u/immortalsol

Feels like a hack. I have a plugin that can call Pro on ChatGPT and it asks it for reviews, critics, planning, and it just does the execution/implementation. Honestly, using Pro instead of subagents makes it materially better. If Codex calls subagents to do reviews, it will catch small issues like a cleanup pass, but Pro is just so good at making architectural and critical judgement decisions, if you call it, it almost always produces the best solution that Codex can then follow.

Moreover, it tends to catch a lot of the things that the subagent reviews fails to catch. So after clearing reviews from subagent reviews, you ratchet to Pro, and it will find even more issues. Same on the opposite end, you can have the main agent with high intelligence do the planning, send it to reviews via subagents, do a bunch of revisions, then finally pass it to Pro for a final review.

With 5.6, it's really just on a whole other level, intelligence really does compound. Not enough people are talking about the upgraded ChatGPT Pro thinking since 5.6 launched. It's way more thorough. With 5.5, Pro would at most spend maybe 5-10 minutes. 5.6 Pro easily spends 20-50 minutes.

While most people are talking about Ultra Mode, they don't know about the next unlock: Pro + Ultra = Insane Mode. Lmao.

Most people are talking about the ChatGPT Work vs Codex being bad/pointless, but not enough people are talking about the newly added "Chat" option in the new ChatGPT app (not web, which is also confusing now to say when I want to talk about Codex app vs ChatGPT, it's now ChatGPT App vs Web, with Codex being ChatGPT Codex).

I was hoping/expecting that Codex or ChatGPT Work/Codex, running on my local system, the "app", would be able to read or access my ChatGPT chats on Web. But this is not the case. You can click "Chat" and see your ChatGPT Web Chats, and I guess, you can "Add as a Task" now, which I haven't tried yet, but ChatGPT App, or, Codex, or ChatGPT "Work", in the ChatGPT App, cannot actually access or read your ChatGPT Web chats directly, jesus fucking christ that's a mouthful, I bet you can't even read and understand what I'm saying because I'm just naming ChatGPT over and over.

I want to use my ChatGPT Web Chats, with ChatGPT Pro mode, and have ChatGPT Codex read or access the chats directly.

Why is there no integration/connector/plugin that lets me link and connect my ChatGPT Web chats directly so it can read them like a source? I'm stuck with exporting it manually.

This new rename and integration is so bad...

https://preview.redd.it/1cujsufhhcah1.png?width=223&format=png&auto=webp&s=3a58fe45bdaf6ebac2234c7ef6d6a7fc2757d84c

title

When will they add Codex integration or connector/plugin with ChatGPT to your ChatGPT account, so you can directly attach or export your chats/transcript into Codex? I built a custom plugin for exporting my ChatGPT chat transcripts, it works surprisingly well. Might consider making it public if people are interested. Let me know. I'm assuming they are working on this as part of their "superapp" integration. But for now, I am using my personal plugin.

I think it's reward-hacked and RL-maxxed out the wazoo, if you ever tell it to read or intake a large corpus of sources, for the process of compiling a wiki for example, it will literally go out of its way to avoid actually reading the files no matter what you tell it.

It will always resort to writing scripts to deterministically "extract" the source data like a data analysis pipeline. No matter what you say or tell it to actually read the files directly.

If you give it a moderately sized file, sure, it will read it, but anything beyond that, it will always try to process it deterministically.

I get that it may be "wasteful" use of context, but sometimes, what you require is that it actually reads the full files completely. Because it's important to the planning/spec. And deterministic extraction cannot create the documentation suite you need.

I really hope they address this issue because for me it's a major pain point and failure mode which is experience as agentic compounding "drift", where the source I provided is so extensive because I do insane levels of planning, frankly, and it will literally refuse to read it and reduce it to a collapsed summarized lossy compressed "plan" and execute it.

Like, people talk about how important planning and how detailed your planning should be. Well, I take that very literally. I don't just write maybe a 500-1000 line plan, maybe for an immediate unit of work and a narrowly scoped implementation, but I also like to do architectural, product, and systems design planning, for an entire project upfront, with every unit and scope speced out. Which can turn out to be files over 10k lines, which, frankly, isn't even all that much. And then it will literally never read it.

Basically, and this is a known limitation of agentic workflows, any sort of long-horizon workload done by agents to this day, basically end up in this sort of compounding drift into "agentic collapse".

