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:
Minecraft is more enjoyable
Minecraft is more addictive
Minecraft found them first
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:
Andrew Carnegie started working at a cotton factory at the age of 12
Henry Ford left home at 16 to work as an apprentice machinist
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:
They are currently busy playing video games (which likely become more important to them at a very young age)
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)
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.
memetic-invariant information remainsconstant 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!
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
The nutty pudding mixAfter being mixed with whole milk
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
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
Longevity mix powderLongevity mix powder mixed with water and encased by glass
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)
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
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 inhibitα-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
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.
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.
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
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.
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!
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 mirrorless camera instead, optionally with a better lens:
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.
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!
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: Oct 10 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:
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.
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:
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.
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 ?
IX: Security Features
Performing an audit on your account security is strongly suggested.
Here is a great guide showing you the features available and how to set proper 2FA (TOTP rather than SMS).
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:
Tweet frequently
Tweet consistently
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:
Funny
Interesting
Useful
Sexy
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.
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 probablyget 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.
Scott Alexander of SlateStarCodex / AstralCodexTen recently wrote Pascalian Medicine, in which he looks at various substances purported to improve covid outcomes, but which have relatively low amounts of evidence in their favor, likening administration of all of them to patients to a Pascal’s wager-type argument: if there is a small probability of a potential treatment helping with covid, and if it’s also very unlikely that this treatment is harmful, should we just give it to the patient regardless of if the quality of evidence is low and uncertain, as it would clearly have a positive expected outcome regardless?
The naive answer to this could simply be to attempt to calculate an expected value (note: I use the term expected value often here, but in some cases the terms hazard ratio, relative risk, or odds ratio would be more appropriate) for each treatment, and administer it if it’s positive. But there could be some unintended consequences of using this methodology over the entire set of potential treatments: we could end up suggesting treatments of 10 or 100+ pills for conditions, and apart from something just feeling off about this, it could magnify potential drug interactions, some treatments could oppose others directly, the financial cost could start to become prohibitive, and it could decrease patient confidence and have many other undesirable second-order effects.
Pascalian Longevity
There are many counter-arguments presented to the above concept which become less salient when the goal is changed from ‘find drug treatments to prescribe to all covid patients’ to ‘find personal health interventions that increase your own lifespan/longevity’.
I am fortunate enough that I am able to evaluate potential longevity interventions myself, pay for them myself, administer them myself, and review their potential effects on me myself. I might not do a perfect job of this – research is difficult, time-consuming, and lacking in rigor and quantity, and finding appropriate longevity biomarkers to quantitatively asses the effects of interventions is also difficult. But uncertainty is a given here, and that is why we incorporate it into our frameworks when deciding if something is worth doing or not by calculating an expected value. Furthermore, any harm that I may accidentally incur will only be done to myself, reducing the ethical qualms of this framework to near-zero (I would strongly oppose arguments that I should not have the right to take drugs which I think may significantly improve my own health, although some may disagree here).
My modus operandi with respect to longevity may have many uncertainties in its output, but still operates with a very strong (in my opinion) positive expected value: If a substance significantly and consistently increases the lifespan of organisms similar to humans (ideally in humans), and is also very safe in humans, then it is something that I want to take
This is how I operate personally with longevity, and it does result in me taking quite a few things (currently I’m at around 15). I do still try to minimize what I take as a meta-principle (for example, setting a minimum threshold of expected value that a substance must provide to warrant inclusion, rather than simply accepting any positive expected value) for a few reasons: firstly, to reduce potential drug interactions (which we do attempt to asses on a per-substance basis, rather than account for as an unknown, but unknowns are unfortunately a very large component of messing with biology regardless). Secondly, to keep my costs relatively sane, although I am not too worried about this as there are few ways to spend money more effectively than on trying to improve your health. Thirdly, to reduce the occurrence of interventions that may have the same or opposing mechanisms of action (taking two things with the same mechanism of action may be okay, but sometimes dose-response curves are less favorable, and taking >~2x of something will result in diminished or even negative returns). Lastly, to minimize potential secondary side-effects that could be cumulative over large classes of substances (for example, effects on the liver).
