CjHuber

Every good thing is alike, every slop is sloppy in its own way

> Probably because the general purpose subagents inherit the parent model

only if you don't specify which model should be used

> Instead of requiring developers to script every step or passing every tool response back through the model, Programmatic Tool Calling in the Responses API can filter large amounts of intermediate data, retain only what matters, and adapt its workflow along the way.

this seems very interesting

but 5.5 was also no major version bump

> fit a lot more work inside the model's context window before you're forced into a slow and lossy compaction step

This is something I never understood. Why the reasoning is not included until the context is full, then the reasoning stripped optionally to allow the conversation to continue. and only then when its truly full offer a compaction. Was it to optimize caching? Well I guess it doesn't matter now that you hinted that this choice was made because of prior limitations and may change very soon

Well, obviously its true as you can see in the silbing comment. But still interesting how experiences differ. I wonder did you ever use codex in more demanding workflows, because that at least something like that is going on is obvious if you use it for a few hours

Interesting to hear people like gpt-5.5. For me it feels smart only at one shot prompts, but if you try to build up session context before doing something it feels magnitudes inferior to Claude. I'm almost sure its because the thinking of previous turns is stripped with the responses API, so if I tell it to analyse something deeply, what remains of the understanding in future turns is only the short response text of that analysis

> so you now have to wait in line for hours

Interesting, I go there pretty regularly and while It is well visited, I not once encountered a queue there

I agree, adaptive thinking is a pest and without a minimum thinking budget especially Claude for me currently defaults to not think at all even on max effort.

Sequential-thinking was really a step in the right direction, and works almost exactly how you've described, though when it was popular before the reasoning models and even now when I tried it recently I have never once see it use its branching feature and it tends also to have the RLHF urge to answer something "helpful" quickly instead.

I think this is a really good cause but I can't help but wonder about the contrast between the puppy analogy and then increasing the friction of installing it by making it a paid tool

What about GBrain

Yeah indeed it's very interesting. And the 60k initial context don't even contain the suggested change yet. For me if I don't do this the current models tend to fixate and local patches instead of tracing symbols and making a holistic model of what a change interacts with in the codebase