Personality Basins

Personality basins are the mental model that I use to reason about humans within their environment. They are an elucidating way to think about many concepts: from modelling why people are they way they are, how they change over time, how mental illnesses and addiction function along with how we should look for their cures, and how the attention economy optimizes itself to consume all of your free time.

What is personality?

Your personality is formed by a process conceptually similar to RLHF. You are first born with a set of traits in a given environment. After this, you perform many interactions with your environment. If an interaction goes well, you’re likely to do it more often, and if it goes poorly, you’ll probably do less of it.

See the learning agent? That’s You!
If your interaction with this post goes well, you’re likely to read more of them later.

If you were born tall and with a commanding voice you might find that you get what you want by confidently demanding it, and this will help to result in a confident personality. If you attempt this strategy as someone born small with a soft voice, it will probably have weaker results and encourage you to try something else out instead. Obviously some traits are more genetic, and thus inherent, than others, but that is not the scope of this post as even highly-heritable traits will result in a large distribution of outcomes.

Periods of high social and environmental entropy during adolescence are the most formative because you will learn the most information about which actions perform well in your environment and which don’t (of course, our meta-learning algorithm knows this, and this is why you have higher neuroplasticity and thus a higher learning rate and more energy during this period. It’s time to learn how to succeed in your newfound environment!)

Your personality basin

As you go about your life, you will continue to modify your personality in response to your environment, and eventually you will end up in something that resembles a basin. Maybe you were born tall and attractive and then this led you to engage in a lot of athletic activities and socialization, and at the end of all of the positive feedback you have ended up with a jock personality that goes on to become a professional football player.

This is a landscape of personalities. The black line is your personality over time, and the last point is the person you currently are. Just like in machine learning, the way that you’ve progressed as a person has been by trying out many things and then doing more of the things that worked well.

If instead you grew up scrawny yet intelligent you might have found things go well for you when you adopt a more quiet persona and focus on solving technical problems in programming or mathematics, perhaps eventually leading to a career as a software engineer or academic. Just like training a model in machine learning, the general gist is that you will try out a lot of things and then do more of the things that went well.

The above image is of a loss landscape in machine learning. Since we are discussing personality, all of the points on the landscape represent different personalities you could have, with the lower points being personalities which are more successful. The personality basin that you find yourself in solidifies over time as you find out who you are and choose your friend group, career path, social and aesthetic preferences, and more.

Most personality changes are unconscious

Most of your movement within personality-space happens outside of your conscious awareness. Although there are many times in life you’ll consciously decide to act in a certain way, this is the exception, not the norm. Your brain is always making millions of gradient updates a day based on what is and isn’t going well and often the most you can do is try to be as observant as possible. This is why techniques like nonviolent communication, dialectical behavior therapy, and mindfulness have observation and introspection as a core facet, because it’s something that you have to consciously practice to become good at rather than something you’re born with.

Most addictive behaviors start without us noticing what is happening until we are sufficiently addicted such that the habit is hard to break. Relatedly, if you introspect on many seemingly-innate preferences you will often notice some of the environmental and social gradients that have helped shape them. An interesting thought experiment you can perform on yourself is to pick a random personality trait that you have and try to answer the questions “why am I like this? could I imagine a version of myself that is not like this, and if so, what happened differently to them?”

Many people think their music and fashion preferences are innate to them and are solely based off of how the music sounds and how the outfits look. But if their most hated political party (or often in the case of adolescents, their parents) adopted the same aesthetic preferences, you can imagine they might start to literally like them less!

Your conscious experience of a stimuli is not dictated by a single-variable function f(stimuli), but rather f(stimuli, personality, environment), at least for broad definitions of ‘personality’ and ‘environment’. If you have a favorite song that your friend thinks sounds terrible, this is because they are literally experiencing it differently from you due to the latter two variables given to this function. They don’t think the thing that you hear sounds terrible, they think the thing that they hear sounds terrible, and it is probably very dissimilar from what you hear. For more information on this line of thought I’d suggest reading about signaling theory and checking out The Elephant in the Brain by Robin Hanson and Kevin Simler.

How do you know if you’re in the right basin?

If you’re reading this you probably have a vague idea of what type of personality basin you’re currently in which you can recall by asking yourself the question “What type of person am I?” But an important question remains: how can you find out if this is the right basin to be in?

A simple answer would be that you could try out other basins to see how they feel. Maybe you’re having a great life as a devops programmer, but you could try to become an artist or a woodworker or a stay-at home parent and see how that fares for you.

The reason why this is hard is that the optimal personality for this basin is not immediately accessible to you – to truly test optimality you will need to go through a full RLHF process. If you want to know how good of a life you’d have as a professional pianist, you will have to practice the instrument for a decade to find out.

You may wonder if you could simply try your hand at the piano for a month or two and see how it goes, and of course you can do this too. Your time (and your meta-learning algorithm’s number of epochs and learning rate) is limited, and it’s reasonable to make the trade-off of sacrificing depth-first search in favor of more breadth-first search.

As you progress in life, you will usually perform less exploration for new personalities and more exploiting with your developed personality

Usually this breadth-first search of trying out many different and creative strategies for life (prioritizing exploration over exploitation) automatically happens during your adolescence, but one of the magic things about the modern world is that there are so many societies, cultures, countries, and fields of work one can move into, and for each different environment could exist a slightly-different-you which finds their own distinct personality that maximizes success. Had you been born as a hunter gatherer or within the roman empire or in ancient china, you’d probably have ended up quite different as a person. Similarly, if you decide to move countries or communities or careers, the optimal-you-for-your-environment will change a lot too.

Personality-space is adversarial

One interesting thing to note about personality-space is that it is adversarial. Rather than a static training set to iterate through, your training data consists of other RL agents, many of which are other people, and all of whom want different things from you.

This is what leads to the concept of Personality Capture. Personality capture is when your environment RLHFs you into becoming a personality that benefits other agents rather than yourself.

If a school bully threatens to hurt you unless you do their homework for them, they are attempting to modify your RLHF process so that it results in an agent which is beneficial to them, hopefully resulting in someone who will always give in to their demands.

Those familiar with high school psychology will find high similarity with this concept and that of classical and operant conditioning as well as concept of a Skinner box. The attempted addition to these concepts here is that of modelling the personality as a reinforcement learning process and changes in personality as gradient updates, which then allow us to view personality-space as a high-dimensional area which will give us some interesting tools to think with. As the saying goes, all models are wrong, but some are useful.

Luckily for humans there exist many symbiotic equilibria where multiple parties can find mutually-beneficial feedback loops within the epochs of personality-space. A mother loves her child because it provides her with the reward of feeling good which encourages further love. In response the child gets food, shelter, and care, which further encourages them to continue the relationship.

Personality Capture

It’s easy to become susceptible to various forms of personality capture when your environment changes. When asked why he isn’t on Twitter, Dario Amodei, CEO of Anthropic, responds to Dwarkesh Patel with:

I’ve just seen cases with a number of people I’ve worked with, where attaching your incentives very strongly to the approval or cheering of a crowd can destroy your mind, and in some cases, it can destroy your soul.

I’ve deliberately tried to be a little bit low profile because I want to defend my ability to think about things intellectually in a way that’s different from other people and isn’t tinged by the approval of other people.

Illustration of a monkey being personality captured by excessive twitter usage

Most people around you want to personality-capture you in some way. Your boss might want you to work harder, your children might want you to give them more attention, and political parties want you to vote for them.

One interesting way to frame personality capture is by combining it with the concept of attention economics. All of the apps on your phone want to turn you into the type of person that uses them all day because that is beneficial for their revenue models. In many cases this is mutually beneficial, but it’s nonetheless clear that the cat and mouse game is starting to favor the felines more and more over the last two decades as they have learned to perfect the craft of user acquisition, the art of user retention, and the science of ARPU maximization.

As I discussed in where are the builders, the game becomes particularly skewed when there is a large difference in ability or judgement between counterparties, with one common example being children and adolescents. It’s easy to become personality-captured by minecraft or roblox at the age of 10 – the game is not only fun and addictive, but a child also has little understanding of the level of optimization their counterparty has put in to making sure that they remain a user for life.

How do I leave my personality basin?

Perhaps you have decided that you don’t like your personality basin. Maybe it used to be working out for you but no longer is, or maybe you’ve always been unhappy with it. Or maybe you just have reason to believe you’re trapped in a local maxima which is far inferior to the global one. What should you do?

The first thing you’ll want to do is to change your environment. If both you and your environment are a constant, you shouldn’t expect to end up in a different basin any time soon. For every new environment exists a new optimal-you, and the world offers many environments to choose from.

The second thing you’ll want to do is increase your learning rate. There are a lot of ways to do this. One interesting note is that your learning rate will automatically increase if your environment changes. This may be why so many people find they are able to be more thoughtful and creative while going on long walks in nature rather than sitting in a cubicle.

This is also a reason why it’s good to constantly be trying new things, because new things will likely involve new environments and new people. If you wonder why trying new things is hard, it is likely because this trait was more maladaptive in our ancestral environment than it is today, as we had less control over our surroundings in the past (If anything, we may have too many options in some cases of the present: our society is so large that defection from a group is less costly as you can simply find a new group to join afterwards. This seems to create challenging game-theoretic equilibria in match-making where commitment to a partner is devalued due to the ease of finding alternatives, the effects of which can be seen by how discontent much of the population is with dating apps).

Although you have a general learning rate curve for how quickly your personality adapts to a new environments, different stimuli will also be paired with differing gradient magnitudes. High-magnitude experiences which result in strong gradient updates can move you within personality space much more quickly.

Humans have many sets of learning rate curves which govern different parts of their brain. In addition to the baseline learning curve, our learning curves are heavily modified by our environment.

If someone uses a psychadelic drug which explicitly gives them high-magnitude gradients they will probably move a lot more in personality space than if they had stayed sober. Similarly if someone undergoes a highly traumatic event, it may push them a long distance within personality space as they quickly adapt to ensure that they don’t have to go through the same experience again. Both of these activities involve large gradient updates.

Common activities which seem to give the largest gradient updates to humans are meditation, drug usage, trauma, religious events, love, gambling, and sex.

Some of these concepts are more negatively-coded than others, for example trauma. But the intended purpose of trauma is obvious, which is to avoid really bad things from happening to you in the future. One of the reasons why overcoming trauma isn’t as hard-coded into us as strongly as we might hope for is because our present society is so much larger than that which we evolved in such that there’s more opportunity to change your environment as to remove the potential source of trauma. Trauma was likely more adaptive in our ancestral environment than it was today due to an inability to drastically change your surroundings and social group in the past.

This is why strong psychedelic drugs like ayahuasca can be dangerous: whatever happens to you during your experience will be fed to you via high-magnitude gradients. Because users may experience hallucinations and delusional thinking during usage of such drugs, it’s possible for their location in personality-space to be thrown far out-of-distribution and into an area which has little overlap with the rest of humanity.

