> the current metric we use for problem complexity (e.g. big-o) is woefully inadequate at measuring the actual complexity of problems.
The complexity of all problems. But big-O isn't the only complexity metric available.
It's extremely useful and very adequate in almost all cases, but it doesn't work well when the numbers are very small and the problems are part of a small subset of all available problems.
But those are edge cases. In practice those are fairly rare and when the datasets are small enough normally all solutions are more or less viable. But as soon as your data set is non-trivial big-O is the right tool to apply at the outset.
Right tool for the job... small dataset, tricky problem: big-O may not apply.
