The author makes a comparison to Haskell, which I think might be a little misleading.

Haskell is a little more complicated to learn but also more expressive than other programming languages, this is where the comparison works.

But where it breaks down is safety. If your Haskell code runs, it's more likely to be correct because of all the type system goodness.

That's the reverse of the situation with Bayesian statistics, which is more like C++. It has all kinds of cool features, but they all come with superpowered footguns.

Frequentist statistics is more like Java. No one loves it but it allows you to get a lot of work done without having to track down one of the few people who really understand Haskell.