I don’t intend to promote any specific substances or interventions here as I don’t give medical advice, nor do I want anything specific to be the focus of this post, but I do want to remind us that just as we can calculate expected values in a utilitarian fashion and get effective altruism as a result, we can do the same for longevity interventions and get a very strong chance at notably increasing our lifespan/healthspan as a result. I do have a list of some of what I take here, but it is definitely not intended to promote anything specific to others.
Why Not?: Potential counter-arguments
Algernon’s Law
Algernon’s Law is sometimes brought up, suggesting that evolution has already put a lot of effort into optimizing our body, and thus we are unlikely to find improvements easily. But, as Gwern notes in the above link, there’s at least three potential ways around this reasoning: interventions may be complex (and/or too far away in the evolutionary plane) and could not have easily been found, they may be minor or only work in some individuals, or they may have a large trade-off involved and cause harm to reproductive fitness.
Although some areas of future longevity treatments may fall under exception one and be complex enough that evolution could not have found them, I would suggest that the majority of today’s potential treatments fall under exception three: evolution optimizes for reproductive fitness, not for longevity, and for this reason there are many interventions which will improve our longevity that it has not given to us already (this is part of why I am more optimistic about longevity interventions than I am about intelligence interventions/nootropics).
For an extreme example of this, it has been noted that castrated males often live longer, and that this is obviously something evolution would not be very interested in exploring. Although this has been found with median lifespan in male mice (maybe in females too?), there is also purported historical data on Korean eunuchs suggesting that they may have lived a full 14-19 years longer (there are definitely potential confounding variables and/or bad data here, but we don’t have RCTs on this in humans for obvious reasons..), and a more recent study in sheep that is also highly relevant: Castration delays epigenetic aging and feminizes DNA methylation at androgen-regulated loci, where epigenetic aging clocks that look at DNA methylation are used in castrated sheep. There are other traits that seem to improve longevity as well, for example decreased height. It seems quite plausible that there are a lot of trade-offs that optimize for strong reproductive fitness early in the lifespan of organisms, which end up costing the organism dearly in terms of longevity. These trade-offs may be involved in many areas such as testosterone, estrogen, growth hormone, IGF-1, caloric restriction, mtor activation, and many others.
Large error in estimating unknown risks
One other counter-argument here is often along the lines of “you are messing with things you don’t understand, and you could be hurting yourself but be unaware of this; the damage may also be difficult to notice, or perhaps only become noticeable at a much later time”
It is true that our understanding of biology is lacking, and therefore also that we are operating in highly uncertain environments. I would be open to evidence that suggests reasoning for why we may be systemically underestimating the unknown risks of longevity interventions, but given how strong the potential upside is, these would have to be some pretty terrible mistakes that are being made. It is often noted how curing cancer may only extend human lifespan by a few years, whereas a longevity improvement of 5% for everyone would provide much more value (and is also much easier to find in my opinion). One could make an argument here that even if I was doing something that notably increased my risk of e.g. cancer, if the expected lifespan increase of this intervention was as much as 1-5%, this could still be a huge net positive for my health! I don’t take approaches that are this extreme regardless, and I try to keep the risk side of my risk/reward ratio low independently of the level of potential reward in attempt to account for this uncertainty. I am also not aware of many interventions that seem to have very high numbers in both the numerator and denominator here, although I am pretty certain that they do exist; I don’t currently take anything that I think has notably detrimental side-effects for the time being.
Is it fair to call this approach Pascallian?
The original nature of Pascal’s wager is that of extreme probabilities resulting in positive expected values, but the numbers that we are operating with are nowhere near as extreme as they could be. It is probably not a good idea to take 10,000 supplements, each of which have a 0.1% chance of extending your lifespan by a year for many reasons (similarly, if 10,000 people that claimed to be God all offered me immortality for a small fee, I would hope to decline all of their offers unless sufficient evidence was provided by one).
As I’m not arguing in favor of taking hundreds or thousands of supplements in the hopes that I strike gold with a few of them, it may be worth noting that ‘Pascallian Longevity’ would be a poor label for my strategy. Regardless, taking just 5-10 longevity interventions with a strong upside potential seems to be significantly more than almost everyone is doing already, so I still stand by my claim that there are many free lunches (free banquets, if you ask me) in this area, and I am very optimistic about the types of longevity interventions we’ll find in the coming decades.
