https://www.youtube.com/watch?v=GO6TsdwxcwM
I wish he had the people and support to help make animations and present the formulas in the correct notations. It starts to make sense though.
I want to get into quantum computing, especially since IBM has one you can play with on-line (your program queues up like old fashion punch cards):
https://quantumexperience.ng.bluemix.net/
..but to really use it, you need to know how these super weird quantum gates work. From what I can tell with QCL, everything a quantum computer can do, we can do with traditional computers. It's just that simulating 100 qbits takes an ungodly amount of memory and processing power. Quantum computers can't replace traditional computers, they're for a very specific problem space that can be defined with these quantum gate concepts.
My simulator, Quirk [2], is a bit easier to experiment with than IBM's. But it still assumes you know the basics.
Unless there are good alternatives to this, a quantum computer will never execute anything more complicated than an algorithm.
A very rough analogy, I suppose, would be "let's make Haskell more accessible by doing away with monads and referential transparency". At that point, you've departed from the paradigm Haskell puts forth, and you actually haven't made Haskell any bit accessible.
Your second point about "prototype in Python, rewrite slow bits in C". There isn't, as far as I'm concerned, that sort of problem with quantum programming at the moment. Maybe in a decade or two. It is difficult enough to even get an algorithm working altogether, let alone reasoning about speeding it up. To reason about speedups, you need a framework in which you can reason about performance on some machine model. One such machine model is described in the aforementioned reference.