[vidarh]

Genetic Programming [1], specifically. I have both his two bricks from '92 and '94 (Genetic Programming: On the Programming of Computers by Means of Natural Selection, and Genetic Programming II : Automatic Discovery of Reusable Programs). I've not read his two later ones.

The big problem they seemed to get stuck at was partially doing it fast enough, and partially ending up with a result that was comprehensible. The latter in particular seems to be far better with LLMs. You tended to end up spending a lot of time trying to reorganise and prune trees to get something that you could decipher, and so it seemed like the primary, and too limited, value became algorithms where you could invest a lot of resources into trying to find more optimal versions of very small/compact algorithms you could justify spending time on. But the challenged there is that there are often so many far lower hanging fruits in most code bases that few people get to the point where it's worth trying.

I still love the idea at a conceptual level...

[1] https://www.genetic-programming.com/johnkoza.html