Upskilling

on

Advice

– Working Draft –

Note: If you are reading this as a PDF,

consider switching to the Google Doc
which may contain new updates.

Authored by Justin Skycak

Updated 5 July 2025
Advice on Upskilling – Working Draft

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 Justin Skycak

Authored by Justin Skycak

Copyright © 2025 Justin Skycak
First edition (working draft), updated 5 July 2025.

All rights reserved. No part of this publication may be

reproduced, distributed, or transmitted in any form or
by any means, including photocopying, recording, or
other electronic or mechanical methods, without the
prior written permission of the author, except in the
case of brief quotations embodied in critical reviews
and certain other noncommercial uses permitted by
copyright law. For permission requests, contact the
author through the website below.

www.justinmath.com/contact
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Contents​

Preface........................................................... 13
Chapter 1. Consistency................................ 15
► You’re Not Lazy, You Just Lack a Habit............ 15
► Don’t Have a Passion? Go Create One.............. 17
► Make the Habit Easily Repeatable..................... 18
► The Hardest Part is Just Getting Started.......... 19
► If You Struggle to Train Consistently, Do ​
It Immediately After Waking Up....................... 20
► Training Sessions Should be Short and ​
Frequent as Opposed to Long and Sparse........ 21
► A Little Extra Consistency​
⨉ A Little Extra Time​
= A Massive Increase in Volume & Progress..... 23
► Don’t Overreact to Bad Days.............................. 24
► Aim for Virtuous Cycles...................................... 25
► Protect The Habit................................................. 26
Chapter 2. Skills........................................... 27
► The Importance of Hardcore Skills....................27
► The “Alien-Level Skills” Hack............................ 28

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► The Importance of Having Your ​

Prerequisites In Place.......................................... 31
► Fortify Your F*cking Fundamentals...................32
► Your Missing Foundations Will Wait ​
For You...................................................................34
► Actively Doing is the Key to Alpha.................... 34
► Everything Matters...............................................35
► You Want Exciting Opportunities?​
Learn Math and Coding...................................... 36
► If You're Not Both Technical and a ​
Domain Expert, Then You're Underpowered...38
► Domain Expertise, Math, Coding, ​
Communication.................................................... 39
► What Math To Learn for Skill Stacking............ 40
► Failure Modes in People Who Develop ​
Math Skills but Don’t Capitalize On Them ​
via Coding..............................................................41
Chapter 3. Discipline................................... 45
► The Magic You’re Looking For is in the ​
Full-Assed Effort You’re Avoiding..................... 45
► At Some Point Doing the Hard Thing ​
Becomes Easier Than Making the Hard ​
Thing Easier.......................................................... 46
► How to Cultivate Discipline................................48
► Keep Your Hands On The Boulder.................... 49

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► Just Do The F*cking Work.................................. 51

Chapter 4. The Grind................................... 53
► Upskilling is Hard and That’s a​
Good Thing........................................................... 53
► The Most Superior Form of Training................ 53
► Outsized Success Requires Outsized Work...... 56
► Transformation Is Discomforting...................... 57
► Enjoyment is a Second-Order​
Optimization......................................................... 59
► Ability is Built, Not Unlocked............................ 60
► What Max-Efficiency Training Feels Like........61
► The Necessity of Grinding Through​
Concrete Examples Before Jumping Up a​
Level of Abstraction............................................. 62
► Be Willing to Do Tedious Work......................... 64
► Don’t Undervalue Turning Up the Dial on ​
Your Grind, but Don’t Overvalue the​
Last Turn............................................................... 65
► When More Volume Equals More Progress..... 67
► Failure Is NOT the Key to Success.....................68
► Don’t Drown Yourself in the Deep End............ 69
► Focus Less on Feelings and More on ​
Measurable Progress............................................ 70
► The Problem with Overly Difficult ​
Problems................................................................ 72
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► It’s Not Just About Attempting Hard ​

Things, It’s Also About Successfully ​
Achieving Them................................................... 73
► It Always Becomes a Battle of Willpower ​
By the End............................................................. 74
Chapter 5. The Journey................................77
► Don’t Get Hung Up on Youth ​
Competitions.........................................................77
► The 3 Stages of Talent Development................. 79
► There Are No Shortcuts in Talent ​
Development......................................................... 81
► If You’re Making Silly Mistakes Then You ​
Need More Practice..............................................84
► No Train, No Gain................................................85
► Why You Should Push Yourself..........................86
► Keep Your Foot On The Gas............................... 86
► You Are a Car........................................................ 87
► What to Do When You Hit a Ceiling................. 87
► Compound Hard Work and Luck.......................89
► Get Yourself In A Position Where You Can ​
Eat Risk.................................................................. 90
► Tie Your Comfort to Real, Tangible Value........91
► If You Can’t Find a Job That Really​
Excites You…......................................................... 92
► How to Allocate Your Bandwidth While ​
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Searching for Your Mission................................ 93

► Repetition Can Lead to Expertise, ​
Expertise Can Lead to Variety............................94
Chapter 6. The Team....................................97
► If You’re Asking Someone to Be Your ​
Mentor then You’re Doing it Wrong................. 97
► Put Pressure on Your Boss to Come Up ​
with More Work For You.................................... 99
► Get On the Right Team......................................100
► Competition as a Means of Collaboration......101
► Your Goal is NOT to Prove You're Smart, ​
it's to Make Problems Go Away....................... 103
► Make Your First Impression On a ​
Contribution, Not a Critique............................ 104
► Never Come Up Empty-Handed...................... 104
► You Need a Berserker At The Helm.................106
Chapter 7. The Mission............................. 107
► Selecting a Good Problem to Work On........... 107
► The “Progress Equals Pressure” Formula....... 111
► Love What You Do..............................................112
► Be a Builder, Not Just a Fighter........................113
► Build Where Building Creates More ​
Opportunities to Build.......................................113
Chapter 8. Motivation................................115

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► Disinterest is Often Just Overwhelm.............. 115

► Why Extrinsic Motivation Matters.................. 116
► How to Become a Super-Producer................... 117
► How The Highest Performers Sustain a ​
Massive Workload.............................................. 118
► Overcoming the Paradox of Serious​
Training............................................................... 119
► How Taxing Work Becomes Fun......................121
Chapter 9. Learning................................... 123
► The Greatest Educational Life Hack: ​
Learning Ahead of Time....................................123
► When Does the Learning Happen?..................128
► There is No Such Thing as Low-Effort ​
Learning...............................................................129
► The Greatest Breakthrough in the Science ​
of Learning Over the Last Century.................. 131
► “Following Along” Versus Learning................134
► The Vicious Cycle of Forgetting...................... 138
► Recall First, Reason Second.............................. 143
► The Vicious Cycle of Context Overload..........144
► Prereq Yo’ Self Before You Wreck Yo’ Self..... 145
► Filling In Your Foundations is the​
Difference Between Omitted Steps Being​
Minor Potholes vs Uncrossable Chasms.........146

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► Plan Your Broad-Strokes Journey ​

Top-Down, but Carry Out the Granular ​
Steps Bottom-Up................................................ 148
► The Efficient Learning Loop............................ 150
► Don't Bloat the Feedback Loop........................ 151
► Some Pitfalls to Watch Out For When ​
Learning From Projects.....................................152
► Review Should Feel Challenging...................... 153
► Learn Like You Lift............................................ 155
► Schooling Versus Talent Development........... 157
► Learning Doesn't Have to Be Synchronized ​
for Camaraderie to Occur..................................161
► A Sanity Check for Effective Study ​
Techniques...........................................................162
Chapter 10. Expertise................................ 163
► The Driving Force Behind Expertise is ​
Long-Term Memory........................................... 163
► Learning is Memory........................................... 165
► Learning is About Bridge-Building,​
Not Jumping........................................................ 167
► It’s All About Domain Knowledge................... 170
► Turn The Magical Into The Mechanical......... 172

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Preface

From summer 2024-25 I wrote numerous scattered

pieces on upskilling while answering questions and
engaging in general discussion about The Math
Academy Way. Eventually I found myself repeating
common themes, analogies, and punch-lines, and I
compiled them into this short book.

If you want to improve (or initiate) your upskilling

regimen, then this book would be a good place to start.
It's short, easy reading, addresses the big ideas, and
gets you in the right mindset. If you want a complete,
comprehensive, academic understanding of everything
down to the nuts and bolts, with hundreds of citations,
then I would highly recommend to go on and read The
Math Academy Way afterwards.

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Chapter 1. Consistency

► You’re Not Lazy, You Just Lack a Habit

If you’re struggling to stick with demanding forms of

practice, then temporarily forget about efficiency and
just build a habit with some less effective but more
enjoyable form of practice. Although the ultimate goal
is to train efficiently and get the largest possible
performance gain out of your limited training time,
that's going to feel taxing, and you might not want to
work that hard at first – not because you're inherently
lazy, but because you haven’t built a habit. You
eventually want to get to the point where performance
improvement is your primary focus and fun is a
second-order optimization, but it’s okay to optimize for
fun at the beginning to help you build a habit.

Consider strength training, for example. If you’re just

starting out, but you’re not looking forward to lifting
heavy-ass weights, then that’s okay! You don’t have to
lift them yet. Your #1 focus should be just getting your
ass into the gym and doing some kind of activity that

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loosely qualifies as exercise. After a week of, say,

shooting hoops, you might be motivated to try some
bodyweight exercises – and then the following week
maybe some light weightlifting, and maybe the week
after that you’ll be ready to challenge yourself by
putting some serious weight on the bar.

It’s the same way with anything else – for instance,

learning math. If you don’t feel motivated to solve a
high volume of problems that are challenging enough
to make you mentally sweat, that’s okay. You can start
off watching math edutainment videos and exploring
Wikipedia. The next week, maybe try to solve some
“math meme” problems each day (and look at the
comments to check if you got it right), and the
following week, maybe work out some easy arithmetic
or algebra problems each day (stuff that you still
remember fairly well but haven’t done in a while). By
that point you’ve gotten yourself into the metaphorical
weight room, doing some light lifting, and you’re ready
to put some serious weight on the bar. And that’s when
you start working through a structured curriculum that
engages you in taxing practice to pack the maximum
possible learning into your practice time.

Once you get to that point, you’ve built a habit, and you
need to do everything in your power to maintain it. If
you want to take a day off, just do a quick 10 minutes –
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something that feels negligible but keeps the habit

going. The habit is a psychological force field that
protects you from all sorts of negative feelings that try
to dissuade you from training.

In summary: You're not lazy, you just lack a habit. So

start simple, whatever gets the ball rolling. (But if you
know this and you’re still unwilling to build a habit…
then yeah, you’re lazy.)

► Don’t Have a Passion? Go Create One.

Be disciplined, set up a habit, compound compound

compound. Develop a relationship with it, put in extra
time when you’re bored, come to it when you need an
emotional outlet. Trust that it will grow on you and
seep into your identity as you spend a lot of time
practicing and developing serious expertise.

It’s just like developing a close human relationship.

You might not have a strong bond with the person
initially, but you get along “enough” at the beginning,
and over time you get to know each other so well, you
go through so much shit together, that you are
inseparable.

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And don't worry about the long-term too much. The

person who became your best friend, you probably
didn't know it the day you met them. You probably got
to know them better and better, week by week, month
by month, until at some point you realized you couldn't
imagine life without them. It's the same way with
creating a passion. If you keep on making short-term
progress then the long-term will sort itself out.

► Make the Habit Easily Repeatable

Don’t make it such a “big thing” that you do it one day

and dread doing it the next day. You know what
happens to people who start their New Year’s weight
loss resolution off with 3 hours at the gym every day?
They come for one day and then don’t come back! So
don’t do that. Instead, start out with a volume of work
that’s small enough that you don’t dread doing it again
the next day.

It doesn’t matter if the volume of daily work is too

small to achieve your long-term goals in the timeframe
you want. Eventually, as you build up a habit and your
mind and body adapt to whatever it is you’re doing, it
will feel easier to ramp up the volume of work until
you’re moving at a pace that puts you on track to
accomplish your long-term goals.
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So don’t worry about total volume of work at the

beginning. Just focus on consistency. As the habit sets
in and you adapt, you’ll find it easier to increase your
volume of work. And as the habit settles into your
identity, you’ll actually want to increase that volume of
work.

► The Hardest Part is Just Getting Started

Most skills can be trained. But serious training usually

isn’t pleasant, so most people don’t do it. That doesn't
mean there's little benefit to training them. It just
means lots of people aren't willing to put in the work
to capitalize on said benefit.

But the thing is, the hardest part is always just getting
started. If you suck at writing, then just sit down and
write for 15 minutes each day. It might be unpleasant
fishing for cohesive thoughts in your brain stew,
pulling them out, and translating them into text. But
that doesn’t mean it will always feel that way.

As you practice again and again, it will feel easier over

time. And as it feels easier you’ll free up more and
more mental bandwidth to notice areas for
improvement. And you’ll get better. Will you become a
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world-class writer? Who knows. Probably not. But will

you open up opportunities that were previously closed
to you? Probably.

And who's to say the training will actually be

unpleasant? When you're not looking forward to it, you
might think that negative feeling is going to intensify
during your (physical or intellectual) workout, but often
it just dissipates and you feel great 5 minutes in.
Procrastinating builds up the dread but just getting
started often makes it dissipate.

► If You Struggle to Train Consistently, Do ​

It Immediately After Waking Up

If you struggle to train consistently, then the #1 remedy

is to do it immediately after waking up. There are
several reasons why.

First, it shields you from those unexpected events that

demolish whatever schedule you had planned for the
day.​

Second, there's no time to even consider skipping the

training session. By the time you shake off the initial
grogginess and become fully conscious of what you're

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doing, you've already started training.​

Third, there's a clear habit trigger and reward: waking

up means it's time to train, and after you train you get
your shower, meal, whatever, and you get to feel good
about yourself all day. And if you skip the training,
then there's the punishment of feeling bad about
yourself all day. It's basically operant conditioning.

► Training Sessions Should be Short and ​

Frequent as Opposed to Long and Sparse

Suppose you’re budgeting 3 hours per week to train. It

would be better to train for 30 minutes six days per
week, as opposed to 90 minutes twice a week. There’s a
handful of reasons why.

First, you want to form a habit. The more consistently

you study math, the more it will become a habit that
you naturally do each day without thinking, just like
(hopefully!) taking a shower and brushing your teeth.

Second, you want to operate at peak productivity

during your session. During a short 30-minute session,
it’s easy to maintain a high level of focus and intensity
– whereas, during the second half of a long 90-minute

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session, fatigue will set in and make you significantly

less productive.

Third, you want to minimize the amount you forget

between sessions. When you have multi-day gaps
between sessions, you’ll have to spend more time
revisiting material you covered previously.‌(Just ask any
teacher how much their students forget over weekends,
and how much valuable class time they have to spend
on Monday re-teaching the things that they covered on
Thursday and Friday.)

However, there are also some caveats to consider.‌

Whenever you switch to a different cognitive activity, it

takes a few minutes for your brain to catch up and
enter a state of flow in the new context. Likewise,
whenever you switch to a new physical activity, it may
take a few minutes (or longer) to get set up. This is
called “context switching cost,” and if you make your
sessions too short (less than 20 minutes or so), then the
proportion of training time that is wasted on context
switching will outweigh the other benefits of daily
practice. Consequently, it’s best to spread out your
practice as much as possible subject to the constraint
that each session is sufficiently long for the
context-switching cost to be proportionally negligible.

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Additionally, if you have a hectic schedule and “six

days per week” in theory ends up being just “three days
per week” in practice, then you’ll obviously need longer
sessions just to achieve the same volume of practice.

Just think of it like max-intensity physical workouts.​

●​ 30 minutes six days per week? No problem, easy.‌​

●​ 45 minutes four days per week? 60 minutes three

times per week? Takes some discipline, but it’s
doable.​

●​ 90 minutes twice a week? It’ll feel like a grind with

slow progress, and you’ll constantly feel tempted to
skip workouts.

► A Little Extra Consistency​

⨉ A Little Extra Time​
= A Massive Increase in Volume & Progress

A little extra consistency and a little extra time per

training session can compound into a massive increase
in volume and progress.

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You know what the difference is between 20 minutes 3

days per week and 30 minutes 4 days per week?
Progressing twice as fast. That’s 60 versus 120 minutes
every week. Up that to 40 minutes 5 days per week and
you’re nearly doubling again at 200 minutes per week.

► Don’t Overreact to Bad Days

Even if you’re making the right decisions, you can still

have bad days. So it’s important to stay consistent and
not let a single bad outcome derail you.

Yes, that can be difficult psychologically. We tend to be

risk-averse and overreact to negative outcomes. But it
can help to zoom out and look at your progress on a
longer timescale.

At the same time, though, you can’t use that as an

excuse to avoid measuring progress and thinking
critically about it. Every time there’s a bad outcome,
you have to ask whether there’s anything you can learn
from it to carry into the future.

Sometimes there’s a flaw in reasoning. Other times

there’s a flaw in assumptions. Perhaps you didn’t have
all the key information to begin with and you should
have done better due diligence. Or perhaps some
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information revealed itself or changed after you made

the decision but you were too slow to react.

It’s not worth beating yourself up over mistakes, unless

they’re mistakes you’re repeating over again.
One-and-done mistakes won’t keep you from making
progress in the long-term, but repeated mistakes will.

