This is an attempt to write down the best possible body of pragmatic psychotechnology for autodidacts, teaching & founding a next-generation education system on a ruthless representation of the most effective tactics.

52 practices were considered and stripped down to my conception of the 10 with the most cognitive leverage, best performing on time-result-generality frontier. All ten work for in almost every context, have fantastic time-to-improvement ratios when invested in, and when integrated as the basis of a learning system have the highest hope of generating phenomenal minds.

38 books, lectures and articles on how to learn were considered, of which I highly recommend 9.The fuller list of practices and resources is included under "Additional Pedagogy Candidates" and "Extended Metalearning Curriculum".

In teaching, we find ourselves forced to abandon the comfortable fog of half-knowledge, those shadowy realms where we nod sagely at complex terms while secretly harboring confusion. Instead, explain things in the simplest possible way, cutting fog into clarity.

Pick something you want to understand. Could be quantum electrodynamics or how a toaster works - doesn't matter.

Try explaining it to a 12-year-old. Not a real one necessarily - imagine you're talking to a smart kid who doesn't know the jargon. If you catch yourself using fancy words or handwaving through parts, stop! That's a red flag that you don't really understand that bit.

When you hit those gaps in your understanding - and you will, we all do - go back to your books or notes and fill in those holes. Keep working until you can explain the whole thing in simple language.

Finally, simplify and use analogies. If your explanation is clunky, streamline it. Find analogies that connect to things people already understand.

The wonderful thing about this approach is that it's a feedback loop - you learn something, try to explain it, discover what you don't know, learn some more, explain again... and pretty soon, you've got it wired into your brain in a way that's rock solid.

Remember, if you can't explain something simply, you don't understand it well enough yet. And that's okay! That's how you know what to work on next.

Let's take playing the violin. A regular person might just play songs over and over. But someone using deliberate practice would isolate the difficult parts – maybe a tricky fingering pattern – and work on just that small section, slowly at first, getting feedback from a teacher, gradually increasing the tempo. They'd record themselves and listen critically. They'd compare their sound to masters.

The key ingredients:

• Having clear goals for each practice session. Not "I'll practice for an hour" but "I'll master this specific technique."
• Full concentration and effort. This isn't the kind of practice you can do while watching TV!
• Feedback – immediate if possible. You need to know if you're getting it right.
• Working at the edge of your ability – not too easy (that's boring) and not too hard (that's frustrating).

Here's a secret most people miss: deliberate practice isn't fun in the usual sense. It's challenging. Sometimes it's frustrating. You're deliberately focusing on what you can't do well yet!

So if you want to get really good at something – I mean really good – you can't just put in the hours. You have to put in the right kind of hours. Break it down, focus intensely, get feedback, push your limits, and repeat.

When I was reading the Deep Learning Textbook, rewriting every section in my own words was crucial to long term, high quality retention. https://docs.google.com/document/d/1KtLsLnMWIZIvb2hbOMrp_ZTocvaaLPJhgOHTkNyeAN0/edit?tab=t.0

Let me tell you what happens. You read a page in one of a fancy textbook filled with equations, and you think, "Yeah, I got it." But then you close the book and—poof!—it's gone. That's not understanding at all!

What really works is this: read something, then put the book down and write it down—in your own words, as if you're teaching it to someone who's never heard of it before.

There are multiple reasons:

• First, it forces you to pay attention to the text in the first place. There's nothing as disappointing and time wasting as getting through a page of text, going to write your own version of it, and realizing that due to your skimming & distracted attention, almost none of the page you just read still sits in memory for you to rewrite. And so after this happens, you realize you have to lock-in while reading to have a hope of doing a great job in recall.
• Second, it immediately puts you in a different position from reading: recall. In recall, you often have to use contextual clues & connected concepts to remember what you've read. Using the progression of meanings, and not just the words, is essential 'chunking' or compression of the content so that you can store it long enough to successfully recall most of it at re-write time. This change in representation of the text makes it much more amenable to long term memory.
• Finally, your representation of the text can then be read by you (or a third party), and so your understanding can be checked & validated against the original text. It's far harder to get away with a fuzzy or BS representation of the text when judgement of your writing can be levied.