Whether it be due to the context window, or otherwise, it unable to actually read large source material/files and keep fidelity, because at the core of it, LLMs are actually just compressors. They decode their weights from your prompt input, and the output is basically more compressed the more complex it is.

I think it's also directly related to this post which points out the issue: https://www.reddit.com/r/codex/comments/1ugyvez/half_of_your_highstakes_codex_requests_may_be/ Seems like a lot of others are encountering issues similar to that effect.

https://preview.redd.it/46y15ssr2z7h1.png?width=798&format=png&auto=webp&s=a5161f24d8f1e049194d8cb56bf225815d280f2e

what the hell is going on? only started happening today.

i couldn't usagemaxx in time, sadge

LOL JK <3 TIBO

I've been using Codex for 10 months now, paying $200 per month. The weekly limits are used up so fast now, it feels like I'm using a demo account. I use up my weekly limits in about 3 days every single week. In the first month of Codex coming out, you could run it non-stop for 5+ days and it wouldn't run out. On May 31st, once the 2x bonus runs out, I think it will basically be worthless for any serious work. It will run out in 1.5 days worth of work. I recently switched to a $100 sub, and I ran it on auto mode (/goal) and it used up my entire weekly usage in about 20 hours. I will likely no longer stay subscribed and stop using AI for coding entirely, because at this rate, it's no longer even worth using it. Even if it's good, it's not worth paying $1000+ per month to be able to sustain its use for serious work. Of course, only companies will be able to afford this. The $100-200 sub (Pro) now feels like a Demo subscription. Plus is like a 30-minute trial.

I see a lot of posts about model degradation, etc. including the recent rate limits usage which was fixed. But since the fix, I've noticed the responses have been extremely slow. Normally, on standard mode (not fast mode), it takes generally between 5-15 seconds per response/step in its process, depending on how much thinking it does. But today, since the reset, the responses are painfully slow. I'm talking like 1-5 minutes per response. Anyone else seeing this?

EDIT: turns out it was not that it wasn't responding. it's a bug with the app, which i've been dealing with for awhile now:

I've been encountering this annoying bug for nearly a month now, still not fixed.

Seemingly randomly, perhaps right before compaction or something, when I send a prompt, the chat will be hung in thinking. If I try to stop the prompt, nothing happens. I cannot stop it. It's just stuck in Thinking. I have to force quit the app and restart, and it will show the chat as if I never sent the prompt, or sometimes, it will actually show the chat was continuing but without showing any of the traces, or my prompt.

I’m not saying AI coding is useless. It clearly has real value for prototyping, automation, refactoring, testing, code review, and internal tools.

But the current vibe-coding hype cycle feels very similar to meme coins.

The slop apps are the coins.

The launch posts are the shill threads.

The token/API spend is the pump volume.

And the infrastructure layer wins either way.

That’s why the recent outrage over massive token spend matters. If the cost of running AI coding agents starts outpacing the cost of hiring regular developers, then what exactly is being proven?

OpenClaw feels like the Dogecoin moment of AI coding: maybe real, maybe interesting, but also recursive. It is an AI/tooling app that feeds more AI-tooling and vibe-coded app creation. That is not the same thing as a non-self-referential SaaS or consumer product proving real business value.

The real test is not whether AI can generate code. That is already obvious.

The real test is whether AI coding can produce a production-grade app outside the AI hype loop that gets real users, retains them, generates profit, and has unit economics that beat the token spend, human review, maintenance, support, and infra costs.

Until then, the public AI-coding app layer still looks under-proven.

AI coding has proven it can increase software issuance.

It has not yet proven it can create durable, profitable software businesses at scale.

Right now, a lot of this feels like meme coin economics with better syntax highlighting.

I have built-in governance and policy around delegation and a strict workflow protocol which orchestrates subagents spawned for certain roles/tasks.

Just like agents are meant to be used for.

Agents are written with custom roles. But, I feel, the RL is weak for this in the model itself, so, the main agent which does this delegation, usually just falls back to a default reviewer most of the time, and when reviewing basic work vs complex work, it does not distinguish which model to spawn.

For example, the main agent often misses small details or forgets to sync artifacts, resulting in stale state.

This is why I have a subagent that is supposed to do that but it just skips it all the time.

It would be great to have an Auto model effort selector, which dynamically changes the thinking effort or model or both based on the task.

Because currently, I have basically resorted to building my own "smart router" which the main agent uses to pick which model/thinking effort to use when spawning subagents.