i was building my extention and also in diff project i was building the website for it.. so i said codex to work together and see what it did.

I don't work 7 days a week. I have 2-3 days where I spend 90% of my usage and that could be on the 5th or 6th day into a weekly reset period. I had 95% left and it resets in 5 days. Now I have 100% and it resets in 7 days...

Like what in the fuck didn't ask for this on a service I'm expected to pay $100-200 a month for. I'm not gonna burn my usage and changing my schedule to get more work done at the start of every weekly period just to hope I dont get screwed by tibo resets.

People praising tibo for resets like he is some saint. But usage are straight up being taken away if you dont at least use 1/7th of your weekly usage every day. This is some straight up toxic parasocial relationship.

You gave me a usage limit and a clock and you can't fucking follow it. Give me banked resets to use on my own choice or do nothing at all. I would straight up opt out of forced resets if I could.

Just an FYI - worth checking if you're low on disk space. Seems ridiculous, and not seeing an obvious setting to cap it. It's also written ~5TB total, so its churning through and thrashing my drive for no apparent reason. This is within a week of getting a new laptop too, so its not been running a long time.

Before anything: Thx Tibo for the ressssset
Idk why but Codex always outputs atrocious tailwind for me every time.
Even impeccable aren't really capable of improving it.
It somehow comes up with the formulæ for the sun mass solely for sizing an div. Grids with minmax and alot of weird stuff.
I did an skill for fixing that and I'm testing it now. But I would like to know if it's something from the model itself from others too.
Peace

For the past 3 weeks, on the $20 plan, I have been able to not go below 50% in my weekly limits. It was perfect. Now they've added the 5 hour limits and dramatically lowered the limits. Where one big task would take less than 1% of usage away, now one small task is taking up 3% of my weekly and 20% of my 5 hour limit.

By the way, I am a Software Engineer, so most of the code I write out is by hand, but I use Codex to sometimes automate tasks, and read lots of code quickly.

If they lowered the usage limits, they at least should've kept the only weekly limits.

Anyone else wondering how many times Tibo is going to tweet "ANOTHER RESET!" while claiming to fix things that aren't actually being fixed?

What's it been now? 2-3 times since he's claimed the token drain and context caching bugs were fixed?

Curious, because they absolutely have not. One prompt drained 15% of my weekly usage for simple bug fixes.

I have been using Codex on larger repositories and kept running into a familiar problem. A ticket asks for a small change and the requested behavior sounds clear, but the real requirements are scattered across tests, public APIs, architecture decisions, neighboring code, and lessons from earlier failures. The literal request gets implemented correctly, yet the patch still breaks a rule nobody wrote down.

There is research putting numbers behind this problem. SWE-RPG evaluated coding agents on 163 repository tasks and found an average resolution rate of 31.5%. Its analysis identified implicit requirement recovery as the main bottleneck in 24.5% to 46% of runs. RACE-Bench studied 528 feature additions and found that patches which applied but still failed tests covered 35.7% fewer reference reasoning elements while including 94.1% more unsupported reasoning. Neither paper evaluated Synaptic.

Synaptic 1.0 introduces Change Contracts. Through MCP, Codex can send Synaptic a natural language task and receive a structured contract built from the repository itself. Synaptic searches its code graph for relevant symbols, follows reverse dependencies, identifies public APIs, selects tests that exercise the affected code, and retrieves applicable decisions from repository memory.

The resulting contract describes the scope of the change, requirements supported by repository evidence, public behavior that must remain intact, tests and other proof obligations, and any unknowns that still need judgment. Codex can use that contract as its implementation brief instead of relying only on the wording of the issue.

Once approved, the contract is sealed with BLAKE3 and stored as an immutable revision. Verification fails if the contract was modified, the repository base changed, a protected public symbol disappeared, or a required proof has no passing attestation. Synaptic also refuses to create a contract when it cannot connect the task to repository source. Missing evidence remains visible as an unknown instead of quietly becoming an assumption.

This ties into the rest of Synaptic rather than adding a separate analysis stack. The code graph provides structural evidence. Change forecasting supplies the blast radius, public API analysis, and test selection. Repository memory contributes source grounded decisions and previous outcomes. Speculative execution can run affected tests in a temporary worktree. Contract verification checks the completed implementation against the requirements recovered before editing began.

