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Well exactly, this is why languages like Lisp are so seductive and powerful - they let you write languages within the language. When you have a really flexible language like Lisp, it's tempting to produce a meta-language to describe your problem which is specific, terse, and powerful. However there's an interesting trade-off here. At first this seems like a wonderful solution, but if you ever work with a few other pe…
That's a legitimate concern. But then again, the world is full of programming languages. Sometimes you really appreciate what an R gives you when needing to do a lot of statistical computing and data wrangling, or what C or Rust offers for systems programming, and so on. And speaking of DSLs, the Pandas and Numpy libraries in Python are super useful, and they're possible because Python offers enough metaprogramming f…
DSLs/Jargon/New Languages are constructing a new world, and you need to be really sure the costs of that abstraction are outweighed by concrete and lasting benefits in the domain (sometimes they are, oftentimes they are not), crucially, this sort of language is often best used for a very specific domain and nowhere else (say R for statistics).