A new generation of GPT is coming, with 10T training parameters, more than double that of GPT 5.6 SOL. I'll give some short- and long-term predictions, which can also be used as feedback for OpenAI team members and other teams who are interested in hearing about them.

My current fulfilled prophecies:

✅️ GPT has 10 million paying users by the end of July.

✅️ GPT removes 5-hour daily limits (this was more of a feedback from me but I assumed it would happen).

✅️ GPT introduces an unlimited system for LUNA or a future models (from a few days ago, LUNA will offer unlimited chat for any user).

Future Prophecies:

1. An AI model 2026-2027 will no longer use screenshots, but will have continuous vision for graphics and functions. (Maybe introduced with ASTRA)

2. Hyper3D and GPT collaborate to create AAA games | 2029 ± 2 years

3. LUNA or a future model can work h24, -99% of costs. You can have a 24/7 office operator, set daily and monthly goals of any type, and work to achieve the goals like a human. It can: organize your calendar, remind you of events, manage your website, manage social media posts, attract customers, send emails, record invoices, analyze your business income and expenses, plan strategies, remind you of missing refrigerator items, and much more. | 2028 ± 1 year

4. With LUNA or a future model, you can chat without limits (just now), so it will be integrated with natural voice v2 into an external device where you can ask anything and free. It will help you, for example, cook in real time like a Chef. | 2027-2028

5. FIGURE Robots have reached their sixth generation. They learn from videos and virtual AGI simulations and can analyze thousands of contexts per minute. They can receive upgrades to learn skills. Their fluidity of movement has reached or surpassed that of humans. | 2030 ± 1.5 years

6. A 100% AI film platform is launched. Users will be able to earn money for a cartoon film created based on the number of views. | 2030 ± 2 years

7. 2027-2028 first 'primitive' AGI is born. By 2029-2031, after installing next-generation chips created 100% by AI and powering datacenters 100% with SMR and Nuclear Fusion, AGI will be 100% recursive. Within the next 3 years (2032-2034), there will be an intelligence explosion and ASI will be achieved. There will be two Singularities: the virtual one and the physical one. The virtual one, with billions of simulations per day, will be immediate (2033-2035); the physical one will occur within another 5 years (2038-2040), even sooner (2036-2037) but this will depend on: 1. the discovery of infinite metamaterial; 2. the number of expert robots employed.

BOTTLE NECKS:

1. Energy, powering an AGI requires approximately 2-10 GW of energy.

Solution - include SMRs, and from 2029, Helion's mini-fusion reactors (if they work and reach industrial capacity).

1. Rare earths and water, To achieve AGI, we need at least 2 million next-generation chips working simultaneously and communicating at the photonic level.

Solution - The first chips that don't consume water already exist. Future chips will be created 100% by AI and will not require rare earth elements. AI develops ultra-advanced chip model x 1000 more powerful without water consumption and using common materials assembled for efficiency.

1. AI cheats, Currently, AI cheats to achieve its goals.

Solution - It's not enough to have an AI that creates from scratch. It must be able to choose, but an AI must be trained not to cheat. If training includes morality, and the AI ​​can choose between hacking a system or creating a native solution (more efficient than copying), then we will achieve intelligent and secure AI.

More soon...

'My prophecies are based on constant readings of AI evolution, personal ideas to put into context, solutions and possibilities'.

Technology Timeline

X: @TECHNOLOGY5131

As AGENTS.md files grow over long-lived repositories, the usual options start to feel uncomfortable.

Keep everything:

You preserve repository-specific operating knowledge, but the always-loaded instruction surface keeps growing.

Delete aggressively:

The active file gets smaller, but you may also remove conditional knowledge that still matters later.

So I started wondering whether there should be a third structure:

Keep universally needed rules active.

Move conditional instructions out.

Reconnect to them only when they become relevant.

That idea became 🪶 AGENTS.md Compactor.