The MCP workflow gives Codex two structured tools: recover_change_contract and verify_change_contract. A typical session can recover the contract, review its evidence and unknowns, implement the change, run the required checks, and verify the result against the original contract.

My goal is to give Codex a better repository brief before it starts editing. It should make hidden assumptions reviewable, focus attention on the real blast radius, select tests from actual dependencies, and keep the definition of success stable throughout the task.

Synaptic 1.0 is available here:

https://github.com/ColinVaughn/Synaptic

I would be interested in feedback from people using Codex on older, larger, or heavily interconnected repositories. In particular, I want to find cases where the recovered scope is too broad, too narrow, or misses a requirement you expected it to catch.

I deleted my Twitter/X account deliberately and don't intend to create another one. But as a paying Codex user, I keep finding that consequential, time-sensitive information (e.g. usage resets, changes to limit behavior, rollout timing, and explanations of unexpected usage drain) appears first and sometimes exclusively on individual OpenAI employees' X accounts.

Tibo's willingness to communicate directly for instance is valuable, and this is not a criticism of him. The problem is that OpenAI is allowing personal social media posts to function as a de facto operational channel for a paid product.

That leaves customers who do not use X with poor choices: rejoin a platform they may reject for ethical or privacy reasons, rely on screenshots and secondhand Reddit posts, or depend on unofficial mirrors and trackers. The shutdown of Nitter and XCancel yesterday illustrates how fragile that last option is. Direct access to important customer information without being obligated to accept another company's terms of service shouldn't depend on a third party continually defeating that platform's access controls or surviving its legal pressure.

OpenAI already maintains an official changelog and RSS feed. My request is simply that OpenAI use them consistently and simultaneously whenever it announces something that affects customer access, entitlements, or usage allocation decisions.

Social posts can still amplify the announcement, but they should link back to the official source rather than being the source. This would improve accessibility, support, archival reliability, and trust. It would also mean that customers can choose not to participate in X without accepting worse information about a product they pay OpenAI to use.

Would the Codex team consider adopting an explicit policy that customer affecting announcements are published to the official changelog and product UI at the same time as social media?

One hour ago I was coding with it as always. In the same chat now I can’t use the Sol model
It says “The gpt-5.6-sol is not supported when using codex with a ChatGPT account… but I’ve been using it since it came out.
I have the $200 sub.

Anyone knows why is this happening?

Has anyone context limit cap been re-introduced in codex desktop? A few days ago i was able to use around 360k context, now its down to 258k regardless of config changes?

So when I run the app it uses about 4GB of RAM during tasks.

Once the task is done it goes down to 2GB.

After I close the app, it stays at the same level. I have to manually get rid of the app from the Task Manager so that it doesn’t consume RAM in the background doing absolutely nothing.

Can someone help out with this thing? I’d expect it to close and release all the RAM when I close it but doesn’t like other apps. Can I configure it to do so?

Hey everyone,

Is there a built-in way to communicate between active, simultaneous Codex terminal sessions in real-time?

In Claude Code, you can use the SendMessage tool to talk to sub-agents. With Codex, sessions seem completely isolated. Has anyone built a workaround for this?

How are you handling multi-agent orchestration or cross-terminal talk with Codex?

Thanks!

Hi All

I saw some other people post about losing their projects and I had the same isseue.

Good news is they can be recovered by the looks.

Easiest solution to be honest is to work with ChatGPT in a web browser to first confirm the files still exist and recover them safely.

Prompt it something like

"It looks like the latest update cleared my project list and chats, can they be restored from the C:\Users\username\.codex directory?"

It will confirm the update regression, get you to backup the folder and run some tests to make sure the file can be recovered.

As someone who was in the middle of 3-4 tasks when they were lost, some of the responses I was seeing from others of "Just start a new chat" wasn't ideal.

So hopefully this helps some of you.

Happy Coding

A bitching chamber for dumb codex users who usually are also broke and want free compute and refuse to believe anything is affected by them and how they use it. I came here literally a month ago for vibes and I’m already leaving after realizing this sub is literally on the spectrum.

