In terms of the method in this thread, I think anything under 500 algorithms is absolutely realistic and to be expected for a method that has 3 algorithmic steps. The 'problem' with a 500 algorithm method isn't learning the algorithms-- it is spending the HUGE amount of time generating-testing-regenerating algorithms for each case. This is because it is often the case that a 16-move algorithm is faster than a 10-move, and when generating algs, anything over 13 moves and you have a titanic number of cases and no good A.I. utility exists to sort long lists of algorithms into finger friendly versions including possible wide moves and rotations. If/when someone develops a human hand model that can convert an alg to finger tricks and predict the speed, and then sort an algorithm list, it will be a titanic advance for new method generation because you save 5+ years of humans doing all the tweaks.