I'm not sure that your example shows that the analysis you learn in school is "crap in the real world". Using O analysis is for seeing how an algorithm scales

I'm not sure that your example shows that the analysis you learn in school is "crap in the real world". Using O analysis is for seeing how an algorithm scales with respect to the input size. If anything, the fact that someone believes a O(nlogn) algorithm is always faster than O(n^2) is a failure on that person's part in properly understanding what O is used to measure.