my current job /role combinations has me working in a variety of projects which feature tasks to be done in: Python/SQLAlchemy (which I maintain), Go, k8s, Ansible, Bash, Groovy, Java, Typescript, javascript, etc. If I'm doing an architecture-intensive thing in SQLAlchemy, obviously I'm not going to say "Claude here go do this feature for me". I will have it do things like write change notes (where I'll write out the changelog in the convoluted and overly technical way I can do in 10 seconds, and it produces something presentable and readable from it), set up test cases, and sometimes I will give it very specific instructions for a large refactoring that has a predictable pattern (basically, instead of me figuring out a complex search and replace or doing it manually). For stuff I do in Ansible and especially Groovy (a horrible language which heavily resists being lintable), these are very simple declarative playbooks or Jenkins pipeline jobs, I use Claude heavily to write out directives and such because it will do so without syntax errors and without me having to google every individual pattern or directive; it's much easier to check what it writes and debug from there. But I'm also not putting Claude in charge in these places, it's doing the boring stuff for me and doing it a lot faster and without my having to spend cognitive overhead (which is at a premium when you're in your late 50s like me).
> The one part I would say LLMs seem to help me with is medium-depth questions about DirectX12. Not really how to use it, but parts of the API itself. MSDN is good for learning about it, but I would concede that LLMs have been useful for just getting more composite knowledge of DX12.
see there you go, I have things like this I have to figure out many times per week. so many of them are one-off things I really dont need to learn deeply at the moment (like TypeScript). It's also very helpful to bounce off ideas, like when I need to achieve something in the Go/k8s realm, it can sanity check how I'm approaching a problem and often suggest other ways that I would not have considered (which it knows because it's been trained on millions of tech blogs).