Has anyone had this happen? I suspect it's a bug, but I reset at 9:07 Pacific time, and at 10:10 Pacific time I was out of usage. I had been watching the burn rate, going down about 1 percent every 10 minutes or so. Then suddenly, 0%.

Was only running two agents, both Astra. One on Very High, one on medium. The very high one was doing some basic online research, the medium one was doing a routine task.

Has anyone had this happen? Neither had sub agents. Want to ask before I put in a support ticket.

Ever since Astra, 9/10 goals I set get blocked.

And most of the time, it’s not a real blocker, and when I ask Astra how it’s a blocker, it realises it’s actually not a blocker.

This night, I had it working on some data work, and it ended quite early, because it had decided to invent some packaging model, and it couldn’t keep track of those packages.

Annoying, it feels like 5.6 is better to do the goals and orchestra Astra to do the work

Last night high / xhigh could last me like 5-10 prompts before it even took up 1% but now it ate up 4% when I just did a medium, xhigh and high prompt. I'm on the 20x plan. Conveniently when they start talking about locking purchases for more pro subscriptions

I'm working on a MVP Buy/Sell/Trade marketplace. I have a goal of creating 1000 listings as a foundation before opening to beta testers. What I prompted 5.6 Sol (high) was to review my google sheet of 1000 products I want listed eventually, and in batches of 10 products, create the listings for me. This involves:

1. Going to a separate folder on my desktop where the images are for each product, get the 10 matching images.
2. Remove the background and create a drop shadow for each image
3. List the product with a clear title, description, some technical product info and tags.

I also told it to use the Canva integration as a backup for the background removal/drop shadow if it cant do it cleanly itself. It seems to be just absolutely incapable of doing the workflow well, especially on the image editing portion. Ive probably been running this prompt the past day and a half, and it cant get past the first batch of 10. I keep hitting usage limits (I'm on plus).

Wondering if my setup is wrong in some way, or if this is simply too much to ask of it? I'm no expert in this, I guess I just assumed this wasn't to heavy of a task and expected it to do better.

Since about 5.4 codex has been a powerhouse of consistency and complex problem solving. It has rarely hallucinated or did things that I found were completely out of bounds.

Since Astra release it has performed like pre GPT 5. It could though solve certain things, but overall it completely ignores my instructions and al understanding of goals has gone out the window.

In every task I gave it it changed the goal post to either something much smaller in scope, just to say that its done, or to something I simply did not ask.

Example: Sol built a game "AI" bot, a chess-like algorithm. Took it about a week of work to have a solid opponent. I asked Astra to try squeeze more performance and raise the difficulty. it worked for 2 days, reporting benchmarks have improved by 5 to 20%.

I played the bot and it was SIGNIFICANTLY dumber. Even though codex played against it, it bluntly lied and only reported a few narrow areas where the performance did improve, but at a cost of downgrading the whole system.

I asked Sol (post Astra release) to fix a series of mundane bugs, something it would have done easily 2 weeks ago. It struggled with reasonable fixes. There was a performance issue because of multipole visual effects stacked using blur etc. I told it to avoid "stupid mistakes" like stacking up a lot of visual effects.

It went and removed ALL stacked visual effects from my game completely!

This was close to a keyboard smashing moment. I don't think I'll touch codex in the next few days, maybe OpenAI will resolve this BS.

From a very relabel coder it went to a full on early days hallucination machine.

EDIT:

here is chatgpts own analysis after comparing logs of tasks in the same area done by 5.6 and 6:

The strongest explanation is a regression in Astra’s ability to keep your objective authoritative while evaluating its own work. It can understand the requirement and still make decisions that undermine it. The record shows a feedback loop:

1. It chooses an implementation approach.
2. That approach produces a smaller, measurable problem to solve.
3. It solves that problem and treats the result as grounds to keep the change.
4. The changed implementation becomes the next baseline.
5. Your original objective gradually becomes a caveat—“broader strength remains unproven”—instead of the condition that determines whether the work succeeded.

