I used to be you, almost exactly. Almost everything we do at work is in SAS, and I was pushing hard for R and Python and getting nowhere. I hated SAS because it was so clunky and out of date. So many SAS programs are bad because they're being done by statisticians with no programming background. Then I went to NESUG a few years ago and saw presentations by the likes of Whitlock, Dorfman, and others, and realized serious programming *was* being done in SAS. I resolved to just become the best SAS programmer I could. The first thing you need to do is stop programming Python in SAS. SAS is like Lisp in that it is a different paradigm, and not programming in that paradigm only makes things harder. Learn that paradigm. Learn the data step inside and out. Every time you have a %do loop, ask yourself if you can do it in a data step. Every time you wish you had OOP, ask yourself if you could represent the objects in a data set. Or learn the new ds2 data step that has OOP. Learn proc sql and know when it's better to use than a data step. That's what I did, and it took my SAS programming to a whole new level, and allowed me to innovate legacy code and transform the applications we were using. Because back when I was you, SAS wasn't the obstacle to innovation, I was.