Lately, I've been asking ChatGPT for answers to problems that I've gotten stuck on. I have yet to receive a correct answer from it that actually increases my productivity.
I've been able to get code working in libraries that I'm wholly unfamiliar with pretty rapidly by asking the LLM what to do.
As an example, this weekend I got a new mechanical keyboard. I like to use caps+hjkl as arrows and don't want to remap in software because I'll connect to multiple computers. Turns out there's a whole open source system for this called QMK that requires one to write C to configure the keyboard.
It's been over a decade since I touched a Makefile and I never really knew C anyway but I was able get the keyboard configured and also have some custom RGB lighting on it pretty easily by going back and forth with the LLM.
It is just very random. LLMs help me write a synthesizer using an odd synth technique in an obscure musical programming language with no problem, help me fix my broken linux system no problem but then can't do anything right with the python library pyro.
I think it is why people have such different experiences. It all depends randomly on how what you want to solve lines up with what the models are good at.
I've been able to get code working in libraries that I'm wholly unfamiliar with pretty rapidly by asking the LLM what to do.
As an example, this weekend I got a new mechanical keyboard. I like to use caps+hjkl as arrows and don't want to remap in software because I'll connect to multiple computers. Turns out there's a whole open source system for this called QMK that requires one to write C to configure the keyboard.
It's been over a decade since I touched a Makefile and I never really knew C anyway but I was able get the keyboard configured and also have some custom RGB lighting on it pretty easily by going back and forth with the LLM.