When I use LLMs heavily, I definitely stop exercising parts of my thinking I used to rely on. That can look like regression. But consider: Stone Age humans spent all their energy just getting food. No capacity left for higher-order thinking. Programming and document creation worked the same way for me - they consumed the mental bandwidth that could have gone elsewhere. Now that AI handles that layer, I can think at a different level. In my case, handing all the coding to Claude has freed up real mental space for product strategy - decisions that actually matter. Maybe the question isn't whether we're thinking deeply, but whether we're thinking deeply about the right things.

I am yet to give any LLM a prompt where I would get a practical and meaningful solution for a real problem, no thinking involved.

The actual thinking task is still very much mine.

LLM helps with solving the task faster, but here too, with lots of corrections and involving an extremely solid supervision process.

So, I kind of doubt the sincerity of your post. In fact, I doubt it very much.

Quite the opposite. Review is the bottleneck. LLMs generate more code, hence more cognitive load on my mind to comprehend and review it all. Review isn't optional if it's a production system that other people use.

After I see how astonishingly poor LLMs are at decision-making (even the best ones, like Claude Opus or GPT 5.4) while writing code, I naturally stop trusting them in other areas of life too much to "just have a conversation with them and get all the answers".

It's all fun and games while the stakes are non-existent, but if the question really matters, would you trust an LLM fully as much as to not exercise thinking at all?