It describes 3 new generics in base R that help their new S7 system.
It all seems motivated by better interop with python which is 'neat' but really doesn't seem like a critical necessity of the language. I guess it's more of a tactical thing where they're trying to make it easier for python users to eventually try R. Or for R users that work alongside python users to not abandon R.
I trust the authors immensely but i don't see what yet another class system in R solves. That's on me, but I'd like to understand more of what motivates this effort.
In other words OOP can be great for tooling, but doesn't make much sense for what R is meant to be used for -interactive analysis- in every day work.
R's mess of OOP systems works great, S3 is "fine" for just dispatching 'methods' based on attributes, one doesn't even know it's happening in base R ALL the time.
R flexibility also makes it possible to build your own class system. i.e. modern ggplot2 has its own ggproto object system.
I'm an old R user forced to mostly use python because that's what the team uses.
R is so much better than python in many areas concerning data pipelines: connecting with external database systems through an unified API, superior data munging utilities, as well as plotting, a more comprehensive (obviously) statistical analysis toolset.
I even find rmarkdown vastly superior to jupyter.
But IMO the best reason to use R rather tha python is that its tools will make you approach the problem as a statistician rather than a programmer.
The sooner SQL is phased out in favor of something more akin to Hadley Wickham's dplyr the better. Don't particularly like the syntax of this but it's the right direction.