For boilerplate, yeah. But when asking research or exploratory questions, or weighing whether a feature is well designed, or asking "can I implement _x_ feature using these libraries without introducing unnecessary complexity", then GPT-5.5 medium is still fast enough.
10-20 seconds times a couple turns on a new feature isn't bad. Kimi is also similarly fast if not faster.
I do agree with smaller models for more constrained/routine tasks though.
well, I can usually think for myself or hit someone up in Discord (or Teams, if it's for a living) and in a worst case (that person just deflects to AI anyway) just save some token budget for myself
I always think for myself too, but when learning to do something I've never implemented before, it's nice to have little sanity checks using something with the reasoning ability (plus the fast natural language search on hundreds of pages of documentation) of a model like GPT-5.5.
Every line I put in my app, I still reason about myself. But when deciding between 5+ ways of building some random, non-straightforward feature, it's nice to have what's essentially a "mentor" AI.
10-20 seconds times a couple turns on a new feature isn't bad. Kimi is also similarly fast if not faster.
I do agree with smaller models for more constrained/routine tasks though.