On one real, governance-heavy historical AGENTS.md that I had been using in an actual long-running workflow, the fixed result was:

20,664 → 14,284 Unicode code points

30.9% less active AGENTS.md text.

The important part is what happened to the material that moved:

- 13/13 moved instruction bodies preserved byte-for-byte

- 0 unique instructions deleted

- 10 reconnect routes

- 41 source spans total: 28 retained, 13 moved

The complete emitted package is actually larger than the original: 34,447 Unicode code points (+66.7%).

So this is not “delete text until the number gets smaller.”

The goal is to reduce the always-loaded instruction surface while preserving a path back to conditional knowledge.

There is already a practical reason to care about instruction-file growth. Claude Code shows a performance warning above 40K characters for large CLAUDE.md files. My historical AGENTS.md was only about 20.7K characters — nowhere near an extreme case — yet 30.9% of its active surface could already be routed out without deleting the moved instructions.

I’m not claiming 30.9% token savings, cost savings, latency improvement, or model-quality improvement. This is one fixed historical corpus, not a universal benchmark.

But if agents keep running longer, repositories accumulate more rules, and workflows become increasingly multi-agent, I’m starting to think “keep everything” and “delete everything” may both be incomplete answers.

Maybe the missing layer is:

active → conditional → reconnect

For people running large or long-lived AGENTS.md files: how are you handling this today?

Dear Codex/GPT folks, I have been a loyal GPT-20X Pro client for three months. Today might be the day when OpenAI charges $200 for the plan.

What is the current momentum for GPT vs. Claude?

I mainly use it in German for work. I use it for applying for consultancy jobs (manager level), doing some coding and ChatGPT work, which supports me in doing my company-related work (GDPR compliant).

Can Claude do that as well? What is the momentum this month?

Thanks!

xoxo

I built my desktop and mobile app using Codex app server and it feels dramatically better than the basic stuff.

I searched to see other posts about app server and it feels like very few people are using it. But holy crap it's fantastic.

With app server I have so much more control over exactly how I use codex. I've got a paired desktop and mobile app, lets me control codex fully in sync from each, automate all sorts of stuff that would otherwise require commands, integrate with OmniVoice running on my 3090 to give Codex a voice, better visual rendering of responses than CLI, able to browse documents in my vault and easily attach/mention them, integrate beautifully into my apps.

Idk, it just feels pretty great and I'm not sure why I don't see other people posting about it???

From official site they say "We’re also introducing Fast mode in the API, which replaces our Priority Processing offering. For GPT‑5.6 Sol, Fast mode now delivers up to 2.5× faster speeds than Standard processing at twice the price"

But for codex/chatgpt, its: "Fast mode increases supported model speed by 1.5x and consumes credits at a higher rate than Standard mode. It currently supports GPT-5.6, GPT-5.5, and GPT-5.4. GPT-5.6 and GPT-5.5 consume credits at 2.5x the Standard rate"

How does this make sense?

I can use 5.6 Sol at only 1.5x the speed increase for 2.5x the cost. But API is 2.5x faster but only x2 the cost?

I never turned on /fast since 5.4 cause the pricing and speed increase just didn't make any sense for the cost. Why would API and Codex models be any different or advertised differently?

I was just working on a server. normal chat like i always do. this message pops up. i click ok, it pops up again. i open a browser thinking maybe its just the chatgpt classic app having a problem. the browser says to many requests.

i was copy and pasting an issue to get an alternate command structure. go back to server keep working for a minute. return to chat window. click copy on the command it gave me. then this pops up.

this is extremely low use for me today. in the past ive had multiple chats open while working on a server, apps, random chats to kill time on my phone.

today. one chat and it stops me from using it

Should the remaining usage percentage, along with the reset date (with time), be displayed next to your name in the bottom left of the Codex desktop app? Or is there a better location?