► Aim for Virtuous Cycles

It’s a fact of life that things compound. You improve

one aspect of your life, it’s going to have carryover
effects, and that other aspect is going to have carryover
effects, and so on.

It’s important to take advantage of these feedback

loops and orient them in a positive direction. Because
if they’re not moving you in a positive direction, they’re
moving you in a negative direction. There is no stable
equilibrium.

You’re going to get pulled into self-perpetuating cycles

whether you like it or not. So it’s important to do all
you can to get yourself pulled into virtuous cycles, not
vicious cycles.

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► Protect The Habit

If I've learned anything about habit formation and

maintenance, it's that you've absolutely got to stay
consistent, even (and especially) during those times
when you need to dial back the total volume. Obviously
you'll move slower when you throttle the volume, but at
least you'll protect the habit. Yes, the wagon will be
moving slowly, but you'll still be solidly on it.

When someone gets derailed from their journey to get

better at writing, math, coding, an instrument, a sport,
or whatever it may be, that's the #1 reason why – at
some point they fell off the wagon entirely and never
managed to get back on. When the time comes to get
back into the swing of things, it's a lot easier to speed
up a slow wagon that you're on, than to get back on a
wagon that you've completely fallen off of. Once you've
got a good habit going, do everything you can to
protect it.

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Chapter 2. Skills

► The Importance of Hardcore Skills

Hardcore skills are the biggest bottleneck to improving

one’s life and society in general. It doesn’t matter
which of those things (yourself versus society in
general) you’re more focused on – hardcore skills are
always the answer.

So many people want to have high impact and improve

the world (and their own lives) in a big way. But desire
is not enough. You typically can’t do anything big
unless you have big skills. I say “typically” because
sure, some people get really lucky being born into the
right family in the right place at the right time and
enjoy an outsized impact despite not having built up
their skills as much – but even for those people, the
difference between a relatively large impact (relative to
other people) versus an absolutely large impact (“put a
dent in the universe”) still comes down to
skill-building.

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Hardcore skill development is also one of the greatest

social mobility hacks. Even if your family is not
well-connected, you can make up for it by developing
real skills. Sure, you have to develop more skills than
well-connected people to reach the same level of
opportunity, and you’re going to have less guidance
developing those skills and finding your way to the
arena – but once you’re in the arena, those extra skills
pay big dividends.

► The “Alien-Level Skills” Hack

Having strong technical chops can be a gigantic

power-up that sets you apart. You get to provide value
that nobody else can, and you get recognized for it.
That’s what happens when you equip yourself with
alien-level skills and solve problems for Earthlings.

But one of the things that keeps people from

capitalizing on this hack is they don’t invest in building
broad technical foundations. For instance, a common
argument against building broad mathematical
foundations is “why not just wait to learn math until
you have a job in a math-adjacent field, and then
backfill all the useful math as you encounter specific
problems on the job?”. On the surface, that might
sound like a way to reduce the amount of work that it
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takes to develop alien-level math skills that set you

apart and boost your career. However, in practice, this
“wait to backfill” approach greatly REDUCES your
chance of being able to capitalize on the alien-level
skills hack. Here’s why.

If you work in a math-adjacent field and don’t have

much math background, then:

1) You’ll underestimate how often mathy tasks come

up. Even when one does, without plenty of math
background, you probably won’t realize how mathy it
is.

2) Even if you do come across a task you know is mathy,

you likely won’t have enough math background to even
realize what mathy approach you need to take to
complete the task (i.e., what specific math do you have
to apply or spin up on).

3) Even if you do know what mathy approach you need

to take, the task might be handed off to someone else
who already has more math background (because it will
take them much less time to spin up and solve the
problem).

4) Even if there is nobody else to steal the task, if there

is time pressure, then you might not have any time to
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actually carry out that mathy approach. This can

happen in a couple different ways:

●​ Defaulting to cumbersome methods: "We don't have

time for you to spin up on math for an ideal solution, we
need to ship NOW. Just do the best you can in a week
using what you currently know, even if it's not great, and
we'll figure out a way to patch over whatever issues
come up afterwards, even if the patches are
complicated."​

●​ Passing up the problem: "This would have been a

great opportunity if we had someone who could solve
this problem reasonably quickly, but we can't spend tons
of time on it, so we're unfortunately just going to have to
pass it up and focus on things that are closer to what
we're able to do at the moment."

I’ll end with one caveat: depending on the field you’re

going into, you typically CAN do a reasonable amount
of scoping down. For instance, if you want to work on
ML/AI then you probably don’t need to learn Abstract
Algebra. But at the same time, there is still a mountain
of math you’d benefit from knowing. Many topics in
calculus, linear algebra, and probability & statistics
tend to come up.

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There’s a balance to be had; there is an appropriate

level of scoping. On one hand, you CAN skip out on
math that is largely irrelevant for your math-adjacent
field – BUT, whatever math tends to show up in your
field in general, if you don’t have broad knowledge of
it, you’re going to struggle to pull off the alien-level
skills hack. You CAN scope down and discard math
that doesn’t come up in your field, BUT if you want to
pull off the alien-level skills hack, you should NOT
scope down further and discard math that doesn’t seem
to appear in a specific problem.

► The Importance of Having Your ​

Prerequisites In Place

Having your prerequisites in place is the difference

between something seeming confusing and
inaccessible versus “wait… that’s all it is?”. It’s easy to
think you lack learning ability when really you just lack
prerequisite knowledge. Differences in learning ability
do exist, but they’re often conflated with presence or
absence of prerequisite knowledge. (Beware: it’s also
easy to think you’re wicked fast when really you’ve just
mastered more prerequisites than your peers.)

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More generally, the way to “unlock” things that feel

inaccessible to you is to shore up your prerequisite
abilities. This applies not just to learning tasks, but
also to opportunities. Everybody knows that luck is
where preparation meets opportunity, but fewer people
understand that if you don't have the prerequisite
abilities in place that prepare you to capitalize on an
opportunity, you probably won’t see it in the first place.
Imagine how many opportunities you’re blind to
because you don’t have the prerequisite knowledge to
even see them whiz by.

► Fortify Your F*cking Fundamentals

To have enough mental bandwidth to think deeply

about what's going on in any complex field, you need to
be very comfortable with the fundamentals. And that's
not going to happen if the fundamentals you need are
close to the edge of your ability. Sure, you can execute
at the edge of your ability… but not *comfortably*, and
that makes all the difference. Your high-level train of
thought is going to get continually derailed by the
low-level details you have to manage. You're going to
have a hard time seeing the forest for the trees.

To hammer in your fundamental skills to the point of

comfortable execution, it helps to not only get plenty of
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practice with those skills, but also layer plenty of more

advanced skills on top.

For instance, consider figure skating. Yes, figure

skaters get really good at skating in part because they
skate a lot, but it's not just that. It's also that they
continually layer more advanced jumps and spins.
Skating around the rink will get you to a decent level of
comfort in your basic skating skills, but being able to
land jumps and spins will force a whole new level of
robustness and fault-tolerance in those underlying
skills. It's like those robot testing demonstrations
where all the engineers stand in a circle shoving the
robot around. It's not enough to just test that the robot
can follow a predetermined path. You gotta bang it
around a bit to make sure it's resilient.

It all comes down to forcing structural integrity of

underlying skills. When you build advanced features on
top of a system, they sometimes fail in ways that reveal
previously-unknown foundational weaknesses in the
underlying structure. This forces you to fortify the
underlying structure so that the system can
accommodate new elements without compromising its
integrity. And when you fortify the system to execute
advanced tasks successfully, it becomes capable of
executing simpler tasks *comfortably*. What's more,
fortifying the underlying structure often requires
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improving its organization and elegance, which, in the

context of knowledge, is what produces deep
understanding and insight.

► Your Missing Foundations Will Wait ​

For You

If you think you don't need to climb a skill tree and

master your prerequisites, then don't. Just go ahead
and do <insert hard thing here>. That's what you claim
you're able to do, so do it.

Or try and fail enough times to gain some humility.

Your missing foundations don't care. They'll wait for
you patiently until you're ready to acknowledge them.

► Actively Doing is the Key to Alpha

Actively doing (as opposed to passively consuming) is

not just the key to effective learning. It’s also the key to
alpha, i.e., developing an edge.

Lots of people consume. Fewer people actively do.

Even fewer people attempt challenging things. And
even fewer people than that build up the foundational

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skills needed to succeed in doing those challenging

things.

And what’s more: alpha compounds. When you succeed

in doing a hard thing, the learning and resources you
acquire position you to succeed in doing even harder
things and acquiring even more alpha. In other words,
your edge gets sharper – not duller – with use.

► Everything Matters

Hard and soft skills, big-picture and detail-oriented

thinking, technical and creative ability... they're ALL
extremely valuable. We all have strengths and
weaknesses, but the best results come from being solid
in every single one of these categories and world-class
where we naturally excel.

Lean into your strengths AND shore up your

weaknesses. You are maximizing a product, not a sum.
Everything matters. Running your gifts and talents to
the max means you have to also play defense against
weaknesses that would otherwise try to interfere. The
running back has to run but the blockers also have to
block.

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► You Want Exciting Opportunities?​

Learn Math and Coding

Learning advanced math/coding opens career doors

you don't even know exist. Sometimes even doors that
the whole world isn't aware of yet.

Everyone knows that the future is here, it's just not

very evenly distributed. You know who it's
concentrated on? The people who are insanely skilled.

Likewise, everyone knows that the easiest way to

become insanely skilled is to skill-stack. You know
what skills pair really well with each other and
basically everything else? Math and coding.

If you've got serious math chops, coding chops, and

deep domain expertise in another discipline, you're
compounding 3 orders of magnitude. Be
one-in-a-hundred on each and now you're one in a
million. Be one-in-a-thousand in each and now you're
one in a billion.

I don't think I've ever run into someone with serious

math/coding chops and deep domain expertise, who
wasn't working on something really exciting.

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You take some area of interest, you go down the rabbit

hole that's been dug by previous explorers, you run up
against the rocky technical problems that prevented
further digging, you smash those rocks to bits with
your math/coding jackhammer, and you just keep going
and smashing the crap out of any more problems that
dare get in your way. What could possibly be more
exciting than that?

Finally, keep in mind that in order to get yourself into

the situation above, you have to actually be skilled. You
can't just "appreciate" or "talk a good game" about
math/coding.

When you run up against a rocky technical problem,

nobody cares how amused you are by the rock, and
nobody cares how hype you get telling the rock how
you plan to destroy it. The only thing that matters is
that you can wield your math/coding tools masterfully
enough to destroy the rocky technical problem.

Basically, you need to develop as strong a command

over math/coding as a musician's command over their
instrument, or a gymnast's command over their body.
And that takes a massive amount of consistent practice
over a long period of time. Which is hard, which is why
most people don't do it, which is why you get such an
outsized competitive advantage if you do.
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TLDR: Pursue a domain you love, but simultaneously

get so insanely technically skilled at math/coding that
you can apply it to your domain of interest in an
innovative way. Deep domain expertise plus alien-level
technical skills equals lots of interesting/rewarding
work to do.

► If You're Not Both Technical and a ​

Domain Expert, Then You're Underpowered

If you're a domain expert but you can't build stuff

yourself, then you're severely underpowered. If you're
technical but you rely on someone else for domain
expertise, then you're also severely underpowered.

If you're one of those people and you found your

complement in someone else, then that’s great, but
you're still somewhat underpowered. Yes, you can get
things done together, but the cycles of communication
and coordination will still turn much slower and cut
much shallower than if they were happening entirely
within your own brain.

It's best to be a technical domain expert and work with

other technical domain experts when possible.

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► Domain Expertise, Math, Coding, ​

Communication

Domain expertise to identify an important problem and

envision a solution, math/coding to build it, and
communication to deliver it.

Without domain expertise you'll choose an

unimportant or intractable problem or your solution
won't really solve the problem (because you don't really
understand the problem).

Without math/coding you'll be limited to whatever

someone or something else (with comparatively little
domain expertise) can build for you. You'll be limited
and you'll lack any sort of technical edge against
copycat competitors.

Without communication skills your solution won't be

understood and adopted. You'll mistake this lack of
traction for lack of merit when it's really just a failure
to articulate value.

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► What Math To Learn for Skill Stacking

What math should you learn if you want to get the

most ROI out of “skill stacking” it, pairing it with
another applied domain you’re interested in? Where’s
the line between it being a true power-up vs a
fascinating distraction?

In my experience, most of the value comes from the

following:

1) Being rock-solid on the applied math that shows up

all the time across all fields of engineering: linear
algebra, calculus-based probability & statistics,
algorithms, etc.​

2) Having broad knowledge of advanced approaches to

mathematical modeling: differential equations,
machine learning, etc. This includes not just
conceptual understanding but also procedural fluency
with foundational techniques.​

3) Knowing the basics of proofs. It’s less about knowing

particular theorems and more about being able to
follow lengthy logical manipulations and carry them
out yourself in general. (However, the way you build up
your general skills here is by practicing on particular

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instances – there’s no escaping the particulars.)​

4) Going deep into mathematical modeling supporting

the particular domain(s) you're interested in. Here, it’s
not just about learning and developing modeling
techniques, but also building domain expertise. Your
models will only be as good as their data, and most
data isn’t available in machine-readable or even
human-readable formats – it’s siloed in the heads of
domain experts who have extracted a massive amount
of learning from a massive amount of hands-on
experience.

► Failure Modes in People Who Develop ​

Math Skills but Don’t Capitalize On Them ​
via Coding

I know some people who were skilled in math but

never really capitalized on it. Two trends I noticed: 1)
they typically were not very skilled at coding, and 2)
they also lacked discipline to work on things that had
to be done even if they weren't inherently intellectually
enjoyable.

The first trend is sometimes surprising to people: how

can someone be good at math but not coding? Doesn’t

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being good at math naturally transfer over to coding?

There’s definitely a positive correlation, but the
correlation is nowhere near as high as you might
expect.

Here are 4 failure modes that I’ve seen frequently in

people who are skilled at math but failed to capitalize
on it in the form of coding.

1) Difficulty grappling with complexity when it grows so big

that you can’t fit everything in your head. Not organizing
and naming things well, not understanding or
maintaining scope, letting responsibilities bleed too
much across scope.

2) Lack of understanding or willingness to accept practical

constraints of the problem and incorporate them into the
solution. It’s good to think about the Platonic ideal but
you can’t let that become a constraint in the sense of
the great becoming the enemy of the good.

3) Getting distracted by low-ROI features/details. In math

there’s typically a really clean line between details that
are absolutely critical vs completely irrelevant. But in
reality there’s more of a spectrum, lots of things matter
at least a little bit but you have to have a good sense of
what things matter a lot and how costly their
implementation will be relative to the impact. Like,
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what are the things that have a 100x or 1000x impact

and ROI relative to other things.

4) Being unwilling to do “tedious” work. This plays into

item #3 because in order to get that good sense of what
really matters, you have to get your arms around the
problem, which typically requires getting your hands
dirty and doing enough manual grunt work to develop
intuitions and strong gut feelings. Mathy people
sometimes justify avoiding the grunt work because it’s
tedious and they already have it all figured out in their
head… but the issue is that the contour of the problem
space in their head doesn’t match up with reality. Their
reasoning tends to be sound, but it’s the assumptions
that get them. There’s some parts of the real-life
problem that they haven’t loaded up in their head.
Sometimes there are important things they think are
negligible, sometimes negligible things they think are
important.

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Chapter 3. Discipline

► The Magic You’re Looking For is in the ​

Full-Assed Effort You’re Avoiding

30 minutes of fully focused deliberate practice 4 days

per week can have you making serious progress
towards most learning or fitness goals. But it has to be
fully focused – a “full-assed” effort – and you have to be
continually upping the level of challenge as your
capabilities increase. You have to work intensely
enough that you come out of each session seriously
winded. Meaning that either your brain feels like mush
or your body feels like jell-o.

When someone fails to make decent progress towards

their learning or fitness goals and cites lack of time as
the issue, they’re often wrong. It’s often not lack of
time but rather lack of willingness to put forth a
full-assed effort under a continually increasing level of
challenge.

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If you put in a half-assed effort then you get a quarter

of the results at most. That’s what causes the purported
lack of time. To get the equivalent of 30 min full-assed,
you have to put in at least 2h half-assed, which you
quite reasonably might not have time for. Or you put in
30 min half-assed and get the equivalent of 7.5 min
full-assed, which doesn’t move the needle fast enough
on your progress for you to reach your goal in a
reasonable timeframe. The magic you’re looking for is
in the full-assed effort you’re avoiding.

► At Some Point Doing the Hard Thing ​

Becomes Easier Than Making the Hard ​
Thing Easier

The condition for getting yourself to do something is

simple: it’s just internal willpower ≥ external friction. If
that condition is false then the way you make it true is
by decreasing friction and/or increasing willpower.

It’s helpful to think of this like balancing a budget:

willpower is like your income and friction is like your
spending. If your budget isn’t balancing then the first
thing to do is cut out any dumb costs. Is there anything
dumb about your environment that’s causing needless
friction? Cut it out. Your life is like a big codebase – if

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you’re struggling to implement a new behavior in some

area, then refactor that area to make it easier to build
on.

But at the same time, you can only take cost-cutting so

far. There are always going to be some basic expenses
you have to cover. And there’s a limit to how easy you
can make it to add a new feature to the codebase. You
can refactor all you want but there’s always going to be
some amount of complexity inherent to the new
feature.

