The idea is not bad but it sounds a bit extreme... Indeed choosing the right sorting algorithm is important and depends on one's problem to solve. But, 99.99% of the time, a general, all-round algorithm will do the job within 99% of the best-one's performance...

But when it fails, well, it will fail big... In my experience, some devs (me included :-)) make tests with a reduced dataset 'cos they can iterate faster and then go in production without testing on a real-size dataset. All of a sudden, the o(n²) edge case becomes, well, a problem :-)