The book went on to become a surprise bestseller, with over 200,000 copies sold and dozens of translated editions. To this day, the bulk of new reader emails I get are from people who discovered me through Ultralearning.

A question I get asked a lot is how the book would change if it were published today. In 2019, the conversation about AI was still a whisper. Now, it’s deafening.

Today, I’d like to walk through Ultralearning and look at what’s changed, what hasn’t, and what I think the future holds for learning and education.

What Hasn’t Changed

The basic message of Ultralearning, I believe, still holds up pretty well:

Technology is widening the gulf between the haves and have-nots of human capital. Learning in school is insufficient. To achieve, we need to continually add to our skills and knowledge, and doing so efficiently is imperative given our information-saturated environment.

AI has only accelerated those trends.

While some early reports suggested AI might be an equalizer, helping mediocre programmers and writers produce at a higher level, I think those early takes now seem naive. If anything, the fruitful branches of the skill tree for becoming a professional programmer have only gotten higher—with tasks that were previously for junior devs now wholly within the grasp of automated agents.

Some prognosticators suggest that the culmination of this process will be the devaluing of all human skills. Why bother learning anything at all if AI will soon do it better than you?



I’m skeptical of this as a final outcome. I tend to think there will continue to be humans doing human jobs far into the future, if only because certain kinds of work are inherently humanistic. But the medium-term outcome seems to clearly back the urgent need for humans to learn deeper and more robust skills to compete.

AI has not fundamentally changed the effort involved in learning. Ultralearning was written from a particular vantage point: a person eager to learn and willing to do the hard work required. These people have always been a minority, and AI cannot change the intrinsic effort required.

So, as a proportion of the population, I don’t expect an explosion in impressive autodidacts any more than we saw with the arrival of the Internet. The world’s knowledge is already at our fingertips, but most people will still prefer to watch funny videos instead. AI certainly isn’t changing that.

But, at a tactical level, AI has created new possibilities (and pitfalls) that didn’t exist when I wrote Ultralearning. So let’s look at some of those, following the nine principles of the book.

Principle #1: Meta-learning

This is probably the chapter most in need of a rewrite. Self-education has always stumbled on the bootstrapping-problem of knowledge: how do you organize an effective learning project when you lack the knowledge to organize it?

My solution in the book was to encourage people to do research: figure out how a skill works, talk to experts and map out what you need to learn before you start.

AI has dramatically reduced the cost of doing this kind of research, and not only for academic subjects. Even obscure practical skills can now be broken down into discrete subtopics, practice activities, lists of facts, concepts and more.



My go-to approach to tackling a new topic area these days is to fire up ChatGPT and get it to start with a Deep Research on the topic, beginning with some of my major questions. The resulting document isn’t usually on par with genuine experts, but I very quickly narrow in on what sorts of directions I need to take to fill in my research.

Similarly, if you’re learning a less academic skill set, using AI can surface the current best practices and give you the basic building blocks for a learning project.

I very rarely stay totally within AI responses for meta-learning. It’s always good to get to the ground truth of some genuine expert or teacher’s curriculum. Finding those teachers and experts and the organizing paradigms that lead to them is much easier now with AI.

Principle #2: Focus

AI hasn’t changed this principle. Learning anything requires time. Even when you do projects efficiently, they’re still an enormous amount of work. If you can’t put the time in, you can’t get the results.

Learning also requires attention. If you can’t devote large chunks of undistracted time to a project, you’ll fail to build deep skills and understanding.



The attentional ecosystem has only gotten worse since Ultralearning was published. When I was doing projects in my early twenties, the major distractions were Reddit threads and the occasional Facebook post. Now, an endless treadmill of short-form video content on our phones means we can play the attentional slot machine all day without pause.


Currently, I see AI-generated content as less appealing than human-generated content, so I don’t see it making the problem of addictive social media much worse. Perhaps in a few years AI-generated feeds will be more enticing than human-created content, and I’ll need to revise this point.

Principle #3: Directness

Practice the skill you want to get good at. Do the real thing and avoid substitutes.

AI probably makes this harder. Because AI is so compelling, there’s a temptation to do AI-mediated practice rather than engaging in the hard, scary, and sometimes uncomfortable, real-world skill that directness suggests.

Take language learning, for instance. In Ultralearning, I was highly skeptical of the gamified drills offered by apps like Duolingo. To me, they simply omit so much of the actual skill of conversing in another language that you could play these games for years and still feel uncomfortable ordering food at a restaurant.

Since then, I’ve heard people claim that they’re using AI to learn languages, writing—and even social skills(!!).

Of course, one could easily imagine someone who is having real conversations, publishing essays and attending social events simply using AI to shore up some weak points. But, more often, I worry that people are using the verisimilitude that AI creates to try to avoid doing the real thing entirely.

Principle #4: Drill

The counterpart to directness is drill: breaking down a complex skill into smaller parts, focusing on those smaller parts either in isolation or with greater focus to make selective improvement. These drills can include conjugation exercises for Spanish, practicing layups for basketball, making value studies for painting, and more.

Here AI presents a whole range of new opportunities through AI-generated practice problems, flashcards, worksheets or feedback.

For instance, one of the major difficulties in my language learning projects had been how much weight to put on vocabulary study through flashcards. On the one hand, an efficient spaced-repetition system, backed by some careful mnemonics, can make it much faster to acquire a few thousand words of basic vocabulary. On the other hand, flashcards can lead to brittle knowledge that is difficult to generalize to real conversations.

A major cause of my ambivalence with flashcards is that the paradigm assumes each word is an atomic fact. But what we are actually learning when we learn new words is not merely a definition or translation. Instead, we’re also learning contextual associations for how that word typically appears in spoken or written language. It’s how we know the difference between the words small and petite, or big and grand. These associations have to be learned implicitly, and can’t simply be memorized as part of the definition.

Now, with AI, we can generate flashcards that always place the to-be-learned word in a novel sentence, giving us the needed repetition alongside the variation required for learning contextual cues. This, to me, is a major upgrade over the flashcard paradigm.

Conjugations are another area that is difficult to learn without premade practice questions. The issue is that what needs to be learned isn’t a fixed association (e.g., agua -> water) or a verbalized rule (e.g., “change -ar to -o for first-person present tense”) but rather a procedural mapping that needs to take a variable input and give a variable output.

To learn procedures like this effectively, we need flashcards that vary the input/output relationship to show all permutations of the pattern. The problem is that this used to be hard to do before AI. Now, of course, we can use AI to generate infinite variations of the same basic practice problems, which solves the material gap that exists for a lot of skills.

Principle #5: Retrieval

Memory is strengthened more by recall than by review. If you want to learn something by heart, you need to practice remembering it, not just looking at it.

I’ve seen a lot of claims that AI can be helpful with this aspect of learning. For instance, AI tools can generate quizzes based on the books you’re reading allowing you to deepen your knowledge of the content.

I tend to be a bit skeptical about the utility here. Not because quizzes or practice questions are bad (they certainly aren’t), but a lot of the value in retrieval comes from selecting what knowledge you ought to retrieve.

For instance, a naive way to do retrieval practice is simply to quiz yourself on every factual claim made in a text or book. But rarely is the main goal of learning a complete verbatim memory of every factual claim in a book. Instead, we typically want to be able to restate the main ideas and understand the key points and concepts.

Sometimes we may have more idiosyncratic goals, like remembering the authors of key studies for future research or knowing the dates to put historical events inside a chronological context. But memorizing every single fact in a text is almost never a good use of limited studying time.