The trick is to be honest with yourself about when you

start asymptoting off in your attempts to reduce
environmental friction. At some point doing the hard
thing becomes easier than making the hard thing
easier. And that’s when you have to muster up the
willpower to overcome whatever friction is left over.
That’s when you have to say “enough refactoring, time
to lock in and implement this sucker.” That’s when you
have to change your focus from cost-cutting to
producing extra income.

In any journey, you can chart an easier, more efficient

course, but there’s always going to be some serious
trekking involved.

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► How to Cultivate Discipline

When there’s something that you know you should do,

but you can’t get yourself to do, it means some habit is
pulling you away from doing it. So what you need to do
is tear down the unproductive habit and build up a
counter-habit whose gravity eventually becomes strong
enough to completely overtake the original habit. You
try to disrupt your momentum on your negative habit
and create momentum towards a positive habit. And
while you might not be able to do this all in one fell
swoop, what you can do is iterate on it and gradually
ease into a transition one little step at a time.

Here’s a concrete example which may or may not apply

to you but hopefully it will illustrate the main idea.
Let’s say you’re having trouble cultivating discipline
with exercising every day. The first question is: what’s
keeping you from exercising? Maybe you plan to
exercise after work but then things come up and you
always find an excuse. Okay, so do it first thing in the
morning. Why aren’t you already doing it first thing in
the morning? Let’s say it’s because you have a habit of
waking up 15 minutes before you have to leave for work
and there’s not enough time for exercise.

That habit is pulling you away from your goal of daily

exercise. So you need to gradually replace it with a
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more productive habit. Maybe instead of waking up 15

minutes before work, you wake up 20 minutes before
and spend 5 minutes doing jumping jacks as soon as
you get out of bed. (Or if 5 minutes is too daunting then
maybe you start with just 1 or 2 minutes and gradually
build up to 5 minutes.) After enough days of waking up
5 minutes earlier for 5 minutes of jumping jacks, you’ll
have created a “new normal” morning routine, and
you’ll find it within yourself to wake up another 5
minutes earlier and replace your 5 minutes of jumping
jacks with a 10-minute run.

You keep going this direction, gradually tearing down

your habit of waking up just before you have to leave,
and building up a habit of waking up earlier and earlier
and doing more and more exercise with that extra time.
Eventually you reach your desired fitness routine goal
and then you just maintain that habit into the future.

► Keep Your Hands On The Boulder

People will do unbelievable mental gymnastics to

convince themselves that doing an easy, enjoyable
thing that is unrelated to their supposed goal somehow
moves the needle more than doing a hard, unpleasant
thing that is directly related to said goal.

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If you want to move the needle on a goal, you have to

concentrate your efforts directly on that goal. You can
exhaust yourself doing other things, fulfilling other
responsibilities and/or moving the needle on other
goals – but at the end of the day, each goal has its own
needle, and the general feeling of exhaustion doesn't
imply you've successfully moved any needle in
particular.

This can be a hard truth, especially for people who

have taxing responsibilities that are separate from their
aspirational goals. But the only way to achieve those
aspirational goals is to somehow find it in oneself to
directly move the needle on them. There is no other
way.

(When you're pushing the boulder, remember that the

boulder is actually a gigantic reaction ball that's
bouncing around everywhere trying to evade you, and
you just have to keep at it and not give up no matter
how many times it bounces sideways or even
backwards. It will never move in exactly the direction
you're trying to push it, but if you just keep pushing
then you WILL gradually wrestle it over to where it
needs to go.)

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► Just Do The F*cking Work

If you want to develop serious skills, you have to

engage in intense, taxing workouts. Amateurs
sometimes make up all sorts of excuses for why this
rule doesn't apply to them, but real pros don’t try to
weasel their way out of the hard work.

You think you’re too good for the grunt work? Too
smart to listen to your coach’s feedback? Then what are
you waiting for – go on, succeed all by yourself in your
current state. Either prove your inherent greatness, or
fail and get your ass handed to you enough times to
knock some humility into your head.

At the end of the day you can either waste time

debating your coach on the training regimen, or you
can use that time to just put your head down and do
some f*cking work. One of those actions will turn you
into a pro; the other will keep you tethered to amateur
level for the rest of your life. It’s your choice.

You want outsized results? Then you’re going to have

to put in an outsized amount of work. Achievement,
expertise, greatness, whatever the hell you want to call
it – it doesn’t happen naturally. It’s about transforming
yourself from normal to abnormal in ways that confer a

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competitive advantage. There’s nothing natural about

it.

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Chapter 4. The Grind

► Upskilling is Hard and That’s a​

Good Thing

Upskilling takes work. That's a feature, not a bug.

Upskilling increases agency and outsized agency is
best held in the hands of people who know what it
means to put in outsized work. We all know what
happens when lazy people have power. The fact that
upskilling takes work is a force against that.

► The Most Superior Form of Training

In the field of talent development, there is absolutely

no debate about the most superior form of training. It’s
“deliberate practice”: mindful repetition on
performance tasks just beyond the edge of one’s
capabilities. Deliberate practice is about making
performance-improving adjustments on every single
repetition. Any individual adjustment is small and
yields a small improvement in performance – but when

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you compound these small changes over a massive

number of action-feedback-adjustment cycles, you end
up with massive changes and massive gains in
performance.

Deliberate practice is superior to all other forms of

training. That is a “solved problem” in the academic
field of talent development. It might as well be a law of
physics. There is a mountain of research supporting
the conclusion that the volume of accumulated
deliberate practice is the single biggest factor
responsible for individual differences in performance
among elite performers across a wide variety of talent
domains. (The next biggest factor is genetics, and the
relative contributions of deliberate practice versus
genetics can vary significantly across talent domains.)

Why, then, does anyone seeking to attain a high level of

skill engage in forms of practice other than deliberate
practice? The answer might be the most hard-hitting 2
sentences in all of talent development research:
"...[D]eliberate practice requires effort and is not inherently
enjoyable. Individuals are motivated to practice because
practice improves performance" (from Ericsson, Krampe,
& Tesch-Romer, 1993, in The Role of Deliberate Practice
in the Acquisition of Expert Performance). In other words,
maximal performance does not happen naturally as a
result of maximizing other things like enjoyment,
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comfort, convenience, and ease of practice. In fact,

maximal performance is at odds with some of these
things. Sacrifices must be made.

Lots of people are unwilling to make sacrifices to

engage in deliberate practice – and that’s fine. That’s a
personal value judgment. But the problem is that many
of these people still claim that they are doing their best
to develop their talent. Typically, they will cut corners
on one of the two requirements of deliberate practice –
“mindful” and “repetition” – and then resist any form
of objective, quantifiable measurement of their
performance that would expose the ineffectiveness of
their practice.

Deliberate practice is not mindless repetition. If you’re

doing the same thing over and over again, then you’re
doing deliberate practice wrong. Deliberate practice is
about making performance-improving adjustments on
every single repetition. Any individual adjustment is
small and yields a small improvement in performance,
but when you compound these small changes over a
massive number of cycles, you end up with massive
changes and massive gains in performance. None of
this happens if you’re mindlessly doing the same thing
over and over again without making adjustments.

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Likewise, even if you’re mindful during practice, you

can’t skimp on repetition and still call it “deliberate
practice.” Deliberate practice necessitates a high
volume of action-feedback-adjustment cycles in every
single training session. Otherwise, the compounding
doesn’t happen. Any activity that throttles the number
of these cycles cannot be described as deliberate
practice.

Many heated debates in education stem from these

misinterpretations of deliberate practice. Mindless
repetition, doing the same thing over and over again
without making performance-improving adjustments,
is not deliberate practice. Likewise, any activity that
throttles the volume of action-feedback-adjustment
cycles (e.g., excessively challenging problems, or
think-pair-share type of stuff) is not deliberate
practice.

► Outsized Success Requires Outsized Work

You want to do something that sets you apart? You’re

going to have to work harder than most. There is no
way around it. If you think you can achieve outsized
success without putting in an outsized amount of work,
then you will never achieve your goals because you will

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never transform yourself into a person who is capable

of achieving them.

And guess what? It’s not enough to simply work hard.

To achieve outsized success, it’s critical to not only put
in enough time and effort, but also to work
productively. You have to work hard AND work smart.
And furthermore, work in a direction where you have
some competitive advantage (or, at least, you’re not at a
disadvantage). Part of this work involves engaging in
activities that maximize the likelihood of you getting
some lucky breaks. You have to work to maximize your
luck surface area.

► Transformation Is Discomforting

If you don’t push yourself to perform beyond your level

of comfort, you don’t improve your performance.
Simple as that. Why? Because performance
improvements come from your body adapting to
additional strain. No strain, no gain.

Strain can be unpleasant. It’s taxing and it leaves you

fatigued. You may feel weak, untalented, even dumb if
you’re training an intellectual skill such as math. But
it’s completely necessary. To avoid the feeling of strain

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is to avoid the process of adaptation, and thus, to avoid

performance improvement.

What you want is a continual cycle of strain and

adaptation. That’s true in athletics, and it’s just as true
outside of athletics. You feel weak while exercising but
you come back stronger. You feel dumb while studying
but you come back smarter. The thing to remember
when studying is that you are physically changing your
brain to execute more complicated cognitive tasks. At a
fundamental level it is just like lifting weights or
practicing gymnastics. The keys to effective training
are the same, and so is the feeling of effective training.

Transformation is discomforting. But keep in mind

that while discomfort is necessary for performance
improvement, discomfort alone does not always
indicate that you’re engaging in
performance-improving activities. You also need to be
able to overcome the challenge that’s inducing the
discomfort. Think of it this way: dropping a
500lb-loaded barbell onto the shoulders of a novice
lifter would be neither comforting nor productive.
They’d get crushed, develop no strength, and the only
thing they’d learn from the experience is that they hate
strength training. The same is true for too-difficult
math problems, too-difficult pieces of music… you get
the idea.
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► Enjoyment is a Second-Order​
Optimization

If you are seeking to maximize your “bang for buck” in

terms of learning per unit practice time, then
enjoyment is a second-order optimization that is often
at odds with the first-order optimization, namely,
deliberate practice. A key feature of deliberate practice
is that it requires continually practicing beyond one's
area of comfort, and this tends to be more effortful and
less enjoyable (as one would expect of something that
is by definition uncomfortable).

If you want to maximize your learning efficiency: 1)

engage in deliberate practice, and 2) make the
deliberate practice as enjoyable as possible (or,
equivalently, as least unpleasant as possible). Ranked
by efficiency, here’s the whole spectrum: enjoyable
deliberate practice > unpleasant deliberate practice ⋙
other enjoyable forms of training > other unpleasant
forms of training.

Now, this is not to say that enjoyment is unimportant.

If deliberate practice is not enjoyable for someone,
then other enjoyable activities can sometimes be useful

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for increasing motivation and softening the discomfort

associated with deliberate practice. But it’s important
to realize that fun is a supplement, not a substitute, for
deliberate practice.

Additionally, while deliberate practice is inherently

uncomfortable, you can normalize yourself to it via
repeated exposure – and once you begin to see your
tiny improvements compounding into massive
long-term gains, it can feel satisfying. As the saying
goes, “nothing succeeds like success.”

► Ability is Built, Not Unlocked

One of the most harmful myths in education is that

ability is something to be “unlocked” by curiosity and
interest (which seems easy), not something “built” by
deliberate practice (which seems hard). It’s so funny
when you imagine what this would sound like coming
from an athletic trainer: “You want to get really good at
basketball? Forget about practice drills – you were
born to ball; all you need to do to unlock your inner
baller is come in with the right attitude and play some
pick-up ball at the park.”

This is not to say that curiosity and interest don't

matter. Just that these things do not themself build
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ability. They don't move the needle directly. They

motivate people to engage in deliberate practice, which
is what directly builds ability. Curiosity and interest
“grease the wheels,” so to speak, but they don't actually
move the wheels.

► What Max-Efficiency Training Feels Like

There is sometimes a disconnect between what people

think max-efficiency training should feel like, and what
it actually feels like. It’s common to think that
max-efficiency learning should feel maximally
scaffolded, perfectly smooth and easy the whole way
through.

While this is more true than not, it misses an

important nuance: max-efficiency training should feel
just-enough scaffolded that the learning tasks are
challenging yet still achievable in a reasonably quick
timeframe. When you’re developing skills at peak
efficiency, you are maximizing the difficulty of your
training tasks subject to the constraint that you end up
successfully overcoming those difficulties in a timely
manner.

A noteworthy corollary is that you are also minimizing

your confidence in your ability to complete the training
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tasks (again subject to the constraint that you end up

successfully completing them in a timely manner). In
this way, confidence becomes more of a “hindsight”
thing than an “in-the-moment” thing. If you feel
confident while engaging in max-efficiency training,
it’s not because the task in front of you seems easy
relative to your abilities, but because you’ve been in
situations before where tasks felt challenging relative
to your abilities but you’ve always managed to come
out successful.

► The Necessity of Grinding Through​

Concrete Examples Before Jumping Up a​
Level of Abstraction

Many learners fail to understand that grinding through

concrete examples imbues you with intuition that you
will not get if you jump directly to studying the most
abstract ideas.

If you go directly to the most abstract ideas then you’re

basically like a kid who reads a book of famous quotes
about life and thinks they understand everything about
life by way of those quotes. The way you come to
understand life is not by just reading quotes. You have
to actually accumulate lots of life experiences. And you

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might think you understand the quotes when you’re

young, but after you accumulate more life experience,
you realize that you really had only the most naive,
surface-level understanding of the quotes back then,
and you really had no idea what the hell you were
talking about.

It’s the same way in any subject – even math, where

information can be packaged into clean theorems that
are provably correct. In general, the purpose and power
of an abstract idea is that it compresses a zoo of
concrete examples. But if you haven’t built up that zoo
of concrete examples then you miss out on that power.
If you study the theorems but shy away from grinding
messy concrete problems, then you will never truly
gain the deep intuition to know what the hell you’re
talking about.

Skipping the concrete examples is a one-way ticket to

existential crisis. If you've lived and breathed concrete
examples, they'll get compressed into tangible,
meaningful abstractions that inject you with a dose of
vitality every time you work with them – but if you
haven't, then the abstractions will feel dull and lifeless,
and you'll constantly wonder what's the point of
pushing meaningless abstractions around in arbitrary
patterns of allowed manipulations. For instance, a
company's balance sheet can tell an incredibly
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interesting story if you have visceral experience with

success and failure in business – but if you don't, then
analyzing financials will make you feel like a robot
checking whether numbers match semi-arbitrary
conditions for being "good" or "bad".

Grinding the concrete examples is NOT about turning

yourself into a robot and shielding you from
intellectual awakening. It's the opposite. It's about
equipping you with invigorating experiences that can
live on through the abstractions, empowering you to
actually know what the hell you're talking about.

► Be Willing to Do Tedious Work

In order to get a good sense of what really matters, you

have to get your arms around the problem, which
typically requires getting your hands dirty and doing
enough manual grunt work to develop intuitions and
strong gut feelings.

Many people justify avoiding the grunt work on the

grounds that it’s tedious and they already have it all
figured out in their head, not realizing that the contour
of the problem space in their head doesn’t match up
with reality.

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Their reasoning tends to be sound, but it’s the

assumptions that get them. There’s some parts of the
real-life problem that they haven’t loaded up in their
head. Sometimes there are important things they think
are negligible, sometimes negligible things they think
are important.

► Don’t Undervalue Turning Up the Dial on ​

Your Grind, but Don’t Overvalue the​
Last Turn

Regret minimization is often used to justify leaving a

comfortable situation to grind towards an
life-changing transition is uncertain and difficult in
the short term. This might seem like flipping a switch
towards 100% grind, constantly pushing the boulder,
but it’s important to keep in mind that regret
minimization cuts both ways. Yes, grind grind grind,
but also don’t forget to take breaks to spend time with
people you care about, especially around big events or
when you’re not going to see them again for a while.

If you’re anything like me and have a nagging feeling

that you should be making progress on “the thing”
100% of the time, what might help justify taking breaks
is to think about relative speed increases: if you’re

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pushing on the needle X% of the time, what kind of

speed multiplier are you leaving on the table?

●​ If you’re pushing 25% of the time, then there would

be a 4x multiplier by pushing 100% of the time. 4x
speedup is the difference between a decade of work
vs a couple years.​

●​ If you’re pushing 50% of the time, then the

multiplier drops to 2x. For me, at least, that’s still
leaving a lot on the table.​

●​ If you’re pushing 80% of the time, then the

multiplier drops to 1.25x. You’re getting fairly close
to max capitalization.​

●​ If you’re pushing 90% of the time, then the

multiplier is down to 1.1x. It’s basically max
capitalization with a slight rounding error.

Sure, if there is a make-or-break moment in your grind,

then it might be worth temporarily turning the dial up
to 100% to try to capitalize on it. But in the long run,
outside of those situations, that last turn of the dial
from 90% to 100% is not going to change the overall
outcome – all it will do is create regret in other areas of
your life. And that regret does not stay external. Even if
you try to compartmentalize it, it will find a way to
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seep into your whole, detracting from your motivation

& productivity, eventually conspiring to derail you
early.

► When More Volume Equals More Progress

More volume equals more progress provided that

you're working productively and not burning yourself
out.