17α-estradiol is a relatively (or completely) non-feminizing form of estradiol (E2), or estrogen. It is a naturally occurring enantiomer of 17β-estradiol (the much more common form of estradiol, usually just referred to as ‘estradiol’) which is found in both male and female humans. This post a a brief essay that discusses the prospect of it extending lifespan in humans. There are two primary types of estrogen receptors, ERα and Erβ, and as you may expect, 17α-estradiol appears to show a stronger binding affinity for ERα. It has a very low binding affinity in locations that generally induce feminization (which appear to be sometimes be both ERα and ERβ), so it’s also possible to take as a male without significantly altering one’s appearance towards the opposite gender. Although we can definitively point to a plethora of effects of regular estrogen, it is difficult to tell what the true purpose of 17α-estradiol is in humans, with Stout et al. (2016) stating “the physiological functions of endogenous 17α-E2 are unclear”. There is evidence it has neuroprotective properties, can help treat Parkinson’s disease, cerebrovascular disease, and much more. This likely involves ER-X, which in turn activates MAPK/ERK and many, many other things down the line (as usual..), but it’s difficult to know for certain. Although these reasons were among the reasons that researchers took into account when deciding to dedicate funding to testing 17α-estradiol in mice for longevity effects, subsequent papers have found more exciting mechanisms of action which are elaborated upon below. For some interesting further reading on this topic that goes into more detail exploring possible mechanisms of action here I’d also suggest reading the following papers: Castration delays epigenetic aging and feminizes DNA methylation at androgen-regulated loci, Hypermethylation of estrogen receptor-alpha gene in atheromatosis patients and its correlation with homocysteine.
17α-estradiol has been found to consistently and significantly extend the median lifespan of male mice, including by the NIH’s Intervention Testing Program, the closest thing we have to a gold standard of longevity RCT experimentation in mice, where three studies are rigorously performed at three separate locations, allowing the results to be instantly compared and reproduced by the two other parties and locations upon completion. Strong et al. (2016) find that 17α-estradiol extends median lifespan of male mice by an average of 19% (26%, 23%, and 9% from the three independent testing sites), and increased the maximum age by an average of 12% (21%, 8%, and 8% from the three testing sites, using the 90th percentile). Harrison et al. (2014) similarly find that median male lifespan was increased by 12%, but did not find an increase in maximum lifespan, and these results have been replicated even more in recent years.
These are some impressive results for such a common and simple endogenous substance! One of the first things we notice is that this effect only applies to males, with female lifespan (both median and maximum) being unaffected. As the substance in question is an estrogen, we can assume that this is either due to female mice already having this benefit, as they already have a sufficient level of it, or that something more complex is at play, and there is a different downstream pathway that is only being activated in males for some reason (more on this later). I had initially assumed the former hypothesis was at least a partial explanation, having known that females consistently live longer than males when it comes to humans, and that this was obviously biological in nature. However, it’s much more complicated in mice as females do not always outlive males, and in fact many times the opposite is true. One meta-analysis (good overview, original book source) finds 65 studies where males lived longer and 51 where females lived longer, with this often depending on the strain of mice used, which varies greatly depending on the type of reseasrch and time period. Regardless, it’s clear there is much more at play in this scenario, and perhaps something special about 17α-estradiol in particular.
Although the ITP studies initially included 17α-estradiol due to the reasons mentioned in the first paragraph, later research such as Stout et al. (2016) has now found that 17α-estradiol not only increased AMPK levels (as some other notable longevity substances such as Metformin also do), but also reduced mTOR activity (complex 1!) in visceral adipose tissue, which is rather reminiscent of Rapamycin, which has extended the lifespan of every organism we have performed an RCT with thus far (and likely can in humans too, if you ask me). In a way, this is significantly more exciting, because it gives us a much more plausible way to explain the lifespan extension effects we are noticing. However, it is also partially a disappointment: if these effects are the real reasons why 17α-estradiol extends male mice lifespan, then this substance may offer us nothing that we do not already have via rapamycin and metformin, among others. The paper also noted that fasting glucose, insulin, and glycosylated hemoglobin were reduced along with inflammatory markers improving. These are similar to the types of positive side effects we would expect from a longevity agent, and the study also notes that no feminization nor cardiac dysfunction occurred.
