Programs are communication between 2 loosely coupled audiences -- the humans who have to maintain / modify the code and the computer that gets to run the code.

Programs are communication between 2 loosely coupled audiences -- the humans who have to maintain / modify the code and the computer that gets to run the code. Human language, used to convey ideas to other humans, is imprecise. It's fine that it's imprecise because the media (humans) have both good error correction and a reasonable set of global defaults. Computer languages require enormous precision because they're some mechanical translation to a set of machine code runtime. Perhaps you can train an LLM on lots of code, and it'll find semantic relationships between some clever code it's been trained on to and your specific request. Perhaps not, and it'll just give a dumb answer or an incorrect answer, (ideally some code copilot will actually try running the candidate answer code against your specific ask?) -- but once the answer gets complex you run into the "it's much harder to debug code than write it, so don't write code that's almost too complex for you to understand" problem. At work, I constantly have to remind people "don't use math data structures for identities" "but int is smaller" "Are you ever going to want the 95th percentile customerID?" "no that's silly" "then it isn't a number". Or I get to constantly remind people "a string with lots of curly braces and quotes isn't necessarily json; if you're not using a serialized API and just sending bytes to stdout someone else has to parse it" "but I'm using a logging library" "does anything else ever send stuff to stdout while your logging library is running?" "oh yes, we're going to open a ticket to debug that." So I'm not optimistic that running code written by a machine is long-term viable. That said -- there are situations where machine generated code works -- I think it's been a long time since anyone manually drew masks for etching dies when making CPUs.