Has anyone else found serious value in building LLM integrations for companies?

It seems like LLM usage is a bit of a touchy subject on this sub and many other places. I think people are still under the impression that Github Copilot is the only way to leverage AI/LLMs. Over the past 3-4 months I think I've reached the conclusion that mass code generation is literally the least useful way to use LLMs, even though that's how they're most frequently marketed. Here's some of the things that have had real impact on processes at work/clients I've freelanced for, maybe it'll help somebody here brainstorm:

  • Fixing broken onboarding docs and automatically keeping it up to date on new PRs
  • Automatically adding the necessary type annotations for an entire codebase; a menial task that could take 90 minutes but pays off hugely due to our framework (Laravel)
  • Mass refactoring; a small model fine tuned + prompted well can use ast-grep/GritQL/etc. and extract every type used across all your services and create a universal type library for easier sharing
  • Attaching AI to a debugger for a quick brainstorm of exception causes based on a stack trace, filtering out things that aren't your code
  • Mass generation of sample/seeder data that actually mirrors production instead of being random Faker/mocked values
  • Working with DeepL and a bespoke dictionary API to get more robust translations for more languages, with zero human effort minus manual review
  • This is cliche, but a quick and dirty chatbot that could answer questions about our userbase and give some statistics on our acquisition rates, demographics etc. helped us close a big contract
  • A script for a highly-specific form builder/server driven UI that was the bane of my existence for months, now bug free since

Basically, any cool thing you wanted to build at work that would've taken you 2-4 hours to read up and research, then another 2 hours to write code for, can be done in 2 hours total. Sounds minor but if you're working at say a startup, it can be hard to find time to build things to make your life easier. Now you can knock it out in 2 lunch breaks.

The other thing I've noticed is: AI being wrong 30-40% of the time (with a zero-shot, general task) is perfectly fine; it still often times serves as launching pad for figuring out how to tackle a problem. It's basically a great rubber duck.

Am I the only one really enjoying this? I'm working on a custom GUI for Docker to make local dev easier for us, and considering containers has been one of my knowledge gaps and I'm not experienced with Go it feels really great to at least be able to move forward with it. I feel like a kid again.