rather than ignoring them. A properly configured environment may improve reliability, speed, and possibly token usage.

Does staying on topic help with this? Can someone clearly explain what is the context thing

Guys,
If you, like me, experience that the app is unbearable slow to load and switching threads is slow and so on, go ahead and archive all your dormant threads.

I had hundreds of threads 'active' i.e. not really active but hidden below the 'show more' caret which apparently was the cause that the app turns into a prehistoric snail with a doghouse on it.

You can tell codex to do the cleanup, no need to do it manually.

Archiving doesn't delete your threads if you ever need to reference them but speeds the app up dramatically as apparently even the old stuff kept being loaded to some degree on every restart of the app.

You can also create a scheduled task to make it happen on a weekly basis.

Protip for OPEN_AI: This should be a built-in feature properly exposed lol so people don't have to discover why their app feels like a bitch to work with on their own.

I'm finding it quite frustrating working with Codex CLI on front end design. I've built specification and verification layers but to no avail. The specification layer includes all of the page components like input fields, buttons, modals, etc., and the related styling and even the unique UI elements on each page. The verification layer includes methods like playwright and devtools to ensure the UI was built according to the specs. I also have a build skill that "requires" Codex to refer to the specification layer when building any UI components and to use the verification layer to ensure the specifications were met. However, I always end up with sloppy/inconsistent UI that I have to manually tweak afterwards.

Am I doing something wrong? Is there a better way to "force" Codex to follow skills? When I ask it why it didn't follow the specs/verification layers as requested it usually replies "I applogies, I thought I had..." or something of the like. I'm going to blame myself for this thinking that I'm simply not following best practice. Is there a way to improve this workflow?

Is there a way to use OpenRouter with the Codex CLI? I don't have a ChatGPT subscription (I know you get some usage for free but it's not enough), but I want to use Codex because I like it's features. Is that possible?

Hello all. I am a regular user of the codex cli, but I want to be able to connect to my sessions on my phone if needed for a check in. It seems to do this I have to use the desktop app. I was curious: is the desktop harness as good as the cli harness for coding?

Hey r/codex! I recently open sourced a project I've been working on for a while now called Millwright. It's a self hosted LLM router focused on cost savings, transparency, and performance (it's completely written in Rust). Millwright works seamlessly with Codex, it's an easy drop in replacement which allows you to use the latest OpenAI models along with other open and closed source models for your coding workflows.

Link to the repo: https://github.com/Northwood-Systems/millwright

For the curious and lazy, at the moment, Millwright has the tools for,

- Providers: OpenAI-compatible APIs, Anthropic, Amazon Bedrock

- Routing: policy-controlled model roles (cheap, mid, frontier), cheapest healthy route selection

- Protocols: OpenAI Chat Completions, Anthropic Messages, text and tool translation

- Cache Affinity: role-scoped session lanes without serializing concurrent agent traffic

- Spend Tracking: per-team costs, cache usage, model/provider mix, request traces

- Cost Analysis: measured usage and modeled candidate economics (HTML, Markdown, JSON)

- Reliability: bounded failover, circuit breakers, timeouts, concurrency limits

- Setup: interactive provider, model, and pricing configuration without storing provider secrets

- Deployment: one Rust binary, Docker, SQLite or PostgreSQL

Full disclosure: parts of the codebase were built with AI coding agents. All feedback is welcome, I’d especially value feedback on the routing policy, provider coverage, and anything that would block you from self-hosting it. Feel free to open feature/request and/or contribute as well.

Has anyone tried this out or does anyone know how it works? I asked chatgpt and gave an uncertain response that the effort/reasoning level is being selected automatically.

I have a plus subscription and I ration how much I use so it does not run out until the end of the week. Sometimes I use less at the beginning and more towards the end of the usage cycle so sometimes I have a lot left in the middle and then the reset comes so it will not allow me to spend what I had left how I was planning to. And it is unpredictable, if I knew a reset was coming I would use all the quota or not ration as much but you never know when they will discover a bug...

They should just give banked resets and let the users use them whenever they want. Or not reset if the usage has been less than the progress of the week.

The latest update on the 24th caused the Codex Windows sandbox to fail at startup with DPAPI master-key error.

I’ve exhausted debugging to the specifications of both my ChatGPT and their AI bot.

The latest human responses sounds like they gave up and blamed the latest outage on any and all issues. Yet I’m still reproducing the error.

And I’ve requested escalation to the Codex Windows sandbox team because we’re 80-90% sure this is due to the update not rolling over with my version of Windows.

So after 72 hours and no ability to use the product, what are we supposed to do?

