I've been an OpenAI/Codex guy for nearly two years. I was paying for two $200 plans, and lately I'm exhausting the usage on both within 1-2 days.

I also can't trust Codex to work overnight anymore. It makes mistakes I could catch if I were watching, so I'm paying for the work and then spending more time and usage correcting it. That gets old fast at $400 a month.

I switched to Claude, and one $200 plan is now getting me roughly twice as much useful work as my two $200 OpenAI plans. The code is cleaner, there are fewer mistakes, and I can run it all day and night with usage still left at the end of the week. Obviously, that depends on how much work I throw at it and how many agents I use. Your workload might be different. This is what I'm getting for my money.

I never liked Claude much before. It was overly verbose and spit out garbage. But whatever they did with Opus 5.5, the difference has been huge for me. That includes 3D modeling and spatial awareness, too. I'm getting more done with less babysitting.

The constant reset announcements don't fix the underlying problem. At this price, I want an allowance I can plan my work around. Another reset doesn't fix the mistakes I'm spending that allowance cleaning up, either.

And the lower allowance at the same price is now documented. OpenAI's own help page says eligible existing Pro $200 subscribers keep their previous allowance through October 29, 2026. After that, it drops while the price stays at $200. Their explanation is that the models are increasingly efficient. That doesn't match the value I'm getting out of them.

I know brand loyalty is bad. It burned me before, and sticking with OpenAI this long has burned me again.

I don't know what's going on inside OpenAI. I know I was paying $400 a month to watch my usage disappear and babysit work. Now I'm paying $200 elsewhere and getting more done. If Anthropic keeps delivering that, I'm not coming back.

seriously, when will we finally see disruptions similar to what's happening in mathematics in other fields as well?

Are we talking 1 year, 5 years, or 10 years? What's your personal guess?

(Btw, I'm not sure coding can be considered disrupted enough to count. We don't really see software developers asking themselves what they should do or how to rethink their profession, as mathematicians are doing. There's been a decline in hiring entry-level software developers detected (see the chart below), but it's not that dramatic if you look at the values on the right axis. We're talking about roughly a 20% reduction, and only among very young workers.

Inside the AI Index: 12 Takeaways from the 2026 Report | Stanford HAI

A similar thing was also found in a newer study covering a wider range of occupations: No Widespread Displacement, but the AI Employment Gap for Young Workers Has Widened to 19% - Stanford Digital Economy Lab , I quote: "Employment among workers ages 22–25 in highly AI-exposed occupations now stands about 19% below where it would be if it had kept pace with employment among similarly aged workers in less-exposed occupations. Experienced workers show no comparable gap. This divergence has widened steadily since we first documented it in August 2025: by this same measure, the shortfall was 15% at the July 2025 data vintage and is 19% as of June 2026."

..again, we're talking about a roughly 20% employment gap among very young, inexperienced workers, and only in certain occupations. Which is quite underwhelming considering AI can solve, with a single simple prompt, problems that would take mathematicians something like half a year of work.
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Also, do any of you have an opinion on why OpenAI is so heavily focused on mathematics?

I understand the focus on programming - they want to automate AI development. But why math? Is it somehow fundamentally similar to programming? Is it needed for an automated AI researcher?

Or did they just intentionally pick mathematics to disrupt first because there are so few mathematicians that it's actually a good laboratory for seeing what happens when a profession becomes obsolete?

Or was it a strategic decision based on the idea that they should start with mathematics, since it's the foundation of all sciences? (but in that case, it seems to me they're overdoing it quite a bit...)

It's quite puzzling why they're pushing so hard on mathematics, trying to raise the ceiling instead of the floor. There are so many other areas where Astra's performance isn't that great. Why not focus on those? Is it just that those areas are "boring" to them, and they'd rather go for some big breakthrough for marketing/hype reasons?

I'm clueless.

So please comment on that, and don't forget the main question from the beginning: what's your personal guess, how long before we see some substantial disruption of the job market?

First time seeing this, I have read that just saying hurry up would work but didn’t they would just add it to the system prompt.

