I have read so many books with some actually good ideas hammered for +200 pages, (just to justify the cost of printing, satisfy the industry standards, or whatever)
A half decent summary of all those would be of actual value. Get 80% of the value in 20% (or less) of the time.
I think the problem is - there's examples and anecdotes and whatever scattered throughout the book that make those ideas connect for you.
And this is different for everyone.
Maybe an ML you train yourself on highlights would be able to find the stuff that will connect for you - but I'm skeptical enough people read & highlight enough to train ML models to do this (or if it would even work).
Could possibly be done by iteratively summarizing section by section but that would give suboptimal results.
- The courage to be disliked (Ichiro Kishimi)
- The simple path to wealth (J.L. Collins)
- Peak (K Anders Ericsson)
- Happiness (Matthieu Ricard)
- Clean Code (Robert C Martin)