●​ If you're tired and your head is spinning and you're

making tons of silly mistakes, then it's time to stop.​

●​ If you're so fatigued that you can't help but zone

out (or get distracted scrolling through memes)
between questions, then it's time to stop.​

●​ If you skip the next couple days because you're so

blown out from the previous study session, then it's
time to reduce the single-session duration and
increase the consistency.

But until you hit those issues, doing more will have you
truly learning more and making faster progress
towards your long-term goals.

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Basically, challenge yourself to put up some serious

volume, but also be honest with yourself about whether
you are working productively and showing up
consistently, and don't lose the long game trying to win
the short game.

► Failure Is NOT the Key to Success

Failure gets over-emphasized as being the key to

success. LEARNING is the key to success. Failure only
moves you towards success to the extent that you learn
from it.

You should never fail twice for the same reason.

Correcting a mistake will move you closer to success,
but making the same mistake over and over again will
lock you into losing.

Always analyze your mistakes. Whenever something

doesn't go your way, deeply analyze the circumstances
to identify what you should have done differently, or,
even if you acted appropriately based on all the
information available, how you could have gotten more
information or taken intermediate actions to extract
more signal to inform later bigger actions.

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Maintain a gigantic locus of control and bias towards

internalizing blame. Don't dwell or make excuses. Just
learn and apply that learning to the future so you don't
make the same mistake twice.

► Don’t Drown Yourself in the Deep End

One of the most common – yet also most preventable –

traps that people fall into, that leads them to give up on
their aspirations, is that they go for the most advanced
challenges and refuse to step back to a better calibrated
level when they struggle. They keep attempting and
failing the most advanced challenge with hopes that
their practice will naturally fill in the swath of missing
foundational skills that are preventing them from
completing the advanced maneuver.

There are some people who can pull that off in some
settings, but if you don’t already have solid evidence
indicating that you’re one of them (or you don’t know
what I mean by that), then you’re almost certainly not
one of them.

For the vast, vast majority of people, jumping in

headfirst without a baseline level of foundational
ability is not a viable approach. It can be exciting at
first, until you come to the realization that you’re
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spending all your time flailing around and being

confused. It’s like going to the gym, getting super
hyped up to lift the heaviest weight, and repeatedly
failing to lift it. Not only are you not getting any
stronger, but you’re also wasting valuable time that you
could be using to successfully develop your strength.

Now, I want to be clear: I’m not saying that you should

avoid trying to jump into things that interest you.
You’ve gotten really excited about something and you
want to see how far you can pursue your interest
jumping in headfirst? Go for it! All I’m saying is that
you need to be honest with yourself about whether
you’re making progress – and if you’re starting to flail
(or, more subtly, doubt yourself and lose interest), then
you need to put your ego aside and re-allocate your
time into shoring up your foundations.

► Focus Less on Feelings and More on ​

Measurable Progress

Anyone who knows about deliberate practice knows

how important it is to spend your time practicing at
the edge of your abilities.

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But how do you really know when you’re at the edge?

Most people can tell when their practice is too easy –
you’re able to complete tasks effortlessly while
thinking about other things. But what about when your
tasks are too hard? That’s often less obvious. Practice is
supposed to challenge you, but how hard is too hard?

Here’s my rule of thumb: Focus less on feelings, and

more on measurable progress. When your practice is
too difficult, you’re going to be running in place and
not making much measurable progress.

Think about what happens if you try to work out with a

weight that’s too heavy for you to lift. Yes, you might
be able to tell that it feels excessively strenuous, but
what really gives it away is that despite trying your
hardest, you’re not able to lift the weight. And not only
are you unable to lift the weight, but you’re not getting
any closer to doing so.

The same thing happens if you work on a math

problem or coding project that’s too hard. Your brain
goes into overdrive, and you work on it for a long time,
but you just don’t really get anywhere with it. You don’t
solve the problem, you can’t point to any concrete skills
you acquired during the process.

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So, if you want to practice effectively, here are some

things you absolutely must do: 1) have some concrete
way of measuring your progress, 2) make sure that
whatever you’re doing is actually increasing that
progress, and 3) make sure that the progress is
increasing fast enough that you’ll reach your goal in a
reasonable (but realistic) amount of time.

By the way, if your goal is really lofty, then a reasonable

amount of time might still be a long time – so long that
it’s hard to tell whether you’re progressing fast enough.
So if you have a lofty long-term goal, I would also
recommend to decompose it into a series of
shorter-term goals where it’s totally obvious whether
you’re making fast enough progress to reach the next
short-term goal in a timely manner.

► The Problem with Overly Difficult ​

Problems

It’s tempting to think that to train up your skills, you

should be focusing on the hardest training problems.
But here’s the thing about “think really hard, struggle
for a long time, solve it once in a while but usually look
up the solution” problems: they can be fun (for a

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certain type of person), but they’re not an efficient way

to learn.

Approaching challenging problems without having the

subskills down pat is like jumping into a game of
basketball without having developed dribbling and
shooting skills. It might feel fun but you’re just going
to be whiffing every shot and getting the ball stolen
from you. You might make one layup the entire game
and feel good about it, but that’s barely any training
volume.

It’s like going to the gym to lift weights but only eeking
out a single rep over the entire course of your workout.
You need to be banging out more reps if you want to
get stronger, and the only way you can bang out those
reps is by working with a level of weight that’s
appropriate for you.

► It’s Not Just About Attempting Hard ​

Things, It’s Also About Successfully ​
Achieving Them

“Hard” or “easy” is conditional on your skill level and

most skills can be improved through training. When
you do hard things, those hard things become easier.

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But it’s not just about attempting hard things. It’s also
about actually doing them successfully.

●​ You can go to the gym, load 500lbs onto a barbell,

try and fail to pick it up, and not gain any strength.​

●​ You can open a quantum mechanics textbook, fail

to understand any of the math that’s going on,
faceplant on a practice problem, and not gain any
learning.

The trick is to do things that are challenging but that

you can achieve given your current skill level.

► It Always Becomes a Battle of Willpower ​

By the End

If you want to upskill to an exceptionally high level,

enough to build a career around it and achieve a high
level of success in your field, then you're going to have
to compete against people who are more advantaged
than you.

There are many different types of upskilling

advantages. Starting at an earlier age is an advantage,

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so is having access to superior training resources, so is

having transferable skills from other skill trees that
you've climbed. Biological factors (cognitive, physical,
dispositional, etc.) often come into play, and some of
these factors cannot be changed through extra training,
or have soft limits to the range of improvement that
can be expected.

Exceptionally advantaged upskillers tend to have some

combination of all of these advantages. They are rare
enough that you may not encounter them initially, but
the higher you climb up the skill tree, the more
frequently you'll run into them -- and even if you
manage to climb high enough that you're no longer in
direct competition with other people, then it means
you're in direct competition with an even more
challenging opponent, the universe itself.

So, while it's a good idea to upskill in directions where

you have advantages, it's important to accept that you
will eventually climb high enough that those
advantages become table stakes. Lean into your relative
advantages, but don't center your identity on them,
because no matter how big of a leg up you have at the
beginning of your upskilling journey, it always
becomes a battle of willpower by the end.

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Chapter 5. The Journey

► Don’t Get Hung Up on Youth ​

Competitions

So what if you didn’t win <insert competition for young

people here>. It’s not too late for you to make your
mark.

For instance, young mathy people sometimes fall into

this trap: they wanted to become a hardcore
problem-solver, and they had fun participating in math
competitions, which they view as the pinnacle of
problem-solving – but they didn’t win, they’re now too
old to compete, they’re disappointed they can’t try
again, and they’re a bit regretful in feeling that they
could have practiced with fuller dedication. The same
situation plays out with science fair, debate
competitions, even elite college admissions.

If this is you, it’s important to realize that these youth

competitions are just practice arenas for early
bloomers, and you can still win in the big leagues even

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if you never won or even stepped foot in the youth

practice arena. While youth competitions can help you
build habits and connections and open some early
doors, they don't gatekeep your future. You can still
become insanely skilled and get recognized for it. This
is just the beginning.

For instance, school-age math competitions are not the

pinnacle of problem-solving. It just seems that way
because in school, that’s what lots of mathy people
focus on and get recognized for, so it’s always in your
face. But think about it – of all the world’s famous
problem-solvers, how many of them gained their
reputation from winning school-age math
competitions? None of them. Even amongst the
minority that did happen to win competitions in their
youth, that’s not what they’re known for. They’re
known for their problem-solving success on more
widely branching paths that they pursued after their
initial schooling. Some published acclaimed research
that pushed pure mathematics forward. Others solved
hard practical problems in industry, applying math to
push other fields forward.

All this to say: in the long run, the long game is the
only one that matters, and missing the short game
doesn’t mean you’ve missed your shot.

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► The 3 Stages of Talent Development

Across various talent domains, the journey to

developing a high level of talent occurs through a
similar general process and can be roughly divided into
three stages. That's what Benjamin Bloom discovered
in the 1980s while studying the training backgrounds
of 120 world-class talented individuals across 6 talent
domains (piano, sculpting, swimming, tennis, math,
and neurology). Below are summaries of the stages:

●​ Stage I: Fun and exciting playtime. Students are just

starting to develop awareness and interest in the
talent domain. The teacher provides copious
positive feedback and approval and encourages
students to explore whatever aspects of the talent
domain they find most exciting. Students are
rewarded for effort rather than for achievement and
criticism is rare.​

●​ Stage II: Intense and strenuous skill development.

Students are fully committed to increasing their
performance. The teacher becomes or is replaced
by a coach, who focuses on training exercises
where the sole purpose is to improve performance.
These exercises are demanding, and the coach
provides constructive criticism to help the student
perform the exercises properly. Positive feedback is
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provided in response to achievement; effort is

assumed.​

●​ Stage III: Developing one’s individual style while

pushing the boundaries of the field. Students are
proficient in all the foundational skills in the talent
domain. They are so committed that they center
their entire lives around the talent domain, no
matter the sacrifice, and typically work with a
world-class expert in the talent domain. The expert
helps the student identify and lean into their
individual strengths so that they can excel beyond
perceived human capabilities.

However, there are several failure modes that one can

run into when attempting to make the journey through
these stages:

●​ Failure Mode 1: The Permastudent. The permastudent

perpetually avoids the leap into creative
production, opting instead to “expand sideways”
and acquire skills that are not foundational for
their talent domain.​

●​ Failure Mode 2: The Wannabe. The wannabe jumps

the gun on creative production before their
foundational skills are in place. They build a
portfolio of work that lacks substance and is made
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trivial by foundational knowledge. Not only is it

cringe, but it also has high opportunity cost
because all this time could be put to better use
actually acquiring said foundational knowledge.​

●​ Failure Mode 3: The Dilettante. The dilettante cuts

their journey even shorter than the permastudent –
they never even make it past playtime, they never
commit to serious foundational skill development
in anything. The dilettante spends all their time in
the land of diminishing returns, engaging in
perpetual playtime across a large number of talent
domains.

► There Are No Shortcuts in Talent ​

Development

If Euler, Gauss, Maxwell, even Ramanujan, Galois, etc.,

needed to spin up on foundational knowledge, then so
do you. Yes, these people all produced plenty of
original research at early ages, but they didn't skip the
foundations.

Even Ramanujan self-studied. He didn't just sit there

and think up math with no prerequisites in place. In
his teens he reportedly worked through Carr’s A

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Synopsis of Elementary Results in Pure and Applied

Mathematics, consisting of 5,000 theorems.

And Galois? Same thing. Galois had a multi-year

period of mathematical upskilling before making
creative contributions. By his mid teens he had
accumulated several years of formal schooling that
included math. Then he caught the math bug, became
obsessed with Legendre's geometry textbook, worked
through it, and continued working through key
research papers for a couple years afterwards. And
THEN he started producing his own creative
contributions.

(Keep in mind there were also far fewer prerequisites

needed to make novel contributions to math back then,
so a person could fill up their prerequisites to
cutting-edge math in a shorter time. Additionally
individuals were presumably highly cognitively
advantaged with outsized learning rate and
generalization ability, which would allow them to move
faster through a curriculum, infer more knowledge
beyond it, and infer more knowledge from self-directed
experimentation. Basically, across all math learners,
these individuals would have been some of the most
likely to have their prerequisites in place.)

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In general, when it looks like someone progressed so

fast they “must” have taken a shortcut, what really
happened is they speed-ran the foundations. Either
that or you’re overestimating their actual ability (likely
because they’re exploiting signaling to trick you).

How can people speed-run the foundations? By way of

a more efficient training environment, advantageous
individual differences leading to more rapid skill
acquisition, or by allocating way more of their time
into training than is typical. Elite performers typically
emerge from a combination of all three of those things.

Take Euler for example.

●​ Advantageous training environment? Check. Euler was

taught by his father, who had studied under
Bernoulli, and Euler enrolled in the University of
Basel at 13 years old, where he also studied under
Bernoulli and self-studied more advanced
textbooks under Bernoulli's guidance.​

●​ Allocating way more of their time into training than is

typical? Check. I mean, geez, what 13-year-old is
taking university courses and self-studying even
more math textbooks on top of that?​

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●​ Advantageous individual differences leading to more

rapid skill acquisition? I don't think there's any
formal record, but you'll see Euler on pretty much
any "highest estimated IQ of all time" list. It seems
pretty safe to conclude he was running on some
exceptional cognitive machinery.

► If You’re Making Silly Mistakes Then You ​

Need More Practice

Climbing a skill hierarchy like math is not just about

conceptual understanding, it’s also about reliable
execution. If you’re making “silly mistakes,” then you
need more practice, simple as that.

If you don’t clean up your silly mistakes on low-level

skills, then you eventually hit a wall where no matter
how hard you try, you’re unable to reliably perform
advanced skills due to the compounding probability of
silly mistakes in the component skills.

Think about gymnastics: if you’re “almost” able to land

a backflip, then that’s great – but at the same time,
you’re NOT ready to try any combo moves of which a
backflip is a component. Even if it’s a silly mistake

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keeping you from landing the backflip, you still have to

rectify it.

And even that’s the most optimistic scenario. Other

times, silly mistakes indicate a deeper conceptual
misunderstanding that you don’t even know you have
until you are held accountable for rectifying those
mistakes.

► No Train, No Gain

If you’re not measuring performance and taking

actions to improve it then you’re not seriously training,
you’re just playing around. Which is totally fine at the
beginning to get a sense of what you like and dislike,
what you’re willing to commit yourself to training… but
sometime you gotta grow up, ya know?

The world rewards those who train. No train, no gain.

If you don’t want to gain anything then sure, just play
around forever, but don’t get mad when nothing comes
your way.

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► Why You Should Push Yourself

Why push yourself? Because the road always stretches

farther than what you can see in front of you, and you
maximize your reward by traveling as far as you can.

Pushing yourself isn’t about racing to a finish line. It’s

about avoiding stagnation. It's about efficiently
growing your skills and continually leveraging them
into new growth experiences. That's how you reach
your potential. To do anything else is to fall short of
your potential.

► Keep Your Foot On The Gas

Any time something initially comes to you easily, it’s

tempting to take your foot off the gas and try to coast
the rest of the way. You coast for a while, just long
enough for coasting to become the new normal, just
long enough to forget that there’s even a gas pedal. And
eventually you grind to a halt just above the base of the
mountain you’re trying to climb.

You play the blame game – first you blame the

mountain for existing, then you blame yourself for
being incapable of climbing it. But at some point you

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mature, come to terms with reality, and realize that all

you have to do is put your foot back on the gas. And
then you start making progress again.

► You Are a Car

You are a car. You go fast on paved roads and get stuck
in mud.

Upgrade your engine to be as fast/powerful as possible,

try to stay on the roads and avoid the muddy zones.
(Train your strengths into superpowers and tailor your
environment & goals to them.)

But at the same time, don’t let a little mud (weakness)

derail your journey. Look for the least muddy zones, try
to cross there, and if you still can’t, then upgrade your
tires. (Shore up your weaknesses so they don’t get in
the way of your strengths.)

► What to Do When You Hit a Ceiling

In many talent domains, upskilling becomes hard and

unintuitive for everyone at some point, and that point
is different for everyone. In math, for instance – some

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people start to experience major cognitive friction in

algebra, for other people it’s calculus, for others it’s real
analysis, for others it’s algebraic topology, for others
it’s research-level math, and there’s even this same
gradation even within research-level math problems.
The friction doesn’t create a hard ceiling, a level at
which one is suddenly incapable of further progress,
but rather a soft ceiling, a point at which the amount of
time and effort required to make further progress
begins to skyrocket until upskilling in that direction is
effectively no longer a productive use of one’s time.

Sometimes people hit a ceiling early due to ineffective

or inconsistent practice techniques. But even if you
practice effectively and consistently, a ceiling still
exists. It’s just like sports: few people practice
effectively and consistently enough to reach their
athletic potential, but it’s just a fact of life that most
people could not become professional basketball
players even with 100% effective and consistent
practice. You can’t detect ceilings with 100% certainty,
but if you’re practicing effectively and consistently, and
you get stuck in a plateau, and one-on-one training
with a coach or tutor doesn’t break you out of that
plateau, then it’s pretty likely.

The natural question is: what do you do when you hit a

ceiling? In general, when you feel yourself running up
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against a ceiling in life, the solution is typically to pivot

and into a direction where the ceiling is higher. For
instance, the story of many a quantitative software
engineer goes like this: 1) loved math growing up and
wanted to be a mathematician, 2) realized during
undergrad or grad school that they had lost their
"edge" compared to other aspiring mathematicians, 3)
also realized that they have a knack for coding and
interest in some applied domain, and that the problems
that need to be solved there boil down to interesting
math that most people in software don't have the math
chops for, and 4) pivoted in that direction where their
ceiling is higher.

