
How Learning Actually Works According to Science
Re-reading and highlighting feel productive but are weak learning methods. Retrieval practice, spacing, and interleaving create durable understanding.
Explore fundamental concepts, mental models, and frameworks for clear thinking. From first principles to systems thinking, learn the ideas that shape how we understand the world.
Concepts are the building blocks of clear thinking. They're the fundamental ideas, frameworks, and principles that help us make sense of complexity, recognize patterns across domains, and make better decisions. From mental models to cognitive biases, from first principles thinking to systems theory, each concept offers a lens for understanding reality more accurately.
This collection explores core concepts from multiple disciplines: psychology, economics, philosophy, cognitive science, and decision theory. The goal isn't memorization, it's internalization. When you truly understand a concept, it changes how you see everything.
What you'll find: Deep-dive explanations of thinking frameworks, practical applications for real-world problems, connections between related concepts, and insights from research and expert practitioners.
How ideas spread, how language shapes thought, and how to communicate clearly
14 guidesFrameworks, mental models, and principles for making better choices under uncertainty and pressure
78 guidesClear, precise definitions of key terms, concepts, and frameworks used across knowledge domains
12 guidesMoral reasoning, institutional accountability, and the principles of responsible decision-making
34 guidesMental models, thinking frameworks, and structured approaches to problems
29 guidesHow people learn, retain information, and develop deep expertise over time, the science of knowledge
27 guidesFrameworks and ways of thinking that help structure understanding
4 guidesWhat to measure, how to design measurement systems, and how to interpret data without misleading yourself
10 guidesFundamental truths and rules that recur across science, business, and life, from Pareto to Goodhart and beyond
27 guidesHow minds work, why people behave as they do, cognitive biases, and the science of human behavior
269 guidesUnderstanding interconnected systems, feedback loops, and emergent behavior
26 guides
Re-reading and highlighting feel productive but are weak learning methods. Retrieval practice, spacing, and interleaving create durable understanding.

The theory of constraints says every system has one bottleneck that caps output. Learn the five focusing steps and how to improve what actually limits you.

The Overton window explained: how the range of politically acceptable ideas forms, why politicians follow it, and how extremes, repetition, and crises move it.

The sunk cost fallacy explained: Arkes and Blumer's theatre experiment, loss aversion, the Concorde fallacy, escalation of commitment, and how to beat it.

The premortem technique explained: how imagining a project has already failed, via prospective hindsight, surfaces risks that ordinary planning misses.

The availability heuristic explained: why we judge probability by ease of recall, how vivid events distort risk, and how to defend against the bias.

The anchoring effect explained through Tversky and Kahneman's wheel experiment, selective accessibility, courtroom and pricing examples, and how to fight it.

Satisficing settles for good enough while maximizing chases the best. Learn the costs of each, when to use them, and how to decide how to decide.

Hick's Law explained: how decision time grows logarithmically with the number of choices, its information-theory roots, design uses, and where it breaks down.

Goodhart's Law explained through its origin in monetary policy, Strathern's famous phrasing, the four flavors of Goodhart, surrogation, reward hacking, and how to defend against it.
Mental models are frameworks for understanding how things work in the world. They're simplified representations of reality that help you predict outcomes, make decisions, and solve problems. Charlie Munger's 'latticework of mental models' approach suggests that learning fundamental concepts from multiple disciplines, physics, biology, psychology, economics, gives you a toolkit for better thinking across all domains.
First principles thinking is the practice of breaking down complex problems into their most basic, foundational truths, then reasoning up from there. Instead of reasoning by analogy (doing things because that's how they've always been done), you question every assumption and rebuild from fundamental facts. Elon Musk popularized this approach in business, but it originates with Aristotle's philosophical method.
Systems thinking is the ability to see interconnections, feedback loops, delays, and leverage points in complex systems rather than isolated events and linear cause-effect relationships. It's important because most real-world problems exist within systems where changing one part affects the whole. Systems thinking helps you avoid unintended consequences and identify high-leverage interventions.
Second-order thinking means considering the consequences of consequences, thinking beyond the immediate effects of a decision to what happens next, and after that. First-order thinking asks 'What happens if I do this?' Second-order thinking asks 'And then what? And what happens after that?' This deeper analysis reveals unintended consequences that first-order thinkers miss.
Probabilistic thinking is reasoning with likelihoods and distributions rather than absolutes and certainties. Instead of asking 'Will this happen?' you ask 'How likely is this? What are the odds?' This approach acknowledges uncertainty and helps you make better decisions under conditions where perfect information doesn't exist. It's essential for risk assessment, forecasting, and strategic planning.
Apply mental models by: 1) Deeply understanding the core principle behind each model, 2) Recognizing patterns in real situations where the model applies, 3) Practicing deliberate application across different contexts, 4) Seeking feedback to refine your understanding, and 5) Building connections between related models. The goal is internalization, making the models second nature rather than memorized frameworks.
Inversion thinking (or inversion) means approaching problems backward, instead of asking 'How do I succeed?' ask 'How would I guarantee failure?' Then avoid those failure modes. This mental model, favored by Charlie Munger, helps you spot risks and obstacles you'd otherwise miss. It's especially useful for risk management, strategy, and avoiding common mistakes.