I'm a bit confused by this idea, maybe someone can clarify. AFAIK, genetic programming/algorithms themselves require some degree of tuning in order to be useful

I'm a bit confused by this idea, maybe someone can clarify. AFAIK, genetic programming/algorithms themselves require some degree of tuning in order to be useful in a reasonable amount of time and for avoiding local minima each generation, via mutation rates, population size, randomized simulated catastrophe, etc. That being said, how does something like TPOT actually ease the pains of tuning the parameters of a different model, if it requires it's own tuning?