Ask HN: What's the best way to get started with LLM-assisted programing?

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.

The developer experience with Aider isn't that great when compared to a full IDE like Cursor, but it's a great way to get started because it's a simple CLI tool that accepts commands.

After that you might decide to switch to Jetbrains AI since you use Pycharm.

To avoid this, just ask Cursor to use suggestion blocks instead of the edit file tool. This way, you can review each suggested change, click apply if you like it, review that specific change and make any edits, then proceed to the next suggestion block.

This is the best way to avoid chaotic changes that become difficult to review thoroughly, and while it takes longer, is a much less risky approach using focused, granular edits.

It’s a much more efficient workflow than alt-tabbing and copy pairing to and from a website, and much more powerful with how easily you can add context, swap out the LLM model being called, and apply suggestions that you deem acceptable with granular oversight.