>Engineering mode shuns uncertainty, because uncertainty may involve risk that corresponds to bad surprises. Discovery mode thrives under uncertainty, especially when a rare but beneficial result leads to finding something new, or a reduction of uncertainty in the face of making strategic decisions.
In summary, to understand the distinctions of Discovery and Engineering modes, one needs to have an appreciation for variation and the underlying distribution of outcomes expected while operating in each mode respectively. Without understanding the asymmetry in their outcome distributions, it would be difficult to convey how these work modes are different.
In the screenshot the window on the right does not look comparable to the output in a jupyter notebook. It looks more like a standard terminal. e.g. does it support interactive charts, html tables etc?
The Python interactive window uses the ipykernel package to allow rich outputs like that.
I still might be wrong and would like to be corrected on this, since it would mean R support in VS Code is now better than I thought (I haven't tried it fora. while)
Oh - nice, thanks - so it looks like the interactive window (which is effectivey the same as the output in a jupyter notebook) is also possible, but not (yet) 'properly'/'officially' supported
none of what you just said would be a plausible explanation for the persistence of poverty, economic instability, environmental degradation, drug addiction, chronic disease, etc etc
I'd bet even the authors of the 2 books you've hinted at wouldn't even make that claim. I'm sure they would see many of the problems listed as systems-level issues