► Compound Hard Work and Luck

Both hard work and luck are necessary for greatness

and neither is sufficient on its own. However, they are
tangled up together, feeding into each other:

●​ If you work hard, you're more likely to get lucky –

you create more lucky opportunities ("luck surface
area") and are better prepared to capitalize on
them.​

●​ If you capitalize on a lucky opportunity and feel

like you're succeeding and your hard work is
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making a difference, you get excited and motivated

to lean into it further and continue working even
harder. ("Nothing succeeds like success.")

Greatness emerges from a virtuous cycle of hard work

and luck compounding on each other.

That said, while many forms of luck can be shaped by

hard work, there are other forms of luck that cannot,
such as some biological advantages. So, while it’s
necessary to work hard to capitalize on the
compounding nature of hard work and luck, it’s also
necessary to choose a direction that enables you to
capitalize on any lucky innate edge you may have.

► Get Yourself In A Position Where You Can ​

Eat Risk

An underrated component of finding career fit is

building enough savings to pursue opportunities where
reward is uncertain. Everybody knows that learning /
upskilling is a huge component of career success, but
so is the ability to eat risk. And it’s also a huge
competitive advantage. It doesn’t matter how smart or
skilled you are if you can’t eat the risk.

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► Tie Your Comfort to Real, Tangible Value

The whole point of skills, technology, superpowers,

whatever, is to accomplish greater things. Not to stick
to the status quo with less work.

Lots of people begin their upskilling journey with this

mentality but lose it along the way. They get lazy and
use their skills to minimize the amount of work needed
for a baseline comfortable life. You follow that path for
a while, you end up stuck in a micro-optimization
arena where more work has diminishing returns
anyway. It's hard to escape from that quicksand.

The way to avoid the trap is to develop strong

emotional ties to a lofty problem where incrementally
solving it incrementally transforms the lives of some
people you care about while incrementally making your
life more comfortable. You need to tie your comfort to
real tangible value that you can begin tasting relatively
early.

The hardest part is the beginning, when there are other

options that provide a more comfortable short term at
the expense of 1) an asymptotic long term, or 2)
de-coupling your comfort from real tangible value that
you provide to the world. The emotional connection
helps you stick with it until your current situation is
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even more comfortable than any alternative, which is

the thing that really locks you in for the rest of the long
term.

► If You Can’t Find a Job That Really​

Excites You…

If you can’t find a job that really excites you, then start
(publicly) doing your own thing. You’ll run into other
people who are doing interesting things, and you can
always re-evaluate whether you want to continue doing
your own thing independently or team up / work for
one of said people.

(Yes, depending on where you are in life you may have

to take a job that pays the bills – but try to find a more
“neutral” one that at least doesn’t crush your soul and
doesn’t consume all of your time, so that you have the
energy and bandwidth to simultaneously keep climbing
towards a better fit.)

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► How to Allocate Your Bandwidth While ​

Searching for Your Mission

If you haven’t found a single mission that you want to

focus all your bandwidth on, and you’re wondering how
to to distribute your bandwidth so as to pursue
multiple interests while avoiding spreading yourself
too thin, then here’s the allocation I would recommend:

●​ one main focus (workload equivalent to a full-time

job),​

●​ one semi-focus (workload equivalent to a part-time

job), and​

●​ everything else a hobby with whatever time you

have left over. (Your remaining bandwidth is about
the equivalent of another part-time job, so
depending on how many things there are in that
"everything else," you might have a small number
of serious hobbies or a large number of light
hobbies.)

The rationale:

●​ You don't want to spread yourself too thin. You

need to be moving at a competitive speed in at least

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one direction, i.e., your focus.​

●​ The semi-focus is like a staging area for something

that you want to eventually merge into your main
focus. In order to successfully complete the merge
you're going to have to develop a serious degree of
expertise in it, so it has to be more than just a light
hobby.​

●​ Hobbies are mainly things that you just do for fun,

but they can also serve as candidates to replace
your semi-focus once you merge your existing
semi-focus into your main focus.

► Repetition Can Lead to Expertise, ​

Expertise Can Lead to Variety

Day-to-day variety can arise from focusing

single-mindedly on one big mission. That's obvious if
you have kids and they pull you into all sorts of things
you never would have anticipated -- but this can
happen professionally too.

Counterintuitively, in hierarchical domains, this

transition to day-to-day variety is preceded by a
lengthy upskilling ramp where you grind through

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repetitive (but challenging, not mindless) exercises.

Eventually, you come out the other end with extreme
capabilities that take you on extreme missions.

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Chapter 6. The Team

► If You’re Asking Someone to Be Your ​

Mentor then You’re Doing it Wrong

The #1 way to increase your productive output is to

have it pulled out of you by an older experienced
person who is unreasonably demanding, incredibly
supportive, and has your deepest respect. Even if you
think you’re working hard already, a person like that
can accelerate your output by multiple orders of
magnitude by pointing you in the maximally productive
direction and motivating you to sprint even faster and
longer than you previously believed yourself capable.

But here’s the catch: in order to find that person, be

worth their time, and have that extra productive output
pulled out of you, you typically have to be an incredibly
hard and talented worker in the first place, already
producing a solid level of productive output. You are
not going to run into this person if you’re just coasting.
You have to turn the dial up from 1 to 10 yourself, and

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hold it there for a while, before you meet the person

who gets you turning the dial up to 100.

If you’re asking someone to be your mentor then you’re

doing it wrong. It should look less like them helping
you and more like you helping them. It starts with you
bringing something to the table. You’re a missing piece
in a puzzle that they’re trying to solve. Except, you’re
not a perfect fit initially. You kind of, sort of fill some
gap initially, and you show signs of being able to grow
to cover the remaining area. And they recognize that,
so they invest their time into helping you grow into
that perfect fit.

As you grow, you also expand into other gaps in the

puzzle, maybe even some that you didn’t anticipate,
maybe even some that your mentor didn’t anticipate.
And you grow to fill those gaps in the puzzle as well.
Eventually you cover enough of the puzzle that you
yourself become a puzzle-master looking for puzzle
pieces. And that’s how the cycle continues.

A key takeaway is that when reaching out to someone

you hope to work under, make sure you very clearly
communicate the following: 1) show that you
understand what puzzle they're solving, 2) state what
missing piece of that puzzle you think you can fill, and

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3) state what evidence there is that you can fill that

piece.

► Put Pressure on Your Boss to Come Up ​

with More Work For You

One of the best career hacks – especially for a junior –

is to knock out your work so quickly and so well that
you put pressure on your boss to come up with more
work for you. It causes your projects to grow in scale,
complexity, and responsibility.

When you’re moving super quickly, your boss can’t

spend all their time communicating hyper-detailed
specs to you, so they have to gradually pull back and
offload more of the “scoping out” work to you. You get
more responsibility to carry out the project with less
scaffolding and supervision, and you build your boss’s
trust in your ability to execute.

And as you keep executing and forcing your boss to

come up with more stuff for you to work on, your boss
eventually gets to the point of thinking “I don’t have
time to scope out more work for them because I need
to get X, Y, and Z done… huh, you know, things X and

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Y are kind of advanced but I bet they could do thing Z

for me with a little bit of coaching.”

Basically, you put so much pressure on your boss to

come up with work for you to do, that your boss starts
giving you work that they themself need to do soon,
which is really the exact kind of work that’s going to
move your career forward.

(Note: There's an assumption here that your boss and

organization are well suited for rapid career growth. If
that assumption is false, then the very first step is to
get yourself into a position where that assumption
becomes true.)

► Get On the Right Team

When you’re on the right team, your working hard

inspires your teammates to step up their game. When
you’re on the wrong team, your working hard causes
your teammates to lean back, do less, and let you make
up the difference.

If you want to create serious change then you need to

get on the right team. You can be the most committed
and capable workhorse on the planet, but if you’re on
the wrong team, the only thing you’ll change is your
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team’s allocation of work (i.e., now you do more work

and other people do less).

You need to get on a team where increasing your effort

produces an outsized gain in your team’s collective
effort. Why “outsized”? Because when you’re on the
right team, stepping up your game will inspire your
teammates to step up their game as well.

► Competition as a Means of Collaboration

Competition and collaboration might sound like

opposites, when there’s actually a way in which
competition can be reasonably viewed as a means of
collaboration. It’s when you’re engaged in friendly
competition with people that you’re connected to and
care about, where the point is to motivate each other
and make each other better.

It's kind of like what you would expect on a serious

sports team. During practice, teammates will be
competing against each other, trying to create a
high-intensity practice environment where they can
make each other better. They might even do some light,
joking trash-talk to get each other riled up and
motivated to put their best foot forward -- not anything
mean, of course, but just enough to get the other
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person to react like "damn, let me show you what I

got!"

But the thing is, it’s not even about winning the
competition. It’s about growing and improving, and the
competition is just a way to enter a psychological state
where you’re motivated to work hard and maximize
your effort.

In this type of competition, it actually feels good to see

the other person take the lead and raise the bar. The
whole idea is that you want the other person to raise
the bar on competition and pass you up, so that you’re
motivated to come right back and do the same to them.
It’s like you’re creating a video game: each time one
person passes another person up, a new level and
challenge is created. Everyone has fun playing the
game and wants to get to really high levels.

You could even call it teamwork: as a team, you try to

maximize your total absolute level by having everyone
compete on their individual relative levels.

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► Your Goal is NOT to Prove You're Smart, ​

it's to Make Problems Go Away

When you're working on a team, your primary goal is

not to prove you're smart. It's to make problems go
away.

Yes, the more knowledgeable you are, the better you're

equipped to solve problems, but if your primary focus
is peacocking your intellect then you're going to create
problems instead of make them go away.

You don't get points for creating an unnecessary

problem on which to demonstrate your smarts. You
don't get points for creating an overcomplicated
solution to a simple problem. You lose points for these
things.

What you get points for is taking a problem and

making it go *poof,* completely solved and easy to
maintain and nobody has to think about it anymore.

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► Make Your First Impression On a ​

Contribution, Not a Critique

When you join a new team, make your first impression

on a contribution, not a critique. It's wiser to spin up
on the surrounding context, demonstrate your ability
and willingness to contribute, and THEN suggest the
improvement. This shouldn't take long.

Almost always, your critique is either 1) completely off

base, which you only realize after spinning up on the
surrounding context, or 2) correct, and everyone on the
team is already aware, but they haven’t had the
bandwidth to address it (possibly because it’s not a top
priority).

► Never Come Up Empty-Handed

When you are tasked with fixing a problem for

someone else, and things are not going so well, it’s best
to keep a log of all the things you tried or looked into,
like a lab notebook. Two reasons why:

1) Even if you can’t solve the issue, if you can

enumerate many instances of “here’s what I tried and
here’s what happened, here’s something weird I

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noticed,” it might spur your supervisor to come up with

a suggestion of what you might look into next.

2) It will also demonstrate how much honest work you

put forth trying to solve the problem.

It’s crucial to recognize that working on a project for

an extended period of time and not having anything to
show for it is a hallmark of a lazy, dishonest, or
incapable person – and such people are everywhere.
They thrive in low-visibility environments like mold in
a dark, damp basement. They gravitate towards
projects that could reasonably not pan out, where they
can maintain the perception of pulling their weight
while continually failing to deliver real results.

You may not be a member of the mold, but if you find

yourself in a situation resembling its natural habitat,
then you need to actively demonstrate your work ethic,
integrity, and capability with tangible receipts. If
you’ve done honest work, you should be able to back it
up. You can’t expect people to take your word at face
value. You need to prove that your work survives when
it’s exposed to the sunlight.

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► You Need a Berserker At The Helm

Progress always comes down to a small number of

people working heads down on a decades-long mission
and seriously holding the line on what it means to join
the team and contribute. It's a constant fight against
mediocrity, and unless you have a berserker at the helm
and an airtight chain of accountability, you will
accomplish nothing.

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Chapter 7. The Mission

► Selecting a Good Problem to Work On

What problem should you work on? At first, it doesn’t

matter. Just work on any toy problem that interests you
so that you can build technical skills and gain domain
knowledge. It doesn’t matter if you solve it or not,
whether it’s been solved before, or how impactful it is.
But once you start getting into problems that require
many years of full-time work, selecting a good problem
becomes very important. This is the land of startups
and research labs, many of whose inhabitants regret
that all the time and effort they invested did not yield a
commensurate reward.

Personally, most of the toy problems I worked on were

bad problems. That’s okay because I learned a lot and
gained a lot of skills – which is the whole point of a toy
problem – but it made me painfully aware of two
failure modes that can make a problem bad.

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Failure Mode 1: You don't have an implementable vision

of what the solution is. In particular, some of the
resources you need (e.g. data, algorithms, compute
power) do not actually exist yet and you don't have a
good plan for obtaining them.

This means the problem is too hard and you probably

won’t be able to solve it. In my experience, many
complex systems modeling problems lie here, e.g.
creating useful predictive models of the human brain
or macroeconomy. For instance, there was a time when
I was interested in modeling the human brain. I framed
it as a regression problem on a time-series data set
containing the activities and connection weights of all
the individual neurons in brain. It took me a while to
realize that the data set I wanted did not exist, and
creating it would require multiple lifetimes and
revolutionary breakthroughs in wet-lab neuroscience
(and I was not interested in wet-lab work).

It’s worth noting that sometimes, Failure Mode 1 is an

indication that you’re not actually interested in the
thing that you think you’re interested in. In my case, I
thought I was interested in neuroscience, but it turned
out that I was interested in a lot of stuff that just
happened to show up in neuroscience: multiscale
modeling, connectionism, human learning/intelligence,
etc. The most obvious thing that encapsulates all of
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those interests is building a model of the biological

brain, but it’s not the only thing. What I’m doing now
encapsulates all of those interests I listed and does not
require any wet-lab work. I did still have to get my
hands dirty with lots of teaching and content writing,
but those were things that I enjoyed.

Failure Mode 2: People don't care about the problem.

They are not willing to pay for a solution with whatever
currency you're interested in (money, citations, their
time/attention, etc).

This means that you’re not going to experience any

reward for solving the problem. In my experience,
theoretical modeling problems can fall victim to this
when the problem framing abstracts away details that
make the problem intractable but are important for
application to real life.

It’s possible to argue that Failure Mode 2 doesn’t apply

to you if you’re ahead of your time. However, there are
two issues with that. First, you're probably not ahead of
your time. Being ahead of one's time is rare,
unverifiable, and tempting to believe. Talk about a
recipe for flawed judgement! Second, even if it's true
that you are ahead of your time, if you are too ahead of
your time, then the reward will come too late in your

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life to feel worth the sacrifice. You might not even live
to experience it.

(That said, I have met some people who seemed

entirely satisfied by exploring their intellectual
curiosity without the prospect of receiving an external
reward or making an external impact in their lifetime,
if at all. These people might be legitimate exceptions to
Failure Mode 2. But for the vast majority of people,
exploring intellectual curiosity is not enough.)

How do you find a problem that avoids both failure modes?

You need to find (or create) an intersection between
your own interests/talents, the realm of what’s feasible,
and the desires of the external world. Unfortunately,
it’s rarely obvious where the intersection is. All the
cards are stacked against its existence: you can't choose
what you're interested in or what you're talented in,
you can't choose what the rest of the world cares about,
and if you're interested/talented in some area to the
point that you want to solve problems in it, then your
reasons for being interested in it are probably not
shared by the rest of the world.

So how do you find (or create) the intersection? What’s

worked for me is to live two parallel lives – one in
which you do solve problems that interest you, and
another in which you solve problems that interest the
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rest of the world. You continually try to push the

parallel lives closer and closer together, and eventually,
you figure out how to unify them.

► The “Progress Equals Pressure” Formula

Most people know you have to build hardcore skills to

do hardcore things. But what a lot of people with
hardcore skills still don’t know is that you also have to
shield yourself from nerd-sniping (xkcd.com/356).

When you build hardcore skills, you increase the

surface area of things you can do – but many of these
things are just fascinating distractions. And if you
allow these side-quests to steal your attention, they
dilute the power of your skills.

Making progress is all about putting pressure on a

problem: applying the force of your skills to a specific
problem area (pressure = force / area). Leveling up your
skills will increase your force, but if you want that to
carry over to an increase in pressure, you have to stay
laser focused on the problem area that you’re trying to
cut into.

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► Love What You Do

If you want to succeed wildly and consider it a life well

lived, you have to love what you do. There’s no way
around it. If you want wild success, and not just on a
lottery ticket, then you have to put in such a high
volume of work that it is life-consuming. And if your
life is consumed by something you don’t love, then it’s
a life thrown away.

This is not to say you must love an activity to get better

at it. Effective practice will make you better at anything
even if you don’t love the thing. But if you don’t love it,
you’ll never be able to keep up with the same volume of
effective practice as someone who does have that love.
You’ll never outwork them.

Love is perpetual hardcore effort. Not as a descriptor,

but as a definition. Love is being consistently hardcore.
To say that a parent loves their kid is to say that the
parent is consistently hardcore about raising their kid.
That their kid is always on their mind and they are
always putting max effort into raising their kid. You
don’t love something if you’re not consistently
hardcore about it, and you won’t be consistently
hardcore about it if you don’t love it. It’s a
biconditional, a definition.