You haven't really learned something until you've used it to make something new. That's the simple truth of it.

The principle applies to any knowledge. If you've just learned about differential equations, don't just solve the problems at the end of the chapter. Try to model something real—maybe the spread of a disease, or the cooling of a cup of coffee. Start with the simplest version and build up.

When you apply knowledge, especially from first principles, several magical things happen:

First, you discover the *practical* gaps in your understanding immediately. There's no hiding from them. When your program crashes or your bridge model collapses, you know exactly where your knowledge is incomplete.

Second, you form connections between this new knowledge and things you already know. These connections are the real gold—they're what turn isolated facts into a web of understanding.

Third, you remember it far better. Our brains are wired to remember things we've actively used, especially when there were consequences (even just the consequence of whether your project worked or not).

The best applications are creative ones. Don't just follow a recipe or tutorial—modify it, extend it, combine it with something else. Ask "what if?" questions. What if I tried this approach instead? What if I combined these two techniques? What if I applied this math to a completely different domain?

And start simple. You don't need to build a fusion reactor to apply your physics knowledge. Start with a small project that you can complete, then build on it. Each success gives you confidence and deeper understanding for the next challenge.

The reason so many of your learning experiments fail is you're *using the wrong material*.

Answer two questions: What resource will you love to learn from? And what resource is at *exactly* the right level of difficulty for you to be both gratified and challenged?

The material should be properly sequenced and incremental. You can't learn calculus before algebra, and you can't learn to run before you can walk. Each new piece should build on what came before, with just the right amount of challenge—not so easy that you're bored, not so hard that you're lost.

Focus on the vital foundations. In almost any field, roughly 20% of the concepts will give you 80% of the power. Identify that critical 20% and master it thoroughly before worrying about the rest.

For example, if you're learning programming, understanding variables, functions, loops, and conditionals will let you build surprisingly powerful things. The other 80% of language features are important eventually, but not at first.

Or if you're studying physics, mastering Newton's laws, conservation principles, and basic calculus gives you the foundation to understand a vast range of phenomena. The exotic stuff can come later.

How do you identify this critical 20%? Look for concepts that:

• Are used frequently in real applications
• Explain many different phenomena
• Have stood the test of time
• Are prerequisites for many other concepts

And remember: the best material is often not the most advanced, but the most fundamental, explained with exceptional clarity. A brilliant explanation of a basic concept is worth far more than a mediocre explanation of an advanced one.

So before you dive into learning something new, take the time to find the right material—incremental, focused on fundamentals, and cutting straight to the heart of the matter. Your future self will thank you.

Our brains are leaky buckets. That's just how they work. You learn something today, and if you don't use it, most of it will be gone in a week. It's not a design flaw—it's a feature. Your brain is optimized to remember things that you use repeatedly and forget things you don't need.

So if you want to remember something long-term, you need to convince your brain that it's important. And the most efficient way to do that is to recall it just when you're about to forget it.

That's the essence of spaced repetition. It's not complicated, but it is powerful. Here's how it works:

Learn something new. Then review it after about a day. If you remember it well, wait longer before the next review—maybe 3 days. If you still remember it then, wait even longer—perhaps a week. Each time you successfully recall the information, increase the interval before the next review.

This works because each time you recall something just as it's fading, you strengthen the neural pathways. It's like exercise for your memory—the struggle to recall makes the memory stronger, just as the strain of lifting weights makes your muscles stronger.

The beautiful thing about spaced repetition is its efficiency. Traditional studying often involves reviewing everything multiple times, whether you know it well or not. With spaced repetition, you focus your time on what you're about to forget, and spend less time on what you already know well.

You can implement this with simple flashcards, reviewing them at increasing intervals. But in my opinion, what is much stronger is building repetition into one's life with community, projects or writing. You can also use software like Anki that automatically schedules reviews based on how well you knew each card.

But here's a key insight: spaced repetition works best for atomic facts or small concepts that can be recalled in a single moment. For complex skills or interconnected knowledge, you need to combine it with other techniques like deliberate practice or teaching.