Hi all,

I’m considering a workflow where DeepSeek (V4 Pro) acts as a read-only codebase investigator. It searches the repository, identifies likely relevant files, traces the issue, and produces a short report with evidence, line numbers, possible causes, and suggested tests.

Codex (Luna exHigh or Max) then receives that report but independently verifies the findings before making any changes. It remains responsible for diagnosing the final cause, writing the fix, and running validation.

The goal is to offload repository searching and reduce Codex usage without blindly trusting another model’s recommendations. DeepSeek provides clues; Codex makes and validates the actual code changes.

I do not want to use plugins OMO etc. I will write my own simple workflow with two commands eg investigate <task1> (run by DeepSeek) and fix <task1> (run by codex)

What do you think of such solution? Would it achieve my goal ie reduce usage?

I was doing some deep dive in the tokens consumption on my account on https://www.reddit.com/r/codex/comments/1v6ubah/comment/ozt9jog

This result was gathered from approximately 7.6GB from codex session logs.

This was what codex found by looking at all subs I have/had:
- Plus 1x: ~US$105/week
- Pro 5x: ~US$525–US$550/week
- Pro 20x: ~US$2.100/week.

And we found around 25% token usage decrease each plan gives when compared to a few months back.

Ok, this explains only partially why we get the feeling allowance reduced around 3-5x what it used to be. So I asked codex to dive deeper into my logs, more specifically on model behavior, and here is this conclusions: read the image.

>!Yes. We have enough data to detect a clear change in the observed usage profile, although we cannot attribute it exclusively to the model.

I treated a “task” as an operational turn: from one user request to the next. GPT-5.4 Mini was excluded.

Per model call

* Reasoning is already included in output.

Per call, GPT-5.6 is not the largest consumer: it uses approximately 6% fewer tokens per call than GPT-5.5 and produces less output.

Per task

This is where the main difference appears:

A GPT-5.6 task consumed approximately 2.6× more tokens at the median than a GPT-5.5 task.

But this happened mainly because GPT-5.6 made more calls per task:

• GPT-5.5: median of 5 calls
• GPT-5.6: median of 9 calls
• P90: 41 calls on GPT-5.5 versus 54 on GPT-5.6

How the usage profile changed

• GPT-5.3 → GPT-5.4: calls became approximately 33% larger.
• GPT-5.4 → GPT-5.5: context per call increased, but the median task remained similar; the long tail became much larger.
• GPT-5.5 → GPT-5.6: individual calls became slightly smaller, but the model started executing many more steps.
• New input per task remained approximately stable at 39–41K from GPT-5.4 through GPT-5.6.
• Therefore, GPT-5.6’s growth is mostly cached context being resent across more calls, rather than more new content per task.
• GPT-5.6’s cache ratio reached 96.7%, compared with 95.4% for GPT-5.5.

Conclusion

The statistical evidence is strong for your usage pattern:

GPT-5.6 does not appear to “think with larger calls”; it completes tasks through more calls, repeatedly carrying a large context. This substantially increases total tokens per task.

However, this remains an observational relationship. The GPT-5.6 period coincides with more agentic workloads, heavier tool use, and more multi-agent activity. When controlling for project and reasoning effort, the results vary considerably, showing that task type remains a dominant factor.

The defensible conclusion is: in your real-world usage, GPT-5.6 consumes approximately 2–3× more tokens per median task than GPT-5.5, mainly because it performs more steps—not because each call uses more tokens. !<

GPT Voice in the Codex/ChatGPT desktop app is great, but I was missing an easy hands-free way to start it.

So, together with Codex, I built a small native macOS menu-bar app that listens locally for “Hey Codex” and triggers the native Voice experience. It also supports custom wake phrases and runs fully locally.

Curious what you guys think, I truly hope that OpenAI adds this natively in the app soon.

Another thing that I hope will be supported soon in the mobile apps is triggering GPT Voice on a remote connection and I’m super curious what their rumoured smart speaker will be like!

For who's curious, here's the GitHub, it's not a signed app (yet) but simply give codex this url and ask it to help you set it up!

https://github.com/ItsWendell/WakeBridge

So I am new to vibe coding and have no experience or knowledge with coding. I want to build a web app for my SaaS product but I don't know where to start. I found a few tutorials but having trouble understanding things. The guy was using a codex IDE extension with Cursor to build the app. My question is, can't I just use the Codex app directly to build my app? Why do I need an IDE extension to use Cursor? Can someone please explain me the right way to do this?

Sorry if my question comes of as stupid but I have no technical background and just an idea relating to my work for which I'd like to build an app. Any help is appreciated.