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Consistently hardcore people achieve extraordinary

outcomes through extraordinary actions; these actions
go beyond the ordinary and are often seen as crazy.
Framed as love, this is familiar: everyone knows that
love makes people do crazy things.

► Be a Builder, Not Just a Fighter

Once you acquire hardcore skills and new career

opportunities open up, try to avoid those that pit you
against other hardcore-skilled people playing zero-sum
games. What you want to do is create new value, not
just fight over existing value. And the way to do that is
to build infrastructure that solves people’s yet-unsolved
problems. Be a builder, not just a fighter.

► Build Where Building Creates More ​

Opportunities to Build

Nobody who’s building something with high future

value is worried about AI taking their job. When you’re
in that setting, building stuff expands your opportunity
surface area to build even higher-value stuff. The more
you do, the more there is to do. The more of your work
AI takes, the more work it creates. Every time AI

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improves and accelerates you towards your goals, it

expands the scope of what's feasible for you to
accomplish during your lifetime, and the goalposts
move further out.

Ironically, this "high future value" stuff is the hardest

to automate because you quickly reach a point where
further iteration requires doing things that haven't
been done or even thoroughly imagined yet (note that
accomplishing these things requires you to be highly
skilled yourself beyond what the AI is able to do). So
you get in a situation where you have tons of work to
do, that AI can't do yet, and you're sad about that.

In short: you're going to be sharing your pie with AI,

and your feelings about this will depend on your ability
to expand the pie.

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Chapter 8. Motivation

► Disinterest is Often Just Overwhelm

It’s amazing how many people turn out to enjoy <insert

hard thing here> when the tasks they’re asked to do are
properly calibrated to their current level of skill.
Making progress is really enjoyable.

Nobody really jumps off the upskilling train because

they lose interest. They jump off because stagnated
progress makes them doubt the train will ever reach
the destination. They jump off because the level of
overwhelm grows too large relative to their level of
interest. They jump off because they hit a point of
diminishing returns where further time investment is
no longer worth the opportunity cost.

It’s kind of like how sports and games in general are

typically enjoyable by default – unless you’re playing
against competition that’s way overpowered (or
underpowered) compared to your skill level and as a
result you’re not improving, especially if you feel like

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you’re getting your ass handed to you every time you

step up to the plate.

► Why Extrinsic Motivation Matters

It’s common to think that “learning for the sake of

learning” is better than “learning for the sake of
achieving an extrinsic goal,” but I’m not convinced
that’s true. People whose motivation is entirely
intrinsic sometimes prioritize “fascinating
distractions” over other things that would be more
productive to their long-term happiness, in a sense
“nerd sniping” themselves.

I think optimal motivation requires a balance of both

intrinsic and extrinsic factors. Intrinsic motivation
gets you working on interesting things with a unique
perspective. Extrinsic motivation keeps you on the rails
with your long-term goals and keeps you from falling
victim to fascinating distractions.

Furthermore, intrinsic versus extrinsic is a false

dichotomy. It’s not like you have a limited amount of
motivation to split between intrinsic and extrinsic
factors. A percentage tradeoff is the wrong way to look
at it. It’s the other way around: there’s no limit to how
many motivational factors you can accumulate in each
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category, and in turn, there’s no limit to how motivated

you can get.

So regarding intrinsic versus extrinsic motivation, here

are two rules of thumb: 1) a balance across both sources
is better than the same amount concentrated on just
one source, and 2) more overall is better than less
overall.

► How to Become a Super-Producer

The #1 trick to super-productivity is interleaving a

wide variety of productive work that you enjoy. You get
tired, bored, and unproductive if you’re moving along
one dimension for too long.

The solution is to get yourself in a situation where your

production function has multidimensional input and
all those inputs have large partial derivatives on the
same order of magnitude. You follow the gradient in
that space by cycling between these component
activities. The activities are orthogonal, so whenever
you start getting tired, bored, and unproductive from
moving along one dimension for too long, you just
switch to a different activity, moving along a different
dimension.

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That said, it’s important to remember that

“interleaving a variety of productive work” is different
from running away from your problems. If you’ve hit a
rut on some activity, and you’re switching tasks just to
avoid dealing with that problem, and it’s been this way
for a handful of cycles, then you’re past the limit of
“taking a break to freshen up” and what you really need
to do is bunker down and bust through the plateau.

► How The Highest Performers Sustain a ​

Massive Workload

In most domains, the most talented performers have

some edge that allows them to level up faster than the
average person, and despite having this edge, they still
choose to put in much more time than the average
person. They spend most of their waking hours
pushing the boulder even though it's way beyond what
most people consider the finish line. For this kind of
person, there is no real concept of a finish line. The
talent domain is a component of their identity, not just
a skill equip.

The way they sustain such a high volume of work is by

interleaving a wide variety of productive activities.
They've gotten far enough in the skill domain that

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they're well past the narrow tree trunk of

fundamentals, and now they have many different
branches they can be traveling outwards along. Of
course, some branches are more productive than
others, so it’s necessary to focus one’s efforts and avoid
spreading oneself too thin, but even still, there are
quite a few highly productive activities they can cycle
between.

(Note that beginners may have a hard time imagining

this because they’re still climbing the tree trunk of
fundamentals and haven’t really experienced the
"branch-out" effect where it feels like the more you do,
the more there is left to do.)

► Overcoming the Paradox of Serious​

Training

The funny thing about serious skill-building is that you

never stop feeling humbled by your training. The
strongest people are the ones who continually lift
weights heavy enough to make them feel weak. What a
paradox!

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But here’s a trick to feel amazingly capable and

confident: Compare the capabilities of your present
self to your past self.

Periodically look back at stuff you originally found

challenging a couple months ago, a year ago, a couple
years ago, etc. That should make the growth obvious.
There should be things you used to be really confused
about (or maybe even confidently wrong about) that are
way more clear now. Or things that used to take a lot of
effort to accomplish, that would be way easier now.

Also – maybe this is less wholesome – but once you

reach a high enough level of skill you can periodically
compare yourself to other people who are clearly less
skilled. Not saying things to make them feel bad, or
even thinking poorly of them, just noticing evidence
that your percentile has changed on the bell curve.

But, of course, you can’t spend too long in this state.

You dip in to get your confidence up again, and then
you snap out and get back to lifting those metaphorical
weights that are heavy enough to make you feel weak
again.

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► How Taxing Work Becomes Fun

Initially you’re missing a crap-ton of foundational

knowledge. It’s a rude awakening. Then you just focus
on taking one bite at a time. Eventually it gets to be
kind of fun. And at some point you look up and realize
you’ve transformed. Not completely, but enough to
know that it’s really happening. “Wait, am I… cracked?
No way. But I just did this thing that I’ve seen cracked
people do and I wasn’t able to do that before. Holy shit
I’m actually getting cracked.”

It’s kind of like you show up to the gym weak and fat,
not really looking forward to working out, but you just
suck it up and do the workout and stick to the plan and
eventually you get accustomed to it and it becomes
kind of fun putting serious weight on the bar. Not fun
in the sense of “lifting this heavy-ass weight feels so
pleasurable” but in the sense of “it makes me feel legit
and each time I put another plate on I feel really good
about myself.”

And then you notice your clothes fit differently, people

make comments about how strong you look, and you’re
like “What? No, I’m fat and weak. But I guess I can lift
some big weights now? Okay, fine, I’m no bodybuilder
but yeah I guess I did put on some muscle. Holy shit,
I’m actually getting ripped.”
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And then you realize that you’re within striking

distance of not just “getting” cracked, not just
“getting” ripped, but you can actually close the loop in
full if you stick with it and ramp up the intensity. And
this is when it really feels like a video game. You’re
climbing this skill hierarchy, you’re more advanced
than most people, it’s more than just a habit, it’s
starting to seep into your identity, you want to climb
higher and see how far you can get.

And people start asking you for advice, they start

looking up to you, you feel like your hard work is
getting recognition, you’re having a positive impact not
just on your own growth but also on other people’s
growth, and it turns into this really positive feedback
loop that continues compounding throughout the rest
of life. You get caught in this virtuous cycle, it leads to
more and more positive chance events you never would
have anticipated, everything compounds and somehow
everything is really fun despite being really taxing.
Somehow the taxing becomes fun.

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Chapter 9. Learning

► The Greatest Educational Life Hack: ​

Learning Ahead of Time

Why learn ahead of time? Because it guards you

against numerous academic risks, opens all kinds of
doors to career opportunities, and allows you to enter
those doors earlier in life (which in turn allows you to
accomplish more over the course of your career).

You know how, when you take a language class, there’s

often a couple kids who speak the language at home
and think the class is super easy? You can do that with
any other subject. When you pre-learn the material in a
course before taking it at school or college, you’re
basically guaranteed an A in the class.

You guard yourself against all sorts of risks such as the

course moving too quickly, brushing over concepts,
explaining things poorly, assuming knowledge of
important but frequently missing prerequisite material,
not offering enough practice opportunities… There are

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a hundred different ways to teach a class poorly, and

most classes suffer in at least a handful of those
aspects. This is especially helpful at university, when
lectures are often unsuitable for a first introduction to
a topic. But if you pre-learn the material, you’re not
depending on the teacher to teach it to you, which
means you’re immune to even the worst teaching.

Of course, the natural objection is “won’t you be bored

in class?” – but if you do super well in advanced
classes, especially at university, then that opens all
kinds of doors to recommendations for internships,
research projects with professors, etc. It doesn’t matter
whether you’re doing super well because you’re
learning in real-time or because you pre-learned the
material.

When you blow a course out of the water while also

interacting with the professor (answering questions in
class, coming to every office hour with super insightful
questions, etc.), that sets you up for a great
recommendation letter – which is vital not just for high
schoolers applying to college, but also for college
students applying to summer research programs and
graduate schools. Plus, it can open the door to working
on a research project with the professor, or having
them connect you to jobs, internships, and other
opportunities with people in their network.
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Basically, you can use pre-learning to kick off a

virtuous cycle. Even if you aren’t a genius, you appear
to be one in everyone else’s eyes, and consequently you
get a ticket to those opportunities reserved for top
students. Students who receive and capitalize on these
opportunities can launch themselves into some of the
most interesting, meaningful, and lucrative careers that
are notoriously difficult to break into.

And why stop at pre-learning one year ahead? It’s

worth it to keep going, keep accelerating. The road
always stretches farther than what you can see in front
of you, and you maximize your reward by traveling as
far as you can.

Let’s consider math, for example. Many people think

calculus is the “end of the road” for math, and that it
doesn’t matter if you get there many years ahead of
schedule. But that’s far from the truth! There are even
more university-level math courses above calculus than
there are high school courses below calculus.

After a single-variable calculus course (like AP

Calculus BC), most serious students who study
quantitative majors like math, physics, engineering,
and economics have to take core “engineering math”
courses including Linear Algebra, Multivariable
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Calculus, Differential Equations, and Probability &

Statistics (the advanced calculus-based version, not the
simpler algebra-based version like AP Statistics).
Beyond those core “engineering math” courses,
different majors include plenty of specialized courses
that branch off in various ways.

There are so many courses that a student could not fit

them all into a standard 4-year undergraduate course
load even if they overloaded their schedule every year –
however, the more of these courses a student is able to
take, the more academic opportunities and career
doors are open to them in the future. (And while it’s
true that students don’t need to know much beyond
algebra to get a basic job a field like computer science,
medicine, etc. – the people in such fields who do also
know advanced math are extra valuable and in demand
because they can work on projects that combine
domain expertise and math.)

When a student learns a lot of advanced math ahead of

time, they unlock the opportunity to dig into a wide
variety of specialized fields that are usually reserved for
graduates with strong mathematical foundations. This
fast-tracks them towards discovering their passions,
developing valuable skills in those domains, and
making professional contributions early in their career,

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which ultimately leads to higher levels of career

accomplishment.

I’m not exaggerating here – this is actually backed up

by research. On average, the faster you accelerate your
learning, the sooner you get your career started, and
the more you accomplish over the course of your
career. For instance, in a 40-year longitudinal study of
thousands of mathematically precocious students,
researchers Park, Lubinski, & Benbow (2013) concluded
the following:

"The relationship between age at career onset and adult

productivity, particularly in science, technology, engineering,
and mathematics (STEM) fields, has been the focus of
several researchers throughout the last century (Dennis,
1956; Lehman, 1946, 1953; Simonton, 1988, 1997;
Zuckerman, 1977), and a consistent finding is that earlier
career onset is related to greater productivity and
accomplishments over the course of a career. All other things
being equal, an earlier career start from [academic]
acceleration will allow an individual to devote more time in
early adulthood to creative production, and this will result in
an increased level of accomplishment over the course of
one's career.
...
[In this study] Mathematically precocious students who
grade skipped were more likely to pursue advanced degrees
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and secure STEM accomplishments, reached these outcomes

earlier, and accrued more citations and highly cited
publications in STEM fields than their matched and
retained intellectual peers."

► When Does the Learning Happen?

Learning is the incremental gain in your ability to

perform a tangible, reproducible skill. If you’re not
getting those gains, you’re not learning.

Imagine signing up for tennis lessons with a personal

coach. When does the learning happen? It’s not when
you pay the coach the money. It’s not when you watch
the coach demonstrate a move. It’s when you actually
start doing things that you weren’t able to do before.
It’s when you attempt a move, the coach corrects your
form, and you attempt the move again with better
results.

It’s the same anywhere else. The keys to effective

training in athletics, music, etc., are the same as the
keys to effective training in any other skill-based
domain (e.g., mathematics). Simply consuming
information doesn’t cut it. You have to actively practice
the skills that you’re hoping to acquire.

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► There is No Such Thing as Low-Effort ​

Learning

Talent development takes work – not just a little work,

but a lot of work. There is absolutely no confusion
about this in the talent development community. Can
you imagine asking an athletic coach to help you
become a star player using training methods that don’t
tire you out and make you sweat? No matter what skill
is being trained, improving performance is always an
effortful process.

A common theme in the science of learning is that

effective learning feels like a workout with a personal
trainer. It should center around deliberate practice, a
type of active learning in which individualized training
activities are specially chosen to improve specific
aspects of performance through repetition and
successive refinement. These practice activities are
done entirely for the purpose of pushing one’s limits
and improving performance; consequently, they tend to
be more effortful and less enjoyable.

Unfortunately, another common theme in the science

of learning is that the perception of learning is often at
odds with actual measurable learning. When using
effective learning strategies, students perform better

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on assessments but may feel they’ve learned less. Why?

Because effective strategies increase cognitive
activation, enhancing learning despite students feeling
it’s harder. It’s like weightlifting – the strongest people
lift weights heavy enough to make them feel weak.

Many types of training methods are ineffective, but

require little effort, and can therefore seem attractive
to even the most well-intentioned, hardworking
students because they create an illusion of
comprehension. Examples include looking at notes,
rereading course materials, and highlighting.

It is useful to familiarize oneself with instructional

material before engaging in effortful practice, and it is
also useful to revisit that material if one runs into
issues while attempting to carry out the effortful
practice – but it is not until effortful practice that true
learning actually occurs. Familiarizing oneself with
instructional material is similar to warming up before a
workout: the warmup does not actually lead to
improvements in strength or endurance, but it does
help maximize performance and avoid injury during
the workout.

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► The Greatest Breakthrough in the Science ​

of Learning Over the Last Century

The greatest breakthrough in the science of learning

over the last century was characterizing the mechanics
of learning in the brain. Learning is all about the
interplay between working memory (WM) and
long-term memory (LTM). If you understand that, then
you can actually derive – from first principles – the
methods of effective learning.

The goal of learning is to increase the quantity, depth,

retrievability, and generalizability of concepts and
skills in your long-term memory (LTM). At a physical
level, that amounts to creating strategic connections
between neurons so that the brain can more easily,
quickly, accurately, and reliably activate more intricate
patterns of neurons. This process is known as
consolidation.

Now, here’s the catch: before information can be

consolidated into LTM, it has to pass through working
memory (WM), which has severely limited capacity.
The brain’s working memory capacity (WMC)
represents the degree to which it can focus activation
on relevant neural patterns and persistently maintain

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their simultaneous activation, a process known as

rehearsal.

Most people can only hold about 4 chunks of

coherently grouped items simultaneously in WM, and
only for about 20 seconds. And that assumes they aren’t
needing to perform any mental manipulation of those
items – if they do, then fewer items can be held due to
competition for limited processing resources. (Note
that this is an emergent behavior of a more
complicated underlying mechanism: the actual WM
limitation is not a fixed number of storage units, but
rather, the ability to sustain relevant neural activity
while suppressing interference from irrelevant activity.)

Limited capacity makes WMC a bottleneck in the

transfer of information into LTM. When the cognitive
load of a learning task exceeds your WMC, you
experience cognitive overload and are not able to
complete the task. Even if you do not experience full
overload, a heavy load will decrease your performance
and slow down your learning in a way that is NOT a
desirable difficulty.

However, once you learn a task to a sufficient level of

performance, the impact of WMC on task performance
is diminished because the information processing
that’s required to perform the task has been transferred
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into long-term memory, where it can be recalled by

WM without increasing the actual load placed on WM.