And remember—the goal isn't just to memorize facts. It's to build a foundation of knowledge that's so solid you don't have to think about it. When the basics are automatic, your working memory is freed up to focus on the novel, creative aspects of whatever you're doing.

That's why musicians practice scales, why mathematicians memorize formulas, and why pilots memorize emergency procedures. Not because memorization is the goal, but because it's the foundation that makes higher-level thinking possible.

There's a peculiar quirk in how we learn: we're terrible at judging what we know. We confuse familiarity with understanding, recognition with recall, and exposure with mastery. It's like thinking you can play basketball because you've watched a lot of games.

This is where testing yourself comes in. Not as punishment, not as assessment, but as a powerful learning tool.

When you test yourself, several remarkable things happen. First, you get an honest signal about what you actually know versus what you think you know. It's the difference between saying "Oh yeah, I know that" when you see a concept, and actually being able to explain it from scratch.

Second, the very act of retrieving information strengthens your ability to recall it later. This is called the "testing effect" or "retrieval practice," and it's one of the most robust findings in cognitive science. The mental effort of pulling something from memory makes that memory stronger and more accessible next time.

Third, testing reveals exactly where your understanding breaks down. Maybe you can solve simple problems but struggle with complex ones. Maybe you know the facts but can't connect them. These gaps would remain invisible if you just reviewed your notes.

How should you test yourself? There are many ways:

• Close your book and write down everything you remember about a topic
• Try to solve problems without looking at examples
• Explain a concept out loud as if teaching someone else
• Create your own questions and answer them later
• Use flashcards for key facts and concepts

The key is to make it challenging but not impossible. If you can't recall anything, it's too hard. If you can answer without thinking, it's too easy. The sweet spot is where you struggle a bit but eventually succeed.

And remember: getting things wrong when you test yourself isn't failure—it's information. It tells you exactly what you need to focus on next. In fact, some research suggests that failing to retrieve something and then learning the correct answer leads to stronger memory than simply studying it in the first place.

So don't wait until the night before an exam to test yourself. Make it a regular part of your learning process, and watch your understanding deepen and solidify.

We are not primarily creatures of reason and willpower. We are creatures of habit. Most of what you do today, you'll do tomorrow, and the next day, and the day after that. This can work against you—or it can be your greatest ally in learning.

The secret is to build learning habits so strong that they feel strange to break. When this happens, continuing to learn takes less willpower than stopping.

Think about brushing your teeth. You don't debate whether to do it each night or calculate the long-term benefits. You just do it, because not doing it would feel wrong. That's the power of habit.

One of the most effective ways to build a learning habit is through streaks—unbroken chains of days where you practice, even if just a little. There's something psychologically powerful about not wanting to break the chain.

Here's how to build effective learning streaks:

First, make it ridiculously small to start. Don't commit to studying for two hours daily—commit to opening your book for just five minutes. The key is consistency, not intensity. You can always do more once you've started, but the habit needs to be so easy you can do it even on your worst days.

Second, attach it to an existing habit. Study right after your morning coffee, or just before your evening shower. This creates a trigger that reminds you automatically.

Third, track your streak visibly. My favorite way to do this, by far, is Google Sheets. Share it with a friend, color-code your wins, and flexibly add more goals as you go. But feel free to use any method you like: cross off days on a calendar, use an app that shows your chain, or keep a learning journal. Make the streak itself rewarding to maintain.

Fourth, plan for failure. Decide in advance what happens if you miss a day. The rule might be "never miss twice in a row" or "if I miss a day, I do a shorter session the next day, but I still do something."

The beauty of this approach is that it works with human nature rather than against it. Instead of relying on motivation (which fluctuates) or willpower (which depletes), you're building automatic behaviors that carry you forward even when you don't feel like studying.

Remember: the greatest threat to mastery isn't lack of talent—it's inconsistency. Mastery is just a (thoughtful) 10,000 hours away. For more on this concept, watch this video on deliberate practice and the path to expertise.

