Earlier quoted context omitted.
> plenty of very good arguments can be made you're better off not-reading at least one of them. I'm extremely confused as to why this would be the case for TAOCP. While I wouldn't recommend TAOCP for "just reading", I don't know why it wouldn't be recommended for study. Knuth provides a very interesting approach for algorithms analysis, deep in substance.
Let's say, like many people, you enjoy the occasional article from The Onion . You can very easily continue enjoying them without reading Animal Farm , Gulliver's Travels or the collected works of Aristophanes. TAOCP, to me, is in a similar category - it's worth remembering Knuth essentially carved the field of study out himself. If you need a reference or textbook, there are by now better places to start. If you are…
For example, suppose you want to learn about Binary Decision Diagrams. I have before me TAOCP Volume 4A, which has 57 pages of text, 22 pages of exercises, 58 pages of answers, and a wealth of references. (Section 7.1.4, you can see the draft Fascicle 1B online: http://www.cs.utsa.edu/~wagner/knuth/) There are simply no other books or papers where you can learn so much about BDDs and ZDDs this well or easily. The writing is crisp and clear, and is really intended to teach, not to be a reference to look up.
Of course, a lot of people have simply no need to learn about zero-suppressed binary decision diagrams, so they can just simply not read TAOCP. But that's a different claim from saying that it's a reference work or not a good read on its topics.