It can be nice not to have to worry about types when you are doing exploratory programming. For example, I once started by writing a function that did a computation and then returned another function constructed from the result of that computation, and then realized that I’d actually like to attach some metadata to that function. In Python, that is super-easy: you just add a new attribute to the object and you’re done. At some point I wanted to tag it with an attribute that was itself a function, and that was easy as well. Eventually I got to the point where I was tagging it with a zillion functions and realized that I was being silly and replaced it with a proper class with methods. If I’d known in advance that this is where I was going to end up then I would have started with the class, but it was only after messing around that I got a solid notion of what the shape of the thing I was constructing should be, and it helped that I was able to mess around with things in arbitrary ways until I figured out what I really wanted without the language getting in my way at intermediate points.

Just to be clear, I am not saying that this is the only or best way to program, just that there are situations where having this level of flexibility available in the language can be incredibly freeing.

And don’t get me wrong, I also love types for two reasons. First, because they let you create a machine-checked specification of what your code is doing, and the more powerful the type system, the better you can do at capturing important invariants in the types. Second, because powerful type systems enable their own kind of exploratory programming where instead of experimenting with code until it does what you want you instead experiment with the types until they express how you want your program to behave, after which writing the implementation is often very straightforward because it is so heavily constrained by the types (and the compiler will tell you when you screwed up).