I think that's going to be a very likely scenario. And the AI will very likely be able to fix the issue.
I just don't want to work that way, as what I enjoy most about programming is understanding things.
Then you are in the wrong space of programming if you want to continue working. AI will improve over time and the scenario I described is going to be a thing of the past, but it won't go as fast as people expect because it is a question of trust and saving that hypotetical money by actually doing the work or at least understanding the output of AI.
I've experimented with both Copilot and GPT and I've gotten some nasty UB and even known security issues. Just looking at some of the GPT output lacking exceptions and errors checking that is clearly trained on tutorials. It will improve over time but currently it is not as good as people say it is.
I've had experience lately of getting GPT4 to output some code, I notice there's a bug, I point out the bug (not even 'it's at this line with this variable', but just that it exists) and, yes, it does fix successfully fix it. So, yes, I think that's likely.
Well that required you to understand the code. My reply is disbelief off codebases that no one understands in the near term when looking at the current output. People don't trust the output and do what you did, review it and catch the potential bug before going further with it.
The issue take with it is that we are able to trust the output of AI models as we trust the output of optimizing compilers. It isn't even close that we can just fire and forget the prompt like I can code up something and trust that it 99,999% the optimizer produces the desired binary that works as intended.
Really? If you have a million dollar bug because of one edge case and you are going to go to your AI and ask it to try again?