alt Hacker NewsThere are plenty of good tasks left, but they're often one-off/internal tooling.
Last one at work: "Hey, here are the symptoms for a bug, they appeared in <release XYZ> - go figure out the CL range and which 10 CLs I should inspect first to see if they're the cause"
(Well suited to AI, because worst case I've looked at 10 CLs in vain, and best case it saved me from manually scanning through several 1000 CLs - the EV is net positive)
It works for code generation as well, but not in a "just do my job" way, more in a "find which haystack the needle is in, and what the rough shape of the new needle is". Blind vibecoding is a non-starter. But... it's a non-starter for greenfields too, it's just that the FO of FAFO is a bit more delayed.
My internal mnemonic for targeting AI correctly is 'It's easier to change a problem into something AI is good at, than it is to change AI into something that fits every problem.'
But unfortunately the nuances in the former require understanding strengths and weaknesses of current AI systems, which is a conversation the industry doesn't want to have while it's still riding the froth of a hype cycle.
Aka 'any current weaknesses in AI systems are just temporary growing pains before an AGI future'