This isn’t to say there can’t be high-magnitude positive outcomes as well, but just that there is a high potential for variance when large gradients are involved. Romantic love can be a similarly dangerous force and has pushed thousands to suicide, yet our society near-universally regards it as a good thing! While there are many other reasons for this, high-variance is not inherently bad and is likely necessary at the societal level in order to promote long-term antifragility (this is also the very reason I am so bullish on America).

Personality basins and mental illness

Personality basins are an interesting way to model many mental illnesses. Similar to attractor states or trapped priors, they allow us to have a simple model with which we can plan to manipulate in order to solve our problems. Just as your personality basin decides how introverted you are, how funny you are, and what type of music you enjoy, it also helps to curate which psychiatric conditions affect you.

One of the reasons why curing depression is so hard is because you need a very large gradient update to escape the basin you’re trapped in. This gradient update could come all at once via an excessively strong positive stimuli, for example a drug which explicitly increases your learning rate like ketamine. But this is often hard to reliably induce, and so the gradient updates instead usually have to be small and continual over a long period of time.

This is what most cognitive behavioral therapy techniques are: we find a simple way to make a small positive gradient update to push you ever-so-slightly out of the personality basin you’re trapped in, and then we keep doing it for months or years until we finally push you all the way out of the undesirable basin.

This is also a nice way to model something like drug addictions: drugs personality-capture you into a basin which feeds off of and depends on them, and this basin can become arbitrarily deep due to the high magnitude of gradients drugs can apply to you (and thus be very hard to escape from). The concept of relapsing on a drug is equivalent to falling back down to the bottom of the basin, and the concept of tapering off dosage over time is equivalent to providing small and continual gradient updates over time.

I have a lot of hot takes that society is collectively becoming so efficient at some forms of personality capture that we will end up inducing various psychiatric conditions in the majority of our population. Societies end up with their own hyperdimensional personality basins just as people do, and just like us, the two ways they can move out of their basin are either gradually via many slow updates (e.g. the industrial revolution), or all at once via a very strong update (e.g. the french revolution). It’s worth thinking about the effects that different types of memetic information may have on our society’s collective personality basins as we become more and more efficient at communication.

Can’t I be in multiple personality basins?

One thing you may notice from the above sections is that your personality appears much more malleable and dynamic than one described by a static point: you probably act differently around your family than you do around your friends or your co-workers.

To solve this discrepancy you can simply model personality space and your personality basin with additional dimensions, allowing you to model yourself not as a 1d point, but as a three-dimensional landscape.

I model my own personality basin with an extra dimension (i.e., 4d): at any given point in time there exists a “me” which implements a given personality landscape in a given personality basin, but I also have many sub-basins which implement my different moods. The set of actions I might perform when I’m angry is very different from that when I’m sad, and these are simply different sub-basins within the containing higher-dimensional basin. You could similarly increment the model’s dimensionality in order to model yourself using internal family systems or even dissociative identity disorder.

Further reading

This post was heavily inspired by other posts including Trapped Priors, Dynamical Systems, and Singing The Blues by Scott Alexander and Personality: The Body in Society by Kevin Simler.

I’d strongly suggest reading The Others Within Us, The Arctic Hysterias, Crazy Like Us, and Neurons Gone Wild as an addendum to this post. Other related topics to explore include signal theory, control theory, set point theory, game theory, reinforcement learning, and deep learning.

Although the concepts presented in this post are similar to pre-existing concepts, I find that applying the analogy of loss landscapes, basins, and basic RL and DL concepts to be useful tools for thought and encourage readers to do further exploration with this mental model in case they find other useful analogies (what might a linear transformation on the loss landscape of personality-space look like and compare to? how can we develop a more comprehensive model of learning rate in humans and how would we modify it? are there any mental illnesses we can use this model with to try to come up with novel types of cures? how can we integrate this with bayesian theories of learning and perception? which other ideas in LLMs, RL or ML might we find useful to further analogize with?)

The explicit goal of this post is to help RLHF you into a personality basin which more easily allows for both thoughtful analogies and practical tools for thought. If you liked this post consider checking out my home page or twitter. Feedback is welcome!

Where are the builders?

What are the brightest and most ambitious minds of our generation currently working on?

  • Here is a video from someone who spent 7 months building minecraft inside of minecraft by painstakingly constructing a redstone computer inside of it with its own graphics card and screen
  • Here is someone who spent 5 years constructing a 3D game within a 2D geometry game by building primitives and constructing 3D illusions from them
  • Here is a video from someone who spent 6 months building a factory inside factorio which recursively self-expands using a lua script
  • And here is someone who spent 4 months building a shader to let the linux kernel run inside of VRchat via writing a RISC-V CPU/SoC emulator in an HLSL pixel shader

I find the above examples fascinating from the meta perspective: while there’s nothing wrong with having fun building inside of games, these are the very same skillsets which tech companies would pay six figures to have on their side! (of course they may enjoy the games more – this is discussed later)

Sometimes people of this caliber even have trouble finding a job – they often don’t really know where to go besides apply online to boomer companies who reject them when they see a lack of credentials. They love building things and are very smart and hardworking, but their milieu is an environment which captured them from a young age (often a video game or social media) and sometimes also ensured that the value they produce is within a pre-existing platform (e.g. a video game).

“Why did you cherry-pick people playing video games instead of talking about, like, everyone currently enrolled in medical school or something?”

The US currently has 125,000 students enrolled in medical school (this seems low to me but I checked several sources). Minecraft has 140,000,000 (1120x) monthly active users. Roblox has 200,000,000 (1600x). This is obviously an unequal comparison, but the magnitude of the difference is still staggering.

Why are you building a graphics card inside minecraft instead of inside nvidia?

There’s several reasons why someone might build a graphics card inside of minecraft rather than being paid $300,000 a year to build one inside of nvidia:

  1. Minecraft is more enjoyable
  2. Minecraft is more addictive
  3. Minecraft found them first
  4. They don’t know the latter option exists, or how they would do it, or think they’d fail at it

The first reason (that minecraft is more enjoyable than working for nvidia) applies to most people who are playing games instead of working, and instead the latter three reasons will be the focus of the following sections.

Addiction & Adolescence

The world has a lot of addicting products. Most of them I’m able to avoid, but some of them just happen to hit my sweet spot: I had no problem avoiding smoking growing up, but world of warcraft consumed years of my adolescence.

Others don’t find world of warcraft addictive, instead procuring their poison elsewhere. Maybe it’s minecraft, or league of legends, or youtube shorts.

One of the reasons these apps out-compete the ‘real world’ is because they start competing for our attention at a very young age. Most kids will grow up inside of roblox, minecraft, discord, instagram, and tiktok. If a kid starts using their smartphone at 10, these platforms will have a full 8 years to solidify within their mind and modify their values and social network before they are even legally allowed to have a job. I refer to this concept as personality capture and have a post on personality capture and personality basins here.

Some comparisons to past historical figures:

I would have killed for a tech internship when I was 14. I had no idea how I could do that, so I studied independently for my CCNA instead and would hop straight into video games when I got home. In hindsight it’s really interesting thinking about past-me playing these games, because I was young and knew so little about the world, yet my counterparty was hundreds or thousands of well-educated adults optimizing for my addiction and spend. It certainly wasn’t a fair battle!

Products induce strong preference modification

When I was 12, the highest-status person in the world to me was zezima. For the ~85% of readers who don’t recognize this name, he was the highest ranked player in runescape and had an aura of infamy that I can only compare to someone like elon musk. What I wanted most in life at this age was a party hat, which was an immensely valuable item in the game which most players could never afford even after years of play.

Many of our values are locally-set by our environment and peers, and when we immerse ourselves into a different world, our preferences change alongside it. This is pretty obvious – the twitter addict is constantly thinking about how many followers and likes they get just as the league of legends player is ever-ruminating over their rank and win ratio.

This is a fully general force too – If my friends and I only had a forest to play in growing up, we’d probably have invented some status game of who can climb the highest tree and would eventually have our own local culture, lexicon, and so on. But the forest is actually much easier to escape from than video games and social media – literally speaking.

I tried to find some user retention numbers for world of warcraft which I was heavily addicted to as a teenager and found a monthly churn of ~5%. In other words, the typical world of warcraft subscriber played the game for over a full year. I wonder if they knew when they clicked the sign up button that, statistically speaking, they would spend hundreds of dollars and over a year of their life playing? I certainly didn’t when I clicked the button at 13. It’s worth noting that the linked paper is a decade old and points to a time when we used spreadsheets to optimize addictiveness rather than machine learning.

That your preferences are locally induced is why the simple heuristic that you become the average of your five closest friends is so useful. If you get to choose your friends, you also get to choose many of your preferences and goals. Although I had the freedom to choose my friends at the time, quitting a game I loved was hard because unless my friends quit too, I’d have to go find new friends. Before this statement appears obviously fallacious to many readers, I need to add the necessary context that most people I knew in MMOs would also play them for ~100% of their free time, easily reacing 8-16 hours a day (yes, there’s a strong selection effect here). Although I had a ton of fun in my years inside these games, I always wondered what I’d have ended up doing if they hadn’t existed.

Agency in the free market

I’m writing this blog post at 1AM right now. In order to do so I’ve had to block twitter, close messenger, and set my phone to night mode. Luckily I’m not battling any video game or youtube shorts addictions, or this post wouldn’t exist. I don’t think I’d be able to sit down and write for hours if I had spent my entire adolescence on tiktok.

As consumer markets become more efficient and we become more skilled at capturing and retaining the attention of the populace, we should expect the average agency of society to decrease.

This is obvious if you think about it for a bit (the goal of almost every app on your phone is to get you to do less of anything which pattern matches ‘not using their app’), but there are few who appreciate the magnitude of this effect as the masses of society engrossed in video games and social media at home alone in their bedrooms every night are well-hidden from us. You can walk to the park to see 50 people enjoying the outdoors, but the millions currently scrolling tiktok at home are hidden from you in every way except via a statistic.

I love how easy generative AI makes it to learn – I sometimes talk to Claude until I’m exhausted and have to sleep. But in the free market, Claude doesn’t stand a chance against Tiktok. This post isn’t about Tiktok either though, as Tiktok doesn’t stand a chance against SuperTiktok (soon).

Outlier Success

Many have wondered why there’s fewer entrepreneurs in their 20s on a path to outlier success than there were in previous decades. Facebook IPO’d at a valuation of $104 billion when Mark was 28. Stripe reached a valuation of $35 billion when John was 29. Snapchat IPO’d at $24 billion when Evan was 25. These are outlier examples, but that’s the entire point. Where are the current outlier examples from the next generation?

