Count me among those who thought validation was a thing you just had to do when training ML algorithms. After all, the most beautiful theoretical model in the world is of no use if the predictions it delivers are terrible.

The real trick (for most algorithms) is to select the correct features to train against. This really is more of a black art than an exact science, so I think labeling it a trick is justified.