alt Hacker News> On the other hand, I haven't been convinced that it's good enough to maintain large codebases or assist with niche topics that are not very well documented.
Same is true of humans. So far my experience is that addressing the issue with the help of AI is faster than not (ie comprehending the system and creating the documentation).
I don't understand the comments of the kind of "same is true with human".
This feels a bit like whataboutism.
It also feels like people don't listen to each others.
For example, reading the previous comment, it feels like the thing that reduce the enthusiasm was that at first GenAI looks like it was "reading, understanding and using its own knowledge to answer the problem", but as soon as it is a ore niche or a more complex situation, GenAI looks like it "does not understand the code, just does the equivalent of a StackOverflow search and try to apply the solutions that it found there, and this is why it felt like it understood the code before".
It does not at all means that GenAI is not terribly useful. And even better than humans in some situations.
But it feels that answering "same with humans" is missing this point: that's the opposite, humans usually try to understand the code and are bad at covering a very large range of very well documented subjects. That's the "uncanny valley" they talk about: they assumed GenAI performance on a subject X is due to a "human-like" approach, and it feels very strange when this impression falls apart.