So, for each concept or skill you want to learn:​

1.​ it needs to be introduced after the prerequisites

have been learned (so that the prerequisite
knowledge can be pulled from long-term memory
without taxing WM),​

2.​ it needs to be broken down into bite-sized pieces

small enough that no piece overloads your WM,
and​

3.​ you need to get enough practice to achieve mastery

on each piece (and that amount of practice may
vary depending on the particular learning task).

But also, even if you do all the above perfectly, you still
have to deal with forgetting. The representations in
LTM gradually, over time, decay and become harder to
retrieve if they are not used, resulting in forgetting.

The solution to forgetting is review – and not just

passively re-ingesting information, but actively
retrieving it, unassisted, from LTM. Each time you
successfully actively retrieve fuzzy information from
LTM, you physically refresh and deepen the
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corresponding neural representation in your brain. But

that doesn’t happen if you just passively re-ingest the
information through your senses instead of actively
retrieving it from LTM.

► “Following Along” Versus Learning

It's common to think that “following along” is the

same as learning – like, if you can follow along with a
video, book, lecture, whatever, without feeling
confused, then you’re learning. While this might “feel”
like learning, it's not. The feeling is completely
artificial.

Comfortable fluency in consuming information is not a

proxy for actual learning. Learning is a positive change
in long-term memory, and you haven’t learned unless
you’re able to consistently reproduce the information
you consumed and use it to solve problems. This
doesn’t happen when you just “follow along,” even if
you understand perfectly. That comfortable fluency you
feel while following along is arising from the fact that
the surrounding context is already on your mind –
you’re not made to pull it from long-term memory.

When you feel like you’re absorbing information while

passively following along, what you perceive is
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information sitting in your working memory, not your

long-term memory. If you want to test whether
information is in your long-term memory (i.e., whether
you've actually retained it), you have to actively attempt
to retrieve it when it's not already at the front of your
mind. You have to put yourself in the position where
it's not already in your working memory, and the only
way to pull it out of your brain is from long-term
memory.

If you don’t practice retrieving information from

memory, it dissipates quickly and almost entirely. Have
you ever had the experience of being unable to
remember something despite repeated exposures,
because you keep automatically looking it up from a
reference instead of trying to retrieve it from memory?
That’s happened to me an embarrassing number of
times with addresses, phone numbers, directions, etc.
And any books you read, movies you watch – the only
ones you remember in proper detail are the ones you
periodically think about and replay in your head. If you
just consume and don’t reproduce then you forget
almost entirely. I can’t tell you how many times I’ve
watched a movie and didn’t even realize I’d seen it
before until I got 20 minutes in and something felt
familiar. And even then I could barely remember
anything about the rest of the movie, just that it felt a
bit familiar.
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Retrieval is the act of pulling information from

long-term memory into working memory. Practicing
retrieval under challenging but achievable conditions
(e.g., when your memory has gotten fuzzy or there is
less priming) is what increases your ability to
remember and use information. Each time you
successfully recall a fuzzy memory, it stays intact
longer before getting fuzzy again. Each time you
successfully recall a memory with less priming, its
recall becomes less dependent on priming in the
future.

But if you don’t practice retrieval, then this doesn’t

happen. The information quickly dissipates. It stays
with you only briefly – just long enough to trick you
into thinking it’ll stick with you, when it’s really on the
way out the door. But, of course, you don’t notice that
it’s gone if you’re not actually testing whether it’s there.

Consuming information without practicing

reproducing it can produce an artificial feeling of
fluency while the information is held and manipulated
in working memory, but since retrieval practice is not
occurring to extend the information’s retention, the
information dissipates quickly. The fact that it’s in
working memory can trick you into thinking it’s going
to stay there, but it doesn’t.
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Once it’s gone, the only way you can bring it back
without reloading it from an external reference is if
you’re able to retrieve the information from long-term
memory. But if you don’t practice retrieval, you won’t
be able to successfully retrieve. When all you do is
consume information, you put yourself in a situation
where the only way to load it back into your working
memory is to re-consume it. This is why learning really
amounts to increasing your ability to recall information
from long-term memory unassisted, an action that can
be trained by repeatedly performing said action in
gradually more challenging contexts, just like strength
training.

Additionally, learners typically do not process all the

key information as they consume, but they are unaware
of this until they attempt to answer a question or solve
a problem that requires them to retrieve some key
information from memory. At that point, they realize
that they never fully processed that piece of
information to begin with, and they have to go back to
find and properly process it. The same applies to
generalization: learners typically do not fully generalize
what they’ve consumed, but they are unaware until
they attempt to answer questions or solve problems
that require them to generalize their understanding.

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The way to avoid this problem and maximize your

learning is to switch over to active problem-solving
immediately after consuming a minimum effective
dose of information. I know that might feel a bit
jarring, like it’s slowing you down, but it isn’t actually
slowing down your learning – it’s only exposing the
fact that your perception of learning does not
accurately reflect actual learning. Really, it’s speeding
up your actual learning, and the only thing it’s slowing
down is your perception of learning.

Now, you might say “but I had learned so much, and I

had it down pat, and then I forgot it all when I focused
my effort on solving a problem.” But the thing is, if you
can’t retrieve that information from memory at the
snap of a finger, after thinking about other stuff or
zooming in to focus on a specific problem, it means
you didn’t really have it down pat.

► The Vicious Cycle of Forgetting

Forgetting is frustrating. After putting forth the effort

to learn something, who wants to waste time
re-learning it later? To mitigate the effects of
forgetting, it might feel helpful to solve problems
alongside reference material.

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But there’s an issue: when you continually look back at

a reference, the information doesn’t stay in your brain.
You hold the information in short-term memory, but
only temporarily – it dissipates after your focus
redirects elsewhere. The reference material becomes a
crutch, and you’re lost without it. You might think you
need to spend more time reviewing the reference, but
really you just need to review properly, pulling
information from memory.

Even people who are serious about their learning

sometimes fall into this vicious cycle of forgetting.
They might take great notes and then refer back to
those notes all the time instead of trying to pull the
information from memory.

The thing is, if you try to keep the information close by

taking great notes that you can reference all the time,
that just PREVENTS you from truly retaining it. That
might seem counterintuitive, but it’s actually pretty
obvious. What’s the thing that transfers information to
long-term memory? Retrieving from memory. When
you take great notes and constantly refer back to them,
you know what you’re NOT doing? Retrieving from
memory.

Retrieval is not just any loading of information into

your brain. Retrieval is the specific action of “pulling”
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information from one part of your brain (long-term

memory) to another part of your brain (working
memory). It’s like your brain is lifting a weight off the
ground of long-term memory and raising it up into
working memory. The fuzzier the memory, the heavier
the weight – but just like weightlifting, as you practice
lifting heavy weights, you get stronger, i.e., your brain
becomes more easily able to activate the pattern of
neurons that represent the information stored in
long-term memory.

If you load information into working memory by

looking at reference material instead of pulling from
long-term memory, then you’re not strengthening your
retention. It’s like you’re going to the gym to lift
weights, but you’re just going through the motions and
letting your spotter lift the weight for you. No strength
is being developed. You end up throwing yourself into
a vicious cycle of forgetting:

●​ You keep looking back at a reference because you

can't remember things.​

●​ You can't remember things because you're not

transferring them to long-term memory.​

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●​ You're not transferring them to memory because

you're not practicing retrieving them from memory.​

●​ You're not retrieving them from memory because

you're always looking back at the damn reference!

As you spiral into this vicious cycle of forgetting, your

whole learning process completely falls apart. You
learn slower, forget faster, and miss out on making
connections that would deepen your understanding.

The only way to break this vicious cycle of forgetting is

to engage in retrieval practice. Initially, that may seem
like a paradox: “how can I engage in retrieval practice
if I’m unable to retrieve?” But it’s not a paradox at all.
Back to weightlifting – you just need to treat the
reference material like a spotter. You try your hardest
to lift the weight, and if you can’t, the spotter
intervenes as a last resort, giving you just enough
assistance to get you over the edge of lifting the
weight. The spotter should be doing as little as possible
while ensuring that you manage to eek out a successful
rep.

In the same way, whenever you're about to look up

information that you've seen before, that you would
like to stick in your brain – always, always, always try
your best to recall it from memory. DO NOT default to
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looking it up. If you cannot manage to retrieve it

despite trying your best, then it’s okay to peek back at
your reference material, but only as a last resort.

Peek once – just a little bit, just the tiniest bit of

priming, just that specific piece of info that you were
trying to remember, nothing else – and then close the
reference, re-pull the information from memory, and
try to recall the rest and proceed forward as far as
possible without peeking back at the reference again.
Never, ever transcribe from the reference. Your brain is
lifting a weight and the reference material is your
spotter – it’s there as a last resort to help you get the
weight up, only when you absolutely can’t get it up
yourself, and the amount of help should be kept to the
bare minimum.

The goal is to wean yourself off of reference material,

using it as sparsely as possible, until you don’t need it
at all. This may be very challenging if you’ve been
relying on reference material as a crutch, but it’s the
only way out of the vicious cycle.

And you know what helps you wean yourself off of a

crutch? Not having easy access to it. As long as you
have a reasonable way to look up a piece of information
if you forget it, then it’s not worth optimizing for
convenience. You WANT it to feel annoying to look
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stuff up, so that you're incentivized not to have to do

that. And if you're engaging in proper retrieval
practice, you won't have to spend much time looking
stuff up anyway.

► Recall First, Reason Second

If you want to build automaticity, then you need to

practice automatic recall. That sounds obvious, but a
common mistake even among serious learners is "I'll
derive/reason the results from scratch to create a cheat
sheet, and then refer to the cheat sheet during practice
problems that involve applying those results."

It's good to practice deriving/reasoning results from

scratch when doing so is within grasp of your skill level
and you haven't done so in a while. However, that does
not count as automatic recall practice on the result
itself. It's just like how recalculating your times tables
on a reference sheet that you constantly refer to will
prevent you from developing automaticity with
multiplication.

So here's what I recommend to do: instead of

deriving/reasoning a result before applying it, apply it
first and then derive/reason it after. Force yourself to
recall the result from memory, and then justify the
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result afterwards. (By the way, this applies broadly, not

just in math.)

► The Vicious Cycle of Context Overload

One of the least efficient ways to learn is to attack the

most challenging “authentic” or real-world problem
context right from the get-go. It creates a vicious cycle
where you

1.​ struggle with the problem due to the additional

complexity,​

2.​ take so long to solve it that there’s time pressure to

move on to new material,​

3.​ struggle even more with the new material because

you didn’t get enough reps in to master the
previous skill,​

4.​ and then the cycle repeats again starting from (1).

It’s a lot more efficient to strip skills down to the

simplest possible context, get some reps in, and
gradually increase the complexity of the context. When
you get that scaffolding right, you can complete each
rep reasonably quickly because the challenge is
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matched to your skill level, and you end up climbing

the skill tree even faster while building a solid
foundation.

► Prereq Yo’ Self Before You Wreck Yo’ Self

Being out of your depth in skill training is a huge

problem because your learning progress grinds to a
halt. It’s not like you’re on a train that left late from the
station. It’s like you’re on a train that’s not even
moving. The train might even start moving backwards:
if you’re so far out of your depth that you’re just flailing
around on new skills, then you’re likely not absorbing
much implicit review on the component skills you’ve
previously learned, and as a result you’re forgetting
them.

The only way to get the train moving forwards again is

to drop down and work at a level that’s appropriate for
you. You need to get yourself in a situation where
you’re successfully accomplishing new challenges. If
you don’t, the situation compounds into a vicious cycle,
getting worse and worse. You continually come into
new skills less and less prepared, getting more and
more out of your depth.

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When you skip prerequisites or otherwise don’t master

them, you don’t have those skills available for
automatic execution, so when you’re attempting to
execute a new skill that depends on them, you exhaust
all your focus and effort attempting to carry out the
prerequisites. You might have the bandwidth to focus
on a single prerequisite if you put all your focus and
effort behind it, but not to execute multiple
prerequisites in parallel, much less monitor and
control the entire complex operation at a high level.

The only solution is to hammer in your prerequisite

skills until they’re rock-solid and easy to execute. That
way, no individual prerequisite takes up much focus or
effort, and you can execute multiple prerequisites in
parallel while seeing the forest for the trees and
strategizing at a high level.

► Filling In Your Foundations is the​

Difference Between Omitted Steps Being​
Minor Potholes vs Uncrossable Chasms

If you fill in your foundations, your missing

prerequisite knowledge, then you'll be able to fill in the
steps that are omitted in those cool technical books
and projects you've wanted to work through. Filling in

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your foundations is the difference between those

omitted steps being minor potholes you can get past
with a bit of a bumpy ride, versus uncrossable chasms
that stop you dead in your tracks.

Too many people go straight for the coolest, most

advanced books/projects, struggle to fill in the gaps in
the advanced material, and then give up, thinking
they're not smart enough. What they don't realize is
that this is typically a solvable problem. Yes, fixed
cognitive differences (IQ, working memory,
generalization ability, etc.) are a thing, but think of it
this way:

If you go into the gym, put a couple plates on the bar,

and fail to lift it, then does it make sense to say "I guess
I don't have enough physical strength encoded into my
genes" and give up?” Of course not! You just need to
train up your musculature, and you can do that by
starting at your level and gradually adding weight to
the bar until you reach your goal.

There is a point where this breaks down and genes

become important, but it's a lot further than most
people think. Most people vastly underestimate how far
they can go with effective training. Can you become a
world-record powerlifter if you're naturally skinny?

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Probably not. But can you turn yourself into one of the
strongest people at the gym? Probably.

► Plan Your Broad-Strokes Journey ​

Top-Down, but Carry Out the Granular ​
Steps Bottom-Up

The top-down approach can be useful for planning a

broad-strokes learning journey towards a goal. For
instance, if you want to learn machine learning, then
you can think top-down to figure out what fields of
math you need to learn in order for machine learning
to become accessible to you. You’ll find that you
absolutely need to learn calculus, linear algebra, and
probability & statistics, and you can skip stuff like
abstract algebra, number theory, etc.

However, the granular steps of the journey, the actual

learning, needs to be carried out bottom-up. For
instance, are you really going master computing neural
net weight gradients via backpropagation by asking
"what does that squiggly 'd' mean," "why do you have
to chain-multiply the derivatives like that," "how do
you calculate the derivative of any activation function,"
etc., all the way down to the depths of whatever is the
last piece of math you’ve mastered?

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No, all you're going to do with those questions is create

a roadmap of what you need to learn. Which is
essentially a calculus course. Except your roadmap will
be terrible because you don’t actually know the subject
yourself – it will have all sorts of gaps that you don’t
even realize are missing because, which is to be
expected given that you don’t actually know the
subject.

You’ll try to climb back up the skill tree implied by

your incomplete roadmap and you'll repeatedly get
stuck trying to climb up to the next branch that you
can't reach because there are prerequisites that you
don’t realize you’re missing.

Most people in this situation will eventually just give

up due to all the friction. Only those who have
extremely outsized perseverance and generalization
ability have any chance of fighting through and making
it to the other side. And even then, it will take longer
(and they'll likely end up with more holes in their
knowledge) than if they just sucked it up and worked
through a well-sequenced calculus course.

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► The Efficient Learning Loop

All the information you consume while learning, every

problem you work out, it comes with the cost of using
up more of your time. It has to be worth it. If you’re
looking to maximize your learning efficiency, then
what want is

●​ streamlined instruction ("no BS, just give it to me

straight" explanations),​

●​ most of the time focused on active problem-solving,

and​

●​ continually switching back and forth between

instruction and problem-solving quickly enough
that your attention span doesn’t run out.

It’s a continual cycle of minimum effective doses:

●​ minimum effective dose of streamlined "no BS, just

give it to me straight" instruction,​

●​ followed by minimum effective dose of

problem-solving,​

●​ then back to minimum effective dose of instruction

to prepare you for slightly more challenging
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problems,​

●​ followed by minimum effective dose on said

problems,

and so on.

► Don't Bloat the Feedback Loop

Lots of people hear "repetitive" as a synonym for

"mindless" when in fact repetition and mindlessness
are completely orthogonal to each other. “Mindful
repetition” is what you want – mindful because you're
practicing just beyond your repertoire, getting
feedback on every attempt so that you can improve on
the next attempt. I.e., deliberate practice.

But even then, it's easy to go overboard and bloat the

repetition with supplemental tasks that, while intended
to support mindfulness, end up throttling the volume
of practice, creating a severe bottleneck in the learning
process. The feedback loop becomes too slow.

For instance, one of the worst offenders is

"think-pair-share," which ensures that the amount of
time wasted scales with the number of students in the
class. If you do think-pair-share in an class full of 30
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students, it's easy to burn most of the class time

dragging out a single repetition, which is next to
nothing in terms of training volume.

Kind of like if you go to the gym for a workout and only

do 1 pushup the whole hour, it doesn't matter how
perfect your form was on that pushup: you only did 1
pushup which is next to nothing. You're not going to
get stronger without a serious volume of reps.

► Some Pitfalls to Watch Out For When ​

Learning From Projects

Once you have acquired the foundational skills for a

cool project that pulls those skills together, then by all
means, go for it! However, here are some pitfalls to
watch out for.

1) Don’t use projects as a way to acquire fundamental skills.

This is typically inefficient due to the
higher-complexity setting. Instead, learn skills in a
more scaffolded context and then use projects to pull
those skills together.

2) Make sure the projects are guided. Don’t put yourself in

a position where you’re spinning your wheels getting

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nowhere. That’s just wasting time that would be better

spent learning new stuff in a structured environment.
Basically, don’t fall into the “discovery learning” trap.

