I think cross validation is a powerful tool but not always necessary and is prone to abuse, such as overfittimg to the test set. A skilled modeller can reduce

I think cross validation is a powerful tool but not always necessary and is prone to abuse, such as overfittimg to the test set. A skilled modeller can reduce variance using domain specific tricks that are more powerful at variance reduction than cross validation. But still cross val is usually good to use as well.