I offer several potential answers:

  1. They are currently busy playing video games (which likely become more important to them at a very young age)
  2. They watched so much tiktok as a adolescent that they no longer have the attention span to build things (that would involve not using tiktok)
  3. They have so little free time due to attention economics that they no longer have original ideas (time spent doing ‘nothing’ is very valuable for quality long-term life outcomes)

Many in the tech ecosystem call me a doomer when I suggest these explanations – they certainly aren’t addicted to video games, and their friends certainly don’t have reduced attention spans from tiktok. But they live in a bubble within a bubble (context: I work in AI in San Francisco), and from my point of view the data points to these hypotheses as strong contenders. Sometimes I talk about this with normal people and they think the above is so obvious that it doesn’t even interest them. Perhaps our future has always been that of bread and circuses?

To clarify – I don’t intend to say that consumption or video games are bad; I love both of them myself! But we may be getting too good at consumer app optimization, and when that is paired with adoption at a young enough age, the outcome is undesirable. Building minecraft inside of minecraft is cool, but when I see a toddler scrolling youtube shorts on an ipad alone I feel really bad.

As the agency of the average consumer decreases, the ceiling for the agency of outliers increases. Examples of inventions which drastically increased the ceiling of agency include venture capital, generative AI, programming, microchips, and trade and capitalism itself. Once AI agents start to actually work it seems like this will be another large driving force here. Many have wondered when the first one-person billion-dollar company will exist, and many predict it may be within just one or two decades. It will be an interesting time to be alive in, if nothing else.

If you enjoyed this post, you may also enjoy: Types Of Memetic Information and my Home Page.

Types of Memetic Information

Three types of memetic information:

  • memetic-invariant information remains constant in value if more people learn it
  • memetic-cooperative information becomes more valuable if more people learn it
  • memetic-competitive information becomes less valuable if more people learn it

Memetic-invariant

Most simple facts are memetic-invariant. That the sky is blue or that water takes the shape of its container continue to be true and have similar value no matter how many people learn it.

Memetic-cooperative

Sometimes we are lucky enough to discover memetic-cooperative information, which becomes more valuable the more people learn it. Most of our society is built upon the fact that memetic-cooperative information exists, is easily socially transmissible, and can lead to stable equilibria built upon common knowledge.

The rule of law has value because of the social consensus that it will be enforced. When a crime is committed, it is often because someone thinks they will get away with it. If everyone stops believing that the rule of law will be enforced, anarchy may break out, and society may cease to exist.

Similarly, centralized fiat currencies are able to be used at scale and over long periods due to the mutual information between market participants that the currency has value. It is in both of our interests that we believe the dollar has value, as that allows us to easily transact with each other (See also: network effects, common knowledge, social equilibrium, minimum viable superorganism).

The general principles of how to found a company are usually memetic-cooperative: it is good for us if we make it easy to found businesses and create new things, generally speaking.

Memetic-competitive

Much of the most useful information, however, is memetic-competitive: its value decrease the more people that find it. If you have ever thought of an idea that was so good that you were reluctant to share it with anyone, that’s a sign it was memetic-competitive.

An obvious example of a memetic-competitive idea is a market undervaluing an asset. If you have an easy way of making money by finding under-priced assets, this will stop working if you share it with enough people, as eventually the inefficiency will be fully exploited. You have a true idea that may literally cease to be true if you share it with enough people.

Those knowledgeable of the basics of game theory may find that some (but not all) cases of memetic-competitive ideas map onto defection. I could discover that if I cut to the front of the line, no one will stop me, and I can selfishly save myself time. If everyone implements this strategy, the entire queuing system will break. But even if they don’t, I am taking time away from them in order to give it to myself. Systems usually solve defection like this by making games iterated: if everyone in my town knows I’m the type of person to cut in line, the reputational hit may harm me enough to serve as deterrence (See also: iterated prisoner’s dilemma, free-rider problem, the virtue of silence).

Memetic-competitive information is a subset of anti-memetic information (information which ‘does not want’ to be shared). Another example of anti-memetic information is information which has little or negative value to a majority of agents in an ecosystem (if I posted a long random string on social media, it would probably not be picked up by any meme-promulgating algorithms and is thus anti-memetic).

Execution specifics of recently successful go-to-market strategies for consumer startups are often memetic-competitive. While it’s common to share generally good sales and advertising advice, it is uncommon for the specific tactics that startups tediously searched for and executed upon to be fully divulged to potential competitors (See also: things I wish more founders would understand about b2c marketing).

Social Media

Most social media (and the broader information economy) exists to propagate memetic information. As memetic-competitive information is anti-memetic (no one wants to spread it, lest it loses value), it follows that it is not something which will be easy to find on social media (See also: alpha used both in its original financial context, but also in non-financial contexts of finding strategies which give you an edge over competitors).

For an uncommon enough individual, it may be challenging to find the most useful information, because you first have to find a community of other individuals that value the same thing. Furthermore, if the information you are after is memetic-competitive, this can only exist in small communities, so you will have to hunt them out. Unfortunately it follows that it will be hard to hunt them out, because if the community has no barriers to entry and lets anyone join, then all the memetic-competitive information they share will quickly lose its value and the community will cease to exist. Luckily not all information is of the memetic-competitive type, although there’s still many other dynamics of virality to consider (See also: geeks, mops, and sociopaths in subculture evolution on the dynamics of community change over time as new actors with different incentives join, the melancholy of subculture society on internet subculture, and border stories: why is it that every unit of life from the cell to the immune system to the country to the planet all seem to have borders).

Further Complexity

Some information can move between different memetic information categories depending on its truth value. For example, take the sentence “AI is going to kill us”. If this sentence is true, then it is memetic-cooperative: we want everyone to know about it so that we can work together to stop it. If this sentence is false, however, it could be (partially) memetic-competitive: perhaps I want you to believe AI is dangerous so that I am able to profit from AI while you are not (I don’t think this is currently the case for most actors).

Things get complicated when we introduce the fact that not only do different agents have different values, but the perceived truth value of statements will also differ between agents (and especially) groups. If we anted to we could also construct a model of memetics which is separate from the delta of informational value that propagation of the meme causes, if we wanted to get closer to fully modeling modern information exchange (See basic reproduction number R0, which is in my opinion the best way to model internet memes).

I’m going to stop the post here before this attempted formalism is over-extended, as my primary motivation is only to publicize the three labels I choose for future reference. My hope is that this post is memetic-cooperative!

See also: home page

Blueprint 1.0 Review

I spent $343 for one month of blueprint. this post shares what I got and what my thoughts on it are!

overall I’m a fan of most ingredients and the overall composition. I came up with many of them on my own a few years ago, many of which are listed here. the doses are pretty reasonable and I trust the sourcing to at least be above average

this post is not sponsored or paid for in any way, but I’ve met BJ and think he is reasonably smart and funny. below I include images, nutritional information, and plenty of links and side notes to share what I’ve learned!

Apr 13 2024 edit: Added response comments from Bryan Johnson / Blueprint: ctrl+F “BP” to find them
May 7th 2024 edit: Blueprint now allows for the purchase of individual components. I’ve added a new Market Comparisons section near the bottom as a result

Everything I got for one month at a cost of $343

Nutty pudding

Ingredients for the nutty pudding mix
  • mostly plant protein, giving you 26g of protein per serving
  • allulose as a sweetener is great and I’m happy to see it becoming more common (see my post on allulose for why). may want to note to consumers what it does and why they might notice it
  • cinnamon and grape seed both great inclusions
  • no opinion on pomegranate and monk fruit extract. I’m assuming the latter is as a sweetener and flavor enhancer (BP: pomegranite included to improve metabolic panel markers)
  • the taste is… alright. some people definitely like it more than I do, but I’d probably only rate it a 5/10 myself. I substituted whole milk in instead of nut milk as suggested and added the blueberry mix (below) to it to finish it. it tastes like a rather bland pudding, but a bit more dense and with little sugar or fat (BP: adding EVOO for taste may help)

Blueberry mix

Blueberry mix!
  • it’s literally just dried blueberries, macadamia nuts, and walnuts
  • tastes great no matter what do you with it really. I’d suggest adding it to the above pudding or combining it with some milk
  • blueberries are great for you and a good snack to have around
  • with that said, this mix is so simple that I’m not sure I gain much from having someone else prepare it for me (BP: mix replaces 2kg of berries and helps not having to acquire them frequently)

Longevity mix

Nutrition info for the longevity mix
  • simple mix that you add to water
  • creatine, glucosamine, taurine, glycine, the gang’s all here
  • allulose again chosen as the primary sweetener
  • I’d increase the amount of glycine (1.5g), especially due to this being earlier in the day so it’s unlikely to be too much to disrupt sleep (this dose would be fine before bed and likely benefit sleep but the instructions online suggest to have this mix in the morning). for more information on why I’m in favor of macrodosing glycine check out the glycine section on my supplements page (hint: it extends lifespan in mice!)
  • sodium hyaluronate is an interesting choice and I wonder why they chose it + this form of it (BP: intended to reduce inflammation and restore HA levels which decline with age)
  • i’m a big fan of ashwagandha, with the note that it can cause digestive distress for some. great for lipid profile and often improves anxiety too
  • there could be a bit more creatine (2.5g) for those lifting, especially since calcium alpha-ketoglutarate was added (BP: amount chosen to be tolerable for mass market while covering omnivores average diet intake)
  • the taste is decent and comparable to most ‘vitamin’ drink mixes that you add to water. I’d probably rate it a 6.5/10, nothing to complain about but not particularly exciting

Pills!

The four bottles that I got along with what the pills from each look like. The daily suggested dosage is 3 pills from each of the larger bottles and 1 from each of the smaller, for a daily total of 8. Certainly not as bad as what was featured on my supplements page!

