I would argue this approach will help you in the long term with code maintainability. Which I feel will be one of the biggest issues down the line with AI generated codebases as they get larger.

AI is so new and so powerful, that we don't really know how to use it yet. The next step is orchestration. LLMs are already powerful but they need to be scaled horizontally. "One shotting" something with a single call to an LLM should never be expected to work. That's not how the human brain works. We iterate, we collaborate with others, we reflect... We've already unlocked the hard and "mysterious" part, now we just need time to orchestrate and network it.

Particularly with the VSCode extension. I was a loyal Cline user until recently because of how good the editor experience was, but the ability for Claude to go off and run for 10+ minutes effectively autonomously, and show me the diffs in realtime is a gamechanger. The token usage has also gotten much more efficient in the last few months. With proper IDE support now I don't see any reason at all to use anything else, especially not the "credit" based middle-man providers (Windsurf/Cursor et. al).

GPT-5 should mean a brand new model/architecture trained from scratch.

This is why I have very specific ruleset and linting for my LLMs, not allowing any at all and other quality checks.

Right, I've noticed agents are very trigger happy with 'any'.

I have had a good time with Rust. It's not nearly as easy to skirt the type system in Rust, and I suspect the culture is also more disciplined when it comes to 'unwrap' and proper error management. I find I don't have to explicitly say "stop using unwrap" nearly as often as I have to say "stop using any".