This is not an idle concern. The world of knowledge is infinite. The effort needed to memorize every fact from one text is effort that cannot be spent on other texts. I’d much rather remember the gist of ten books—their big, important ideas—than know every bit of trivia contained in just one of them.

Practice problems and quizzes designed by a teacher avoid this problem because the teacher has in mind clear educational goals. When they ask a question on a test, it is because they think it is important to know that fact or idea. But if we give an AI a random text without this pedagogical context, the chance that it’s going to narrow in on what is important is much lower—not because of insufficiently capable AI, but because it doesn’t have a useful goal. If you asked a human to generate a quiz from a random text absent any pedagogical goals, they’d also make a bad quiz.

Retrieval, of course, doesn’t need quizzes to work. Free recall, the paradigm where you simply try to remember as much as you can from a source, works remarkably well and definitely doesn’t require AI. So does writing essays about topics you’re learning, which may soon become a lost art. These are low-tech tools that work amazingly well for retrieving knowledge.

Principle #6: Feedback

Feedback is essential for learning. But we often get sparse or incomplete feedback in our learning efforts, which slows down progress.

In symbolic domains, where the skill is primarily mediated through tokens and text, I think currently-existing AI can do a ton to enhance feedback. If I’m trying to improve as a writer, I can get AI to critique my use of research, word choice and storytelling. If I’m trying to improve as a programmer, I can be shown more efficient design patterns or algorithms for solving the same task.


A while back, I recorded some promotional videos in Mandarin for a translation of my book. I wrote the script myself, but then I asked AI to offer suggestions, and it fixed some places where I wasn’t speaking very idiomatically. Before AI, I would have had to pay someone for that advice.

In non-symbolic domains, where AI still underperforms human beings, the value of AI feedback is a lot more limited. I can’t easily use AI to give me feedback on art, skiing or interviewing ability at the moment, so human feedback remains essential.

AI also can’t replace the need for direct feedback from the environment. Entrepreneurs need data about product-market fit. Comedians need to know whether their jokes are funny. Writers like me need to know what their audience already thinks and believes. That kind of feedback is essential to the skill, and AI can’t offer a substitute.

The more dangerous cases are areas where AI could give good feedback, in theory, but it’s been trained not to because people often don’t like getting true feedback. Sycophancy is rampant. For a lot of us, hearing nice things about our ideas and skills is more desirable than hearing the truth.

Principle #7: Retention

I’ve always had mixed feelings about mnemonics. They can be incredibly powerful. The right chaining of visual associations or spatial memories can make indelible links between hard-to-associate facts. But they also take a while to learn and can be time-consuming to apply.

AI has the potential to make mnemonics more valuable. My friend and language-learning inspiration, Benny Lewis, for instance, told me that he’s been using AI these days to help him generate “sounds like” associations for the keyword mnemonic.



For those unfamiliar with the method, the basic idea is to take a foreign language word and create a phonetic clue by mapping it to a similar sounding word or phrase in English (or another language you know well) and then visually mapping that to a highly memorable picture.

For instance, if you’re trying to remember the French word chavirer -> to capsize, you can make a phonetic clue of “shave an ear,” then you have a mental picture of an oversized ear sitting in a canoe, shaving its beard while the canoe flips over. Visualize that mentally once or twice and the association sticks, whereas it may take dozens of repetitions for the direct association to take root.

The keyword method works, but it hasn’t always performed well in lab experiments. The reason is that it often takes too much time and training to get right. Modern LLMs are well-suited to the kind of wordplay tasks required to generate these sorts of images.

Spacing is another area where I expect AI to be some help, particularly the newer agentic AI paradigm. A major hiccup in applying spacing in learning is that it is a logistical nightmare to keep track of all the things you’ve learned and ensure some measure of regular re-exposure. Spaced repetition software does this for flashcards, but, as already discussed, those have fairly narrow applications.

However, I can easily imagine a future where an AI agent helps you manage your workload by resurfacing questions and ideas from material you’ve recently studied. With some guidance, you may even solve some of the retrieval problems mentioned earlier by getting it to quiz you on the major ideas.

Principle #8: Intuition

Understanding is central to learning. But the process of gaining understanding is still somewhat mysterious and poorly understood.

While I’m generally in favor of a knowledge-in-pieces model of conceptual learning, where understandings are built bit by bit through many exposures, it’s also clear that a well-chosen analogy, metaphor or explanation can suddenly make the entire idea “click.”

In Ultralearning, I shared the Feynman Technique my somewhat-apocryphal method of self-explanations that I made heavy use of during the MIT Challenge. The basic method is simple:

1. Write down the concept or idea you want to explain.
2. Write out an explanation as if you were teaching it to someone else.
3. Whenever you get stuck, go back to your study material and notes and re-read until you understand.

The technique works, but it is often frustrated by #3. If you don’t understand, even after reading the notes more deeply, you may waste a lot of time trying to find a better explanation.



Similarly, the method can backfire when conceptual confusion is glossed over rather than dug into—you may maneuver around your own ignorance rather than confronting it. This is why the method benefits from specificity: if you’re having difficulty solving a problem, make the topic of your teaching that exact problem, not the concept it tests in general terms.

AI has massive power to resolve both of these problems. For starters, while I find AI explanations are still somewhat inferior to good teachers, the gap is closing, and well-posed questions can generally get accurate answers. Using AI as a Socratic tutor is one of the ways it can help build understanding.

Second, AIs can ask pointed follow-up questions to reveal gaps in knowledge you don’t even know you are missing. I now frequently upload portions of essays I write where I explain some bit of science or history and ask the AI what I’m getting wrong. Often it nitpicks, but there are definitely occasions where I have a basic misconception.

The pitfall, of course, is that an on-demand system that can explain anything can also make it easy to skip steps #1 and #2 of the Feynman Technique. It’s very easy to ask AI to generate the explanation, skim through it and convince yourself you could have generated it on your own.



The risk of using AI to learn is that not learning at all is always the lowest effort strategy, and most models are designed to allow you to do exactly that. Without guardrails, the default is to skip over the mental work needed to build intuition, even if the technology can, in theory, assist in constructing a deeper understanding.

Principle #9: Experimentation

Experimentation, the process of trying out different things and figuring out what works, both within the skill you’re trying to master and in the process of learning itself, is a recurring theme in Ultralearning.

The new AI tools offer an acceleration of these possibilities. Not only because many new possible methods for learning now exist, such as on-demand Socratic tutoring, procedurally-generated practice problems, knowledge management, mnemonics generation and more, but also because many of the seemingly-useful applications are really pitfalls in disguise.

If I had to go back and redo any of the challenges I wrote about in Ultralearning, the possibilities for learning them would have changed dramatically. The MIT Challenge could have used AI to fill in material gaps, given me extra practice problems and gotten me unstuck when my self-explanations only led to confusion. The Year Without English could have had auto-generated flashcards, grammar explanations and corrective feedback on conversation recordings. I could have vibecoded software that could automatically give me detailed corrective feedback on the accuracy of my portrait drawings.

What wouldn’t have changed is the mental effort involved in learning skills, nor the joy and struggle in actually learning them. Despite the momentous technological changes we’re experiencing, I am still convinced that both the value and strain in learning new things will be an enduring constant.

The post I Wrote Ultralearning. This is What I’d Change Because of AI appeared first on Scott H Young.

This observation isn’t new. I’m certainly not the first to notice this problem, and this is far from the first time I’ve written about it.


