I think of Jupyter Notebooks as scratch paper on my desk. It's not to archive things, it's for developing ideas. Once ideas are developed, I transfer them to a long-term medium (LaTeX or Markdown document, Python source file, etc).
It was easy to use as a presentation, with figures and plots embedded. With controls enabled, you could demonstrate what varying certain parameters would do and pitch proposed cleaning profiles.
I was rather easily able to send a directory and it's notebooks/data sources to colleagues in the water sciences team so they could validate my results on their own (they were luckily also familiar with Python and Jupyter), and caught some minor bugs in the pipeline.
This was all much more collaborative and concise, and I feel Jupyter played a huge part in it.
Once it was done, it and a "final draft" pdf were added to the Docs in the repo and the pipeline was written out into a full application of it's own.
Add in # %% and it makes the code executable in isolation. Like a cell in jupyter. This means i can write a py file. Execute bits indepentantly and when im ready to check it in just remove the block comments