NP-hardness is indeed often not a big deal in practice because NP-hardness is a statement about asymptotic worst case complexity. In practice you have some finite size problems that are often of average difficulty, not of worst case difficulty. For example, we solve instances of SAT every day, some of them quite large. Even humans are able to solve many Sudoku puzzles, even though Sudoku is NP-hard.

If you hang with the right crowds (for example people into software correctness), PSPACE completeness is easy and you even solve undecidable problems every day.

Chess on an 8x8 board is not NP-hard. That doesn't mean it's easy but invoking NP-hardness is kind of meaningless.

The reason chess is hard to solve is not because it's NP-hard (which it is not, being a constant-sized problem), it's because chess is a big problem.

It can simultaneously be true both that NP-hardness matters, and that constant-sized problems can be hard.