But I thought I’d try to categorize, in general, what holds us back from doing things we want to do, but can’t seem to find the motivation to stick with. This doesn’t result in any quick fixes, but it does help us diagnose the problems we face and what the solutions might look like.

Motivation Problem #1: The Work is Too Unpleasant

Many of the things we have a hard time feeling motivated to do involve immediate pain or drudgery for potentially long-term or abstract benefits. Research suggests that our weighting of the present moment over the future self is a major cause of procrastination.

Sometimes this unpleasantness is unavoidable. If you need to go to the dentist to get a root canal, the next couple of hours aren’t going to be much fun—but doing nothing will only make things worse. Impulsiveness, or the propensity to weight the present higher than the future, is a major factor in such problems of willpower.

In other cases, the unpleasantness is at least somewhat malleable. For instance, a major factor I credit for my exercising more regularly is the fact that exercise becomes less aversive the more you do it. When you’re in great shape, exercising is fun (or at least less painful), so getting in shape forms a positive feedback loop.

In other cases, modifying the task itself can make doing it less unpleasant. You can change the environment, combine it with other rewards, make it easier, more interesting, turn it into a game or pair it with other activities you enjoy.

Motivation Problem #2: The Work is Too Scary

Fear and anxiety can undermine motivation when we anticipate pain, even if that pain is less likely or less severe than we imagine.


It’s probably best to distinguish anxiety from unpleasantness by the kind of belief we have about the task. Something might be genuinely unpleasant, but its benefits still outweigh the costs. There, the problem is impulse control and trying to tilt the balance in favor of our more prudential self.

In the anxiety case, the problem isn’t that the actions we need to take are necessarily unpleasant, but that we exaggerate how bad they’ll feel or the likelihood of a really bad experience. Here, the problem is courage, and we can solve that by exposing ourselves to the fear to undermine our irrational beliefs.

Since the problem here is that our beliefs don’t match reality, exposing ourselves to the anxiety-provoking situations and confronting the discrepancy between our expectation and reality is a powerful method for overcoming fears and anxieties. The fact that fears are often driven by unconscious threat-detection circuitry lends credence to the idea that we can’t generally talk ourselves out of these anxieties; instead, we require direct experience to combat them.

Motivation Problem #3: We Don’t Know How

Knowledge is often dismissed as a poor excuse for not taking action. After all, if we were really motivated to solve a problem, wouldn’t “learn how to solve the problem” be step number one?

But lacking skill and knowledge can hold us back. Part of it is that ignorance changes our calculus of the effort required. If I’m not sure how investing works, I might hold off on saving money because I imagine a long project of learning about investing as a necessary prerequisite before doing anything with my money.

The bigger way know-how impacts our motivation, however, is when a lack of knowledge prevents us from even thinking about a kind of problem, let alone how to solve it. Knowledge often creates both the awareness of an opportunity as well as the means for reaching it.

For instance, knowing an inventor is a major factor in becoming an inventor yourself. No doubt this is partly because having contacts helps you succeed with your creations. But another big part is that knowing an inventor not only gives you knowledge about how to succeed in that career path, but even the idea that you could become an inventor in the first place.

Motivation Problem #4: We Don’t Believe We Can Do It

Our sense of self-efficacy is a major driver of our behavior. If we don’t feel like putting in effort will yield results, we’ll quite rationally hold back.

Yet self-efficacy is built through mastery experiences. So if we hold back, we can’t learn. If we can’t learn, we can’t build confidence. If we can’t build confidence, we’ll have low self-efficacy and remain stuck.

Still, I think low self-efficacy drives a lot of motivational challenges. The trick is figuring out how to get out of the loop of being stuck in our beliefs. In general, I’ve found two approaches that have worked for me.


The first approach is to apply a lot more focus and attention than the problem deserves. Basically, convince yourself that you’ll succeed through overwhelming force, and put in way more effort than the problem seems to merit. Then, when you start to experience some traction, it’s easier to shift into a more stable pattern of motivation and effort more commensurate with the value of the goal.


This works, but it has the Catch-22 problem of being difficult to apply when self-efficacy is really low. We need to believe that we can succeed with unreasonable effort, even if modest effort hasn’t been sufficient in the past.

The second approach is to start building from very small successes. Pick goals that seem super easy and doable, succeed at those and build up your confidence. Think of this as a behaviorally-motivated positive spiral: you try to do something that you can definitely do, you do it, and then you try something slightly harder.

This also works, but it has the limit that small successes don’t always build much self-efficacy for really hard problems.

Motivation Problem #5: We Don’t Value the Outcome Enough

Values are tricky. On the one hand, if we don’t value something, it’s rational not to be motivated to pursue it. In this case, we don’t value something enough because our beliefs about the benefits and costs don’t weigh things highly enough for us to focus on it. Failure to be motivated is simply a difference in priorities.

But a rational lack of motivation can still be ignorant.


For instance, if you’re a heavy smoker, but don’t think smoking is all that bad for you, or you think it’s only going to cause problems when you’re too old to make life worth living anyways—so why not have a cigarette?—then lacking the motivation to quit isn’t exactly irrational, but it is ignorant.



I’m not sure there’s a solution here, other than to say it helps to read broadly and stay informed about many topics. Motivated reasoning can lead us to discount information sources that present inconvenient truths, but if we’re sufficiently curious in the broad sense, we’ll probably stabilize on a responsible level of beliefs about the true costs and benefits of certain courses of action.

Motivational Problem #6: We Have an Incentive to Fail

Perverse incentives are a mainstay of pathological psychology stories. Consider a person who “fears success”, so they self-sabotage. Or a person who likes to be taken care of, so they don’t take care of themselves.

I tend to think these stories are exaggerated, and that the Freudian impulse that all behavior is really a repressed motive is not nearly as common as people may think.

However, perverse incentives can explain a lot of problems that we may be quick to blame on “motivation.” For instance, if you work a job where the only reward for working hard and getting your work done quickly is to be assigned greater tasks and responsibilities, then it’s unsurprising that the natural tendency is to throttle your effort. Or, if saving a lot of money means spendthrift friends and relatives needle you for a loan, it’s unsurprising if you aren’t motivated to save some of your cash for a rainy day.

Motivation Problem #7: It’s Simply Not a Priority

In isolation, of course we should exercise. And maintain our relationships. And keep a clean house. And eat healthy. And journal. And meditate. And focus on our hobbies. And also our careers. And community service.

In short, many problems of motivation are not “failures” of willpower. They’re simply rational decisions to allocate our limited time, attention and effort in places that matter more.

Time, of course, is fixed. We can only ever spend 24 hours in a day. Thus, anything that has a fixed time commitment must necessarily crowd out other opportunities for that same slice of time.

Energy and attention are more malleable. But they’re still limited. This is one reason why habits can be effective. If a behavior requires the same time, but less attention or effort, it may be easier to “afford” compared to a new behavior which requires both time AND effort.

Still, in a lot of cases, our self-described motivational failings aren’t failings at all. They’re simply a rational prioritization of something more important.

What Do These Causes Have in Common?

The common denominator of all these causes is that they’re breakdowns of an otherwise-rational system that weighs costs and benefits in making motivational choices.

 We’re:

• Overweighting the present compared to the future. (Cause #1)
• Exaggerating the expected costs and downside. (Cause #2)
• Underrating our long-term ability to succeed. (Cause #4)
• Underrating the long-term value of success. (Cause #5)
• Faced with hidden costs. (Cause #6)


Only #3, which has to do with our knowledge of the problem itself, and thus the precondition to be motivated in the first place, properly lies outside of this kind of calculus. And, of course, #7 isn’t a problem at all, rather it’s a rational consequence of our having finite time, energy and attention.