NAC, ginger, curcumin

Nutrition info for the NAC, ginger, and curcumin capsules
  • NAC is reasonably popular in the longevity community and pretty interesting
  • not 100% sure what the reasoning behind ginger was – I wonder if it was due to its ability to ameliorate potential gastrointestinal side effects of other supplements? (BP: intention is to improve metabolic panel, reduce inflammation, improve mood)
  • circumin is generally a good choice, although I have concerns about lower bioavailability here. does one of the other supplements included notably modify this? (BP: curcumin bioavailability 4x higher in this case due to being bio-enhanced)

Essential capsules

Nutrition info for the essential capsules
  • not going to list all the vitamins as they’re all reasonable choices
  • glad to see a higher amount of vitamin D (2,000 IU). could go even higher but the average blueprint consumer probably gets more sunlight than I do
  • I don’t know what the benefits of including e.g. iodine, calcium, manganese, and selenium are. would these be missed at all if excluded? feel free to enlighten me if you’re a reader! (BP: these deficienties are moderately common so worth including, calcium as excipient of CaAKG)
  • lithium is interesting at 1mg but I’m not sure that’s high enough to do very much (although perhaps this is the intention to keep it on the safe side)
  • I didn’t know that the body converts glucoraphanin into sulforaphane via myrosinase. good supplement!
  • fisetin at100mg daily is an interesting choice. curious how they decided daily was the correct increment and 100mg was the correct dose – I found this one hard to decide on myself (BP: dosage most studied wrt fisetin)
  • spermidine 10mg is perhaps one of the most promising supplements here due to directly improving lifespan in mice! how did they source this? see more info in the spermadine section on my supplements page
  • genistein is an interesting choice as it is pretty estrogenic. there are a lot of gender-ambiguous benefits to this, but i’m curious what the specific reasoning was and how the dose of 300mg was decided. it has affinity for α estrogen receptors, but not as much as β. if it was easier to source and include 17α-estradiol, would that have been included instead? was this included for entirely different reasons, of which there could be many? see also: does 17α-estradiol/estrogen extend male human lifespan? (BP: genistein does not increase blood estrogen levels in men, 17α generally requires Rx)

Essential softgel

Nutrition info from the essential softgels
  • nothing particularly exciting here, nice to see the better forms of vitamin k (k1, k2 mk4, k2 mk7) all included
  • astaxanthin is a nice inclusion
  • less excited over lycopene, lutein, and zeaxanthin, but I don’t know anything bad about them. would like to research them more later

Garlic, red yeast rice

Nutrition info for the garlic and red yeast rice pills
  • unsure why these are in their own pill instead of included within one of the larger mixes (from which you take 3 daily from)
    (BP: pills were grouped to reduce amount. water soluable actives went into longevity RTM, fat soluble into softgel, bitter tasting into capsules, and small amounts into essentual. RYR and NAC were separate SKUs due to regulatory concerns.
  • garlic is great if we give them the benefit of the doubt on the 12:1 exact including enough allicin
  • does the red yeast rice (500mg) actually contain a lot of monacolin k? some countries like the US dislike this due to it being bioidentical to e.g. lovastatin (BP: no, this is why CoAs are shared)
  • interesting side note: when you research a lot of natural compounds (roots, vegetable extracts, etc), it’s very interesting how many of them are bioidentical to actual pharmaceuticals. when I was young I didn’t understand why ‘vegetables’ or such should be good for me: adults would tell me they had “vitamins and minerals” in them, but I could obviously both a) test myself for vitamin and mineral deficiencies and b) supplement them if I was deficient in them. it wasn’t until many, many years later that I learned how amazingly complex everything we eat is and how many biologically active ingredients are in dishes. think of a dish with many vegetables, spices, roots, meat, etc, as basically having 20 different drugs in it, but with all of them in very small doses. many of them are also very slightly psychoactive too! just as you can get high on nutmeg and sweet potatoes inhibit α-glucosidase and are thus anti-diabetic like the drug acarbose and red yeast rice is literally the same as a statin medication and berberine found in plants like barberry is a mimetic of the anti-diabetic drug metformin, the foods we eat on a daily basis have an astoundingly large amount of downstream effects in the body which have nothing to do with the vitamins or minerals in them. the cases we tend to know about like marajuana or opium are not rare in that they have strong biological effects, but rather are only rare in the dose response curves that are common with consumption. the present epistemic milieu we reside in with respect to nutrition doesn’t talk about this much primarily because we know so little about the topic and actually learning what is going on enough to have high confidence and rigor is extremely tedious and slow

Olive oil

  • it’s olive oil. it is made from olives
  • the branding of ‘snake oil‘ is honestly pretty funny given how most supplement marketing is basically fraudulent

Marketing

  • no cards or instructions were included in the box. this is missing out on a gigantic free lunch!
  • I’d strongly suggest adding instructions, a thank-you card, and a discount code for future purchases
  • the discount code should be notable as user retention may be more challenging than other monthly supplements due to the tediousness of consumption (8 pills, one drink mix, one pudding mix, olive oil, and another mix, every single day!)
  • given the higher price point it would be great if the bags could be redone to have a high-quality zipper on them as sealing them is annoying
  • the supplement bottles should be shinier. this will increase conversion as this product is offered at a ‘premium’ price point. I’d look into making a bespoke logo for blueprint as well or otherwise refining the font and decor around it. you will be surprised how much of a return you can get by spending $0.10 more on shiny paper and branding!
  • I would move supplements with the highest probability of causing digestive distress into their own pill so that users can modulate dosage or ablate it themselves for e.g. supplements like ashwaganda and curcumin. this should be included in the instructions as otherwise users who feel unwell may simply never try blueprint again
  • current marketing paradigm likely favors a cohort of more males than females and more adolescents than the elderly. this is reasonable and likely the correct choice to make early on, but I’d consider long-term strategies on how to improve this. encouraging gifting to the elderly (e.g. one’s parents) is likely a great idea here for obvious reasons
  • (BP: agreed on much of the above, some are already being implemented)

Research and sourcing

  • most of what is included is good, but I’m not told why it was included! if there was so much money spent on research and reviewing studies, it would be great if some of it could be shared to me as a lowly and uninformed end-user
  • why does the blueprint page advertise ‘non-gmo’, and what does ‘no artificial ingredients’ mean? generally the latter means next to nothing, but I don’t actually care if something as simple to synthesize as e.g. glycine is ‘artificial’ or not as long as it is the right chemical and without contaminants or impurities! modify labels for your intended audience accordingly
  • similarly to sharing research the website states that you “test the ingredients” yourselves. I assume this means more than just eating them and making sure you don’t die, but this seems like a great thing to share more about, especially because this is very tedious to do (BP: manufacturers are asked for CoA and then we test the individual ngredients ourselves)
  • having users share metrics before and after a few months of blueprint consumption would be great (BJ told me isn’t necessary as the individual ingredients already have sufficient evidence on their own. but if you ask me, there is never enough science being done and there is never enough data, so I’d prefer we continue to learn all that we can even if it only confirms our priors) (BP: a few thousand people are on it and sharing biomarkers, we will share this data)
  • relatedly I’m concerned that some of the supplements may inhibit various enzymes that then cause unknown and/or undesired changes of bioavailability in other supplements or drugs. both curcumin and ginger inhibit CYP3A4 and this may be suboptimal if combined with other longevity drugs like rapamycin (which, similarly, could block astaxanthin which blueprint includes as well). this is challenging as we have limited knowledge on this topic for most supplements and drugs, but is worth at least being aware of
  • fortunately i’ve written from-scratch personal tracking software that I can throw all of this data into in order to solve a few of the questions (those which are easily answerable via blood tests at least), but this is costly and tedious and I am tired of getting blood tests. I may try A/B testing all of blueprint RCT-style to see if I can notice any other variables it effects that I wouldn’t have otherwise predicted

Market Comparisons

  • As of May 7th 2024, Blueprint now allows for the purchase of individual items listed above instead of only all of them as a bundle.
  • If you only buy the four pill bottles, the cost comes to $146 for a month ($139 if you subscribe)
  • I did a rough but incomplete analysis of competitors on amazon, building up the ingredients myself from reasonable sources, attempting to find a cheaper alternative to blueprint
  • I failed at this task. In other words, if I try to get everything in the blueprint pills from reasonable alternatives on Amazon, I ended up spending more money, not less
  • Because I think most of the ingredients in the blueprint pill bottles are desirable and I trust their sourcing to be at least average (hopefully above-average), I’ve decided to replace some of my supplement stack with blueprint
  • I am not publishing my full spreadsheet as it could be done with more rigor, but the numbers I got were close to break-even for the essential softgels ($49), notably over for the essential capsules (~$75 to $110 rather than $59), break-even for the nac+ginger+curcumin capsules ($27), and under for the red yeast rice and garlic capsules (which are by far the cheapest at $11 currently)
  • This is impressive for a consumer product!
  • Compared to most mass-marketed supplement products (e.g. athletic greens/AG1, blueprint basically murders them in cold blood and is probably ‘better for you’ by a factor of 5-10x. I have unusually high standards compared to the typical consumer here, but this is worth stating explicitly for those that come across this post but aren’t used to this.

Final thoughts

  • overall this is a decent purchase if you find the price range affordable. It saves you a lot of time, logistics, planning, research, and so on, and a lot of the ingredients are top-notch and actually do things that you won’t otherwise get the effects of from even a good diet. It is certainly better than the rest of what is out there.
  • with that said, there’s secondary effects to note: a) the substitution effect of having something decent rather than what you’d have had instead (this is why most ‘diets’ are always an improvement: the typical American diet is so bad that basically anything that is not insane is likely to be a net-benefit), and b) the psychological effect of causing you to consciously think more about optimizing for your health. I would strongly bet that there is a ‘healthy user bias’ among blueprint users that results in them having e.g. better lipid and glycemic profiles than non-blueprint users even if they stopped taking blueprint as they probably get more exercise than average
  • the largest benefits in longevity may still be things that we cannot easily sell in a bag or bottle, whether that is because it is intangible like exercise, or because of excessive regulation (e.g. the revolutionary weight-loss drug semaglutide requires a prescription and often insurance, although notably can also be purchased online regardless from parties which are not fans of the US patent system. even so, clinical trials for it began 15 years ago which likely resulted in the early death of millions of americans due to obesity. other longevity drugs like rapamycin are also challenging to distribute to the average consumer for similar reasons (and that one is FDA-approved too!). the FDA is excessively conservative in what they allow, with drugs requiring a decade and ~$600M to be later slowly distributed to the general public, and this is before we even bring in talk of gene therapies or anything newer
  • alpha in longevity (both personal and scientific) still remains in copious quantities for those who are willing to search for it!
  • I have currently decided to continue to purchase the pill section of blueprint, but I’m not subscribed to the other components at this time.
  • If you enjoyed this post you might like my website (see also: supplements) or my twitter
  • feedback (especially any potential corrections) is very welcome! DM me on twitter or submit anonymously here

LLMs are strangely-shaped tools

few hit AI apps exist because LLMs are what i’d call very “strangely-shaped” tools.

most tools are built with a specific purpose in mind like a screwdriver or a car.

but LLMs were something we stumbled upon by predicting text and playing with RL – we didn’t design the shape of them beforehand, we just let them naturally evolve into what the loss optimized for.

it’s clear they’re good at many things, but they are so strangely shaped that it’s easy to fall into traps when making products.

AI agents are a good example of a trap (for now), where it’s easy to spend months trying to perfect your scaffolding yet never quite reaching the level of reliability you’d hope for.

long-term memory implemented solely via RAG is another trap. it’s just tempting enough to try, but the results aren’t as good as they should be.

other common inadequacies include poor search, hallucinations, and high inference costs. but there’s a long list of subtle weaknesses which few tinkerers ever notice as well as many weaknesses (and strengths) which remain unfound.

much of the frontier of LLM posttraining is currently concerned with these inadequacies – wondering how we can mold these strangely-shaped LLMs we have grown into a slightly more suitable form for the problems we face.

this is hard, even for the major labs. as we slowly progress on it, i’d expect to continue to see most AI products attempt to solve the same problems via the same methods, further suffering from lack of distinctness both in performance and aesthetic, because they don’t have the right connection between research teams and product teams (or perhaps the right vision to begin with).

it’s telling that among the few recent consumer successes like midjourney or perplexity, competitors are hyper-focused on directly copying winners rather than exploring the vast new frontier of things which could be built instead. this makes sense because the frontier is strangely-shaped, as a result of the underlying catalyst itself being strangely-shaped.

it’s not uncommon for services to launch a feature literally called “AI” which is primarily composed of literal magic wands and glitter emoji simply because the product designer has no idea how to actually convey the intended experience to the user. 2024 is certainly not a year one would be fired for using too much AI.