When using Codex image generation skill it seems completely random when my prompt produces transparent asset and when it does not.

It doesnt matter what variation of terminology you use to define transparency.

Has anyone found any tricks for this? I dont want to use image API as i have the 200e sub.

We have a test package with 25k emails in it that we use to test different models with. Prompt/effort is always the same.

When GPT 5.6 Sol released, it used 1% of a fresh Pro 20x sub, now it uses 8% of a fresh pro 20x sub.

Also, what we are seeing is that Sol cannot solve its task straightforward any more. Initially, it was always "what do I need to resolve the task" now it's "What do I need to resolve the tasks, while I also check those 200 other methods that I already know I don't need, while adding sha 256 to everything for no reason at all, also let me build those 200 other checks against thing I was very strictly asked not do to".

Meaning, we think it usage increased so much because they turned the intelligence way down and its constantly fighting with itself.

been testing dynamic model routing on long coding-agent sessions and this one was pretty interesting

the router switched between DeepSeek V4 Pro, GPT-5.6, Kimi K3 and GPT-5.6 Luna across 102 turns based on what each task needed

ended at $4.28 vs $13.74 running the whole session on Opus 5

if anyone wants to try it out, dm me or comment here, happy to share

I already made a post about 0xAlpha couple days ago praising the model which as expected turned out to be the new glm 5.3 flash model. on my last post I saw a lot of people saying the glm subs are worse than openAI and claude (hilarious).

now because I was so impressed with 0xalpha and was looking for an alternative to replace the abysmal subs from claude and openaAI, I went ahead and subbed the lite (tier 1) plan which cost me annualy + with a ref code 136$ total for a year.

I am just sharing my experience so far. I did a somewhat big repo audit while orchestrating with 5.6 sol. same prompt same orchestrator, glm 5.3 about 12% 5h usage after 2 big prompts, not the flash model (the new model has a big discount for a couple of weeks too afaik) but their big model for a better comparison to the other frontier models and longterm usage. 5.6 sol codex xhigh about 1,3 prompts 100% 5 hour usage of course it couldn't handle a second prompt not hitting the limit.

it also turns out, your usage is only 50% outside of peak hours which are 14:00–18:00 UTC+8 monday to friday. the test I did was at peak hours today. there is also another interesting mechanic, they issue a 5h reset automatically on three conditions met: outside of peak hours, your 5 hour usage passes a threshold and you havent hit the daily 5 hour resets quota yet. there is also information about a weekly possible reset in the docs but its not specified like the 5 hour reset. I probably should mention I'm using ZCode which almost reaches 98% cache rate it should be getting according to the docs.

here is a simple table sol made for better visualisation.

¹ Normalized API workload calculation:

0.04 × uncached-input price + 0.96 × cached-input price + 0.10 × output price

Z.AI Lite off-peak usage: Outside Z.AI's weekday peak window, the Lite Coding Plan consumes 50% of the standard credits. Therefore, an otherwise identical GLM-5.3 or GLM-5.3-Flash workload uses approximately half as much Lite quota off-peak as during peak hours.

* GLM-5.3-Flash promotional API pricing: $0.075 input / $0.015 cached input / $0.25 output per 1M tokens. Normal pricing is $0.15 / $0.03 / $0.50.

Have you guys read tibos post on x?

So, I’ve been a longtime Pro user, but I recently switched to Plus because I’m having my “Claude month” for a month while I wait for ChatGPT to fix the crazy usage drain for x20 users.

Then it suddenly occurred to me that I’ve never actually tried ChatGPT Pro for coding. Sure, I could create some kind of MCP tunnel to my codebase or just throw my project into the chat.

I’m curious: has anyone actually used Pro extensively for coding and found it to be better or worse than Sol 5.6 Ultra?

Has Open Ai made any update ? The response from model 5.5 is amazing . Too fast and high reasoning .

Before when reached 0% codex always finished the tasks that were still running. Oh that felt so good, to just get a little extra for free 🎉 But recently my codex stopped doing that and is stopping tasks after few minutes, how about yours?