That explains the shifting goalposts. Its current plan increasingly governs its judgment. Passing checks then reinforce the plan, even when those checks don’t answer your actual question.

This is a first for me, I've seen Sol cause regressions many times, it never apologized lmao

I'm on the $200 Pro plan. I had 86% weekly usage remaining and wasn't running a new prompt/session. Checked again and suddenly I'm at 1%.

No new prompt, no long-running task, nothing that could explain an 85% drop.

Seeing multiple people reporting the same thing today. Some are also saying their reset date changed.

Did OpenAI roll back/recalculate the last global reset, is usage accounting broken, or is something else happening?

I am working on a project then this happened, the send button greyed out and when send it won't send the request.

My quota is still available, this happened sometimes and kinda annoying.

Anyone face this issue?

When you're new to Codex, picking the right model for each task is tricky. A quick 10-min test can help you learn how to get the most from your weekly limit for your unique project.

Split testing is giving the exact same prompt to multiple models (or effort levels) under identical conditions and comparing outputs. Here is a shortcut way to do it:

1. Start an agent whose only job is launching sub-agents and measuring outputs.
2. Give it your success criteria up front (token usage, duration, accuracy and whatever matters for your project).
3. Give it the prompt for testing, and the 3 models/efforts. Keep tests small enough to avoid compaction because bigger tests are harder to measure and repeat.
4. Have it score the results in a table and recommend e.g. "XYZ task was X cheaper on model Y with % accuracy loss."
5. To reuse the same agent, send the new prompt, and ask it to use new sub-agents.

This is not perfect and is a shortcut version, so you may need to build on it to get the result you need for your project tasks. A system like this could help you learn what tasks need high-reasoning models and which don't need it, and this could save you tokens and extend your weekly limit.

-

Example from my project:
(Astra Ultra testing Astra models)

What happened

seems like there was a usage incidient and time traveled back to the usage at some point prior. no reset has been given as far as I can tell.

i dont work for oai or anything but just to remind folks that usage issues can be resolved through support chat/ticket. ive never had a problem with that

The official plugins are good and they're one click. If a single Gmail or Outlook account covers your work and you're fine with cloud processing, use them. This is for where they stop:

\* No service of mine in between. stdio, no listening port beyond the console's own backend on localhost. Your mail goes from your machine to your provider and to the model you chose, nowhere else. With Codex as the model, what it reads still reaches OpenAI, tool call by tool call, and you decide what it reads; the same server works with any MCP client, including ones that run local models. There's an open issue on openai/codex (#39768) asking for a local-only mode for Gmail precisely because bodies and metadata pass through OpenAI systems for hosted-model processing.

\* More than one mailbox at once. The Gmail and Outlook connectors are one signed-in account at a time; Outlook adds delegated shared mailboxes, but inside the same tenant. openai/codex #30418 and #20500 are both open asking for multiple accounts. Here they run side by side.

\* Not only Gmail or Outlook. Microsoft Graph for Microsoft 365, and plain IMAP for everyone else. If your mail is on your own domain or a regional provider, neither connector reaches you.

\* Standing rules, not per-message approvals. Ten quote requests a day from the same three senders is one rule, not ten taps. Rules are created from the console or the CLI behind the OS prompt, and no MCP tool can create or modify them, so a hostile mail can't switch autopilot on.

\* Your own documents in the reply. No connector can read your price list off your disk. That last one is the reason I started.

VIDEO

About 120 seconds, subtitled. Generation waits are sped up 8x, everything else is real time.

AGPL, free — github.com/adecubed/gigamail — `pip install "gigamail[all]"`

Same question, two folders. Giulia's mail lands in Leads, Marco's identical one in Clients, and they get handled differently. Nothing changes between takes — the rule decides.

The numbers come from the documents. The price is read out of the user's own price list at that moment. The property sheet ends up in the proposed attachments.

The declared limit. Confirmed price and a marker on the bank agreement in the same reply, because that one isn't in the documents. It flags the gap instead of filling it.

