You're 100% correct, most models these days know most programming languages and will quickly learn the syntax of more niche languages.
For users that end up benefitting from rules, it's typically because of encoding "personal knowledge" or "preferences". When building small side projects from scratch, this typically matters much less: you probably want it to "just work" using the canonical tech stack. Pretty quickly though projects end up with a lot of implicit knowledge and idiosyncratic practices that are great candidates for custom rules!
I guess you would be paying for pushing all of these tokens to the LLM. Also, too much irrelevant context can "confuse" the model about the task at hand
Check out NVIDIAs latest releases. Paying for tokens is going to be a history in about 6 months. You run the model on your laptop.
Maybe you're right about the confusion...but given the velocity, that's going to be fixed also.
All the knowledge about the field of programming is digitized, one could argue that having a model that digested all that information in a right way, is better than separate.
Absolutely +1 to the progress of local models! We hope Continue is and continues to be a great place to use them. Tons of blocks in the Ollama page for example that can be used: https://hub.continue.dev/ollama
For users that end up benefitting from rules, it's typically because of encoding "personal knowledge" or "preferences". When building small side projects from scratch, this typically matters much less: you probably want it to "just work" using the canonical tech stack. Pretty quickly though projects end up with a lot of implicit knowledge and idiosyncratic practices that are great candidates for custom rules!