You're Wrong All the Time, But All You Need Are Better Explanations

May 6, 2026

A host grapples with finding a foundational book built on shaky research and uses that to explore how to update beliefs when facts change. Listeners get a plain explanation of the replication crisis and why failed studies are common. The conversation reframes beliefs as evolving calibrations, warns against ego-driven clinging to old ideas, and highlights progress through better explanations.

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ANECDOTE

Host Confesses Doubt About A Once-Trusted Book

Jonathan Cutrell describes how Thinking Fast and Slow profoundly changed his thinking but many studies underpinning it failed replication checks.
He admits struggling with keeping a standing offer to buy the book because parts of its scientific basis appear questionable after the replication crisis.

INSIGHT

Replication Problems Are Systemic Not Singular

The replication crisis revealed many psychology findings, including ones Kahneman cited, don't reliably replicate under new studies.
Jonathan notes base rates: randomly sampled psychology studies are more likely than not to have replication issues, so this is systemic.

INSIGHT

Progress Means Replacing Explanations With Better Ones

David Deutsch's Beginning of Infinity frames progress as iteratively creating better explanations atop incomplete ones.
Cutrell argues improving explanations is the core move: Newton → Einstein is an example of replacing partial models with broader ones.

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What happens when you discover that a book that fundamentally changed how you think is built on a shaky foundation? In today's episode, I share my own struggle with the replication crisis surrounding Daniel Kahneman's *Thinking Fast and Slow*, and I use it as a springboard to talk about a much bigger skill: knowing how to update your beliefs when reality shifts underneath you. This isn't about throwing out science or losing trust in your heroes. It's about developing the muscle to replace old explanations with better ones — a skill that has never been more important for software engineers.

The Replication Crisis, Briefly Explained: Understand the difference between reproducing a study (re-running the analysis on the original data) and replicating one (recreating the study from the ground up), and why a surprisingly large portion of well-respected psychology research, including studies cited in Thinking Fast and Slow, doesn't hold up under scrutiny.
Base Rates Matter: Kahneman didn't pick uniquely bad studies. If you randomly sampled from the broader academic literature, you'd hit the same failure rate. The lesson isn't about one author — it's about how we evaluate any body of knowledge.
The Beginning of Infinity Framework: Drawing from David Deutsch's book, explore the idea that all progress is rooted in the assumption that we are fundamentally incorrect, and that improvement comes from continually building better explanations on top of incomplete ones.
Beliefs as Calibration, Not Truth: Your beliefs about what makes a good engineer, what makes good code, or what makes a good career move are not eternal truths. They are calibrations to your current reality, and that reality is changing fast.
The Ego Trap of Old Beliefs: Notice the very human, very subtle pull to defend things you previously argued for — not because they're still right, but because admitting otherwise creates a discontinuity with your former self. This is one of the biggest blockers to learning.
Two Competing Explanations of AI Adoption: Walk through a worked example of holding two predictions about AI in tension and asking honestly which one better explains the reality you're seeing — at both a macro industry level and the micro level of debugging a system.
Moving Goalposts Aren't a Conspiracy: A lot of what feels like shifting goalposts in our industry is just goalposts moving on their own. A big part of our job as engineers is figuring out where they are now and predicting where they're heading next.
Episode Homework: Pick one belief you hold strongly about your work — about what makes a good engineer, about a tool, about a process. Try to deconstruct it into its parts and ask whether a better explanation exists for what you're actually seeing.

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