I expect it to get more interesting later this year and especially in 2025, but it’s still been a surreal experience continually contrasting my day to day life in san francisco with that of the actual real world (note: SF is not real in this example).

the above is also relevant to some of the reasons i have longer agi timelines than i did a few years ago. agi is not a strangely-shaped tool. in fact, it is quite literally the opposite.

Originally posted via Twitter/X, but mirrored here for convenience.

If you liked this post you may be interested in the rest of my website too!

Music

This post has a bunch of unordered youtube videos with music I love
A few themes: strong piano leads, polyrhythms, Japanese influence, OSTs, beautiful singing
Some of them are niche (~1-10K YT views) so hopefully you find something new you like!

Logical Emotion: トライアングルどら息息子


Dimash Qudaibergen: SOS d’un terrien en détresse (Piet Arion Cover)


Polyphia: Playing God


Boa: Duvet [Serial Experiments Lain] (Extended)


Kevin Penkin: Hanezeve Caradhina [Made in Abyss OST] (Takeshi Saitou Cover)


Deemo: Marigold (ふぃくしのん / phyxinon cover)


Nobuo Uematsu [FFXIV OST]: Great Gubal Library (Hard) Theme


Masayoshi Soken [FFXIV Endwalker OST]: Piano Covers by SLSMusic


Tosin Abasi: Thump


Keiichi Okabe [Nier Automata OST]: 壊レタ世界ノ歌 / Weight of the World


Shibayan Records: Fall in The Dark


Xi: Anima


Clowncore: Computers


Animals as Leaders: Behaving Badly


Coprofago: Motion


Gojira: The Art of Dying


狼と香辛料 (Spice and Wolf: 旅の途中 (OP)


Bobby Jarzombek: Selected Drum Solos


Infected Mushroom: Dancing With Kadafi


Ashleigh Bridges (OSRS OST): Coil


ダンベル何キロ持てる?: お願いマッスル (OP)


Meshuggah: New Millennium Cyanide Christ


Keiichi Okabo (NieR Automata OST): 遊園施設 (Amusement Park)


Iconoclasm: perditus†paradisus


Nobuo Uematsu [FFXIV OST]: The Lost City of Amdapor (Hard) Theme


Uneven Structure: Awe


Shiho Fujii, Atsuko Asahi, Ryo Nagamatsu, Yasuaki Iwata [Mario Kart 8 OST]: Dolphin Shoals


UNDEAD CORPORATION: The Revolution


Indricothere: III


Nekomimi Syndrome: Fur War, Pur War


All That Remains: Six


An: Sadistic Confusion


Andy James: Burn it Down


Kevin Penkin (Made in Abyss S2 OST): VOH ft. Takeshi Saito


Free Alpha By Design

Complex systems of life often contain a multitude of shortcuts: sources of alpha which, should you choose to exploit them, give notable advantage. Many classes of these shortcuts are features rather than bugs, and it is no accident of many systems that only a select minority are able to tactfully navigate them.

In many cases there exists zero-sum shortcuts, which, if all of society were to adopt them tomorrow, would have their effectiveness instantly curtailed to zero. Luckily there also exists many which are positive-sum and benefit both parties involved. This post contains a few notes and examples from both classes.

Venture Capital

In venture capital, it is strongly preferred that one receives an introduction to an investor prior to pitching them. This is, in general, a much easier way to meet with many classes of professionals than a cold-email.

At first glance this may appear shallow or nepotistic, but it’s more accurate to view it as one of the first tests to becoming a successful founder. If you’re unable to find any way to get an introduction to a person, it is more likely that you may also have difficulty with other similarly important roles that a founder must perform such as recruiting, sales, management, and further fundraising.

This warm-introduction requirement therefore functions less as “this person happens to know someone”, and more as “this person has the right set of traits in order to acquire this warm introduction, which we consider a modestly bullish investment signal”.

Due to the generality of this phenomenon, this paradigm repeats itself in many categories of society.

Job Hunting

It is much easier to get a job somewhere by messaging someone at that company and asking them to help you out, preferably with some baseline level of evidence that you are at least reasonably competent and aligned with the organization.

This may seem obvious, but at any given moment there are millions of reasonably-intelligent individuals bulk-sending their CVs to hundreds of unsuspecting organizations, when their time may be better spent narrowing their hit list down to only a select few companies, then delegating several hours of their time towards each of them.

You can go much further than this, of course. To give an example: the few times I’ve had an employer other than myself were because I specifically asked to be hired for a role I made up. Rather than seeing an available position on a job posting, I looked at the intersection between the needs of the organization and my own abilities, and proposed that intersection directly to the CEO as my job description. Many find this to be much more agentic than something like “asking the neighbor with overgrown grass if he will pay me $20 to mow it for him”, but the exact same thing is happening in both of these scenarios. Negotiating your salary is in a similar category of actions.

The reason why the above two sections describe intentional shortcuts is because they’re positive-sum. Negative-sum shortcuts are often unintentional (for example, stealing merchandise from a store), and zero-sum shortcuts can be of arbitrary intentionality.

User Support

Many are familiar with the basic techniques of escalating one’s user support channel with a large corporation to an agent which is both more responsive and more capable. Some classes of individuals may formalize this as e.g. “I’d like to speak with your manager”, but there’s often more effective methods depending on your use case. Patrick McKenzie has many good examples among his blog posts, and I’ve included a wonderful excerpt from him on banking and credit reports below.

While the above example is aimed at individuals that have been wronged by large financial institutions, many of the principles apply more generally.

On occasion, when I’ve had a particularly egregious and frustrating issue with a large company, I’ve emailed an executive in the relevant department with concise and kind language explaining the issue, where its alleviation is in the self-interest of my counterparty. This can sometimes be done all the way up to the CEO, but results vary depending on who both parties are, what the issue is, and how it is communicated (this is, however, a skill you can very much learn and perfect).

I’m fortunate to have a twitter account with a large amount of founders and investors in my following, which affords me the luxury of sometimes having CEOs fix issues I complain about. You don’t need a twitter account for this though; there are many executives and engineers that read forums like e.g. Hacker News and will directly respond to the right classes of issues on occasion.

Every Day Life: Flying

If you spend time thinking about the systems you regularly interact with, you can forecast some potential shortcuts by modelling both the incentive structures of the arbitrators of the system as well as the behavior of the average system participant.

Simple example: I fly pretty frequently. I often do things like:

  • Changing my seat an hour before takeoff to get two or three seats to myself. Laying down and taking up a full row is a much better experience than first class! This is done by combining 1) last-minute seat selection with 2) picking flight times where the flight is likely to be <80% full (which is unfortunately not a given for an arbitrary itinerary)
  • If I’m feeling particularly voracious when flight attendants decide to hand out biscuits, I might ask for three of them. I’ve never had a response of ‘no’ as there’s no reason for them to decline. I never ask for additional pretzels, should my choice of airline condemn me to such a fate.
  • If I want to board earlier than my boarding class, this is generally not scrutinized. I don’t abuse this, but sometimes it is simply more convenient both for myself and others (one reason it can be positive-sum is that I’m particularly quick both with my movement and with handling any luggage). Some airlines are okay with you taking up a first-class seat without paying for it, should one be empty.
  • Should the airline lose you your flight (or they require a set amount of passengers to switch flights), the compensation offered to is often highly negotiable (as most things in life are!), and can take many forms (flight credits, class upgrades, lodging, etc).
  • If you fly frequently in the US you should get TSA pre-checked. The advantage is more “reduces the variance and maximum time through security” rather than “reduces the average time through security”, as the former allows you a significantly more generous grace period. It’s also worth looking into credit card optimization if you travel frequently, but I’ll consider this outside of the scope of this post lest it turns into the equivalent of “they don’t want you to know this but you can bring candy inside of the movie theater”.

Exercise for the reader

Think about a system you regularly interact with and take some time writing down the incentives of the actors within the system. Think about actions which could be taken which are not frequently given as examples to follow, but which nonetheless match the ‘desires’ of the system.

It will be easier to find zero-sum examples in systems which are less heavily-optimized by market structures, e.g. searching for a secret to getting rich by trading derivatives better than anyone else will probably result in disappointment, whereas acquiring multiple snacks while on a flight won’t be a problem. I’d suggest picking something fun which is a quotidian yet mostly unscrutinized part of your daily life.

Try to come up with novel ideas, ideally by writing down things that come to your mind with as few stimuli to distract you as possible. I find this to be a really good exercise both in critical thinking and in agency.

If you enjoyed this post you may like other posts or my Twitter account. Thanks!

Optimal Webcam Setup

If you have important video calls (for example, you fundraise as the CEO of a company), you should have a good webcam setup. This post contains everything you need for one, at a cost of $700-$2,000, depending on which options you choose.

I. Camera

Most webcams are not very good, and you’ll want a real DLSR camera instead, optionally with a better lens:

Camera: Sony Alpha ZV-E10 ($800 with lens, $700 without)

Lens: Sigma 16mm f/1.4 Lens ($380)

II. Microphone

Although cheaper microphones work, it may be nice to have a high-end microphone which doesn’t get in your way:

Microphone: Rode NTG4+ Shotgun Microphone ($340)

III. Camera Accessories

Buy a power adapter for the camera so you never have to charge it: F1TP AC-PW20 AC Power Adapter ($25)

Buy a capture card for the camera for the best video quality and lowest latency: Elgato Cam Link 4K ($90)

IV. Mounts

You probably want to mount your camera behind and above your primary monitor. I use a large desk mount for this, but if you are often travelling or on a laptop, a smaller one works.

Base camera mount: Elgato Desk Clamp ($40)

Camera mount extension: Elgato Flex Arm ($40)

If you have a shotgun microphone, you should buy a mount for it too, placing it right behind your monitor and aiming the microphone towards you.

Desk-Mounted Boom Mic Arm ($72 with Amazon coupon)

Microphone Shock Mount ($13)

V. More accessories

You will need to connect your camera to the USB capture card, which then plugs into your computer:

4K Micro HDMI -> HDMI Cable ($10)

You will need to connect your microphone to your camera to include it in your HDMI stream, which also ensures it’s perfectly in sync with your video:

3.5mm Male to XLR Female Cable ($9)

If you want to use the microphone without the camera, you’ll want this cable

USB Male to XLR Female Cable ($13)

If you want to use your camera for outdoor filming, you’ll also want:

SD card ($12-$156)

SD Card Reader ($13) as well

If you don’t have a good lighting setup, you may want to purchase some lights as well:

Elgato Key Light – 2800 Lumens ($180)

VI. Configuration

You’ll have to change a few settings on the camera to have a good streaming experience.

