Books like Thinking in Bets

Julia Galef's The Scout Mindset draws a line between two ways of processing information: the soldier mindset, which fights to defend existing beliefs, and the scout mindset, which tries to form an accurate map of reality regardless of whether the truth is comfortable. Like Duke, Galef is concerned with the gap between thinking well and thinking in self-serving ways, and she provides specific techniques for catching yourself when you have slipped from scouting to soldiering.

The book draws on research in psychology and decision science, but its real strength is the concrete exercises: Galef teaches readers to run thought experiments, calibrate their confidence levels, and notice when they are using reasoning to justify rather than to investigate. The writing is clear and conversational, less anecdotal than Duke's and more focused on building a systematic practice of intellectual honesty.

Readers who found Thinking in Bets' poker framework useful will find The Scout Mindset provides a complementary framework from the rationalist tradition, with more emphasis on emotional awareness and less on probabilistic calculation.

Philip Tetlock's Superforecasting presents the findings of the Good Judgment Project, a massive research effort to identify what separates accurate forecasters from poor ones. Tetlock found that the best forecasters share specific habits: they break problems into components, update their beliefs frequently, think in precise probabilities rather than vague feelings, and actively look for information that challenges their views.

Every one of these habits aligns with Duke's poker framework, where the best players are constantly updating their hand assessments as new cards appear. The book is more data-heavy than Thinking in Bets, grounded in years of tournament-style forecasting experiments, but the conclusions are similar: good prediction is a learnable skill, and the key ingredients are calibration, humility, and a willingness to change your mind.

The writing combines academic rigor with accessible storytelling, profiling specific superforecasters and showing how their thinking processes differ from the confident-but-wrong pundits who dominate public discourse.

Dan Ariely's Predictably Irrational documents the systematic ways humans deviate from rational behavior, running experiments that show people anchoring to arbitrary numbers, overvaluing things they own, and making different choices depending on how options are framed. Where Duke focuses on how to overcome these tendencies, Ariely focuses on cataloguing them with a scientist's thoroughness.

The experiments are clever and often amusing: Ariely tests how free items distort perceived value, how expectations shape taste perception, and how social norms interact with market norms in surprising ways. The writing is accessible and built around specific studies, making it easy to see the principles in your own behavior.

Readers who appreciated Thinking in Bets' argument that humans are bad at separating skill from luck will find Ariely provides a much longer list of the specific ways rationality breaks down, with each chapter offering a new category of predictable error.

Daniel Kahneman's Thinking, Fast and Slow is the foundational text for everything Duke writes about in Thinking in Bets. Kahneman's framework of System 1 (fast, intuitive, prone to bias) and System 2 (slow, analytical, effortful) provides the cognitive architecture that explains why poker players, investors, and ordinary decision-makers fall into predictable traps. The book covers decades of research on heuristics, framing effects, overconfidence, and the planning fallacy, with each chapter presenting a different way the mind cuts corners in ways that feel reasonable but produce errors.

Kahneman's writing is more academic and thorough than Duke's, organized as a comprehensive survey rather than a practical guide. This means the book takes longer to read but covers more ground. Duke herself cites Kahneman extensively, and reading the two books together gives you both the theory (Kahneman) and the application (Duke).

For readers who want the full scientific basis for Thinking in Bets' recommendations, this is the source.

Shane Parrish's The Great Mental Models presents a toolkit of thinking frameworks drawn from multiple disciplines, including inversion (approaching problems by thinking about what you want to avoid), second-order thinking (considering the consequences of consequences), and the map-is-not-the-territory principle. Where Duke provides one specific mental model, probabilistic thinking from poker, Parrish provides dozens of models from physics, biology, mathematics, and philosophy.

The book argues that the quality of your thinking depends on the models in your head, and that most people operate with too few, defaulting to the frameworks of their own training or profession. The writing is concise and example-rich, with each model illustrated through historical events, business decisions, and everyday situations.

Readers who found Thinking in Bets' betting framework useful will find Parrish provides an entire armory of additional frameworks, each designed to improve reasoning in a different type of situation.

Peter Brown, Henry Roediger, and Mark McDaniel's Make It Stick synthesizes cognitive science research on how people actually learn, as opposed to how they think they learn. The book shows that popular study strategies like rereading and highlighting are largely ineffective, while strategies that feel harder, like retrieval practice, spaced repetition, and interleaving, produce dramatically better retention.

The connection to Thinking in Bets is about feedback and calibration: Duke argues that most people learn the wrong lessons from experience because they confuse outcomes with decision quality, and Make It Stick shows that the same problem afflicts all learning when people mistake familiarity with mastery. The writing is accessible and practical, aimed at students, teachers, and anyone who needs to acquire new skills.

Readers who appreciated Duke's emphasis on process over outcome will find Make It Stick applies the same principle to learning itself, showing that the feeling of difficulty is often a sign that real learning is happening.

Richard Thaler and Cass Sunstein's Nudge takes the same cognitive biases Duke describes in individual decision-making and shows how they can be used to improve decisions at the institutional level. The book introduces choice architecture, the principle that how options are presented shapes what people choose, and demonstrates that small design changes (like making retirement savings the default option rather than an opt-in) can produce enormous behavioral shifts without restricting freedom.

Where Duke teaches individuals to recognize and correct their own biases, Thaler and Sunstein show how institutions can structure choices to compensate for biases at scale. The writing is accessible and often funny, with examples from healthcare, education, and environmental policy.

For readers who finished Thinking in Bets thinking about how to apply better decision-making beyond their personal lives, Nudge shows what happens when probabilistic thinking and bias awareness become policy tools.