None of these mean that problems of motivation are easy to solve. But they do suggest some diagnostic starting points if you feel you ought to have more motivation than you do towards a particular course of action. Tilt the equation in your favor, and you can motivate yourself to do anything you choose.

The post How to Motivate Yourself to Do Anything appeared first on Scott H Young.

Yet, the evidence is pretty clear that most people don’t exercise. Nearly half claim not even to meet the standard guidelines, and there’s good evidence that most who claim to meet the guidelines actually do not.

I say this not to scold, but to sympathize. Prior to a few years ago, I was also someone who probably thought I was getting enough exercise, but I actually wasn’t. I was busy, and I wasn’t motivated. Exercise was always on my “should-do” list, but not always achieved in practice.

Today, I feel like exercising nearly every day is relatively easy. Not automatic, I never find myself jogging spontaneously, but easy in the sense that I don’t find it harder to stick to in my schedule than other daily chores like cooking meals or cleaning up the kitchen.

And, perhaps predictably, the benefits of that shift were both substantial and as-advertised. I do have more energy, less stress and better sleep. I even lost some weight.

Given all that, I’d like to share some of what I think made the shift possible for me. This isn’t to preach or indulge in self-satisfaction, but simply to try to understand what factors might have held me back in the past on the off chance they’re holding you back too.

Behavior, Then Beliefs

Interestingly, if I had to weigh their relative importance, I think changes to my beliefs made exercise stick more than changes to my habits did.

But even if mindset matters more than habits, if I look at my own case, the behavior changes came first.

I started out my recent exercise habits with a fairly rigid early-morning exercise routine, though I have largely defaulted back to afternoon or evening workouts, as was most convenient in the past. The difference now is that I actually do my workouts pretty much every day rather than just a couple times a week (at best).

One of my biggest attitude shifts was simply changing the belief of how much exercise I thought I ought to be getting. I exercise more now, in large part, because I believe I should be exercising a lot more. But I doubt I could have adopted that belief when I was getting far less exercise—it just would have made me feel guilty, and I would have rationalized it away.

For any change to stick, I think you need to change your mindset. But the mindset changes you need are generally only possible once you already have seen yourself succeed behaviorally.

Behavioral Strategies to Get Started Exercising

The basic recipe I followed for exercising regularly was simple:

1. Make exercising regularly a committed priority for at least a month (preferably 2 to 3 months).
2. Aim to get some exercise every day (not just X days per week).
3. Start easier than seems necessary, and ramp up the intensity slowly.

The first part is simple: you can stick to almost any behavior if you focus on it. Prioritizing exercise for a month is probably the minimum, but making exercise a priority for the next three months is better if you’ve struggled with it in the past.

Contrary to a lot of popular wisdom, simply repeating a behavior for a month (or three) doesn’t make it automatic—but it does make it feel more normal.

The rationale for daily exercise is simply that inconsistent schedules lead to constant decision making. Every day, you are asking: should I exercise today? If the answer is always “yes” then there’s nothing to think about. Whereas if you give yourself the opportunity to skip days without a good reason, you’ll end up skipping workouts much more often.

Daily exercise forces problem solving. If you have to fit exercise in every day, it forces you to be a lot more creative about scheduling in a busy life. Maybe you can’t always do an hour-long workout at the gym, but you can fit in twenty minutes.

Finally, the slow ramp up is critical. Any change in how much or what you do to exercise is likely to leave you feeling sore or physically tired. If you really overdo it, your efforts can result in injury. By keeping early workouts well below what you feel capable of, you can prevent those physical symptoms from becoming obstacles to making the behavior stick.

Part of the reason exercise can be a hard habit to create is that exercising feels awful when you’re out of shape. This is doubly true for more intense exercise. A lot of people know they should exercise, but starting with too much intensity means they find the whole thing so unpleasant that they can’t stick with it.

Ultimately, getting in better shape tends to make the act of exercise more intrinsically rewarding. It feels good to run when your chest isn’t pounding during a slow jog. It feels good to lift heavy weights and not have agonizing muscle pain. Some of getting over a dislike of exercise seems to be a matter of overcoming that initial change to your fitness levels.

Mindset Shifts That Mattered for Me

As mentioned previously, I think the habit-changing protocol is fairly straightforward, but that’s not what leads to long-term stickiness. My own habits have changed multiple times since I started exercising every day, and I suspect they’ll turn over again in the years to come. Life is simply too chaotic to expect the exact same routine to work perpetually.

Belief changes, in contrast, can be more durable. Here were some of the biggest mindset shifts that have helped me stick with exercise:

1. Exercise is about health and mind, not about looking good. You should want to exercise (a lot) even if it never results in losing a single pound of fat or looking any better in a bathing suit. Physical appearance is a poor motivator, and emphasizing it crowds out the actually-good reasons to stay fit.
2. Cardio matters; lifting weights is not enough. This may be a gendered thing, but, like a lot of guys, I used to focus on lifting weights and treated cardio as an afterthought. Strength training matters, but for different reasons. If you want to get the full benefits of exercise, you need to get your heart pumping.
3. The goal is to plateau, not progress indefinitely. I used to get motivated when I’d see new results. The problem was that mindset led to feeling demotivated when I was plateauing. Now I try to view exercise more like bathing or tidying, it’s not an aim to ever-higher perfection, but a maintenance activity that is successful even if it just keeps you at the same place.
4. Focus on the minimum, and the average will follow. Another trap I would fall into was an obsession with workout quality. I’d make overly complicated regimens to follow and fail to stick with them. However, when I focus on hitting a minimum target, the overall quality of my workouts tends to improve with fairly little added effort.
5. It is both desirable and achievable to exercise a lot more. Perhaps the biggest mindset shift was simply the amount of exercise in my routine I considered sufficient. As mentioned previously, I used to be a fairly regular 3-4x per week gym goer, with the caveat that 3-4x per week often ended up being 1-2x, or even zero during busy or stressful weeks. Shifting to the expectation that I should exercise every day, and often for more than thirty minutes, has made exercise a consistent part of my schedule. At the same time, I don’t think this belief could have changed at all had I not first established the habits that made this new baseline feel achievable.

What worked for me may not work for you. Indeed, it’s totally plausible to come away from reading this essay with a reinforced belief of why this wouldn’t work for you; you’re probably quite different from me, and you are dealing with different challenges and obstacles.

But I do think that, however you make it work, exercise is one of the highest value-added habits most of us have available. So finding a way to motivate yourself to do so regularly is one of the better investments you can make.

The post How to Motivate Yourself to Exercise Regularly appeared first on Scott H Young.

This blog followed the formative years of my life. I wrote my first post when I was 17, still a senior in high school. When I started, I was closer in age to my children than to my current age.

The internet today is unrecognizable compared to the place I started writing two decades ago. In 2006, YouTube was less than a year old, Facebook was still limited to college students, Netflix sent DVDs in the mail, and Instagram, Twitter and TikTok didn’t exist yet.

The internet was a smaller, weirder place back then. Sharing writing online was a hobby for nerds like me who could set up their own website—normal people read magazines and newspapers. Today, nearly everything people watch and read is online.

The personalities that were attracted to blogging were also different. The mostly text-based media meant early blogging afforded quasi-anonymity. Despite using my real name, I didn’t tell many people I knew in real life I was blogging. Writing online allowed me to connect with people over shared interests, even when those interests didn’t always overlap with my real-life peers’.

