ChatGPT gave me a very plausible-sounding result, but mixed up the meaning of two very important values of key parameters which are unfortunately not very well named, so the mix-up can go unnoticed very easily. I did only notice it when some things didn't quite match up and I decided to carefully compare all the result from ChatGPT with the actual spec content. After all, ChatGPT didn't save me any time, it rather cost me quite some, cause I still had to dive through the original spec and cross-check ChatGPTs' statements.
Yeah, if all you ask are simple questions which were already answered a thousand times on StackOverflow and in beginner tutorials, ChatGPT might be quite helpful. It might even be able to write some simple glue code Python scripts. But whose job is limited to that kind of trivial stuff? Mine isn't, except maybe during the first few days when learning a new technology, but after those it usually gets tricky very quickly, either because I must tackle problems that lead me knee-deep into delicate details of the tech stack, or because I need to extend the scope of my work again in order to integrate whatever I'm working on into a larger system. Sometimes it's both at the same time. I'd be bored to death if it was different.
That's why I don't really consider ChatGPT and similar systems to be a threat to my professional career.