> The point of probabilistic programming is write inference algorithms once for a large class of models and be done. So the advantage of using a fancier method is amplified.

So that should be something where a few standard libraries or toolsets should emerge that push out the "easy-to-implement" default choice? Are there any contenders yet? (As you might be able to tell, I don't really know anything about the field)