If you were going to use genetic algorithms, you should have gone all in- seed with a randomized neural network, have them compete, and breed the winners.
Hehe, yeah, I did something similar later, using game score as the fitness score (so still a chance of breeding even though you didn't win) in a kind of tournament selection. The problem is each generation then takes loads of time to simulate, compared to just observing their behavior for a short time.
But that worked much better as a fitness score, yes. It's very true that what you measure is what will be optimized for. Both for employees and robots.
Literally survival of the fittest!