Imagine you're trying to understand a forest. You could study it from a satellite view, seeing patterns of growth and the overall shape. Or you could examine a single leaf under a microscope, understanding its cellular structure. Both perspectives are valuable, but neither alone gives you complete understanding.

This is the power of alternating between levels of abstraction when learning. You need both the forest and the trees—and everything in between.

At the highest level of abstraction, you're asking: What's the big picture? How does this connect to other fields? What are the core principles? This gives you context and meaning, helping you see why the details matter.

At the lowest level, you're breaking concepts down to their simplest components. What are the fundamental building blocks? How exactly does this mechanism work? This gives you precision and clarity, ensuring your understanding isn't just vague handwaving.

The magic happens when you move between these levels, repeatedly. Start with the big picture to get oriented. Then dive into the details to build solid understanding. Then zoom back out to see how those details fit into the larger context. Then dive into a different set of details. Back and forth, like breathing in and out.

This approach works because knowledge isn't flat—it's hierarchical and networked. Concepts contain subconcepts, which contain further subconcepts. And everything connects laterally to related ideas.

Here's a concrete example: If you're learning about evolution, you might start with the big idea (species change over time through natural selection). Then examine the mechanisms in detail (genetic variation, inheritance, differential reproduction). Then zoom back out to see how evolution connects to other fields like geology, genetics, and ecology. Then dive into specific examples like the evolution of antibiotic resistance or the Galápagos finches.

This alternation helps you in several ways:

• It prevents getting lost in details without understanding their significance
• It ensures your high-level understanding is grounded in concrete reality
• It helps you transfer knowledge between domains by recognizing patterns
• It builds a mental model that's both broad and deep

One practical technique is to decompose and recompose concepts. Take something complex, break it down to its simplest elements, understand each one thoroughly, and then rebuild the whole. This is like taking apart a watch, examining each gear and spring, and then reassembling it. Once you've done this, you don't just know what the watch looks like—you understand how it works.

The methods described above represent some of the most powerful learning techniques available. However, there's a rich ecosystem of additional approaches that, while perhaps not quite as universally impactful, can still significantly enhance your learning journey. These techniques are particularly valuable when tailored to your specific learning style, subject matter, or circumstances.

Consider experimenting with these approaches as supplements to the core methods:

• Get into a social environment that reinforces the right beliefs and values
• Work for 10,000 hourstowards your learning goal
• Develop "scales" - a core set of skills practiced daily
• Modify environment to support learning
• Eliminate distractions in the environment
• Structure behavior, at least on a weekly and daily basis
• Get into a space with experts in what you're looking to learn
• Pomodoro technique - small steps toward goals, process-oriented
• Set timer to 25 minutes, cut interruptions, focus hard, then reward
• Create abstractions/chunks by combining sets of ideas for working memory
• Use metaphor/analogy, transferring mental models between fields
• If procrastinating, focus on process instead of outcome
• Let yourself fall into the diffuse mode while thinking about a problem
• Alternate between focused thinking and diffuse thinking
• Establish the smallest step towards working on a problem
• Intentionally look to dream about what you're studying
• Concept mapping to visualize relationships
• Learn in different environments to avoid overfitting learning to context
• Promise a reward after a work session
• Create a library of chunks / latticework of mental models
• Overlearning (putting in extensive work in batch)
• Interleave content to increase flexibility of understanding
• Have a trigger-action plan when caught in a bad habit routine
• Create an emotional reward for new habitual behavior
• Plan quitting time on daily goals
• Strongly isolate work from leisure
• Work on hard/disliked tasks when you wake up, with fresh willpower
• Use mnemonics for difficult-to-remember information
• Memory Palace Technique (link visual/spatial thinking with concepts)
• Meditation / Deep Breathing to improve focus
• Thoroughly understand the basics of content, the building blocks
• Take breaks to avoid drops in attention span
• Visualization of concepts or processes
• Focus tracking to measure attention quality
• Urge propagation - acknowledging distracting urges without acting on them
• Apply the 80/20 principle to learning priorities
• Cultivate a growth mindset
• Optimize nutrition for cognitive performance
• Define a consistent study schedule
• Goal-factor your learning objectives
• Zone Reading: Read text while listening to its audio at 2x speed
• Incremental writing to develop ideas gradually
• Incremental reading to process large volumes of material
• Learn in public - share your learning journey with others

The beauty of these additional techniques is that they can be mixed and matched according to your needs. Some may resonate strongly with your personal learning style, while others might be particularly well-suited to specific subjects or learning challenges. The key is experimentation—try different approaches, observe their effects on your learning, and gradually build a personalized toolkit that works for you.

