If you're talking about prompting to production, no, I generally am not doing that yet.
Other people in my organisation are certainly trying all the time to get it to that point but it's not quite there yet for me because I've got a fairly large codebase, limited time and I need to manage when I start to move into that.
As an autocomplete though (github copilot), it has gone from token to near reading my mind at times.
It probably writes 20%+ of my code. I think it will be 80% in 3 years or less.
(I'm a firmware engineer, mostly in C)
I remember doing a presentation to my team about four years ago. It was about 20% then.
It is good to automate boilerplate.
We will know that AI was really arrived when it can do the following:
1. Debug dense code and tell me exactly where and why it is failing
2. Suggest refactoring based on cyclomatic complexity/maintenance/performance parameters I set
3. Predict second/third order effects of a PR, give me an explanation in natural language, tailor to a specific audience (devs/managers)
The above are the remit of mid/senior engineers, AI is not even close to doing these yet.
Good to hear you are doing C, I have massive respect for programming close to the machine