The Feynman Technique: Master Any Coding Concept in 4 Steps

richardfeynman
WHAT

The Illusion of Understanding

Ever felt confident about a concept until someone asked you to explain it? That gap between “I get it” and truly understanding is exactly what the Feynman Technique destroys.

Named after Nobel Prize-winning physicist Richard Feynman (nicknamed “The Great Explainer”), this method is based on one simple truth: if you can’t explain something simply, you don’t fully understand it yet.

For software engineers juggling microservices, algorithms, and design patterns, this technique is your secret weapon.

4 STEPS

The Four Steps That Change Everything

Step 1: Pick a Specific Concept

Choose a focused, well-defined topic—not a vague domain. Specificity is crucial because it keeps your learning manageable and prevents you from fooling yourself into thinking you understand something when you’ve only grasped the surface.
 
Why specificity matters: According to the University of York’s guidance on the Feynman Technique, breaking concepts down to their core components helps you “understand it as a whole” rather than collecting disconnected facts. When topics are too broad, you can’t effectively test your understanding.
Do: SPECIFIC
You can actually master this
  • “How does React’s virtual DOM diffing algorithm work?”
  • “What’s the difference between useState and useReducer?”
  • “How does React’s reconciliation process determine what to re-render?”
Don't: TOO BROAD
You’ll never finish
“Learn React”

Step 2: Teach It to a Beginner (Or a Rubber Duck)

Now comes the heart of the technique: explain your concept as if teaching it to someone with zero technical background. This means no jargon, and no assumptions.

Why teaching works: According to E-Student’s research, this step “forces you to not only deeply master the information but to also grasp how all of the different elements join together.” The act of teaching reveals whether you truly understand or are simply parroting memorized definitions.

The Rubber Duck Connection: This directly connects to rubber duck debugging from The Pragmatic Programmer (Hunt & Thomas, 1999). Developers discovered they could solve bugs by explaining their code line-by-line to an inanimate rubber duck. Why? Because articulating your thinking exposes logical gaps and faulty assumptions you'd otherwise miss.

Different teaching methods work for different people:

Step 3: Identify Your Knowledge Gaps

While explaining, you’ll inevitably hit walls—moments where you realize you can’t clearly articulate something, or questions you can’t answer. These gaps are gold. They pinpoint exactly what you need to study.

The psychology behind this:
According to Ali Abdaal’s analysis, “identifying where we’re struggling makes us more intentional about our learning. Instead of covering stuff we already know (like when we reread or highlight), we automatically focus on topics that need the most work.”

As Carol Dweck’s growth mindset research demonstrates, students who believe their intelligence can be developed (growth mindset) outperform those who think abilities are fixed (fixed mindset). Embracing knowledge gaps—rather than avoiding or hiding them—is the hallmark of a growth mindset. These gaps aren’t failures; they’re your roadmap to mastery.

Richard Feynman’s own words: “The first principle is that you must not fool yourself and you are the easiest person to fool.” When you can’t answer a child’s “why?” question about your topic, you’ve found a gap that needs filling.

The iterative nature: As Noji’s comprehensive breakdown explains, “this step may repeat several times before you’re ready to say ‘I nailed it!’ But the more you explain the topic, the better you get.” Learning isn’t linear—it’s iterative.

Action steps when you find gaps

Step 4: Simplify and Use Analogies

Now take your refined understanding and make it even simpler. Strip away any remaining complexity. Create analogies that connect abstract concepts to concrete, familiar experiences.

 

Why analogies are powerful: According to University of York’s research, using analogies “improves comprehension by connecting concepts to personal experiences.” Our brains remember stories and comparisons far better than abstract definitions.

 

As Goodnotes explains, “Understanding starts with simplicity—we don’t understand something unless we can explain it simply. Using technical language or assuming our listener has existing knowledge means we’re relying on memorization, not understanding.”

 

The simplification challenge: E-Student notes that “to explain something so clearly that even young children with limited vocabulary can understand is extremely difficult. Attempting this forces you to not only deeply master the information but to also grasp how different elements join together.”

