I guess the only limiting factor in dual booting would be a lack of skill to set up dual boot. It's quite intimidating at first. I have been dual-booting for ~8 years and I have had my fair share of blunders but nowadays setting up a dual boot pc is very easy especially for the tech savvy (people who are running a k8 cluster) people. I cannot even recall if there was any time where I could restore atleast windows part of the os.
This type of reasoning can be extended to any high-level tool. " Does no one writes there own OS. I don't understand the need for Linux or windows. I honestly thought windows or linux was nothing but a tool for undergrads to use Excel or host a WordPress site". And this is not a caricature of your argument. There is a lot of stuff under the hood that Tensorflow or Pytorch implement for a programmer. So much so that people have written wrapper for using TF or Pytorch to even further abstract the working of the library. Implementing deeplearning architecture is less of a science and more of a "let me try this or that" and iterating ideas quickly if of the utmost importance. Also, I can implement a neural network in C (CUDA) although not the auto diff part, but I could if given time to research) but if I started implementing my own library, it would take an order (or even more) of magnitude more time to do the stuff I do daily. We don't need to reinvent the wheel here guys.