3) Don’t let the projects cut too much into your foundational
skill-building. Projects can be fun and productive for
pulling existing skills together, but you don’t want to
let them become a distraction from further
fundamental skill-building. For instance, you can
imagine someone who learns algebra and then spends
months doing algebra-based projects instead of
learning the fundamentals of calculus, linear algebra,
etc. And then once they gain these higher-level
fundamental skills, many of these algebra-based
projects are rendered trivial. While I wouldn’t go as far
to say those trivial projects were a complete waste of
time, it’s definitely inefficient compared to the
alternative, which is to first focus on fundamental
skill-building first, and then switch over to more focus
on projects as you get closer to the edge of your field.

► Review Should Feel Challenging

Students often expect review to be easy. At least part of

this expectation is due to conditioning: in school, when
the teacher says it’s a “review day,” they might as well
call it an “off day.” But if you’re actually trying to
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maximize learning efficiency, then reviews should feel

tough. Why? Because recalling tricky information
improves memory, while recalling easy information
doesn’t.

That’s the whole idea behind spaced repetition: your

memory has to get a bit fuzzy before the next
repetition, otherwise the desired effect – slowing the
rate of forgetting and remembering longer next time –
doesn’t happen (or at least not nearly as much). It’s the
act of successfully retrieving fuzzy memory, not clear
memory, that extends the memory duration.

And if review problems are easy, not actually extending

your memory duration, then what’s the point? It’s
better to learn something new. A maximum-efficiency
teacher will intentionally let your memory fade a bit
before review so that the act of refreshing your memory
actually deepens your long-term encoding, and they’ll
use the extra time to cover more new material.

In general, learning requires introducing “desirable

difficulties” into the recall process, making it tough yet
achievable. During an initial lesson, the desirable
difficulty comes from manipulating new information.
During review, the desirable difficulty comes from
successfully recalling fuzzy memory – you’ve already
learned how to manipulate the information, but now
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you’re practicing in a trickier setting where enough

time has passed for your memory to fade.

Consequently, reviews should feel as mentally taxing as

initial learning. You’re getting better, but the bar for
success also is getting higher. Your brain has to hold
the memory for a longer period of time – just like a
muscle holding a weight.

The analogy to weightlifting runs deep. In the context

of spaced repetition, the way you increase the weight is
by waiting longer before retrieving the knowledge
again. But you also don’t want to wait too long before
retrieving the knowledge, because then you won’t be
able to successfully retrieve it. This is just like how in
weightlifting, you need to increase the weight to the
point where you struggle to lift it, but you are able to
overcome the struggle. That’s how you build muscle,
and that’s also how you build long-term memory.
Spaced repetition = “wait”lifting.

► Learn Like You Lift

Spaced repetition is so similar to weight training that

you might as well call it wait training. You’re lifting a
memory off the floor of long-term memory and raising
it up into working memory. The fuzzier that memory,
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the harder it is to lift. The wait creates the weight. And

just like successfully lifting a heavy weight strengthens
muscles, successfully recalling a fuzzy memory (lengthy
wait) strengthens memory.

But you have to retrieve from memory. Spaced

“re-reading” doesn’t count – that’s like letting your
spotter lift the weight for you. The movement you’re
trying to train is the lift from long-term memory into
working memory. Re-reading brings information into
working memory, but it doesn’t exercise the lift, and
improving the lift is what improves retention.

The only time the spotter should help you lift the
weight is when you can’t lift it despite trying your
hardest. And even then, the spotter should only give
you just enough assistance to get you over the edge of
lifting the weight. The spotter should be doing as little
as possible while ensuring that you manage to eek out a
successful rep.

In the same way, the only time you should look at

reference material during review is if you can’t recall
something after trying your hardest. And while it’s
okay to check reference material as a last resort, you
should only peek once for a cue, and then try to recall
the rest without looking again.

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This weightlifting analogy generalizes beyond spaced

repetition: in general, learning requires introducing
“desirable difficulties” into the recall process, making
it tough yet achievable. But remember: just like little
strength is built by attempting and failing to lift a
too-heavy weight, little knowledge is built by
attempting and failing a too-difficult learning task.
Even a desirable difficulty becomes undesirable if the
learner is unable to overcome it. Additionally, not all
difficulties are desirable. Plenty of difficulties are
undesirable even if they can be overcome. For instance:
sleep deprivation. Even if you overcome it, it’s not a
productive challenge for building strength or
knowledge.

► Schooling Versus Talent Development

The fundamental principles of effective training are

similar across domains. But you only see this if you're
actually optimizing for performance. That's what's
done in the field of talent development: an individual’s
performance is to be maximized, so the methods used
during practice are those that most efficiently convert
effort into performance improvements. But elsewhere
in education, the norm seems to be optimizing for fun
and entertainment while, as a secondary concern,

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meeting some low bar for shallowly learning some

surface-level basic skills.

Schooling and talent development are completely

different things. In schooling, students are grouped
primarily by age, rather than ability, and each group
progresses through the curriculum in lockstep. Each
member of the group engages in the same tasks at the
same time, and it is expected that different students
will learn skills to different levels.

In talent development, students progress through skills

at different rates, but learn skills to the same threshold
of performance. Their progress is measured not by
their level of learning in courses that they have taken,
but rather by how advanced the skills are that they can
execute to a sufficient threshold of performance. This
is accomplished through completely individualized
instruction. Learning tasks are chosen based on the
specific needs of individual students, each student
must learn each skill to a sufficient level of mastery
before moving on to more advanced skills.

This contrast between schooling and talent

development is not new. Researchers have known
about it for many decades. For instance:

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●​ “Schools do not seem to have a great tolerance for

students who are out of phase with other students in
their learning process.” –Benjamin Bloom, 1985​

●​ “In general, school learning emphasizes group learning

and the subject or skills to be learned. Talent
development typically emphasizes the individual and his
or her progress in a particular activity.” –Bloom &
Sosniak, 1981

At the heart of it all, here’s the core difference: Outside

talent development, lots of people in education
disagree with the premise of maximizing learning.
Whereas in talent development, an individual’s
performance is to be maximized, so the methods used
during practice are those that most efficiently convert
effort into performance improvements.

Here’s a concrete example. On one hand, “testing” and

“repetition” have become dirty words in education.
However, practice testing and distributed practice (also
known as spaced repetition) are widely understood by
researchers to be two of the most effective practice
techniques. Moreover, deliberate practice – which has
been shown to be one of the most prominent
underlying factors responsible for individual
differences in performance, even among highly
talented elite performers – is centered around using
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repetitious training activities to refine whatever skills

move the needle most on a student’s overall
performance.

So what gives? Why are there debates about

scientifically proven learning techniques like testing
and repetition? Because lots of people in education
disagree with the premise of maximizing learning. The
debates aren’t about whether testing and repetition are
effective learning techniques – the debates are about
whether education should seek to maximize students’
learning.

Outside of talent development, the typical approach to

education involves maximizing other things like fun
and entertainment while, as a secondary concern,
meeting some low bar for shallowly learning some
surface-level basic skills. I’ll admit that de-prioritizing
talent development ends up working out okay when
students aren’t expected to achieve a high level of
success. For instance, if every student in gym class
were expected to be able to do a backflip by the end of
the year, things would have to change – but the
expectations are so low that meeting them does not
require talent development.

But serious skill development is different. Take math

class, for example. Students are typically expected to
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achieve a relatively high level of success in math: many

years of courses increasing in difficulty, culminating in
at least algebra, typically pre-calculus, often calculus,
and sometimes even higher than that. As a result, in
math, de-prioritizing talent development leads to
major issues. When students do the mathematical
equivalent of playing kickball during class, and then
are expected to do the mathematical equivalent of a
backflip at the end of the year, it’s easy to see how
struggle and general negative feelings can arise.

► Learning Doesn't Have to Be Synchronized ​

for Camaraderie to Occur

You don't need to be moving in lockstep with your

peers. There's plenty of shared experience to bond over
when you're all working hard to climb the same skill
tree along whatever individualized path and starting
point is most efficient for you. You don't need to be
taking each step and climbing each branch in sync.

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► A Sanity Check for Effective Study ​

Techniques

Every time you study, imagine the Grim Reaper is

going to show up at the end of your session to quiz you
on what you covered, and if there’s any question you
can’t answer correctly, you die. Whatever study
techniques you’d use in that situation, you better be
using them already.

(I should emphasize that getting stuff wrong

occasionally is totally okay and expected. The thought
experiment here is more about the actions than the
results: truly optimal study strategies would be
conserved even in the theoretical highest-stakes
scenario. When a high-accountability situation induces
change in learning techniques, it exposes that the
emperor was originally wearing no clothes.)

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Chapter 10. Expertise

► The Driving Force Behind Expertise is ​

Long-Term Memory

An important mechanism behind expert performance

is "perceptual learning," the ability to extract key
features from complex environments while filtering out
irrelevant noise.

Whereas a beginner perceives individual isolated

pieces of information, an expert perceives "chunks" of
information organized into meaningful patterns and
structures. These chunks are physically encoded as
wiring in the expert's long-term memory, and they are
the building blocks that make up the expert's
representation of what they're looking at in working
memory.

This is the critical point: it's not just that the expert
actively thinks about things differently from the
novice. It's that the expert literally perceives them
differently to begin with. The same sensory signals are

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processed into different working memory

representations. What the expert holds in working
memory is very different from what the novice holds in
working memory.

What's more, these memory representations in the

expert brain can also include predictive information
that's not in the original stimulus. The stimulus
activates a neural representation, and that neural
representation may contain more information than is
in the stimulus. It may include missing details or even
future events associated with the stimulus. The expert
will perceive all of this additional information while
perceiving the stimulus, and they can use this
information to make better decisions and sense/correct
mistakes before they fully manifest.

For instance, consider an expert pianist. Without even

pressing the keys of the piano, they can predict what
sounds will be made purely based on hand position. If
the hand position is wrong, they can quickly detect and
correct the issue to avoid playing a wrong note. A
beginner, on the other hand, will not realize that there
is an issue until they hear the wrong note.

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► Learning is Memory

At the end of the day, learning is memory.

Understanding amounts to memory that is
well-connected and deeply ingrained.

The difference between "just memorizing" and "deeply

understanding" isn't the substrate of the
representation, it's the depth of the representation.
Deep understanding consists of not only declarative
facts, but also connections that link facts into related
groups or "chunks" (think: concepts), connections that
link smaller chunks into bigger chunks, and so on -- as
well as procedures for operating on chunks (think:
skills), connections that chunk sub-procedures into
meta-procedures, and so on.

This is all raw mechanical memory. It's just storage

and retrieval of information. The point of building
superior representation is to build superior recall
abilities, including broadening and fine-tuning the
range of stimuli that activate the information. If
someone is "just memorizing" as opposed to "deeply
understanding," it really means they haven’t stored
enough information in memory.

"Learning is memory" might feel obvious, but many

learners don't fully grasp the implications. If you don't
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realize that learning is memory, then you won’t realize

that the most effective way to learn is to use
memory-supporting training techniques.

It’s easy to get confused, thinking: "Truly

understanding something is different from just
memorizing it, so learning doesn’t require
memory-focused techniques like retrieval practice,
spaced review, and interleaving (mixed practice). Those
are about memorization, not true understanding." And
if that’s what you think, then you'll likely shirk the hard
work required to build memory, use fun/easy but
ineffective training techniques instead, and end up not
actually learning much.

I used to think resistance to "learning is memory" was

genuine confusion, but now I think it's mostly laziness.
If you accept that learning is memory, then you have to
accept that maximizing learning requires
memory-supporting training techniques. But those
techniques are highly effortful and measurable, which
make them unattractive to low-accountability /
low-effort folks. The only way to reject the premise is
to latch onto the idea that "understanding" is some
supernatural thing that can't arise from raw
mechanical memory. Which is problematic because
there's decades of research showing how expertise
arises from having lots of domain-specific information
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encoded into memory that is well-connected and

deeply ingrained.

(A response to the most common genuine objection:

Even learning to generate new ideas amounts to
searching a space of possibilities, combining pieces of
memory in ways that haven't been combined before.
Now you might say "aha, the skill of
searching/combining is something other than
memory," but let me ask you: when a someone trains
the skill of coming up with novel ideas, such as a grad
student learning to come up with research ideas that
contribute to the cutting edge of knowledge in the
field, where is that skill stored for future use? In
memory.)

► Learning is About Bridge-Building,​

Not Jumping

In the cognitive science literature, there's a lack of

research evidence that people can actually increase
their "raw" working memory capacity and
generalization ability through training general
problem-solving skills. There’s a mountain of evidence
that you can increase the number of examples and
problem-solving experiences in a student’s knowledge

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base, but a lack of evidence that you can increase the

student’s ability to generalize from those examples.
(For a brief overview, see Sweller, Clark, & Kirschner,
2010: Teaching General Problem-Solving Skills Is Not a
Substitute for, or a Viable Addition to, Teaching
Mathematics.)

However, there IS research evidence that you can

effectively turn long-term memory into an extension of
working memory if you acquire domain-specific
foundational skills and develop them to the point of
automaticity. And as you layer more advanced skills on
top, those foundational skills naturally get compressed
into more generalizable neural representations that can
be applied more flexibly across different contexts.

The phenomenon of turning long-term memory into an

extension of working memory was observed as early as
1899 by Bryan and Harter: "The learner must come to do
with one stroke of attention what now requires half a dozen,
and presently in one still more inclusive stroke, what now
requires thirty-six. He must systematize the work to be done
and must acquire a system of automatic habits
corresponding to the system of tasks. When he has done this
he is master of the situation in his [occupational or
professional] field. ... Finally, his whole array of habits is
swiftly obedient to serve in the solution of new problems.

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Automatism is not genius, but it is the hands and feet of

genius."

For about a century, the evidence was gradually

bolstered, and the 1980s marked a tipping point that
led to an explosion of research interest and behavioral
studies. For instance, Chase and Ericsson (1982) found
that "rapid access to a sizeable set of knowledge structures
that have been stored in directly retrievable locations in
long-term memory ... produce[s] an effective increase in the
working memory capacity for that knowledge base." And as
explained by Unsworth & Engle (2005), "..[I]ndividual
differences in WM capacity occur in tasks requiring some
form of control, with little difference appearing on tasks that
required relatively automatic processing."

Today, in addition to behavioral studies, this

phenomenon of turning long-term memory into an
extension of working memory can be physically
observed in neuroimaging. At a physical level in the
brain, automaticity involves developing strategic
neural connections that reduce the amount of effort
that the brain has to expend to activate patterns of
neurons. This has been observed, for instance, by
Shamloo & Helie (2016), who studied functional
magnetic resonance imaging (fMRI) brain scans of
participants performing tasks with and without
automaticity and found that only subjects who had
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developed automaticity were able to perform tasks

without disruption to background thought processes.

In summary, it appears that skill development all

comes down to building domain-specific chunks in
long-term memory that allow you to bring more
information into working memory without actually
increasing the amount of cognitive effort you have to
put forth to rehearse that neural activation. In other
words, the way you increase your ability to make
mental leaps is not actually by jumping farther, but
rather, by building bridges that reduce the distance you
need to jump.

► It’s All About Domain Knowledge

There is a lack of evidence that you can increase

someone's ability to problem-solve by any other
method than equipping them with more domain
knowledge. If this seems counterintuitive, it's because
1) we tend to vastly underestimate how much of our
problem-solving ability comes down to accumulated
domain expertise, and 2) courses typically don't cover
all the domain expertise that's needed.

For instance, an opponent might argue that debugging

code is more than just domain knowledge: it's about
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the general ability to tinker around with things, and

you don't learn that at school. However, what's really
happening is they've amassed a vast zoo of tinkering
techniques -- printing out specific relevant info,
dumping all info into a logfile, setting a breakpoint,
setting a conditional breakpoint, stepping through
code, refactoring messy code in the hopes that
reducing complexity will make the problem go away
naturally or at least be easier to identify, reproducing
the issue on a simpler case, etc. -- and they've gotten
tons of practice selecting and using these techniques in
different problem contexts.

This is domain knowledge. It comes more quickly to

some people than others, but there's nothing magical
about it. If you learn these granular techniques, get
really good at executing them in technically complex
settings, and get really good at matching debugging
problems to techniques, you'll be an expert debugger.

Unfortunately, this stuff is typically not covered in CS

courses, and students typically get very little structured
practice with it. It seems like most CS grads barely
even know how to use a breakpoint, and that's just
scratching the surface of debugging techniques. So
what happens is people will sometimes learn an
incomprehensive structured curriculum, learn a bunch
of stuff outside of it, and then think that the stuff they
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learned is magical and cannot be taught in a structured

manner -- when, in fact, it can, and the problem is just
that nobody has put in the hard work to create that
structured curriculum yet.

► Turn The Magical Into The Mechanical

When a process or phenomenon feels magical, that’s

typically an indication you don’t really understand
what’s happening under the hood. You don’t have the
nuts and bolts in your head, so the outcome just feels
like a magical result from some sorcerous incantation.

This magic can be exciting, even inspiring – but many

learners make the mistake of leaning further into
activities that increase this magical feeling, when
really, the goal of learning is to turn the magical into
the mechanical.

The shift from magical to mechanical doesn’t diminish

the beauty. It just changes the lens. You stop being a
spectator of wonders and start becoming a builder of
them.

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