Interesting questions. Bootcamps are clearly incentivized to do this. However, they do not seem to be particularly good at it. Algorithms are over represented in interviews relative to most jobs, and yet (as our data shows) bootcamps are not very good at teaching this. Now, we are measuring algorithmic skill by asking candidates to actually implement non-trivial algorithms. We've observed that a lot of interviews involve what is essentially trivia about algorithms, and it's possible that the bootcamps are better at preparing students for this (we don't measure this skill so I am not sure). I think that this gets at the answer. If you make your interview go deep, it gets increasingly hard to specifically prepare for it, to that point where preparing is actually becoming a better programmer. Rather than a 30-minute question that covers knowledge of sorting algorithms (easily learnable), have your candidate spend an hour building a collision detection systems using a axis-sorted list of rectangles, and reason about maintaining this sort as objects move around. That's the theory. In practice there will always be some noise.