Today, the idea of going into writing online as way of expressing yourself quasi-anonymously feels quaint. With the dominance of video and viral media, achieving celebrity is seen as the end goal rather than an unwanted side-effect of trying to share your perspective.

This blog feels like a bit of an anachronism. Here I am, still writing blog posts on a personal website like it’s 2006. I’m lucky that I got to build an audience during those early days, and that I can continue to write here despite my idiosyncrasies. It’s hard to say if I had been born twenty years later if I would have had such an opportunity.

On Changing My Mind

Precocity cuts both ways. My early arrival to the internet likely made my current career possible. But it also meant that I made a lot of early mistakes I probably wouldn’t have made had I began today.

Re-reading old essays sometimes makes me cringe. Watching old videos even more so.

 At some point, my essays stopped sucking by my own standards (admittedly, a low bar), and I no longer feel embarrassed by my writing. But, given that I started writing as a teenager, all my old writing (and dorm-room videos) are still there for all to see.

Intellectual consistency is another victim of starting so early. I’ve flip-flopped on many ideas. Sometimes more than once. So much so that it’s become a bit of a joke among my team members that my most popular essays begin with “I was wrong about __.”

These varying perspectives, taken over twenty years, mean I sometimes end up getting in disagreements with myself or with readers preferring a stance I took years ago. While I’d like to think my writing and ideas have gotten better, I’ve also changed as a person. The perspective at 17 and at 37 necessarily differs in ways that can’t simply be accounted for as accumulating wisdom.

I expect twenty years from now my perspective will be quite different again. Assuming, of course, I’m still lucky enough to spend so much of my time writing.

On Giving Advice

Writing online, of course, is a pretty good gig if you can get it.

 I have, for two decades, had my dream job. Being able to make stuff, share it online, and earn enough to survive was my dream at 17. It still is, although by now I’ve gotten so used to it that it’s easy to take for granted.

I have a lot of sympathy for people who email me asking how they might be able to do what I do. But I’m not certain I’m well situated to give good advice.

The metamorphosis of the internet means the path I took to get here literally doesn’t exist anymore. Back then, a nobody with a personal website could rank for top search engine terms, webcam footage could go viral on YouTube, and the hot thing for gaining subscribers was something called a “blog carnival.” (Seriously.)

If anyone reading this eventually does find success creating things online, it will certainly be through a very different route than the one I took.

While I can’t really give any help to someone who wants to replicate my job, I can hopefully offer some suggestions for keeping it. After twenty years, I think my only advice is to write the kind of stuff you like to read. That way, you’ll know you’ll reach an audience of at least one person.

The post Reflections on Writing for 20 Years appeared first on Scott H Young.

On Monday, I’ll be opening registration for my new course, Everyday Energy. The course is a three-month program designed to help you build practices into your life that promote greater vitality—and productivity.

In case you missed it, I’ve written a brief essay series discussing our human energy crisis, the biological roots of our exhaustion and the need to return to natural rhythms of effort and rest. Today, I’m going to examine the meanings we ascribe to work, and why our society’s dominant paradigm so often leads to burnout.

Burnout is not just being tired. If it was, a good night’s sleep would be enough to fix our energy. Instead, burnout is what happens when exhaustion becomes entrenched.

The research into the causes of burnout is complex and fascinating. To put it simply, burnout happens when:

• First, we’re overworked. Demands exceed our ability to cope or recover. Fatigue results.
• This leads to feeling a lack of control and an inability to keep up, which results in our feeling less competent. We feel helpless and impotent.
• Finally, our feelings of exhaustion and helplessness give way to increased cynicism about the work itself. Work is not simply too much and too hard, it feels ultimately meaningless.

These three components of burnout—exhaustion, cynicism and inefficacy—explain why going on vacation doesn’t fix burnout. We may be able to fix momentary fatigue, but by the time burnout has set in, our beliefs about the work itself and our ability to cope with it have soured.



Fixing burnout isn’t easy. The hardened feelings of cynicism and inefficacy need to be replaced with renewed feelings of competence and meaningfulness of our striving. Sometimes that can be fixed within an existing role, but often it requires finding a new workplace, job or even career path.

The persistence of burnout explains why energy management is so important. We want to stop the vicious cycle of exhaustion before it settles into hard-to-adjust beliefs of inefficacy or cynicism.

Avoiding burnout isn’t the only reason to care about energy management. There’s a state opposite to burnout that’s worth cultivating: flourishing. Just as burnout can become entrenched, flourishing can create enduring resilience and offer a wellspring of energy.

Flourishing: The Opposite of Burnout

If burnout is caused by a combination of fatigue without recovery, feelings of inefficacy, and increased cynicism about the meaning of work, flourishing is the opposite. When you’re flourishing at work, you:

1. Have a healthy balance between effort and recovery.
2. Feel confident about your abilities.
3. Feel stable and secure about the meaning of your work.

When these three conditions are met, the effect is resilience. You have more capacity to dig deep in moments of crisis, and you can take on much bigger efforts without feeling overwhelmed.



Flourishing also neatly illustrates that the opposite of burnout isn’t being relaxed, sprawled out on a beach somewhere. While fixing the state of physical exhaustion is often a priority when we’re overwhelmed, the fantasy of fleeing from all work—whether that’s counting the days until retirement, buying lottery tickets or escaping in video games—is a means of coping, not thriving.

Flourishing isn’t a compromise. It’s not a protective stance to prevent us becoming burned out, but one that embraces challenges and strivings in a way that brings more vitality to our lives.

A Flattening of Meaning

I’ve previously explored the biological roots of fatigue and how our culture of work helps to promote burnout. When we undermine our sleep, diet and exercise, fail to manage stress and work outside of natural rhythms, we create conditions ripe for exhaustion to creep in.

But our philosophy of work exacerbates these problems. Our culture sends us conflicting messages on the meaning we’re supposed to derive from work.

On the one hand, we’re supposed to follow our passions, find our voice and have an impact. Work, in this light, isn’t simply things that need to be done, rather it becomes a transcendent mission. That’s a noble vision, but it often conflicts with the mundane reality of our actual jobs. By requiring meaning in our work to reach some ecstatic ideal, we often pass over the actually existing meaning in our everyday tasks.

On the other hand, we’re taught to maximize economic value, to see work as a means to an end—namely leisure. In this view, work is the price you pay to do the things that really make life valuable.

In an interesting essay, the philosopher Agnes Callard writes about teaching a class on Aristotle’s views on work and leisure. She comments that what the students are doing now, pursuing the life of the mind, was true leisure in Aristotle’s sense. But, for most of the students in her class, attendance is more like “work”—a thing they need to do to get good jobs and live in society.

Both of these visions make it harder for us to find genuine meaning in our work. The transcendent calling ignores the mundane and leaves us longing for a kind of work that doesn’t exist. The transactionalist attitude negates the possibility of meaning in work, with everybody working for the weekend.

What’s needed is a philosophy of work that grounds work in a stable appreciation of its value. Ultimately, the value of our work, and the meanings that will sustain a life of flourishing, are not limited to a few rare professions. It is something available to us all, provided we are able to see it.

If you’ve enjoyed this lesson series and would like to go deeper, I’m opening registration for Everyday Energy on Monday. The course will dive deeper into the biology, psychology and philosophy of energy, and help you cultivate enduring practices for a flourishing life. I hope to see you there!

The post Lesson Four: The Opposite of Burnout appeared first on Scott H Young.

