I'm someone who has been programming for a very long time and has been using notebooks for a reasonably long time (and almost always starts projects with them),

I'm someone who has been programming for a very long time and has been using notebooks for a reasonably long time (and almost always starts projects with them), my feeling is that they are a bit like C in that they make it easy to accidentally shoot yourself in the foot if you aren't careful. I always strive to end up with a notebook that can be "Run All" from a fresh clone, and I'd say that I'm successful with that maybe 60-70% of the time, and am close enough that I can fix it in the remainder. As the article (and the many others like it that have frequently cropped up as soon as IPython Notebooks first started ramping up in popularity) points out though, a lot of newer users don't have the discipline to ensure that they're not jumping around too much. It's not a problem for them in the immediate term since they know how the state ought to work, but then it becomes a mess when they try to share it with someone else (or to run it themselves again 3 months later). The challenge though is that the data analysis workflows that it allows are unbeatable by any other tools I've tried. In the end, it may just be that it's the worst form of data programming except for all of the others that have been tried.