How do these effects (such as AMPK and mTOR modulation) occur? I don’t know, and apparently neither does anyone else. As is often the unfortunate case in biology, the paper has this to say: “The signaling mechanism(s) by which 17α-E2 elicits downstream effects remains elusive despite having been investigated for several decades”. Perhaps just a few more decades to go and this section will be updated with more information, then. Mann et al (2020) find that male mice without ERα do not benefit from 17α-estradiol, which helps us narrow down the first step by excluding Erβ, ER-X and other less-predictable initial mechanisms. Interestingly, they also note that “both 17α-estradiol and 17β-estradiol elicit similar genomic binding and transcriptional activation of ERα”, which would leave us with the question of why we are focusing on 17α-estradiol specifically, if 17β-estradiol (which is much more common) suffices as well. Importantly, they also seem to think changes in the liver might be involved. Garratt et al. (2018) add that distinct sex-specific changes in the metabolomic profile of the liver and plasma were found, and also notes that the longevity benefit for males disappears post-castration. They first supplement males and females, showing many differences related to metabolism including with amino acids. Then they use castrated males and notice that their profiles are the same as the control group, and thus conclude that they are no longer being positively affected by 17α-estradiol. I am unsure if we should be focusing on the AMKP/mTOR effects (which arevery relevant to longevity) or on the liver/metabolic effects (which are also very relevant), or if these are in fact just two different temporal points on the same biological pathway which we don’t yet fully understand, but this helps us connect at least a few more dots.
All of the above sounds exciting, but it’s also all in mice. Sometimes this is useful, as mice are actually quite similar to humans (more so than many may expect), but a lot of it is also less useful or outright misleading. I cannot find a way to take only 17α-estradiol in a safe way as a human, however there is a topical cream of it (alfatradiol) which is used to treat pattern hair loss.
Luckily, one thing that the ITP study found was that 17α-estradiol was among one of the substances that seems to perform well with respect to longevity (if not fully) when given later in life (this has replicated afterwards as well), contrary to some others which have the best effect when started in youth and continued until death. In theory I wouldn’t mind waiting a decade or two until we have a better idea of what is going on here, after which point I would hope we have more fruitful and actionable results (especially in humans); although at the same time there’s likely many reasonable and safe ways we can go about achieving this (hopeful) effect in human males (assigned at birth) already, either via a type of estrogen or an estrogenic drug such as a SERM.
It is worth reminding ourselves that 17α-estradiol is already present in humans, and in both sexes, with women generally having significantly higher levels, as one expects of estrogen. Similarly, regular estrogen binds to both estrogen receptors, including our target, which we now know to be the alpha receptor. Given this, is it possible that just taking regular estradiol (for example, estradiol valerate, which for most purposes ends up biologically equivalent to endogenous estradiol and thus also binds to both primary estrogen receptors) to increase the levels of estrogen is a potential longevity intervention?
This is a difficult question to answer with the data currently available, although there are millions of persons assigned male at birth that are already on various forms of estradiol for various reasons, one of them being to assist in gender transition from male to female. As the lifespan benefit only applied to male (assigned at birth) mice, there would be benefits to analyzing these cohorts for more information, especially if we were able to have DNA methylation clocks used on these groups alongside a control (although this would not be a true RCT, as which persons decide to undergo feminizing HRT would not be random, I suspect we could still get the information we’d want with a good sample size).
