We use papermill extensively, and our team is all good programmers. The difference is plots. It is a lot easier to write (and modify our existing template) to create a plot for X vs Y than it is to build and test a script that outputs e.g. a PDF.

For example, if your notebook runs into a bug, you can just run all the cells and then examine the locals after it breaks. This is extremely common when working with data (e.g. "data is missing on date X for column Y... why?").

I think most of the "real" use cases for notebooks is data analysis of various kinds, which is why a lot of people dismiss them. I wrote a blog post about this a while ago: https://rachitsingh.com/collaborating-jupyter/