alt Hacker NewsI was super interested in genetic programming for a long time. It is similarly non-deterministically generated.
The utility lies in having the proper framework for a fitness function (how to choose if the generated code is healthy or needs iterations). I used whether it threw any interpretation-time errors, run-time errors, and whether it passed all of the unit tests as a fitness function.
That said, I think programming will largely evolve into the senior programmer defining a strategy and LLM agents or an intern/junior dev implementing the tactics.
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> The utility lies in having the proper framework for a fitness function
Exactly. As always the challenge is (1) deciding what the computer should do, (2) telling the computer to do it, and (3) verifying the computer did what you meant. A perfect fitness function is a perfect specification is a perfect program.
> That said, I think programming will largely evolve into the senior programmer defining a strategy and LLM agents or an intern/junior dev implementing the tactics.
That's basically what goog wants alphaevolve to be. Basically have domain experts give out tasks that "search a space of ideas" and come up with either novel things, improved algorithms or limits / constraints on the problem space. They say that they imagine a world where you "give it some tasks", come back later, and check on what it has produced.
As long as you can have a definition of a broad idea and some quantifiable way to sort results, this might work.