I love genetic algorithms and find using LLMs as part of them super compelling. I always find the fitness functions to be the most difficult part. The algorithm naturally tries to exploit any little gap you leave it in cheating. Best part is not needing back propagation in solving a problem. However that is also the worst part in all the solutions just being one level above a random walk. The LLM augmentation really helps to give it a gradient and intelligence beyond random chaos. Love the idea of it being applied to hardware.