It’s a popular camera, so if you don’t know how to do something, just search on Youtube. I found this video which helped me with a few settings such as: set the overheating threshold to high, add ‘USB streaming’ mode to the quick menu if you are not using a capture card, and turn the steady shot option off.

The most important item in this list by far is the camera – the microphone and lighting isn’t nearly as crucial for a good setup. Special thanks to Cory, CEO of Spellbrush, for helping me with all of this myself!

How to Twitter Successfully

Twitter/𝕏 is one of the best social networks in the world.

It’s among the best places to make friends, find a job, find co-founders or investors, attend events from, date from, learn from, and now even make some cash on the side from. This is still true as of 2024 (last updated: Jun 9 2024).

Despite this, many people haven’t given it a serious try and are missing out, likely because it takes time to learn how to make your Twitter experience great. In order to help remedy this, this post will cover:

  1. Twitter features you should use
  2. How Twitter accounts grow
  3. Social tips for success

Twitter Features You Should Use

I. Twitter Blue

X premium (previously Twitter blue) is generally worth it. Although the value it adds in some areas is subtle, if it helps you out even a bit socially, it will easily be worth $8.

An example of this is if it encourages someone to respond to you, check out your profile, or read your DM, when perhaps they otherwise wouldn’t have. Premium is purported to give algorithmic boosts, making you more likely to appear in the For You feed and causing you to appear higher in responses to parent tweets, but I don’t have explicit data to support this.

If your account has a large amount of impressions (5M+/month currently) you will make money from X Premium, so this should be a no-brainer. Based on the numbers I have, you should get a CPM of $0.01, although some accounts get higher rates. If you have 5M impressions per month, this should make you $50/month. Some accounts that I surveyed have a CPM of up to 5 times this as much. This may be due to having a much higher-value audience from an advertising perspective (many founders, investors, etc), or due to other unspecified favoritism.

I looked at the accounts I consider the highest-value, and around 50% have premium, so it’s a good signal that you’re a strongly above-average account.

II. Lists

source, well worth reading this thread!

Strongly consider trying out the lists feature of twitter! Lists are a collection of accounts that you choose which constitute a separate feed that you can browse. Twitter lists can be public so that anyone else can browse and follow them, or private so that only you see them.

The best two ways to use lists are 1) to make lists for specific topics you are interested in so that you can just browse that topic, and 2) to make lists of high-quality accounts which you don’t want to miss any tweets from.

You can add someone to a list by clicking the ‘…’ on their profile and then ‘Add/remove from lists’.

I personally use a ‘high priority’ list with ~140 accounts on it, allowing me to check this list in full daily with only a few minutes of time. This makes sure I don’t miss anything from the accounts that I think are the highest value. A subset of this list of people on my links page.

Bonus #1: lists do not have any advertisements on mobile

Bonus #2: you can pin a list on the mobile app so it appears at the top of the main app view next to the ‘for you’ and ‘following’ feeds. This can be done by visiting the lists page and then tapping the pin to the far right of a list.

Although my lists are not public, some others are! Here are a few examples compiled by Lama:

III. DMs

Twitter has a DM feature. You’re probably under-using it.

You can just talk to people. It’s okay if they are a famous researcher, a CEO, or even a billionaire. Many of them not only have their DMs open, but will check them. The worst that may happen is you don’t get a response, and that’s okay too.

This isn’t to say you should be spamming people – you should definitely focus on starting a conversation when you think it will provide value to both participants. But Twitter is simply a network of humans, and humans love to socialize and make friends and help each other out, and it’s important not to forget this. No matter how much fame or money someone has, there is almost always something they are looking for more of in the world.

A cold DM on twitter from someone who you have ‘seen around’ is significantly less cold than a cold email, where you see nothing but an email address and name. If you are, for example, looking for a job at a company, you may want to look at who is hiring for that company on Twitter and ask them how you can improve your chances.

When I went to San Francisco for the first time I didn’t know anyone there. I had zero friends. But what I did have was an anonymous Twitter account with 400 followers! I sent 6 cold DMs to some people who seemed cool and 4 of them agreed to hang out with me (one non-response, one busy). I had a great time with all 4, and I still chat on and off with two of them to this day.

I know a lot of people who have dated off of twitter and many others who have met their wife or husband from Twitter. I haven’t done this myself so have fewer tips in this area, but it probably beats the state of most dating apps.

Make sure your Twitter DMs are open (not verified-only, explicitly check this setting as for some users it was modified!) unless you have a good reason to close them.

IV. Muting & Blocking

You can mute keywords of things you don’t want to see. This was useful to many users during the NFT bubble, and in general can be a good way to keep politics or outrage-bait out of your feed.

You can also mute or block users. Muting a user ensures that you don’t see what they say, while blocking a user also ensures that they cannot respond to your tweets. Blocks can be considered rude the user will know you blocked them if they try to visit your profile), so muting may be a better idea in some cases (which has plausible deniability, should you desire that).

Some users strongly advocate for the liberal usage of mutes and occasional blocks, although if you aren’t overly political and don’t engage with trolls (which I encourage!), your need for them should be minimal unless you’re otherwise excessively controversial and/or popular.

With that said, your twitter account is yours and your time here is likely limited, so make sure you’re enjoying yourself rather than spending your nights arguing with strangers.

V. Likes

Liking a tweet makes the twitter algorithm more likely to show you tweets similar to it. I don’t use the For You feature frequently, so my personal usage is a little different. I sometimes use likes in a manner almost close to read receipts: the cost of clicking like is very low, it’s nice to notify people that I have read their post, and it also means that my likes are not particularly indicative of what I actually like, so it creates plausible deniability should someone point out that I ‘liked’ a tweet which goes against a given narrative.

If you subscribe to twitter you can hide your likes page from other users if you don’t want anyone to be able to visit your profile and see all of them in one place. As of late 2023 Twitter has also added a bookmark feature within the app which can be useful for saving content.

VI. Aggressively Curating Your Feed

If you see tweets from someone you don’t like, either unfollow them, mute them, or block them.

I generally unfollow accounts which are excessively political, and my Twitter experience is vastly improved as a result. Whenever something outrageous is happening that is covering the headlines (e.g. every day of ‘US politics’), I often don’t even see a single tweet about it. If it is something that actually matters and affects me, it’s likely someone I follow will bring it up. Twitter has been experimenting with many low-quality For You feeds to increase engagement as of mid-2024, so sometimes this isn’t enough and you’ll have to stick to using alternative feeds.

Experiment with using the Following feed rather than the For You feed. I find my For You feed to be mediocre at best, and an easy way to waste time without getting much value.

VII. Advanced search

Twitter has an advanced search feature which lets you search by account, engagement, date range, included words, excluded words, and more.

It is not the default search or accessible via the app, so many people do not know about it. You can use it by visiting this page: https://twitter.com/search-advanced

VIII: Desktop Keybinds

If you use twitter on a desktop or laptop, you may find the keybinds useful!

Frequent-used keybindings are shown below as well as the full keybind list from twitter.

Frequently-used Twitter keybinds
Twitters’s full list of keybinds, itself accessible via ?

How Twitter Accounts Grow: 0 To 1,000 Followers

I. Foreword

Being popular on Twitter is probably not what you want.

You probably want something that correlates with it, like reputation, influence, friends, or money. You can make great progress on these metrics without having an absurdly high follower count. If you think do in fact desire true fame, my suggested reading for you is Reasons Not to Become Famous by Tim Ferris, or the replies to any tweet Elon makes.

Ask yourself which is more valuable, a twitter account with 100,000 followers randomly sampled from the Earth’s population, or a twitter account with 1,000 followers entirely comprised of CEOs, journalists, billionaires, and heads of state? I’d take the latter any day myself.

This may be an extreme example, but it’s true that higher-quality conversation is harder to find in the replies to larger accounts. Elon Musk may be an interesting person, but the average reply to his tweets is anything but that. I personally find the sweet spot of good conversations to occur with accounts in the 1K-20K range, but your mileage may vary.

Starting from zero followers sucks. Even if you post something good, it may go entirely unnoticed. Here are some tips to help you out.

II. Put an unreasonable amount of effort into your content.

This is the most important tip here, and that is why it’s first. The Internet is filled with content, and if yours is significantly better than average, it’ll help your odds tremendously.

If you’re summarizing a research paper, don’t just paste it into ChatGPT and tweet whatever comes out. Go over sections of it yourself, help explain it as clearly as possible, add or even hand-annotate and crop images yourself, and so on. A good example of an account that quickly grew from 0 -> 70K in a matter of months with this strategy is AI Pub.

If you have years of interesting experience in a field, you may just be able to tweet stream of consciousness thoughts and takes on things successfully, in which case the above doesn’t exactly apply: the unreasonable amount of effort that you put in was applied elsewhere (e.g. in your career), and you’re just translating your knowledge from there to Twitter. In general long posts are not a great idea and should be separated into threads, although Andrej’s tweets are particularly high-quality, so I included him as an example.

III. Make your tweets as easy to consume as possible

Most tweets which go viral are very short and easy to consume. The exception to this tip is ‘essay’-style threads like the example shown above which have a different art to them. You should generally delete as many words as you can from a tweet, space out any sections of a tweet which are long, and then apply this style of thinking to everything else too. Images should be cropped so they’re easy to read and quick to consume, videos should be shortened to not be too long and have an alluring thumbnail, and so on.

IV. Respond frequently, early, and with high-quality content

When someone popular tweets about something you know a lot about, respond to it with something useful (or funny). If you do this shortly after the parent tweet was made, there’s a good chance you will appear near the top of the responses, enabling you to piggyback off of the popularity of the original poster.

One of the best things about this is that people will notice. If you give high-quality responses, even accounts with 6 figures of followers will read them and notice. That’s all it takes to talk with the main characters of the world: your desire to post a response to them on Twitter.

V. Source followers from external locations

If you have other social media accounts (or any friends), you can direct people to your twitter there. I like to include a link to my profile at the end of blog posts in case someone wants to follow me. If you have a friend who has a lot of followers, a single good quote-tweet or endorsement can really speed up starting a new account!

Most growth is based on your current number of followers (e.g., you should expect to gain a given percentage of followers per month), so it can take high-quality accounts months to go from 0 to 1,000 followers. Don’t give up and stick with it, and you’ll make it eventually!

How Twitter Accounts Grow: 1,000 To 100,000 Followers

After you have a few thousand followers, you’re at the point to where your tweets have a large initial seed userbase. This is great, because now if you post something with the propensity for virality it has a much better chance of getting thousands of likes and being ‘picked up’ by the algorithm.

To help demonstrate how social media growth generally works I’ve made a few charts of my Twitter metrics from a period where I was having fun growing my account.

Aggregate followers over time

This first graph is my followers over time. It is going up, and the slope is mostly increasing. That’s good.

To make it more useful, now we’ll adjust for the amount of followers that I had in each month to show the relative growth instead of absolute.

