I went that route since reading the CLI parameters was something I needed to do, but wasn't actually part of the issue I was trying to solve. I could have spent a few cycles of googling+testing+fixing/refactoring, but it was a trivial task (that I didn't remember how to do off the top of my head) and would have distracted me from the main task.
Disagree. I can be more or less certain that documentation authors or write-ups have knowledge about the topic im researching to a reasonable degree, because
1) they need accurate and efficient code that makes sense to establish a relationship with the reader and compete with other solutions
2) humans are bad at explaining things they dont know about opposed to executing or managing unknowns
ChatGPT? None of these. Its a giant probability calculator that wants my prompts and its own answers to foster itself. This also nurtures its inaccuracies and makes it easier to confidently lie. I hardly find any reasonable use for ChatGPT other than quick completion suggestions for at a maximum of 2-3 lines, because thats what its designed for.
> you aren't entitled to feel superior for not using it
I will break the HN spirit but you kind of wanted to say that there. I didnt imply that at all, nothing near that. The dataset is just, imo, too big to give extremely accurate (or more accurate than human-thought) answers for specific questions.
But also, this is the area where an LLM shines; tasks that you technically could solve yourself but are so boilerplate that you should spend you brain power elsewhere. Then again here it looks like not much brainpower got put into this project at all (and that's OK, sometimes it be like that )