There are other potential avenues of statistical analysis that could be attempted here, although they prove to be difficult for various reasons. Most male to female transgender individuals decide to transition earlier in their life, and this was also a particularly uncommon choice to make many decades ago in comparison to the present, so we have very few deaths due to age-related causes that we would be able to analyze to attain a proper hazard ratio. Even if we waited a long time for this (or had this data already), it would be terribly confounded due to the lack of randomization and many potential selection effects. Even so, one of the following must be true:
17α-estradiol does not extend male (assigned at birth) human lifespan
17α-estradiol does extend male (assigned at birth) human lifespan, however this does not apply to most/any transgender (m->f) individuals. This could be due to insufficient dosage, insufficient affinity for the alpha receptor, the inclusion of 17β-estradiol, the common addition of other substances such as anti-androgens, or another unknown factors/confounders
17α-estradiol does extend male (assigned at birth) human lifespan, and this effect therefore does apply to most transgender (m->f) individuals, however we have either failed to notice it completely, or other effects/confounding variables ablate this, for example an increased risk of blood clots from estrogen supplementation (which depends greatly on the route of administration as well as type of estrogen used) or various potential side-effects from anti-androgen usage
Option one is certainly a possibility, as it always is in longevity when all of our studies are only in mice. We could differ too much from mice for the mechanism of action to apply to us (perhaps if it is related to metabolism or some newer subset of liver functionality), or if the mechanism of action is indeed the AMPK/mTOR pathways, perhaps 17α-estradiol does not modulate these in humans as it does in mice. This could have implications for other potential longevity agents such as metformin and rapamycin in humans as well, which also heavily involve these pathways, which could cause these agents to interplay synergistically or perhaps cancel one another out, as there may be no further benefit that can be gained after one of these agents is already taken at the optimal dosage. It is worth noting that many aspects related to AMPK/mTOR and DNA methylation are heavily evolutionary conserved as well (mTOR quite strongly, which is another reason why rapamycin likely extends human lifespan). We also already know that human females have longer lifespans than males for biological reasons, and that there are quite a few reports that the lifespan of castrated males is significantly increased. If 17α-estradiol (or estradiol valerate perhaps) does not extend human male lifespan, I would have to believe there is some other similar route that likely does, and we just have to find the best way to go about pursuing it.
Option two is, in my opinion, moderately plausible. It could the case that when we do have groups that supplement estradiol, the dosage taken is nowhere near sufficient for a noticeable longevity improvement, and that if we would simply increase it by some factor, longevity benefits would become apparent. There does seem to be a dose-dependent relationship for the longevity benefits in mice, and it may be possible that estrogen receptor alpha simply isn’t being agonized nearly enough. This may depend on the type of estrogen and route of administration used, as well as other drugs that may be taken (for example, most male to female transgender individuals take an anti-androgen as well as an estrogen, and this could potentially ablate benefits). My personal conjecture would be that estrogen monotherapy via injections would have the best probability of a longevity benefit for those assigned male at birth, although modulating or combining this with SERMs may also be of interest, although much more experimental and difficult to get right (I may add more to this later as this is a pretty interesting avenue to me for multiple reasons).
As for option three, it may seem difficult at first glance to think that millions of male to female transgender individuals are all currently supplementing a substance that may increase their lifespan by 5-20%, but yet none of us (or them) have noticed this yet. However, there are no preventative reasons for why this couldn’t be the case, nor statistical evidence against this possibility. It could even be that suppressing testosterone and activating estrogen receptor alpha are additive in nature, and we end up with a particularly impressive lifespan extension effect from conventional feminizing HRT.
Although I obviously cannot be sure of any specifics, I do think there is likely some hormonal intervention that should significantly increase male (assigned at birth) human lifespan, but that we just may need another decade or two to get the optimal intervention figured out properly. It would be great to have substances like 17α-estradiol in human trials already, as the potential ROI for successful longevity interventions is massive both in terms of billions of additional QALYs and trillions of dollars saved in healthcare expenditure.
In conclusion, 17α-estradiol might notably extend human lifespan for those assigned male at birth. There are many potential mechanisms of action that could cause this, with the most interesting one perhaps being activation of the mTOR and AMPK pathways, resulting in more ‘feminine’ DNA methylation. This longevity benefit, if it exists, may apply to many male to female transgender individuals, or could also be weaker or stronger for various reasons, such as due to the common usage of anti-androgens. If this longevity benefit does not apply to these groups, there may be alternative hormonal interventions that work instead, such as supplementing 17α-estradiol directly, using a SERM with a strong binding affinity in the right areas, or other modifications to the HPG axis that reduce some potential negative longevity effects of testosterone.
Disclaimer: I’m a random person on the Internet and none of this is medical advice. I’d like to rewrite and expand on the potential mechanisms of actions in this post and talk a bit more about what I do myself in this area some time too. Feel free to mention any corrections or comments to me (see: About page).
