Sure, you’ll probably want to learn about priors, and invest a little in understanding diagnostics such as those provided by ShinyStan. But rstanarm is really designed to work well out of the box (i.e. with your existing code).
What I really appreciate is that it has useful warnings and error messages, and extensive documentation. Sometimes the documentation shows that quantitative analysis has something to do with mathematics, but even those who skip the Greek letters and formulae will get enough guidance. You’ll get nudges to use your own priors rather than rely on the default priors, but in my experience for most simple applications the default priors work reasonably well. You’ll also get suggestions right on your screen what you can do when there are say divergent transitions.
Once you can handle rstanarm, you’ll find it easy to upgrade to brms, where you can still use your trusted syntax for regression models in base R.
I had fun this morning when checking the results of the routing plagiarism check. There was one paper flagged as suspicious because it used quotes from published articles without quotation marks. It turns out, the student was guilty of using French-style quotation marks for English quotes — clearly inappropriate… not!