 

Refinement tips from research:

 

According to Todoist’s Feynman guide:
The iterative improvement process:

 

Virginia State University’s research portal emphasizes: “If there are areas where you’ve used technical terms or complex language, challenge yourself to rewrite these sections in simpler terms. Make sure your explanation could be understood by someone without the knowledge base you believe you already have.”

 

This might take multiple passes. That’s normal and expected. As Ali Abdaal notes, “this may take some time (or may have to be done multiple times) to get right.” Each iteration builds deeper understanding.

 

The ultimate test: Can a sixth-grader understand your explanation? If yes, you’ve achieved genuine comprehension. If no, you’ve found more work to do—and that’s valuable feedback, not failure.
WHY
The Protégé Effect

Why This Works

The Feynman Technique leverages the Protégé Effect—teaching is the most effective way to learn. When you teach, you must organize information coherently and own the material completely.

According to research from Growth Engineering (2026), this technique “systematically converts surface-level knowledge into deep, applicable understanding” by forcing you to monitor your own comprehension—the very skill missing in the Dunning-Kruger effect.

Real-World Example: Git Rebase vs. Merge

Step 1: Choose the concept
“How does git rebase differ from git merge?”

Step 2: Explain simply

MERGE: “I kept my diary, you kept yours,
now we’re combining both with a bookmark
showing where we joined.”
git merge feature-branch

REBASE: “I’m rewriting my diary as if I’d
already read yours first—one clean storyline.”
git rebase main

Step 3: Find gaps
– What happens to commit SHAs during rebase?
– Can I rebase pushed commits? (Yes, but…)
– What’s interactive rebase?

Step 4: Refine
“Merge adds a ‘the stories came together’ chapter. Rebase edits your manuscript to make events flow linearly from the start.”

Career Impact at Every Level

Junior Developers:
Build confidence, improve communication, accelerate learning

Mid-Level Engineers:
Ace technical interviews, enhance mentorship, deepen system design knowledge

Tech Leads/Managers:
Write better documentation, explain complexity to stakeholders, identify team knowledge gaps

CTOs/Entrepreneurs:
Pitch technology simply to investors, make better hiring decisions, rally teams around clear visions

Common Pitfalls to Avoid

Using jargon as a crutch
→ Explain to your non-technical friend
Skipping uncomfortable gaps
→ Remember Dweck: “Failure doesn’t define you. It’s a problem to face and learn from”
Over-simplifying to inaccuracy
→ Simple ≠ wrong; maintain technical accuracy

Quick-Start Action Plan

The Feynman Technique isn’t just a learning hack—it’s a fundamental shift in how you approach understanding. In a field where imposter syndrome runs rampant and new frameworks emerge weekly, having a reliable method to deeply learn anything is your competitive advantage.

Every expert was once a beginner who refused to pretend they understood what they didn’t. Stop reading more articles. Grab a rubber duck and start explaining.

Any intelligent fool can make things bigger, more complex, and more violent. It takes a touch of genius—and a lot of courage—to move in the opposite direction.

E.F. Schumacher

Thank You for Spending Your Valuable Time

I truly appreciate you taking the time to read blog. Your valuable time means a lot to me, and I hope you found the content insightful and engaging!
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FAQ's

Frequently Asked Questions

Start with 25-minute Pomodoro sessions. Complex topics like distributed systems may need multiple sessions. As research indicates, this technique "requires time and effort" but depth beats speed.

Use rubber duck debugging! Talk to any inanimate object, write blog posts, or create documentation. The articulation is what matters, not having an audience.

When you can: (1) explain without jargon, (2) answer "why" questions, (3) create original examples, (4) connect to related ideas, and (5) identify common misconceptions.

Absolutely! System design interviews essentially ask you to use the Feynman Technique on the spot. Practice explaining systems like "design Instagram" or "how Netflix streams video" to develop interview-winning clarity.

Yes! Break the language into specific concepts: "How does Python's GIL work?" or "What makes list comprehensions different from map/filter?" Research shows this technique applies effectively across programming, languages, and technical subjects.

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