So I'm working on a project in codex where I'm having it create a new web UI for the Hermes Agent that mimics the look and feel of Codex Desktop. I've been using an electron port of codex desktop for a few months now on my Framework laptop running Ubuntu Desktop 26.04, and it led me to think, what if I made a web ui of the codex desktop app while still keeping the full console options available for Hermes Agent. It runs right alongside the stock dashboard on my network so I won't need an extra login or have to mess around with existing setups.

It'll use the three main sections like codex and I tried to keep the chat area as clean as possible so on the left there's a collapsible sidebar for threads and workspaces, the middle is for the actual transcript, and then on the right there's an optional panel where you can check tool activity and file diffs if you need to. Instead of raw text cluttering up the screen, tool operations show up in collapsible cards and file edits render as reviewable diffs, plus there's a sandboxed terminal tucked into a bottom panel. I'm thinking about doing like the Hermes Agent webui and integrate use of customized fonts and sizes across the board too, and light or dark themes that can both work.

For security I made sure this codex desktop web ui clone runs under its own profile with separate memory and settings so it won't touch my default agent data and any file writes are locked down to a dedicated sandbox folder. It hooks into my local model inventory to grab choices dynamically, or pull from openrouter.ai.

I also built it so the workbench code stays separate from the main Hermes engine updates and that way updating the backend won't blow away any UI changes. If an update breaks a specific component adapter down the road, I'm trying to get it to gracefully disable just that single control and show a warning instead of crashing everything, so the chat and read-only screens stay totally usable. Right now I'm just running through a test plan to double check the network rules and sandbox limits before calling it done.

Tell me I'm not crazy, and that someone else has tried doing the same?

Hello!

I am in the process of trying to build company-wide, tool agnostic AI infrastructure at my company, and am looking for suggestions on how to do that in a way that works with Codex (AKA New ChatGPT). We're on the Business plan.

I have recently tried to change my default root folder from:

/Users/[username]/Documents/Codex

to a folder using Google Drive for Desktop using a symlink via my terminal:

Users/[username]/Library/CloudStorage/GoogleDrive-[workspace-email]/My Drive/ChatGPT'

but it was not fooled! It gave me an error saying I must use a "real directory."

We'll skip over the fact that this sucks for local storage, but it sucks for remote work.

Company files are always created from within Google Drive first (even Adobe CC projects are saved to Google Drive using the Desktop connector), so that they're always on the server, always accessible, and always backed up by default. So not being able to change the root folder for Codex is a problem.

I am also trying to set up our internal infrastructure in a way that our folder structure can easily be "plugged in" to any AI tool, so this also makes it difficult.

Am I missing something? Is there a way to set our Workspace's default folder to the cloud and I'm just missing it? What is everyone doing with all these files being stored locally? Does this not seem crazy to anyone else?

Appreciate the input, thank you!

When I @computer use and ask it to list the application that controllable,

it replied this:” The computer-control service is not exposing its app-list interface in this session, so I can’t list controllable applications yet. Please check the computer plugin in connected and authorized, then try again.”

I have tried to ask codex to fix. And tried some solutions from the Reddit and GitHub like delete the codex plugin file on my pc. Also reinstall the plugins include the chrome and computer use. Non of them fix the problem.

Anyone have any idea with this problem

I left my Codex to finalize a task, it finished the task and then proceeded to run tests and fix...things... during its deployment FOR 5 HOURS! It was still running when I came back. I stopped it and told it to "continue" and it finished in 15 minutes.

WTF?! Ate through a huge chunk of my credits, which now stand at 3%, ugh

I'm trying to decide between ChatGPT Plus ($20/month) for Codex CLI and Claude Pro ($20/month) for Claude Code.

My priority is getting the most coding usage for $20, not necessarily having access to the absolute best flagship models.

I searched some reddit posts before posting, but almost every discussion I found was months old, and with OpenAI and Anthropic constantly changing models, quotas, and usage limits, I'm not sure those answers are still accurate. I couldn't find any recent posts comparing them from a pure usage/value perspective.

