LLMs are designed for text completion and the chat interface is basically a fine-tuning hack to make prompting a natural form of text completion to have a more "intuitive" interface for the average user (I don't even want to think about how many AI "enthusiasts" don't really understand this).

But with open/local models in particular: each instruct/chat interface is slightly different. There are tools that help mitigate this, but the more you're working closely to the model the more likely you are to make a stupid mistake because you didn't understand some detail about how the instruct interface was fine tuned.

Once you accept that LLMs are "auto-complete on steroids" you can get much better results by programming the way they were naturally designed to work. It also helps a lot with prompt engineering because you can more easily understand what the models natural tendency is and work with that to generally get better results.

It's funny because a good chunk of my comments on HN these days are combating AI hype, but man are LLMs really fascinating to work with if you approach them with a bit more clear headed of a perspective.