It’s just a feature that explains a web platform doc using LLMs.
They can be inaccurate sometimes, but as long as that’s clear to the end user (in this case, developers) I don’t think that’s a problem. Heck, many of us do this day-to-day with ChatGPT.
In this case, the sin was not making the potential for inaccuracies clear enough.
No need to make things up if you have the sources anyways.
The latter would be very different interpretation and some here would probably agree with that accusation
Also hallutination was probably the wrong word to use for LLMs being incorrect since it might imply they could be correct if they would only just focus on the right input data rather than, say, simply not understanding complex technical concents, but I guess that ship has sailed.
I completely agree and the tone of some of the comments in the issue are disproportionate to the problem.