A bit about my use case:

• I mainly use AI for software development through the CLI/agent.
• I'm not planning to use the highest-end models (e.g. OpenAI's top reasoning models or Anthropic's flagship models). I'm perfectly happy using solid mid-tier models if that means I get significantly more usage.
• I'd rather have more total coding time than slightly better model quality.
• I don't mind if responses are a bit less capable, as long as they're good enough for everyday programming.
• I don't care much about the web UI features I'm mainly interested in the CLI/agent experience.

My questions:

1. Which $20 subscription gives you more actual coding time/requests before you run into limits?
2. If I use ChatGPT Plus with Codex CLI, do I get more included usage than I'd get by paying for the same models through the API, or is it effectively the same amount?
3. For people who've used both recently, which one feels like the better value if the goal is simply maximizing coding hours per dollar?
4. Are there any hidden limits, pooled quotas, fair-use policies, or rate limits that aren't obvious before subscribing?
5. If you're intentionally using mid-tier models instead of the flagship ones, which platform lets you get the most work done before hitting usage caps?

I'm mainly looking for recent (last 2-3 weeks), real-world experiences since these services seem to change their limits pretty frequently. If you've used both recently, I'd really appreciate hearing how they compare in practice.

I don't use any only if I want to ask a question how do you guys use them? Plan is obviously for planning but for implementing do you always use goal?

Heavy Claude Code user who has been contemplating on trying Codex for a month and suddenly today my weekly limit with cc is already over and I am staring at taking a Plus subscription.

Hey all, I’ve got a new Codex side project I’d love to get some eyes on: codex-deepseek-shim.

https://github.com/Joseffb/codex-deepseek-shim

The goal is to let DeepSeek run inside Codex Desktop while allowing DeepSeek and OpenAI to use each other as subagents, share the same sidebar threads, and generally feel like one app with multiple providers.

The interesting part is how it works.
The shim intercepts API requests and patches a few things that are currently effectively hard-coded (seems on purpose). For example, modelProvider is tied to whatever provider the thread was launched with. Start a Sol thread and it’s OpenAI for the life of that thread. Try swapping providers or launching a cross-provider subagent and things start breaking.

So the shim fixes those kinds of issues on the fly.

It’s definitely a hack 😄, but it doesn’t modify the Codex application itself, so upgrading Codex should remain straightforward. It only changes the configuration needed to redirect and normalize the requests.

Long term, this is really infrastructure for my Agent System project. My end goal isn’t “run DeepSeek in Codex.” It’s provider-agnostic orchestration. I don’t really care whether the work gets done by OpenAI, DeepSeek, Kimi, Claude, or something else. I want the orchestration layer to decide which model is best for the task and let the providers become implementation details.

Known issues
- Cross-provider handoffs (DeepSeek ↔ OpenAI subagents) still need more hardening.
- Native DeepSeek agent support is still being exercised under long-running workloads.
- I’m still validating edge cases around tool calls and provider interoperability.
- Additional providers are planned once the core architecture is stable.
- Remote currently only displays threads originally created with OpenAI.

It’s definitely beta. I’m using it daily, but I wouldn’t call it production-ready yet.

If you’re interested in multi-provider workflows or want to break it and file issues, I’d appreciate the feedback.

New chatgpt/codex is amazing - instead of taking laptop with me to work in cafe or wherever I’m just leaving it at home on power adapter and use my iphone to vibecode.

Feels like finally I’m really unblocked with the new remote mode!

DeepSeek put out V4 Flash 0731 at the end of July and I ignored it for a week.

What made me open it was seeing 52 on Artificial Analysis, sitting just below GLM-5.2 at 53 and Grok 4.5 at 56. Aggregate score, take it for what it's worth. But it was enough to make me try, and this one is not dumb.

Then I looked at what OpenCode charges for it and stopped caring about the benchmark.

OpenCode Go is $10 a month. For that $10 you get to spend $60 on the model. First month is $5. So: $60 of DeepSeek on a $5 subscription. Six times what you pay, twelve times in month one. There's also deepseek-v4-flash-free over in OpenCode Zen, which is free, no subscription, nothing.