Remember that learning how to learn is itself a skill—perhaps the most valuable meta-skill you can develop. By thoughtfully combining these techniques with the core methods described earlier, you can dramatically accelerate your learning in any domain.

If you're serious about developing your learning abilities to their fullest potential, these resources provide a comprehensive foundation. Each offers unique insights into the art and science of learning, from different but complementary perspectives.

This curated collection represents some of the most valuable works on learning how to learn—books and courses that have transformed the learning journeys of countless individuals:

• The Inner Game of Tennis by W. Timothy Gallwey
  The Classic Guide to the Mental Side of Peak Performance
  Though ostensibly about tennis, this pioneering work explores how our minds often interfere with our learning and performance, and offers profound insights into overcoming these internal obstacles.
• The Art of Learning by Josh Waitzkin
  An Inner Journey to Optimal Performance
  Chess prodigy and martial arts champion Josh Waitzkin shares his personal journey and the principles that allowed him to reach the top of two entirely different disciplines.
• Atomic Habits by James Clear
  A practical system for building good habits and breaking bad ones, with profound implications for learning. Clear explains how tiny changes in behavior can lead to remarkable results over time.
• Learning How to Learn [Coursera]
  This popular online course by Dr. Barbara Oakley and Dr. Terrence Sejnowski provides a comprehensive overview of evidence-based learning techniques, explaining the science behind effective learning strategies.
• Ultralearning by Scott Young
  A blueprint for aggressive, self-directed learning projects that can help you quickly master hard skills, based on Young's experiences learning MIT's four-year computer science curriculum in one year.
• Your Brain at Work by David Rock
  Explores how your brain functions throughout the workday, offering strategies to overcome distractions, regain focus, and work smarter with what your brain does best.
• Deep Work by Cal Newport
  Rules for Focused Success in a Distracted World
  Presents the concept of deep work—the ability to focus without distraction on cognitively demanding tasks—and provides a training regimen for transforming your mind and habits.
• How to Read a Book by Mortimer J. Adler and Charles Van Doren
  A classic guide to intelligent reading, offering a systematic approach to extracting the maximum value from books across various genres and difficulty levels.
• You and Your Research [Talk] by Richard Hamming
  A legendary talk given by mathematician Richard Hamming on how to do significant research and creative work, filled with timeless wisdom about learning, focus, and intellectual ambition.

These resources complement each other beautifully—some focus on the psychological aspects of learning, others on practical techniques, and still others on the habits and environmental factors that support deep learning. Together, they provide a comprehensive foundation for anyone serious about mastering the meta-skill of learning itself.

The journey to becoming an exceptional learner is itself a learning process. As you explore these resources, you'll likely find that some resonate more strongly with you than others. Trust this intuition—it's a sign that you're developing your own philosophy of learning, one that's tailored to your unique mind and circumstances.

Once you've explored the foundational resources, this extended curriculum offers additional perspectives and specialized approaches to learning, cognition, and performance. These works delve into specific aspects of mental development, from memory techniques to flow states, from cognitive biases to mindfulness practices.