Despite the number of followers increasing more and more over time, the percentage of followers that I gain in a month is surprisingly constant. My month-on-month growth was around 24% on average.

If you are familiar with the power of compounding this should strike you as a very impressive metric and is the exact type of thing venture capitalists look for in the revenue or usage metric of companies. A 24% MoM growth rate would amount to 1,300% per year or 40,300,000% across five years.

But in some months I tweeted more, and in other months I tweeted less. Let’s take that into account to make another chart.

This graph is answering the question “for each tweet that I made, by what percentage did it cause my account to grow, on average, per month?”. Although it’s a bit messy, it is still surprisingly consistent and its data has the lowest standard deviation out of all three graphs.

Thus, numerically speaking, to grow your twitter account:

  1. Tweet frequently
  2. Tweet consistently
  3. Do this for a long time, ideally for years

The best example of someone that has done this well, but for Youtube instead of Twitter, is MrBeast. He consistently made videos for years, getting very few views, but kept at it and kept improving until the subtle 10%/month gains compounded. The first few years sucked, but now 2% of the Earth’s population watches every video he releases.

With that said, none of this will matter if your tweets are low-quality. The above guidelines assume both that there’s some value in your content but also that your goal is to maximize follower count. This isn’t the same as my personal goal, so I usually don’t tweet more than once or twice a day, if that.

Okay, but what do I actually post?

Well, that depends on what kind of followers you want. You can become popular by posting 4chan memes, but if your goal is to network and get a job, this probably won’t help you very much. You could also become popular by posting research summaries of arxiv papers, but if your goal is to hang out with the boys and joke around, this might not hit the spot.

Broadly though, you should decide who you want to surround yourself by (you will become more similar to them, so be careful!), and what type of value you will provide in order to achieve this.

Most social media accounts can be mapped into a category based on the type of value they provide. Broadly those categories are:

  1. Funny
  2. Interesting
  3. Useful
  4. Sexy
  5. Entertaining

These are rough categories, but if you think of some of your favorite twitter accounts, you should be able to map them onto one or more of the above categories.

The next section will go over more explicit advice that might help you to have a good time on Twitter.

Social Tips for Success

I. Be positive and constructive

The most important tip I have is to be positive and constructive. You can get engagement with dunks, but the followers and network you’ll end up with won’t be pretty. I’d avoid the political areas of Twitter at all costs.

II. Err towards saying things rather than being shy

This is hard for some people, but exposure therapy is the best way to fix it. Never be scared to tweet something because you have a lot of followers, or overly important followers, or anything like that, as long as it’s something you actually want to say. This is good advice for life in general. Trying things is good, and not trying things is bad.

III. Optimize your content for twitter

Linking to a 30 minute youtube video will generally get very low engagement, but specifically cropping out the best 30 seconds and adding a quick summary, quote, or thread will do much better. You should keep most posts short and crop images accordingly.

IV. Don’t tweet walls of text

Both spacing out your tweets and tweeting with images are usually good ideas. If the first one or two sentences of your tweet aren’t interesting, few people will finish reading it. It’s possible to succeed with long-form essays and threads if you have good content, but this is usually more difficult and vastly depends on your niche. I strongly advise reading Scott Alexander’s writing advice as well, even if it wasn’t made for Twitter.

V. Make your own images

There’s a lot of value in making custom images. Most of my best performing tweets contained images that myself or someone else made, some which took as long as 5-30 minutes to make.

VI. Pseudonymity is cool but optional

Having a pseudonymous account can be advantageous. A lot of people are scared to tweet their true thoughts publicly in a permanent form with their face and name directly adjacent to them. This is understandable and there’s nothing wrong with that. Even if you don’t have your name and face on your account you can still make friends, meetup with people, and even network professionally or get a job as long as you’re willing to share more details with individuals. A great example of someone who has managed this well is roon.

You can probably get away with tweeting more provocative content than you think. Cancellation may have been a formidable force a few years ago, but as of 2024 unless you’re diving straight into hard-politics you shouldn’t let it scare you out of trying to live your life.

If you’re fortunate enough to be skilled in a field like software engineering, you have strong marketplace value and leverage. Consider working for an employer which has courage and will not fire you over a few people on the Internet typing mean words into a text box (thanks @patio11).

VII. Cold DM people more

You should cold DM people more. It’s a great way to get a job, make a friend, find a partner, and much more. If you’re curious why this tip has been repeated twice, it’s because it’s at least twice as important as the other tips.

VIII. Only follow people you want to become more similar to

Only follow someone if you want to become more similar to them in some way (at least with respect to the content that they tweet about). Following someone gives them a limited type of write access to your brain, which for powerusers may be reinforced multiple times a day over the course of many years. This will significantly alter the type of person that you become, so use this super power wisely.

A relevant quote from Moxie Marlinspike on career advice is to look at those senior to you in a field and decide if you’d truly like to become just like them: “They are the future you. Do not think that you will be substantially different. Look carefully at how they spend their time at work and outside of work, because this is also almost certainly how your life will look. It sounds obvious, but it’s amazing how often young people imagine a different projection for themselves” (source)

IX. Optimize for virality only at the cost of your soul

I would advise not purely seeking virality, even if you manage to avoid politics. Our best selves are probably not consistent with the versions of ourselves that maximize engagement online. I’ll leave you with the below quote from Dario Amodei, CEO of Anthropic:

That’s all I have here for now! If you have feedback to add, please add it to my tweet for this post or send a DM. If you made it this far you may also like some other posts on this site.

FAQ / Addendum

Hasn’t Twitter gotten worse with Elon?

I don’t personally find that the amount of value I get from it has gone up or down by much since the acquisition. but I do find that it takes more effort to get a good experience (for example, the default feed is worse for me). Although some updates have been negative, I’m glad new things are at least being tried. I also exist in an area (AI, startups, tech, San Francisco, etc) which likely uses and enjoys Twitter more than average.

There are of course many alternatives to twitter, and if you prefer their leadership and product choices over the ability to actually have a large and influential audience, that is a choice one could make. As of 2024, Twitter remains largely influential to the world, and that’s why I continue to use it. You don’t have to be a fan of the CEO or ownership of a company to use a product from them, and Twitter is no exception.

What are some other resources similar to this?

How did you calculate CPM?

I compiled self-reported impressions and payments from some accounts. I don’t have a good sample size, but the data I have is available here:

AccountImpressionsPaymentCPM
https://twitter.com/nearcyan7,100,000?$454.62$0.064
https://twitter.com/Austen67,500,000$3,337.51$0.049
https://twitter.com/nickfloats31,300,000$1,253.88$0.040
https://twitter.com/FlyeKitesJay6,200,000$66.30$0.011
https://twitter.com/markgadala61,100,000$667.63$0.011
https://twitter.com/Danizeh60,000,000$650.00$0.011
https://twitter.com/concept_central/21,400,000$120.65$0.006
https://twitter.com/dom_lucre/472,000,000$2,402.16$0.005

Leveraged and alternative ETFs: Investing with higher risk tolerance and significantly greater potential upsides

I often end up talking about finance a lot, and in doing so often mention investing strategies and asset classes that many regular retail investors aren’t aware of. Although the world of financial derivatives is vast and unknown to most, I wanted to make a brief post about some simple products which I think should have more publicity, primarily that of leveraged ETFs. This post is a brief introduction to some investing strategies that some retail investors choose to use for higher risk tolerance and significantly greater potential performance. This post is not investment advice, in case I need to actually say that. I should also add that suggesting holding leveraged ETFs for longer periods is a relatively controversial view within the wonderful world of dollarmancy; nonetheless I present my own views here honestly should anyone wish to know them.

stonks
this could be you!

Cash is not your friend

At the lowest level of risk tolerance, many choose to simply keep their savings in cash. This is bad when done for longer periods. It is often pointed out that you will slowly lose money to inflation over time (whether that is the 2% inflation rate that the FOMC targets per year, the ~7% rate of 2021, or perhaps much more..), which although true, is not nearly as large of a loss as the opportunity cost incurred by investing in nothing. Many will provide APY estimates for investing in common market indexes between 6% and 9%, but examining as much as the last few decades (or even just the last decade) will show significantly greater numbers. $SPY has returned over 10% per year since its inception 29 years ago, and around 16.5% per year for the last decade (the last 3 years are even more impressive at 26% each on average!). I do not attempt to claim these are indicative of future results, or that we should be promising anyone these numbers, but it does seem to be unfair to weigh our expected market growth by including past decades that go so far back that we lacked not only much of our modern monetary policy knowledge, but also inventions as basic as the Internet itself.

If casual returns of 10.5% per year were not enough to motivate oneself, I often like converting these APYs to the period of a decade – in which case 10.5% corresponds to a 171% gain (1.105^10), 16.5% APY to a 360% gain, and 26% APY to a >900% gain. We could, of course, make these numbers even more grandiose by telling someone what returns they may expect by holding an investment for 20 or 50 years, but I find a decade to be a relative sweet spot, perhaps because people have an easier time imagining themselves a decade in the future rather than several.

I have heard many reasons for why people choose not to invest in ETFs (or anything similar such as individual stocks), from the reasonable “I am purchasing a house in a few months and now is not the time to take on any risk”, to the questionable “I am waiting for things to cool down a bit and I am a bit worried about some things in the near future”, to the absurd “I do not trust wall street or bankers, sorry” (and indeed, much can be said about how poorly we educate our citizens in the US about basic personal finance, which unfortunately involves much more than just basic investing). I am not going to spend many words attempting to convince someone that holding cash long-term (a year or more) is sub-optimal, because it seems obvious enough to me that it’s considered outside the scope of this post.

What margin is and isn’t

Most young professionals are now fully aware of what index funds are, and often have some simple strategies for investing in them. While it’s not my job to decide the risk tolerance of others, I do think it’s nice to at least be aware of some options that can generate significantly higher long-term returns than these traditional index ETFs. This is not investment advice, and regardless of if it was, I would not want to be responsible for someone else’s choices should things turn south.

The primary product I’d like to mention is that of leveraged ETFs. Many will initially recoil upon hearing the term ‘leverage’ mentioned in the context of personal finance, because they know that it’s scary and can be involved in situations where someone loses their entire principle (that is, 100% of their portfolio). It’s for this reason that I want to start with mentioning the difference between buying stocks on margin and purchasing a product which itself uses margin.

Buying stocks on margin is generally considered to be risky, because you are buying more than you can afford with your own money, effectively taking a loan from your broker in order to afford additional shares. Generally leverage of up to 4x is attainable with popular large-cap stocks on most US brokers, although there’s many exceptions to this. Although buying stocks on margin is not something I would generally suggest for many reasons, it does have a lot of uses, and it can be much less intimidating and dangerous than many may guess. Tools to analyze, manage, and properly limit one’s risk to a comfortable level are readily available, and rates for margin loans can be as low as 1% or under (IBKR is generally the golden standard for the lowest margin rates for regular retail investors, but some other platforms do offer better interfaces, tools, or additional products, and will also be able to negotiate rates with you should you have sufficient capital).

