Probably not. It’s more likely it’s due to OpenAI having some problems raising funds which forces them to be more efficient with their capital: https://news.ycombinator.com/item?id=50312922
> Since ChatGPT chats cannot spawn or control subchats/subganets so I had to be a bit creative in order to do multi-agent development and orchestration.
Multi-agent is mostly dead. One big agent loop running GPT6.1 absolutely dominates any weird ideas like this now. I still use sub agents for some tasks where I want to compress the action space and context. For example, testing a workflow that requires 100+ tool interactions for each logical test. Without a subagent it's really hard to guarantee a test makes it E2E. I have some very "persuasive" methods for long horizon tests that would break the main loop's dynamics.
We may not feel so compelled to exploit the system if we could figure out how to not be so wasteful. Multi agent schemes can bloat token usage by orders of magnitude. They force us to consider consuming less ideal tokens from contexts and vendors with higher variance.
HN loses its marbles when I suggest it's economically feasible to prepay for API tokens and use these as the exclusive means of performing AI work. I get done with a thousand tokens what my peers cannot do with a million. It doesn't matter how many hammers or workers you have if you don't have the aesthetic preferences and domain expertise to employ them correctly.
Probably not. It’s more likely it’s due to OpenAI having some problems raising funds which forces them to be more efficient with their capital: https://news.ycombinator.com/item?id=50312922
> Since ChatGPT chats cannot spawn or control subchats/subganets so I had to be a bit creative in order to do multi-agent development and orchestration.
Multi-agent is mostly dead. One big agent loop running GPT6.1 absolutely dominates any weird ideas like this now. I still use sub agents for some tasks where I want to compress the action space and context. For example, testing a workflow that requires 100+ tool interactions for each logical test. Without a subagent it's really hard to guarantee a test makes it E2E. I have some very "persuasive" methods for long horizon tests that would break the main loop's dynamics.
We may not feel so compelled to exploit the system if we could figure out how to not be so wasteful. Multi agent schemes can bloat token usage by orders of magnitude. They force us to consider consuming less ideal tokens from contexts and vendors with higher variance.
HN loses its marbles when I suggest it's economically feasible to prepay for API tokens and use these as the exclusive means of performing AI work. I get done with a thousand tokens what my peers cannot do with a million. It doesn't matter how many hammers or workers you have if you don't have the aesthetic preferences and domain expertise to employ them correctly.
I understand preferring Claude models in the abstract, but as a product? The random restrictions have significantly reduced their usability.
We had 2 major threads in the past 48 hours complaining about this:
* https://news.ycombinator.com/item?id=50319358 (AI/ML work with large models)
* https://news.ycombinator.com/item?id=50320255 (reverse engineering)
The threads are full of upset comments!
The only non-OAI options are open models and I guess Gemini 4 now.
> To be clear, I am not breaking any rules.
> I am simply making the best use of what OpenAI has made available to me
People like this are why you can't have good things.
But if you get a Claude subscription, don't you have to use Claude Code? Why not pay the $20/month for OpenAI and use your favorite coding agent?
I've been doing that and it seems like quite a deal.
Anyone building products on cloud models is building in a swamp, a sand trap, a flood zone.
Anyone whose buainess wont be competitivw without a cloud model is going to lose their business.
Any government letting cloud models consume its private infrastructure is yielding its authority to private intetests.
[dead]