I think that it kind of is momentous because 2 years ago (and probably even 6-9 months ago) you would have lol'd at what you're using it for today - or at least the confidence you have in it. And if it has somewhat plateau'd now - in terms of model capabilities - it means there is unresolved (and maybe unresolvable) friction still and that's worth exploring. It's cool that it's there, but does it meet up with expectations? And what does and doesn't work?
A lot of stackers are using chatbots (the usage among us seems to be really high thus far, especially if you realize that the alleged global penetration rate is about 1.5B/5.5B) but the problems we feed it are all different, and results do vary, probably through a mix of prompting effort put in, expectations and problem-space alignment. So I'd like to get a better feel for what experiences people have outside of the common ~AI commenters too.
I typically paste my writing and ask it for a critique that covers good bad and ugly.
Interesting. I generally ask "explain x" when I write about something, to make sure I that I am not completely off the mark. Like a double check. But I never say "I wrote this" - to avoid the PC. The other day I was challenging Qwen3 because it was being generic to a specific question and it actually started calling me names, lol. The training must be absurd at times.
x" when I write about something, to make sure I that I am not completely off the mark. Like a double check. But I never say "I wrote this" - to avoid the PC. The other day I was challenging Qwen3 because it was being generic to a specific question and it actually started calling me names, lol. The training must be absurd at times.