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Best and Worst Books, 2025

I read another 50+ books in 2025, and these are the ones that stood out--both the good and the terrible. Each link below will take you to my review and discussion notes.

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Thank you for reading, and all the best for 2026!

See also!

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Best (5/5 stars or close):
Deep Response by Tyler Disney
Before the Dawn by Shimazaki Toson
Broken Money by Lyn Alden
The Collapse of British Power by Correlli Barnett
Uncommon Therapy by Jay Haley
The Dhandho Investor by Mohnish Pabrai
The Practicing Mind by Thomas M. Sterner
Perpetuity by Kevin Joseph
Ghost Boy by Martin Pistorius


Worst (1/5 stars or close):
Why We Sleep by Matthew Walker
By All Means Available by Michael Vickers
Empire Incorporated by Philip J. Stern
The Best of S.J. Perelman by S.J. Perelman
Breaking Twitter by Ben Mezrich
Number Go Up by Zeke Faux

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The Dhandho Investor by Mohnish Pabrai

Worth reading, and rereading, and re-rereading. An elegant book that teaches fundamental principles of value investing, and much more. The Dhandho Investor  also has the highly unusual quality of being useful at a wide range of reader sophistication levels: you can gain tremendously from this book as a beginner or as a deeply experienced investor. I'll single out Chapters 5 and 6 for particular mention: Chapter 5 describes author Mohnish Pabrai's investing framework, with nine interlocking and synchronistic rules. Chapter 6 describes in very simple language all of the gigantic structural advantages of investing in the stock market, as it offers low frictional costs, a tremendous selection of possible businesses, and, most importantly, periodic incredible opportunities. These two chapters explain why you will take a pass on almost all investments--but then, once in a while, make large bets on specific situations that meet your requirements. [A quick  affiliate link to Amazon ...
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Good Thinking: The Foundations of Probability and its Applications by Irving J. Good

This collection of scientific papers is a challenging but useful discussion on statistical methods, probability, randomness, logic and decision-making. Much of the book centers around Bayesian statistical methods and when and why to use them, as well as "philosophy of science"-type discussions on when a scientist should--or sometimes must--apply subjective judgments to scientific problems. It will help enormously if you've had a semester or two of statistics to really get at the meat of this book. If not, scroll down a few paragraphs for a short list of layperson-friendly books that address many of these subjects more accessibly. [A quick  affiliate link to Amazon  for those readers who would like to support my work here: if you purchase your Amazon products via any affiliate link from this site, or from my sister site  Casual Kitchen , I will receive a small affiliate commission at no extra cost to you. Thank you!] Author Irving Good worked with Alan Turing at ...
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