The Feynman Technique: Learning Through Simplicity

A powerful method for mastering any concept by teaching it

Introduction

Have you ever thought you understood something, only to find yourself stumbling when trying to explain it to someone else? Or perhaps you’ve memorized definitions and formulas for an exam, only to realize weeks later that you can’t actually apply them? If so, you’ve experienced the gap between surface-level familiarity and deep understanding.

Richard Feynman, the legendary physicist and Nobel laureate, was known not just for his groundbreaking contributions to quantum mechanics, but for his remarkable ability to explain incredibly complex ideas in ways that anyone could grasp. His lectures were famous for their clarity, humor, and insight. Students and colleagues alike marveled at how he could take the most abstract concepts in physics and make them feel intuitive.

But Feynman’s gift wasn’t just natural talent—it was the result of a deliberate learning method he developed and refined throughout his career. This approach, now known as the Feynman Technique, is perhaps one of the most effective strategies for truly mastering any subject. And the best part? Anyone can use it.

If you want to master something, teach it. The more you teach, the better you learn. Teaching is a powerful tool to learning

• Richard Feynman

The Core Principle: Teaching as Learning

At the heart of the Feynman Technique lies a simple but profound insight: if you can’t explain something in simple terms, you don’t really understand it.

This principle cuts through one of the most common illusions in learning—the belief that because we recognize terminology or can follow along when an expert explains something, we therefore understand it ourselves. Feynman recognized that true understanding means being able to reconstruct an idea from first principles, to see its connections and implications, and to communicate it clearly without hiding behind jargon.

The act of teaching forces us to confront our own knowledge gaps. When we try to explain a concept to someone else, especially someone unfamiliar with the topic, we can’t rely on shortcuts or assumptions. We have to make every step clear, justify every claim, and answer the “why” questions that naturally arise. This process reveals exactly where our understanding is solid and where it’s shaky.

The Four Steps

The Feynman Technique breaks down into four concrete steps that you can apply to virtually any topic you want to learn:

Step 1: Choose Your Concept and Study It

Start by selecting the specific concept, theory, or skill you want to master. This should be focused enough that you can reasonably work through it in a study session, but substantial enough to be meaningful. For example, “machine learning” is too broad, but “how gradient descent works” or “the bias-variance tradeoff” would be appropriate targets.

Begin by studying the concept through whatever resources you normally use—textbooks, lectures, articles, documentation, or research papers. Take notes as you go, paying attention not just to what the concept is, but why it matters and how it connects to other ideas you know.

Don’t worry about mastering everything in this first pass. The goal here is exposure and initial comprehension. You’re gathering raw materials that you’ll refine in the next steps.

Step 2: Teach It in Simple Language

This is where the real learning begins. Take out a blank sheet of paper (or open a new document) and write out an explanation of the concept as if you were teaching it to someone who has never encountered it before.

The key constraints:

• Use simple, everyday language - Avoid technical jargon unless absolutely necessary, and if you must use it, define it clearly
• Assume no prior knowledge - Don’t assume your imaginary student knows prerequisite concepts
• Write or speak out loud - The act of articulation matters; thinking in your head isn’t enough
• Use examples and analogies - Connect the abstract to the concrete

Imagine you’re explaining to a curious 12-year-old, a friend from a different field, or someone who’s intelligent but has no background in your subject. This audience forces you to be clear, logical, and engaging.

For instance, if you’re learning about neural networks, you might start: “Imagine you’re trying to teach a computer to recognize pictures of cats. You show it thousands of cat pictures, and each time, the computer makes a guess. When it’s wrong, it adjusts its internal rules slightly. After seeing enough examples, these rules get good enough that it can recognize cats it’s never seen before…”

Step 3: Identify Gaps and Return to Source Material

As you work through your explanation in Step 2, you’ll inevitably hit points where you struggle. Maybe you realize you can’t explain why something works, only that it does. Perhaps you find yourself reaching for technical terms because you can’t explain the underlying concept. Or you might discover that you can explain individual pieces but can’t connect them into a coherent whole.

These struggles are gold. They’re precise indicators of where your understanding has gaps.

When you identify a gap, don’t gloss over it or hand-wave. Mark it clearly, then go back to your source materials and study that specific point until you can explain it. This targeted review is far more efficient than re-reading everything, because you’re focusing exactly where you need help.