• The Mind Illuminated by John Yates
  A comprehensive meditation guide that offers insights into attention, awareness, and cognitive development.
• Flow: The Psychology of Optimal Experience by Mihaly Csikszentmihalyi
  Explores the state of complete immersion in an activity, where challenges and skills are perfectly balanced.
• Mastery by Robert Greene
  Examines the lives of historical masters to extract principles for achieving excellence in any field.
• Mind Hacking by John Hargrave
  Applies programming concepts to mental processes, offering practical techniques for "debugging" thought patterns.
• The Rise of Superman by Steven Kotler
  Investigates how extreme athletes achieve flow states and how these principles can be applied to learning.
• Peak: Secrets From New Science Of Expertise by Anders Ericsson
  The definitive work on deliberate practice by the researcher who pioneered the field.
• Teach Students How To Learn by Saundra McGuire
  Practical strategies for metacognition and self-regulated learning from an experienced educator.
• Metacognition by John Dunlosky
  A scientific exploration of how we think about our own thinking and learning processes.
• Making Thinking Visible by Ron Ritchhart
  Techniques for externalizing thought processes to improve understanding and retention.
• Make It Stick by Peter C. Brown
  Evidence-based techniques for effective learning, challenging many common but ineffective study habits.
• Moonwalking With Einstein by Joshua Foer
  A journalist's journey into the world of memory championships, revealing ancient and modern memory techniques.
• The Memory Book by Harry Lorayne and Jerry Lucas
  Classic guide to memory improvement techniques that can be applied to any learning challenge.
• The Power of Now by Eckhart Tolle
  Explores how present-moment awareness can enhance focus, reduce anxiety, and improve learning.
• Mind Gym by Gary Mack
  Mental training techniques from sports psychology that can be applied to learning and performance.
• 4 Hour Workweek by Timothy Ferriss
  While primarily about productivity, contains valuable insights on minimal effective doses in learning.
• Stress for Success by James Loehr
  Reframes stress as a potential catalyst for growth and improved performance when properly managed.
• Black Hole Focus by Isaiah Hankel
  Strategies for developing intense concentration and purpose-driven learning.
• The One Thing by Gary Keller
  Explores the power of narrowing focus to achieve extraordinary results in learning and performance.
• The Intellectual Life by A.G. Sertillanges
  A classic work on developing the habits and mindset necessary for serious intellectual endeavor.
• The Art of Mental Training by DC Gonzalez
  Mental conditioning techniques from elite sports that can enhance learning performance.
• Educating the Reflective Practitioner by Donald Schön
  Explores how professionals learn through reflection on their practice and experience.
• How to Take Smart Notes by Sönke Ahrens
  A guide to the Zettelkasten method of note-taking that transforms reading into understanding.
• The Hypomanic Edge by John D. Gartner
  Examines the relationship between certain personality traits and exceptional achievement.
• Zen Mind, Beginner's Mind by Shunryu Suzuki
  Classic work on cultivating an open, receptive mindset conducive to learning and insight.
• The Champion's Mind by Jim Afremow
  Mental training techniques from elite athletics that can be applied to learning challenges.
• Heuristics and Biases edited by Thomas Gilovich et al.
  Academic collection on cognitive shortcuts and errors that can impact learning and decision-making.
• Misbehaving by Richard Thaler
  Explores behavioral economics and the predictable irrationality that affects learning and performance.
• Predictably Irrational by Dan Ariely
  Examines systematic patterns in human irrationality that can be recognized and overcome.
• The Great Mental Models Volume 1 by Shane Parrish
  Introduction to fundamental thinking tools that improve learning and decision-making across domains.

This extended curriculum represents diverse approaches to learning and cognitive development. Some focus on specific techniques like memory systems or note-taking methods, while others address the psychological and philosophical foundations of effective learning. Still others examine the cognitive biases and limitations that can hinder our progress.

As with any curriculum, the goal isn't necessarily to read every book, but rather to explore the areas that most resonate with your learning style and current challenges. Each of these works offers valuable insights that can be integrated into your personal approach to learning and cognitive development.

This essay emerged through the collective wisdom of many: The Inspired Autodidacts Community (facebook.com/groups/inspiredautodidacts) for their experimental spirit; Lillian Tara of the Center for Educational Progress for the initial vision of reimagining education; Michael Tartre and Ivan Vendrov for their critical feedback that refined these ideas; Nielda Gagne and Lauren Moos for their accountability support; and the countless researchers whose empirical work on learning effectiveness forms the foundation of these approaches. Any insights belong to this broader community; any errors are entirely my own.