I think Github Copilot paired with ChatGPT fails the most in idiosyncratic code bases where you are doing maintenance or complex refactors. I think Github Copilot with ChatGPT shines in writing green field code in areas where you are will to use the best practices and the open sources libraries that Chat GPT recommends. Basically, if you align with where Chat GPT recommends to go, then it will help you a lot more than if you try to fight it all the way.
Due to hallucinations, beginners can get knee deep very quickly, but experts can see through this and use these tools will skill.
I don't write as much code as I used to, but I still write code daily and appreciate how they can turn what was a 10-60 minute task into 1 minute of prompting plus 30 seconds of generation/reading to make sure it is valid.
Seriously! I write a documentation comment like:
/// Given: blah
/// When: blah
/// Then: blah
and Copilot writes the test for me. I can generate a dozen tests like this and it's awesome. I write a lot more tests because of Copilot.Cut to few months later with OpenAI API release, so many code completers released in many useful form factors willing to go wherever I code even if its Android Studio or Xcode. The product has stagnated completely.
I do expect it to change significantly in the future though, might go back then.
I am not sure why so many people have hard time getting value out of it.
I find that ChatGPT/Github Copilot knows certain types of patterns, libraries better than others. If you get it to suggest the path forward, and then do that path, it will be better at maintaining that code. Basically ChatGPT sort of has happy paths which you want to follow.
Or you could say it in another way: AI designed code / architecture is easier for an AI to maintain.