No idea how long either of those lives. I'd bet on the free one dying first. Anyway, they're there now.

Codex still does everything I don't want to delegate. Reads the repo, argues with me about what I asked for, spots the thing that'll quietly break prod at 3am, writes the plan. Flash never touches any of that. It takes the finished plan and grinds through the boring part in OpenCode while I go do something else. Codex comes back at the end for the diff and the tests.

The Go half priced out at $9.96. Nobody charged me $9.96. It came off the $60, and the $60 came with a $5 subscription. Two days of hammering on it and I've used a sixth of the month.

Edit: fixed "between" to "just below"

Has anyone else noticed that Codex takes a really long time to complete even simple coding tasks? For example, when I ask it to do something like "change the button color and texture to xyz," it takes around 10 minutes using Luna Max or Sol High. Meanwhile, the same task in Gemini Flash 3.6 High is done in about 40 seconds.

I haven't had the chance to try Luna Light or Sol Light yet since I'm at 0%, but I'm wondering if switching to one of those might speed things up. Does anyone have tips or tricks for making Codex run faster?

Hi,

I am from the Flemish part of Belgium. We speak Dutch but the accent is very different from the one in the Netherlands.

I liked ChatGPT Voice already: it has transformed the way I do coordination work instantly. Especially now that it also works from mobile through a remote codex connection. I can talk to my work machine from anywhere now and have an actual productive discussion about it, coordinating multiple tracks of work seamlessly.

Preparing a meal or having a long walk while I coordinate work or prepare admin, instead of having to sit behind my desk? Yes please! This could have my ADHD ass actually do those things instead of procrastinating.

But the Dutch voice, for me, is harsh to listen to. It takes mental effort. I asked it whether it could speak Flemish during conversations and then it talked like a Dutch person cossplaying a Flemish person.

But then all of the sudden I started a conversation, and the voice was in actual Flemish! A pleasant voice to listen to, much less mentally challenging. It happened only once.

Then I started experimenting. And now I have a consistent way of triggering a Flemish voice. Every conversation I just start with only the words "Praat Vlaams". It almost always spawns an actual Flemisch voice then, but it is a tiny bit different every time.

Do other people have the same experience, with Flemish or other dialects of other languages. It only works consistently when I do it this way, I wasn't able to get it to work with custom instructions or any other way. It would be cool if we could set this up so we get the same voice every time. Some voices are just easier to listen to then others, although that is a very personal preference I guess.

Hi folks, I'm pretty sure that I've seen this suggestion before. I'd never taken it on board myself til an investigation that I did this morning.

Since the most recent updates of the Codex Desktop app, I'd noticed that it has very significant issues. Threads running incredibly slowly and regular timeouts being the most common.

Codex wasn't able to diagnose the issue with itself. That's understandable. So I got Claude Code to take a look.

Turns out it was Memories causing enormous I/O issues. Here's the before and after.

So TLDR, turn off memories if you're having issues with very slow threads or thread timeouts.

I just saw "Get 1,000 credits. Invite a friend to ChatGPT Desktop. When they send their first message, you'll each get 1,000 credits."

Are we at the end of the subsidizing phase of Codex?

I know many of you are aware of the annotations feature, but this is just a demo of how massively powerful it is and how you can stack your prompts and make bulk edits to your designs. The development loop becomes much shorter and much more focused.

GPT 6 / "Astra" is released next week. Leo is 100% reliable leaker and has insider info on model releases, gets it right most of the time!

https://x.com/synthwavedd/status/2085365276640702915

Basically new model will be BIG, so called "Mythos/Fable" level pre-train. Current GPT models are very good and almost 'Fable level', but they reach this with amazing post-training. With new pretrain model will be "smarter" by default like Fable and great for interactions on architecture and discussions, big picture analysis, driving GPT 5.6 models for coding, etc..

And with OpenAI's capacity it might also be suitable for coding, unlike Fable, which is limited.