Registration for my new course, Everyday Energy opens next week. In anticipation, I’ve written an essay series covering the central philosophy of the course. If you’re just joining us, check out the first essay on why we’re living through a human energy crisis, and an essay on the biological roots of our exhaustion, which we cover in more depth in the first month of the course.

Nature works in rhythms. Machines work non-stop. Many of our psychological difficulties with work—procrastination, burnout, strain and exhaustion—reflect a misguided attempt to use the logic of machines instead of the logic of nature in guiding human effort.

It wasn’t always this way. Early human existence was rarely easy, but it did follow the logic of nature’s rhythms.

Anthropological research into hunter-gatherer communities, often used as a stand-in for our Paleolithic ancestors, shows that they work much harder than we do, physically. The Hadza in southern Africa, for instance, engage in a little more than two hours of moderate-to-vigorous physical activity per day. That’s roughly 4x the standard recommendation for health, and as much as 14x the amount we typically get in Western countries.



But while this lifestyle is laborious, it isn’t unceasing. Other researchers, looking at a !Kung tribe found that they only “worked” an average of two and a half days per week. Even the most industrious member studied, who went hunting over half of the days researchers recorded, put in a little less than 32 hours per week.

The invention of farming, and our exit from the proverbial Eden of our Paleolithic ancestors, left us relatively poorer, with worse diets, shortened stature and new diseases.

But despite the poorer material conditions, we still worked within natural rhythms. Days began at dawn and ended at sundown, often with a rest during midday. Effort was seasonal, with intense periods during harvest and lighter efforts in winter. In as much as a third of the year, work was restricted due to feast days, festivals and religious observations.

The Invention of Clock Time

This changed with the invention of clock time. Before clocks, our understanding of time was intrinsically tied to nature’s rhythms. Even the length of an hour could vary, depending on the amount of daylight in each season.

With clocks came a new understanding of duration. Instead of flexible rhythms, time now had a fixed, unvarying duration, untethered from the natural world. With clock time came new possibilities to regulate labor and demand more machine-like adherence to a schedule.

Clock time’s dominance became complete during the Industrial Revolution. Workers put in 12–16 hour days, with few breaks and no vacations. In the course of a year, a medieval peasant might have worked 1200 to 1800 hours. In contrast, an early factory worker might have put in over 3000 hours.

Today, few of us have the same grueling schedule as an early Industrial-era factory worker. But while we may have gained perks in the form of better pay, free coffee and comfortable chairs, we have only become increasingly alienated from natural rhythms of work and rest.

Smartphones and email mean that work doesn’t end when we leave the office. Work projects and meetings spill into evenings and weekends. Deadlines and performance reviews leave us wary of taking too many days of vacation.

A Return to Rhythm

The way we work is unhealthy and unnatural. By replacing our prior rhythms with clock time, we’ve severed the traditional cycles of work and recovery. As a result, we feel squeezed between procrastination and frenzy, exhaustion and apathy.

The solution is a return to rhythms. Not simply working less (although, for many of us, it would be an improvement) but switching from an unceasing pace to a work routine characterized by periods of effort followed by recovery.

Unfortunately, any would-be reformer of our current system runs into two problems.

The first is that, despite its unsuitability as a model for human work, the machine-logic of unceasing effort is embedded in our economy. While I think we would be healthier and happier if we had working rhythms tied to nature, as our ancestors did, I don’t long for a return to the days before antibiotics, indoor plumbing and refrigerators.

Is our machine-like approach to work simply a necessity to maintain our modern standard of living?

I believe not. There is considerable cultural variation in our approach to work, from the extreme workaholism of white-collar Japan, to the leisurely lunch hours taken in France. Despite this, it’s the French, not the Japanese, who have higher labor productivity.

This suggests to me that the way we work is a product of culture, rather than a natural result of some path to ever-increasing optimization. Office workers in Japan put in heroic hours because it is expected of them, not because it maximizes useful work. We do what is “normal”, even if what is “normal” is deeply unnatural.

This leads us to our second problem: if the ways we work are part of our culture, how can an individual buck the trend? How can we have healthy cycles of work and rest when surrounded by a culture that operates on the machine metaphor?

This is a tricky problem, but not an insurmountable one. It goes without saying that some compromise is necessary. We always flow, in part, to the rhythms dictated by the broader society. Depending on our position, that may be a gently nudging tide or a rushing rapid.

Yet we’re not entirely at the mercy of our environment. Compared to our factory-working forebears, most knowledge workers have considerable autonomy in many dimensions of our work. We can create healthier rhythms, even as the broader work culture persists in its ceaseless flow.

In my upcoming course, Everyday Energy, we will spend a month working on exactly this problem: how do you carve out natural cycles of rest and recovery within the constraints imposed by your job? We may not be able to return to the past, but we can return to a rhythm of life that is humane and sustainable.

In the next essay, I’ll talk about how the meaning of work has flattened, and the problem of burnout and disillusion that this entails. After that, I’ll open registration for the full three-month course, Everyday Energy. I hope you’ll join me!

The post Lesson Three: Rhythmic Productivity—A More Humane Way to Work appeared first on Scott H Young.

Next week, I’m opening registration for my new course Everyday Energy. In the last essay, I discussed why we’re living through a crisis of human energy. Today, I’d like to share some thoughts on how to fix that, with insights drawn from the first month of the three-month curriculum.

Energy starts with biology. All human physical and cognitive performance is constrained by the fundamental reality that each of us exists as a biological system. When we incur debts—in sleep, stamina or stress—that remain unpaid for too long, the result is breakdown of that system.

Data show that, biologically-speaking, there’s a lot we could be doing better to enjoy greater vitality.

We’re in denial about our fitness. According to self-reports, over half of Americans meet the recommended amounts of weekly exercise. But, when that figure was measured objectively using wearable devices, only one-in-ten actually met the recommendation.

And the recommendations aren’t even optimal! Indeed, while most of us would benefit from exercising more (and a few extreme individuals would benefit from exercising less), the recommended amount of exercise is still below the amount where health benefits plateau.

We sleep poorly. Roughly a third of us fail to get enough sleep. One in ten of us have insomnia. Even worse, our sleep consistency is a disaster. Nearly 85% of people exhibit some degree of “social jet lag” with diverging weekend and weekday sleep rhythms that have a negative impact on health and energy.

The culprit is biological. The clock cells in our brains run slightly longer than a normal twenty-four hour day. Strong light cues provided by the sun constantly adjust that clock backwards. But, in our environment of bright indoor lights, insufficient daytime sunshine, and non-stop screens, we don’t get the resetting signal. Instead, we live in a state of perpetual jet lag.

Our food is fast and low-quality. While our ancestors had to worry about caloric deficits, for most of us the problem is caloric excess. Ultra-processed diets lead to energy that spikes and crashes, and subtle micronutrient deficiencies can leave us tired all the time without us knowing why.

We live in an era of anxiety. Stress in bursts energizes us, but sustained stress leaves us exhausted. Non-stop psychological threats, increasing social isolation, and fewer outlets for coping have resulted in an explosion of mental health diagnoses, and the energy-sapping effects they entail.

Turning Back the Cycle

Worse, these continual shocks to our system can form a vicious cycle. We get overwhelmed at work, so we cut back on exercise. This degrades our body’s ability to turn down the stress response. The increase in stress causes us to eat more junk food and keeps us up at night. The cycle turns, and we end up even more exhausted than we were before.

The self-reinforcing cycle of fatigue can be debilitating. We lack the very energy we need to do the things we need to gain greater energy!