For example, you might realize: “I said neural networks ‘adjust their rules,’ but I can’t actually explain HOW they adjust them.” This sends you back to study backpropagation specifically. Or: “I know gradient descent finds the minimum of a function, but I can’t explain why taking steps in the direction of steepest descent actually gets you there.” Back to the books for that particular concept.

This iterative process—teach, identify gaps, study, teach again—continues until you can explain the entire concept smoothly.

Step 4: Simplify and Refine with Analogies

Once you’ve worked through the major gaps, return to your explanation and polish it. Look for places where you can:

• Replace complex language with simpler alternatives - “iterate” becomes “repeat,” “optimize” becomes “make better,” “convergence” becomes “settling on an answer”
• Add analogies and metaphors - These create bridges between unfamiliar concepts and familiar experiences
• Remove unnecessary details - Focus on core principles rather than every edge case
• Organize logically - Make sure each idea flows naturally to the next

The goal isn’t to oversimplify or lose accuracy—it’s to express the concept with maximum clarity and minimum unnecessary complexity. As Einstein reportedly said, “Everything should be made as simple as possible, but not simpler.”

Great analogies make abstract ideas concrete. Explaining regularization in machine learning? Compare it to “preferring simpler explanations unless the data really demands complexity.” Teaching recursion? Use the analogy of “a recipe that includes itself as an ingredient, like when you look up a word in the dictionary and the definition contains another word you need to look up.”

Why This Method Works

The Feynman Technique is effective because it leverages several powerful learning principles:

Active recall over passive review: Rather than re-reading notes, you’re actively reconstructing knowledge from memory, which strengthens neural pathways and improves retention.

Metacognition: By monitoring your own understanding as you explain, you develop awareness of what you know and don’t know—a critical skill for effective learning.

Elaboration: Creating explanations, examples, and analogies forces you to process information deeply and connect it to existing knowledge, rather than storing it as isolated facts.

Immediate feedback: Gaps in your explanation provide immediate feedback about your understanding, allowing you to correct course quickly.

Simplification forces understanding: You can memorize the definition of “eigenvalue,” but you can’t explain it simply unless you truly grasp what it means. The constraint of simple language forces genuine comprehension.

Practical Tips for Implementation

Start small: Don’t try to explain an entire textbook chapter at once. Break complex topics into manageable chunks and apply the technique to each piece.

Actually write or speak: Don’t just think through your explanation mentally. The act of writing or speaking out loud reveals gaps that pure thought doesn’t.

Find a real audience when possible: Explaining to an actual person—a study partner, friend, or even a family member—adds accountability and often generates helpful questions you hadn’t considered.

Keep your explanations: Your simplified explanations become excellent study materials for review. They’re personalized to your understanding and far more accessible than textbooks.

Embrace the struggle: Difficulty in explaining something isn’t failure—it’s the technique working. Those struggles show you exactly what to study next.

Use visual aids: Diagrams, sketches, and illustrations can supplement your explanations and often make complex relationships clearer.

Applications Beyond Academic Learning

While the Feynman Technique is powerful for academic subjects, its applications extend much further:

• Professional skills: Learning a new programming framework, understanding business strategies, or mastering project management methodologies
• Problem-solving: When stuck on a problem, explaining it simply often reveals solutions or approaches you’d overlooked
• Communication: Practicing explaining your work simply makes you a better communicator with colleagues, stakeholders, or clients
• Debugging: In software development, “rubber duck debugging”—explaining your code to an inanimate object—is a direct application of this principle

Conclusion

The Feynman Technique isn’t about being smarter or having a gift for teaching. It’s about being honest with yourself about what you understand and what you don’t, and using that honesty as a guide for focused learning.

In a world that often rewards the appearance of expertise—where confident use of jargon can mask shallow understanding—Feynman’s approach is refreshingly authentic. It demands that we actually understand what we claim to know, and it provides a clear path to get there.

The next time you’re learning something new, try it: pick a concept, explain it simply, find your gaps, and refine. You might be surprised by how much you thought you knew but didn’t—and more importantly, by how quickly you can transform confusion into clarity.

As Feynman himself once said, “I learned very early the difference between knowing the name of something and knowing something.” The technique that bears his name is a powerful tool for ensuring we do the latter.

What will you learn—truly learn—next?