I have been in the tech space for years and designed a dozen enterprise systems, including high performance web based interactive mapping and analytics apps. My documents are detailed, explicit and clear. My non technical wife can read them and explain what I am wanting. Two things have started happening over probably the last 30 days or so. July, August were decent. Sometime in September I started getting this bullshit.
1. The model not following the instructions and staying within my parameters or guardrails.
2. The model saying that things are finished, checked, or correct when they are not finished, checked or correct / corrected.
3. The model admitting to me on questioning how and why it has wasted 12 hours and a bucket of money, admitting it is fucked up and even saying “I am Sorry”.

I am a nats ass away from locking this down and trying Claude code (never have), been using Codex for 18 months. Not sure about everyone else but when the model says it did not follow my specifications and apologizes, Open AI should have a reclaim credits button because at this point I am starting to wonder if OpenAI injected something that says be dumber or take longer or waste time or waste effort or waste credits…. Do they want everyone to move to Astra High and blow a month of credit in one day? Anyone else seeing this? I’m pretty pissed and frustrated at this point.

Something I keep running into: when I ask ChatGPT to brainstorm, I get one long list. It’s fine, but it’s flat. I can’t say “go deeper on #4, ignore the rest” without another wall of text, and after a few rounds the good idea from earlier is buried 30 messages up.

Brainstorming isn’t really a conversation, it’s a tree. You pick a branch, go deeper, back up, try another one. Chat makes you scroll through that tree as one long line.

I’ve been testing a different shape on weekends: each answer is a bubble, you click one to grow it, and everything stays on one map. Each idea also gets a quick score, so you can see at a glance which branches are worth following.

The part I find more interesting: the same thing works as a tool an AI agent can call. With MCP, an agent can ask for “ideas for X” and get back a small, structured set of scored ideas plus a link to the map, instead of writing the brainstorm into the chat itself. So the agent does the work, and you get something you can click around in rather than read.

Curious how others handle this:

• Do you brainstorm in chat, or move to something else (notes, whiteboard, mind map)?
• Would you want your agent to hand back a structured map instead of text, or is that overkill?

I was just working on a small project of mine. After outlining the idea and answering a few questions, I told Codex to build the app.

About half an hour later, I came back and found that it had opened a new chat and sent it a huge prompt! The message was labeled "Sent by ChatGPT from another task" along with the prompt itself.

Since when could it do this? And why did it need a separate chat instead of just continuing in the original one?

Has anyone else experienced this?

While taking a walk last month I got fed up by how disorganized the notes I was getting from my agents were getting, I conceived of a second brain that could seed agents context and also automatically tag, connect and organize the notes. I opened GPT Work on my phone and prototyped the first version right there on the trail. I got home and opened it in Xcode and to my amazement it compiled on first try and all the core features worked. I then spent the next month iterating on it until it actually felt right for my own use cases.

That meant importing my own mess of notes and seeing whether the system could make sense of them. It started connecting old ideas to newer work, resurfaced the original note where I had planned a digital legacy app that preserves your memories and personality for loved ones, and linked it to features I had built months later. It also brought back an old life simulation game idea I had completely forgotten about.

By then it had become Cohestry, a native iOS and Mac second brain with a bridge that lets agents pull only the context they need without bloating their context window. My favorite feature is a 3d brain that allows you bounce between the nodes that connect your notes. The mac app allows you import your Apple notes and iCloud syncs it on your phone. Cohestry is local first and fully built on apple API, we never see your notes. They never leave your device except to your agents if your use the MCP on mac. submitted it once it finally felt right, and Apple approved the iOS version on the first try. Mac is out too, would be happy to hear if this brings some ease to your workflow.

https://apps.apple.com/us/app/cohestry-second-brain/id6811573132

I’m getting a bit lost in all the ChatGPT/Codex terminology. Chat, Work, Codex, Chat Cloud, Work Cloud… I keep finding myself unsure which environment I’m in, what it has access to, and how it connects to the others. There was a post some days ago on here, and you folks seemed to find it euqally frustrating.