The solution is to take small steps to turn the vicious cycle of energy sapping into a virtuous cycle of energy replenishment. Go to sleep ten minutes earlier. Take a brief daily walk. Learn some relaxation exercises. Switch from a late-afternoon energy drink to a healthy snack.

Small changes, implemented consistently, can build up to a great deal more energy. While the overall trends undermining the biological sources of our energy are dire, they are not destiny. Each of us has the power to live in the way our body and brain were designed—even in our modern world.

In my upcoming course, Everyday Energy, we will spend the first month making concrete changes in our daily practices to build more energy. You’ll learn the science of caffeine, the biology of stress, the neuroscience of light, and even researched-based answers to questions like whether standing desks work or which dietary changes science backs as actually boosting energy.

Energy starts with biology, but it doesn’t stop there. In the next lesson, I’ll cover some ideas drawn from the second month of the course, flow, where we dive into the psychology of work and rest, and how we can build sustainable rhythms to do the work we need to get done.

The post Lesson Two: Life Doesn’t Need to Be Exhausting appeared first on Scott H Young.

I’m excited to announce a new course I have coming out next week, Everyday Energy. It is a three-month program designed to help you build new practices into your life to feel more energetic and complete meaningful work. This course builds on the topics I’ve been writing about over the past few months. It’s not just a deep dive into the research, but transforms those insights into doable changes that make sustainable improvements to your energy levels.

Registration opens on Monday, March 23rd. In the meantime, I’m sharing a brief essay series that discusses the problem of energy, and samples from the Everyday Energy curriculum (fuel, flow and flourish).

The Human Energy Crisis

We’re living through a human energy crisis. One in three people report feeling fatigue. One in eight report feeling tired most days or every day. At our jobs, 76% of people feel burnout at least some of the time, with nearly a third feeling burned out “very often” or “always.”

In some ways, our exhaustion is paradoxical. As a society, we’re richer than we’ve ever been. The amount of labor needed to get enough food to survive is far less than at almost any point in history. We’re saturated with entertainment and new leisure activities. And, for most of us, the physical effort needed to do our jobs is at an all-time low.

Describe our lives to almost any human being plucked from history, and they would imagine a life of ease and convenience: machines that wash our clothes and dishes, water that flows from pipes in our homes rather than being hauled from rivers or wells, desk jobs, and food delivered to our doors—ready to eat.

Yet there’s evidence that all these modern luxuries haven’t left us brimming with extra energy. Researcher Robert Hockey, author of The Psychology of Fatigue, even argues that the notion of fatigue itself, the unpleasant experience of feeling drained, is an invention of the modern age; people in past societies felt tired after work, certainly, but they didn’t have our modern problems of burnout and exhaustion.

Instead, we have trends of pervasive fatigue and burnout, rising incidences of energy-related mental health issues like depression and ADHD, and increases in our consumption of coffee and energy drinks—these all point to something deeply wrong with how we manage our energy.

Why Are We Exhausted?

This crisis of energy has three root causes:

First, our modern lifestyle puts heavy burdens on our biology. Indoor lighting and always-on entertainment disrupt our sleep. Sedentary habits undermine our health and fitness. Poor diets leave us simultaneously overfed and undernourished. Chronic psychological stress drains our bodies and our minds.

Second, our work culture is unnatural and unhealthy. For most of human history, work was governed by natural rhythms of effort and recovery. Hunter-gatherers had to work hard to survive, but they also got plenty of rest throughout the day. Before electricity, work ended when the sun set. Even medieval peasants likely got more days off than we do.

Third, social trends have robbed our work of much of the meaning it once had. Few premodern people had “dream” jobs, but they didn’t have “bullshit” jobs either. Work, even hard labor, fit into an understanding of the world that meant it could fill psychological needs. Divorced from that understanding, we oscillate between an unhealthy obsession with work and escape fantasies of perfect dream jobs or early retirement.

These three forces mean that, despite lives of material abundance and apparent ease, many of us feel exhausted and apathetic.

Energy Management is Key to Productivity and Well-Being

The forces that leave us exhausted and drained are much larger than we are. And nostalgia for a simpler time is a daydream, not a solution.

Even so, we can cultivate practices that restore the prior, more humane, ways to manage our energy.

In the face of a world designed to drain our biological sources of energy, we can create new fuel. We can cultivate deliberate practices of sleep, exercise, consumption and stress-management to restore our full capacity to live with energy and vigor.

In the face of unrelenting pressure to work more, longer and harder, we can design a new flow. We can craft rhythms of work and recovery that allow us to avoid exhaustion—while actually getting more done.

In the face of unsatisfying jobs divorced from meaning, we can create work that allows us to flourish. Neither a burden nor an obsession, we can choose work with greater meaning, and we can also cultivate an attitude that enriches the work we have already chosen.

These are not easy aims, and the overall cultural trends certainly do not help. But these aims are achievable, provided we take them seriously.

Next week, I’m going to begin working with a cohort of students for my new program, Everyday Energy. If you’re serious about improving the quality your energy in your life, both for work and for well-being, I hope you’ll consider joining us.

The post Lesson One: The Human Energy Crisis appeared first on Scott H Young.



I’m sure most of us can think of at least a few people who fit that description. Maybe it’s a friend who continually makes bad choices in their dating life. Or a person who complains endlessly about their job but seems unable to take even trivial steps to improve it. “If they only did X,” we think, “their problem would go away.”

In almost all of these cases, the problem lies in their beliefs. The person struggling isn’t able to see a solution that’s obvious to everyone else, because their worldview won’t allow them to.

Limiting beliefs are easy to spot in other people; they’re much harder to notice within ourselves.

Today I want to recommend a new book on the science of beliefs, written by my friend Nir Eyal. Beyond Belief explains the fascinating science of how beliefs shape what we perceive, how we feel and the actions we take. It also provides tools for helping us identify our own limiting beliefs—and how to change them.

Nir sent me an advance copy of his new book to read, and I recorded an interview with him about what he learned digging deep into the research:

Belief, Reality and Delusions

Writing about belief is hard to do well.

On the one hand, there’s ample evidence for the power of beliefs to transform what we perceive, feel and do. We’re never just neutrally observing reality. Instead, what we experience is always a combination of the outside world and our beliefs about what that outside world is like.

On the other hand, a lot of self-help has taken the belief-shapes-reality notion too far. There’s a whole genre of delusional, quasi-mystical books that argue that simply believing in something is enough to change reality. These books teach a kind of unsustainable optimism—every time something bad happens, the explanation is that it’s because our beliefs were imperfect. Thus, every failed prediction becomes more evidence we need to double-down on our delusional optimism.

Nir does a good job of avoiding the extremes of both delusional optimism and faux-intellectual pessimism in his coverage. In reviewing the science on the placebo effect, for instance, he points out a great study which found that placebo inhalers for asthmatics had a similar effect on relieving symptoms as real ones, but, critically, the placebo didn’t actually change lung capacity.

There’s a sort of meta-question here that seems important: what actually can be changed by our beliefs, and what are the stubborn truths about reality that don’t change based on how we think.

Belief and Energy

Nir’s book release comes as I have been researching and writing on energy management, spurring me to think about how our topics overlap.

Fatigue and energy levels are exactly the kind of domain where our beliefs can have a big impact. Indeed, one of the early critiques of ego depletion research was that depletion can be moderated substantially by mindset. If we believe working hard “depletes” or “energizes” us, that belief itself can make a big difference in our persistence.

