My experience is that chatgpt consistently showed me API functions that don’t exist. But I tend to do very obscure things in embedded, that googling for can be tricky or impossible. At first I had high hopes, because the shape of the code is good, and the logic looks good, but when I go to look up details of the parts I actually need help with, they’re just made up functions, like placeholders I might write until I can go back and implement them.
Where it’s shined for me was writing code where I couldn’t be bothered to put together ideas from several distinct tutorials. It’s fantastic for writing code that you can basically google for, even if you have to read several disperate pages to get a clear picture of what to do.
> was writing code where I couldn’t be bothered to put together ideas from several distinct tutorials. It’s fantastic for writing code that you can basically google for, even if you have to read several disperate pages to get a clear picture of what to do.
I think this description of yours nails it.
Soon, though, you’ll be able to feed it a corpus of documentation and/or library code and question it based on those. That might help your use case.
I've been writing an open gl based game engine for scratch, but I'm using c#, which means I'm using a lot of bindings for libs that only really exist in c++. Because of this chat gpt seems to get stuck on functions that don't exist in my context
Where it’s shined for me was writing code where I couldn’t be bothered to put together ideas from several distinct tutorials. It’s fantastic for writing code that you can basically google for, even if you have to read several disperate pages to get a clear picture of what to do.