Indeed I have met professors who claim since something is O(1) it doesn't matter if you run it 4 times. No need to optimize. I think it's just part of the wider divide between theory and application. For instance big O also requires a register machine to make sense, which most courses don't define. Somehow addition and multiplication are O(1) in some places and O(n) or O(n^2) somewhere else. Also quite common is the fact that sets are slower than lists for lookup for small n, despite being O(1).
It's just a tool and we shouldn't miss the trees for the forest. I also understand this comment has nothing to do with the ETH or the article, but just some thoughts I have after reading the first chunk on complexity