More deeply, the story we tell ourselves about what we’re doing and why we’re doing it can have a big impact on our energy levels.

A major finding in research on fatigue is that intrinsic motivation plays an enormous role in moderating the tiring effect of mental effort. It’s why doing sudoku puzzles can be a relaxing activity on a Sunday morning, but we might find the same task straining if it was a work assignment.

Intrinsic motivation is all about beliefs. The best theory of intrinsic motivation is that we feel intrinsically motivated to pursue activities that allow us to satisfy our basic psychological needs of autonomy, competence and connectedness. But those, in turn, depend critically on our other beliefs about whether our job is a burden or a calling, if we feel skillful or inept, and whether the work is meaningful or useless.

Further Questions on Beliefs

One sign of a good book is that it leaves you thinking about its ideas long after you’ve finished. Some of my lingering questions after finishing this book include:

• How much of having “better” beliefs is a shift towards greater accuracy versus useful self-deception?
• Are explicitly articulated beliefs and unconscious expectations governed by the same mechanisms? Are there some beliefs that we can change simply by introspection, while others require direct experience to shift?
• Is it better to shift beliefs by affirming the desired belief, or by increasing doubt on the limiting one? In other words, is the action of belief change more like increasing confidence or increasing skepticism?
• How should we reconcile the “beliefs as tools” notion with the idea of degrees of belief, as espoused by Bayesian models of rationality?
• If limiting beliefs are easier to spot in others than ourselves, how do we see past the self-fulfilling logic of our own worldview? What techniques and practices should we cultivate to help spot when our own beliefs need adjustment?

I encourage everyone to check out Nir’s book. I found it a compelling read that pushed me to rethink some of my own beliefs.

The post Book Recommendation: Beyond Belief appeared first on Scott H Young.

“Work expands so as to fill the time available for its completion.”

This “law” was proposed by the British naval historian C. Northcote Parkinson in a satirical 1955 essay for The Economist. Taken literally, it’s obviously false. Simply setting a deadline doesn’t make a goal achievable on an arbitrary timeframe.

There’s a heap of academic literature making the opposite case. The planning fallacy describes the well-documented tendency for complex projects to have cost overruns and delays. Indeed, the truth is perhaps closer to Hofstadter’s Law, where the author Douglas Hofstadter argued tongue-in-cheek that, “It always takes longer than you expect, even when you take into account Hofstadter’s Law.”

Despite its definitively un-lawlike empirical status, Parkinson’s Law does capture an essential human truth: when we loosen time constraints, the time needed to do something somehow expands to fill at least some of the gap.

Energy, Pacing and the Limits of Human Endurance

I was thinking about Parkinson’s Law as I was reading Endure, Alex Hutchinson’s excellent book examining the limits of human persistence and some of the scientific controversy as to the exact nature of those limits.

Hutchinson, an impressive endurance athlete himself, retells a story of trying to beat his personal best time in the 1500m race in his days in track and field. He notes that despite giving every bit of effort he could muster, his pace would always speed up right at the end. He even tried to “trick” himself into running flat out, but consistently found the same dip in speed in the middle of his races.

If we assume that endurance is limited primarily by the body’s internal resources—muscle glycogen, oxygen uptake, ATP and whatnot—this makes no sense. If we’re giving it absolutely everything we’ve got, how is it possible that we can speed up as the race reaches its final stretch?

Hutchinson wasn’t alone in his peculiarity, however. It turns out that world-record runs show the same pattern of a dip in pace followed by a slight acceleration toward the end of the race. Even the most well-trained, disciplined and motivated runners must be holding something back.

Phenomena like this suggest to some academics that the true limits on endurance are not physical, but in the brain. Runners like Hutchinson don’t top out because they reach their true physical limits, but because the brain throttles performance so they never risk reaching those limits. This gives a comfortable margin to prevent bodily damage, and it anticipates future requirements for performance, holding back some when the race is still far from over.

The Connection Between Physical Fatigue and Mental Energy

The presence of a “central governor” that throttles athletic performance makes evolutionary sense. If we run so hard we tear our muscles, break blood vessels or starve our brain of oxygen, it doesn’t matter that we just set a personal best.

But do the same rules work for mental fatigue? After all, nobody’s brain starves of oxygen because they stop procrastinating.

The links between mental and physical fatigue are interesting. Participants who perform difficult mental tasks and then do an endurance test on an exercise bike give up earlier than those who haven’t done hard mental tasks. Mental performance is generally enhanced by exercise, but our performance typically suffers when we try to do cognitive tasks while exercising.

Some scholars even argue that physical and mental fatigue are the same thing. That, while there are certainly different facets to the phenomenon (e.g., being sleepy, muscle weakness, etc.), there is a general component of fatigue that seems to encompass both physical and mental work.

It’s not yet clear what the function of mental fatigue is. It’s possible that, like physical fatigue, mental fatigue is tracking some underlying biological state: energy availability, local sleep debt or stress hormones.


Another possibility is that fatigue in general, and mental fatigue specifically, is really about protecting us from investing in undesirable goals. When we work too long at an activity that lacks intrinsic value and is not immediately satisfying, fatigue begins to build. Perhaps fatigue is a more general emotion that creates pressure to change activities—protecting our bodies from physical overexertion in athletics and our limited attention from being absorbed by tasks that seem uninteresting or futile.

In either case, the effect of mental fatigue is similar to physical fatigue: throttle performance to prevent overexertion, both in the moment and anticipating future demands.

Getting More Done by Working Less

I bring all of this up because a key idea in energy management is working within natural rhythms of effort and rest. Work non-stop and we’ll exhaust ourselves. But if we can adopt periods of intense focus with complete recovery, paradoxically, we can get more done in less time with less exhaustion.

I’m certainly not the first to point this out, and the idea that we somehow get more done when we restrict our working hours within natural rhythms is a long-standing finding in productivity literature. From the earliest days when H. M. Vernon found that reducing workloads from then-common 70 to 80 hour workweeks did not result in reduced work output, to modern incarnations like Cal Newport’s fixed-schedule productivity, the paradoxical finding that we’re more productive when we force ourselves to work less has long been a self-help staple.

These ideas on fatigue add an interesting twist to the explanations. If the effort we put into tasks is not simply a measure of our underlying mental capacity, rather a subtle “pacing” strategy our brain is implementing to get through the work, it explains why punishing, non-stop schedules so often lower productivity.

Anticipating that we’ll be unable to rest, we unconsciously reduce our willingness to put in effort. This can mean sticking to the task but putting in less effort and accepting reduced performance. Alternatively, it can mean procrastinating, slacking off or engaging in trivial aspects of the work that are lower effort and less important.

As a result, the time needed to finish the work to a given standard expands, and we get an effect akin to what Parkinson described in his 1955 essay.

What Does it Mean to Manage Energy?

This, I think, gets at the heart of what it means to manage energy. It’s not simply about finding “balance” or making trade-offs between self-care and time for work. Instead, it’s reflecting the fundamental reality that we work best when we have healthy rhythms of work and recovery.

Too often, our culture pits extremes against each other. You’re either an ambitious striver committed to the hustle, or you’re a delicate orchid that must be sheltered from excess stress. Then, predictably, people line up to denounce one side and support the other.

I think what the research I’ve been covering shows, convincingly, is that this is a false dichotomy. Meaningful work, natural rhythms of work and rest, and healthy lifestyle habits like nurturing good sleep, diet and exercise: these practices for managing energy aren’t just key to working hard, but to living well.

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