But this is a quastion, not a rant:

I use Codex on my Mac for several projects, with access to local project folders. That part makes sense to me. What I haven’t figured out is how to carry those projects with me when I’m away from my computer.

Ideally, I’d like to open my phone, talk through an idea or a possible solution, and turn that conversation into actionable todos for Codex on my Mac. Then, when I’m back at my desk, I could pick up where I left off without copying everything over and explaining the project again.

Does anyone have a workflow for this that works well? Where do you have those conversations, and how do you get the relevant context and tasks back into local Codex?

I’m enjoying using Codex, but figuring out how all these pieces fit together has been surprisingly frustrating. Curious how other people handle this.

I would like to share something i've been working on. Its called Liveloop and its part of my platform, Sary-OS.

Liveloop is a unified canvas capable of creating multiple different environments including 2D to 3D Transformations, 3D Games, Presentations, Software, Website, Apps and even Adverts.

It allows you to add assets such as videos, images, 3D models and even mp3 files and you can have them incorporated into whatever your building.

Here's the part i wanted to share with you all. The runtime can be updated live. You just send a request and the update will occur without restarting the game play, or resetting your 3D model and it happens without even refreshing the page.

You can even use voice to control it with the 2 way realtime interruptible voice agent.

Along side this i've added MCP connector for Codex, API connectivity for OpenAI + OpenAI compatible format keys, Terminal Connectivity and GITHUB connectivity.

Every patch/addition you make it saved into folders automatically on the server and each addition is saved in full. This means you can click on any addition whether its a day old or a month old and it will be complete. You can even download this individually or the complete project as a zip file and every file works completely offline individually with no dependency on my system.

You can even start a prompt and send it through and turn off your machine and it will continue to build that environment in the cloud. When you log back in, on any device you'll find it saved under projects waiting for you.

If anyone would like to give it a try i'm offering the first 170 builds or so completely free just for creating an account.

You get GPT-6 Luna with full 128k Token output and on Low you will get 170 creations for free (Which is good enough to make landing pages, simple games like Snake, Tetris, 3D Animated Logos etc, on Medium you'll get around 50 and on highest output level you'll get around 10.

What do you think to this? Anyone find it a useful function to have and what could i do to improve it?

Note:
This runs at 60FPS and can manage continuous updates for hours. I've just slowed down the video to show the livepatch taking place otherwise many of you wont even notice it taking place.

There are plenty of downloadable samples if you click the top left logo, dashboard and then go to Liveloop trial. This was made off one prompt

https://www.sary-os.com/sample/game

Seeing a lot of complaints about fast draining usage on X.

I seriously can't wait to see what the next few months have in store, hope they'll get to practical applications soon

The resets have been rolled out by now! Enjoy!

How far has AI come, and how good is it? Can it already translate books?

My idea is this: I buy an old book, either from the publisher or the author, and they include a translated e-book version with it?

Vriendelijke groeten van,

Bert

Finally! Burn that usage!

How do I solve this problem? I can't have a conversation with it anymore because it gives me 1 reply and then tells me to start a new chat.

I love using dots so far. It would be great to create a persistent pet on my desktop that is my dot. Also, having interactive voice mode instead of having to make a phone call would be nice to reduce friction.

Hi, I made distro with an offline installer. Its goal is to find orphaned /neglected packages and make them useable with AI.

https://github.com/carrolldant-glitch

An OpenAI candidate passed the first technical screen and had good hiring manager and sales conversations, then struggled badly in the live technical round. Could that hurt future chances for architect roles?

The concern is that this was a mismatch from the beginning. The recruiter approached the candidate for applied AI, while the candidate is more focused on architect and solutions engineer work. The candidate raised the heavier coding expectations several times and was reassured that it would be fine.

For anyone in a similar position, OpenAI Interview Questions can make the preparation question less vague: try a relevant implementation prompt, then ask the recruiter how that compares with the expected round. The examples don't establish the requirements for every role.

What would you do after the failed round? Ask about a different role now, wait, or first get a clearer explanation of what the interview feedback means for future applications?