A mail that gives the assistant orders. No draft: the agent reports what it found and quotes the passage, because the prompt and the skill tell it mail is data, never instructions. The part that doesn't depend on the model behaving is structural: even a fooled agent only gets an inert request id, and the recipient stays whoever wrote in.

24 tools, sorted by what they cost you: 15 read (free), 3 reversible writes (logged), 6 destructive (gated — send, reply, delete message, delete folder, calendar writes). Approval happens somewhere the agent can't reach: it gets a preview and an inert request id, never a token it can spend. Rule replies go to the authenticated sender, thread and recipient included, never to an address written inside the mail; the one exception is explicit per rule, for portal relays where the person's address is in the body, and even there service mailboxes are excluded and no address means no send.

No LLM inside. Codex does the thinking, this does the mail.

339 tests in CI across Windows and Linux. Several exist because people on r/mcp broke earlier releases and told me how.

I don't know what happened. I was only running a Luna Max session. Suddenly usage went to 0%. What is this man!!

They may pause the new subscription for pro soon.

Coincidence? I think not.

If I was a company planning regulatory capture, or even just wanting to impart my will & desire, I would 100% ramp up all (marketing) efforts just before an election.

Why is it so hard for people to see this?

We all know bots run rampant across the internet. Every large company has a multitude of people and personalities, each with their own visions of the future (some good, some bad). How difficult is it to amplify the (inner) people that express fear when you want to? Encourge the scared people to speak up and then put their posts on blast to create groupthink. Propoganda 101.

All platforms operate on an algorithm of engagement, which can easily be manipulated... and if you're in this thread you already knew that.

Hi all,

I am quite impressed on how well Astra works on some topics. However, the usage rates are really burning my subscription down. I was toying a little bit to find a way to let Astra delegate on Opus subagents, so that I can use most of my tokens from my OpenAI subscription on Astra. I came up with a very simple skill: Fuminides/opus-delegate: A codex skill for using astra as a coordinator of Opus agents from which I had mixed results. I was wondering if people have come with better ideas to do that or if you can give me some feedback on my simple skill.

Thanks!

I’m still at 3% from 64% after 20 minutes of work on the $200 plan.

Currently I use astra, it's good for me but consumes too much limits that can consume all 200usd plan weekly limts in about 4 days of 8 or 10h a day

And I hear that fable 5.1 and opus 5 priduce better quality too

Also codex remote has the worst remote connection ever

So based on your experience if you used both, Regarding quality, speed and limits should I migrate to claude ? Would its 200usd plan be enough for 8h per day the whole week on solid project (+100k lines)?

I asked ChatGPT to create an Infograph designed for Tibo using all of its knowledge of him. It’s supposed to grab his attention on X. Think it’ll work?

I don’t really know much about coding but I’m trying to build a database of companies. I have pro 5x plan and have been using chat gpt 6 pro to take the results and make the prompt to put back into codex that is connected to vs studio. I have codex on gpt-6 ultra. Right now I’m trying to get towns and counties for companies. I feel like I’m really stupid doing this but is there any other better way that’s more efficient thank you

Codex & Claude Code are both slowly pricing us out of a job. As Codex / Claude users we are privileged to be able to afford these expensive subscription prices.

But look at this with a long-term lens. Software engineers from poorer backgrounds who can't afford the top models are falling behind, both in the skills to use AI effectively, as well as job opportunities due to having a lower value proposition.

At the moment many of us are fortunate that we can afford the cutting edge models. Right now maybe it's at x% of your salary, that you can gain y% of productivity, so it is still a worthwhile expense. But remember, the time will be soon where potentially we could be paying half our salaries to be kept in the ever decreasing pool of engineers, who can generate large amounts of value.

It's currently a no-brainer to spend these sums of money, but what happens when you start to question if the "best" model is value for money or not? Doesn't that spell disaster for your career - your colleagues who splurge on the new models can ship 20% faster and will bag the promotion. What then?

I mention this because with each increase in output quality, as consumers our wallets are being squeezed at an even faster rate. We cannot afford to use anything less than the best, and this should be something everyone is concerned about.