"However, LLMs aren't capable of writing proofs." LLMs != AI. I'm not worried about LLM's impact on my career. In their current form they're nothing more than

"However, LLMs aren't capable of writing proofs." LLMs != AI. I'm not worried about LLM's impact on my career. In their current form they're nothing more than a trap, who will suck in anyone foolish enough to grow a dependence on them, then destroy them, both personally and corporately. (Note difference between "using them" and "grow a dependence on them".) Code that no human can understand is bad enough, code that no human has ever understood is going to be even worse as it starts piling up. There are many characteristic failures of software programming that LLMs are going to suffer from worse than humans. They're not going to be immune to ever-growing piles of code. They're not going to be immune to exponentially increasing complexity. They'll just ensure that on the day you say "OK, now, please add this new feature to my system" and they fail at it, nobody else will be able to fix it either. If progress froze, over the next few years the programming community would come to an understanding of the rather large amounts of hidden technical, organizational, and even legal and liability debt that depending on LLMs creates. But LLMs != AI. I don't guarantee what's going to happen after LLMs. Is it possible to build an AI that can have an actual comprehension of architecture at a symbolic level, and have some realistic chance of being told "Take this code base based on Mac OS and translate it to be a Windows-native program", and even if it has to chew on it for a couple of weeks, succeed? And succeed like a skilled and dedicated human would have, that is, an actual, skillful translation, where the code base is still comprehensible to a human at the end? LLMs are not the end state of AI.