Yeah, prototyping with JSON is one place where dynamic languages are more nimble.

For example, the Python bindings to Amazon S3 let you access files through dictionary notation. BeautifulSoup lets you iterate over child nodes with a for loop, or access attributes as a dict. NumPy lets you use standard arithmetic operators on matrices. Judicious use of this in libraries makes the resulting code much briefer.

Yes, this is another specific area where dynamic languages do prototyping better and can produce shorter code. I did an exercise where someone implemented a routine in Clojure that I had written in Python. The Python was shorter! In part, this was due to list comprehensions. In part, it was due to an excellent library. What you describe is what many Smalltalkers did as well: create your own control structures and DSLs.

I've sometimes wondered what could be done with a dynamic superset language of Go, such that one could mostly add type definitions and compile to Go.