> Better off learning a better (compiled) programming language.

I didn't really go too much into my background beyond the task at hand, but I have a CS degree and did C++ development professionally in the engineering space for years (and golang after that). I switched to data engineering because I enjoy the work, not because of an inability to work in "better" languages.

I'm not a rockstar or anything, but assume I'm as competent as a typical person who's been writing software for 20 years.

> If you have to use AI, use Groq or Ollama as you can keep these outputs to train or fine tune your own AI one day.

How do I train models via ollama? As I said, I've been using it for my work, but I've been leveraging it for "fuzzy matching" data, extracting pertinent elements from free form text, or general research. I'd love to be able to shove some of my datasets into one and use a prompt to interact with it. The best I've been able to do currently is showing it my database schema and having it write queries for me, which is not that valuable to me.

I don’t think you can “train” these LLM models. You can augment them by providing tools they can reference, but you’re not changing the underlying model.

What you’re describing - training your own model - would be a huge undertaking. You effectively want an LLM trained for next token completion, but with a narrow knowledge set.