The obvious downside to margin is that you can lose much more of your investment. Theoretically, if you bought a stock with 4X leverage and it then declines by 25%, you would find yourself broke. In practice, you will get liquidated by your broker before this happens, unless the 25% decline happens instantaneously and they do not have enough time to sell your securities on your behalf (If you have heard the term margin call before, that is what happens when you do not have enough capital to maintain your leverage, generally after whatever you own performs very poorly. You can either deposit more money to get back to your maintenance margin, sell some of the products you own via leverage, or let your counterparty liquidate them for you). I am not going to get into the different types of margin or ideal scenarios for using it (of which there are many – remember, this is a loan with an interest rate of only 1%!) in this post, but rather have included this information to help it contrast with what a leveraged ETF is.

Leveraged ETFs

A leveraged ETF is not the same as buying stocks on margin. It is similar in that it is a higher-risk investment that easily allows one to lose or gain much more than usual, but it is different in that you are not taking out a loan explicitly nor implicitly, are not in debt, and therefore cannot be margin called, liquidated, or otherwise lose your shares via any means except via deciding to sell them yourself (this doesn’t mean they can’t still decrease in value by an arbitrary amount of anything less than 100%, however).

A leveraged ETF functions similarly to a regular ETF – it is a security that you can purchase, in which the work of managing your portfolio is abstracted away from you, and instead done by the issuer of the ETF. Instead of buying shares in 500 companies and managing their proportions yourself, you can simply purchase a share of $SPY and forget about it. In exchange for this convenience, you are charged a fee of 0.094% per year (this is often listed by brokers and compiled by ETF websites, but the original source is in the prospectus for the given security). The goal of an ETF is to track its underlying index – if the S&P 500 index is down by 1% in a given day, $SPY should be down close to that amount as well. A leveraged ETF attempts to perform the same function, however it introduces a linear multiplier which multiplies the intended gains and losses. In the US you will generally only find products that offer 2x or 3x leverage due to SEC regulations (3x products are often grandfathered in, as a 2020 update from the SEC suggests a general cap of 200% leverage via derivatives being allowed), although this introduces much more than enough additional risk and volatility for most investors’ appetites (should one want more leverage, they can create additional artificial leverage through the use of options, but that is also outside the scope of this post. Also, gambling is bad, Just Say Neigh!)

Leveraged ETFs are re-balanced daily, and thus intend only to match the performance of their underlying index (multiplied by 2 or 3) for a given day. If the S&P 500 index goes up 1.5% in a day, then a 2X leveraged ETF for it should return close to 3% that day. Due to their targets being daily, some investors often misinterpret this as being equivalent to matching returns on longer periods, although this is not the case. This has been misunderstood enough that the SEC has an alert attempting to inform investors of this, providing some historical examples of leveraged ETFs declining in value during longer periods, during which the underlying index performed positively. This is generally referred to as ‘volatility drag’, and is one of the largest reasons for which many discourage investors from purchasing these products. Much has been written about it, so I will just offer a very short summary: during periods of volatility, leveraged ETFs will perform worse than one would expect at first glance. To give a simple example as to why, imagine that portfolio A returns 5% on day one and then loses 5% on day two. If you started with $100, you will end up with $99.75 ($100 * 1.05 * 0.95). If portfolio B multiplied these daily fluctuations by 3X and returned 15% on day one and -15% on day two, $100 would turn into $97.75 ($100 * 1.15 * 0.85). As you can imagine, if we iterated over these scenarios many times, portfolio B would start to perform terribly in comparison to the portfolio with less leverage.

Volatility drag, aptly-named, is bad during periods of volatility, but it’s particularly bad when there’s not enough underlying momentum in the upward direction to counteract it during longer periods. During a market that is performing even moderately well, generally the greater returns provided by leveraged products don’t just return more than is lost due to volatility drag, but return so much more that being fearful of the concept can be actively harmful (this is likely a controversial opinion in many areas, for what it’s worth – but many people become scared of an investment that could feasibly return 1,000% over a period because of a potential loss of 10% or 50%, even if it’s clearly a very high expected value. In some cases this may be rational due to the diminishing returns of utility provided by additional capital (money may buy a little happiness, but this caps out pretty quickly, and having no money is definitely much worse than having just a little!), but it is well-known that humans are far too risk-averse as a general principle regardless).

To provide some examples, I will mention some leveraged ETFs alongside the returns that they have provided historically. As usual, past performance is not an indication of future results!

$SPUU, a 2X-daily-leveraged ETF that tracks the S&P 500 index, has returned an average of 32% annually for the last 5 years, and 27% annually since inception. $SPXL, a 3X-daily-leveraged ETF that also tracks the S&P 500, has returned an average of 41% annually for the last ten years. Those of you used to performing basic calculations on compounding annual rates will quickly realize how absolutely insane these numbers are – 41% returns compounding for a decade comes out to a return of +3,000%! This is something that is possible, and that many investors have actually attained, providing they didn’t sell during draw-downs (this is not the same as it being guaranteed, or even probable, however).

If past performance is not a promise of future performance, then why is it being mentioned so saliently here? Because although strong performance is not guaranteed, this helps to illustrate the potential of what happens with leveraged ETFs when things go really well, which we can reasonably say has been the case since 2010 to 2022. Because things are not guaranteed to go well, putting 100% of your net worth into these leveraged products is reckless and is very likely a bad idea. However, just as some people like to have hedges just in case things go south, I think it’s important to have some minor positions in place just in case the opposite occurs: If we get lucky and the next 10 years go as well as the last, it is quite possible to attain a 20x, 30x, or greater return on your investment. If you get unlucky, you may lose some or most of your investment, but no more than 100% of it, so the risk to reward is very strongly in your favor (yes, the math is much more complicated than this, but the result holds in more nuanced conditions regardless). In the next section I will go over a few basic common questions about leveraged ETFs, as well as mentioning more of the negatives.

Leveraged ETFs exist for most popular stock indexes, including sector indexes. For example, $SOXL is a 3X-leveraged ETF based upon the ICE Semiconductor Index, which primarily consists of companies related to semiconductor manufacturing. As it is my personal opinion that we are going to tile the world several times over with semiconductors (or something equivalent) in the coming decades, this is a product that I’m a fan of personally, even if it is very high-risk. For some listings of leveraged ETF products, check out out these pages from Direxion and Proshares

Responses to common concerns about leveraged ETFs

Aren’t leveraged ETFs not intended to be held for longer than a day?

This is mentioned in many locations, but it functions primarily for the purposes of legal liability and investor protection. There is nothing wrong with holding these products for longer periods, as long as one is properly educated about them. This is the type of warning where those that it does not apply to will know they can ignore it. There are other similarly-accessible products that are much worse ideas to hold for longer durations, for example inverse-leveraged ETFs, which return the opposite of what the underlying index returns, and thus trend towards zero over the long-run (for an example, $SPXS has returned -47.22% since inception, which leads to over a 99% loss after a decade. If you’re curious why inverse ETFs exists, they are primarily for short-term speculation and various types of hedging).

Aren’t leveraged ETFs subject to volatility drag, and thus a bad idea to hold long-term?

As mentioned above, volatility drag is an important thing to be educated about and aware of. However, if markets actually perform well, the potential gains from leveraged ETFs significantly outweigh (often by more than an order of magnitude) losses due to volatility drag. Regardless, it is worth noting that as many leveraged ETFs are recent financial products, there is an inherent cherry-picking present in the data used to show how well they perform, as the previous 5-20 years have been favorable financially for most US sectors.

Don’t leveraged ETFs have much higher management fees than most normal ETFs?

This is true, and is also something to note. As with the above two examples, $SPUU’s gross expense ratio is 0.88%, and $SPXL’s is 1.03%. Similarly to volatility drag, while it’s important to be aware of these expenses as they do add up and eat into long-term profits, if the market performs well, you will make so much that you will not even notice it.

I don’t want to get margin called, gamble with money that is not mine, or be in debt

Luckily none of these things occur when purchasing leveraged ETFs. You can still lose almost all of your money, but you cannot go into debt or have your shares taken away from you (unless you are engaged in other things that may cause this).

Leveraged ETFs have draw-downs that are far too high for the risk tolerance of every day people

I would say this is completely true. If we take a fund like $SPXL and look at what happened during the covid crash, it crashed from $76 to $18 in a single month, or a decline of around 77%. Apart from this being bad financially, drawdowns this large often cause significant emotional distress to investors and can easily cause them to make poor choices and panic-sell at market bottoms. While $SPXL may have returned back to $76 in less than a year (and then somehow doubled in the year after that..), this will obviously not always be the case. It’s quite possible for drawdowns in some leveraged ETFs to reach 90% or more, even if very rare.

This is gambling

All investing is gambling, mathematically speaking. The absence of investing is also gambling due to opportunity cost – if you hold USD, you are literally betting for it and the US to do well! While it’s true that this is more like gambling than other financial products in the views of many, it should not be compared to acts such as buying a lottery ticket or going to a casino, where there is a known large house edge against you, with the objects in question having been specifically constructed in order to gain the upper hand over you.

Markets exists everywhere and will not go away any time soon, so there is no option of ‘not playing’ the game, as unfortunate as that may be for some of us. The only question is what one’s risk tolerance and personal choices are, not whether they exist or not, because they are forced into existence by our environment. While it may be easy to lose a lot of money on leveraged ETFs, it is nowhere near as bad as buying short-term out-of-the-money options, binary options, 100x leveraged cryptocurrency swaps, 250x forex trades, writing uncovered cryptocurrency options, and many other ‘fun’ products that exist and are often traded by young males addicted to gambling.

How much of my money should I invest into leveraged ETFs?

I have no clue; the right answer for you, dear reader, could very well be 0%, 100% or anywhere in between, but I am not the one that can decide for you. I can say that it is worth your time to learn a lot about how personal finance works however, regardless of your risk tolerance or intentions.

Something something trading leveraged-ETFs or other things

Although I am not in the business of telling people what to do financially, I do enjoy telling people things I think that they should not do, and one of those is ‘trading’. The short version of my advice on this matter is that you should be buying and selling things as infrequently as possible, and you should avoid things like ‘day trading’ like the plague. If you find yourself constantly checking prices, you are likely over-leveraged. I have watched too many bad things happen to too many amazing people, many of them very smart, and most of them young males, and I want to do what I can to cause gambling addictions and casual day-trading to happen less. The humor of places like r/wallstreetbets may be quixotically funny at times and comically sardonic at others, but behind all of the fun people are having with memes about cryptocurrencies and options on Reddit and Twitter, lay thousands of people who have lost their life savings, many of which who end up taking their own lives or losing decades of accumulated capital. Markets are not a game, and if they find a way to eat you alive, they will, as they have become exceedingly efficient at it in the recent few decades.

Further Reading

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