Invest Like the Best with Patrick O'Shaughnessy - Tyler Cowen & Daniel Gross - Identifying Talent - [Invest Like the Best, EP. 277]
Episode Date: May 17, 2022My guests today are Tyler Cowen and Daniel Gross. Tyler is an economics professor and creator of one of the most popular economics blogs on the internet. Daniel is the founder of start-up accelerator ...Pioneer, having previously been a director at Apple and a partner at Y Combinator. Both Daniel and Tyler are prolific talent spotters and that is the focus of our discussion and their new book, which is called Talent. Please enjoy this conversation with Tyler Cowen and Daniel Gross. For the full show notes, transcript, and links to mentioned content, check out the episode page here. ----- This episode is brought to you by Canalyst. Canalyst is the leading destination for public company data and analysis. If you're a professional equity investor and haven't talked to Canalyst recently, you should give them a shout. Learn more and try Canalyst for yourself at canalyst.com/Patrick. ----- This episode is brought to you by Brex. Brex is the integrated financial platform trusted by the world's most innovative entrepreneurs and fastest-growing companies. With Brex, you can move money fast for instant impact with high-limit corporate cards, payments, venture debt, and spend management software all in one place. Ready to accelerate your business? Learn more at brex.com/best. ----- Invest Like the Best is a property of Colossus, LLC. For more episodes of Invest Like the Best, visit joincolossus.com/episodes. Past guests include Tobi Lutke, Kevin Systrom, Mike Krieger, John Collison, Kat Cole, Marc Andreessen, Matthew Ball, Bill Gurley, Anu Hariharan, Ben Thompson, and many more. Stay up to date on all our podcasts by signing up to Colossus Weekly, our quick dive every Sunday highlighting the top business and investing concepts from our podcasts and the best of what we read that week. Sign up here. Follow us on Twitter: @patrick_oshag | @JoinColossus Show Notes [00:02:38] - [First question] - Defining what talent is to them writ large [00:03:34] - The differences between means and ends in regards to talent [00:04:14] - What the Diet Coke idea is and why it’s relevant [00:06:32] - Types of energy that are valuable and the subtle differences between them [00:07:40] - Thoughts on using a moneyball-like approach to acquiring and evaluating talent [00:11:49] - The talent market and thinking about pricing talent specifically [00:13:14] - What is seemingly overpriced in today’s talent landscape [00:15:50] - Relationship between experience and/or age when it comes to talent [00:20:34] - Lessons about the utility of intelligence and where they’ve lead them wrong [00:23:35] - What’s beneath being an outsider and why it’s important [00:24:46] - Why what people do in their downtime is worth considering [00:31:41] - Things to try and get out of a reference call as an objective [00:32:40] - Disabilities and what lead them write that chapter specifically [00:35:01] - Whether or not talented people are happier [00:38:40] - Lack of contentment and it’s dynamic influence over individuals [00:41:01] - Where they think the other is most talented [00:43:33] - Thinking about the physical side of mental performance [00:45:49] - What was frustrating about writing the book [00:48:25] - How they evaluate talent most differently now after having finished the book [00:50:41] - What makes for a good bat signal and how to cast one well [00:53:27] - Personality inventories and what they would and wouldn’t recommend [00:54:15] - Geographical frictions and their role in high success rates [00:56:08] - Antonio Gracias; Existing supply constraints on talent development [01:00:01] - How they would redesign the current attractors of talent that we rely on today [01:01:18] - Assembly line development and how we can improve and scale talent filters [01:02:29] - The biggest open questions for talent today writ large [01:05:16] - The kindest thing anyone has ever done for Tyler
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That's BREX.com slash best. Hello and welcome, everyone. I'm Patrick O'Shaughnessy and this is
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My guests today are Tyler Cowan and Daniel Gross.
Tyler is an economics professor and creator of one of the most popular economics blogs
on the internet.
Daniel is the founder of Startup Accelerator Pioneer,
having previously been a director at Apple and a partner at Y Combinator.
Both Daniel and Tyler are prolific talent spotters,
and that is the focus of our discussion and their new book,
which is called Talent. Please enjoy this conversation with Tyler Cowan and Daniel Gross.
Tyler and Daniel, I just a few days ago finished your fantastic new book on talent. I think it's a
topic that everyone is implicitly interested in and is incredibly important in the modern world.
And I think we have to begin our conversation since we'll go into lots of facets of this topic
with some basic ground leveling definitions. So I'd love for each of you, maybe Tyler,
starting with you, to just give what your definition is of talent, having now investigated
this topic so much so that you're able to write a book about it. We treat talent as having a creative
energy that can alter outcomes and make projects better in ways that matter. Daniel, would you define it
any way different? I think it's very related and thank you, of course, for having us on. We're honored
to be here. I think it is the ability ultimately to positively manipulate whatever current
environment you're in to achieve your desired outcome. There's many different ways of doing that.
Some people do that by intellect. Some people do that by charisma. Some people do that by physical strength.
But that is ultimately, I think, the basic definition of talent.
How do you think about the difference between means and ends when it comes to talent specifically
if both of you mentioned something kind of around the ability to shift the environment
in which you're in or affect some end, some goals, some outcomes, some achievement?
Maybe others are just really good at doing something.
They're talented at something without a goal in mind.
What did you learn or think about means versus ends when assessing talent?
I look for people who really value the means.
So if someone says to you, I want to be.
be the best drummer of all time. Well, that's definitely better than no ambition at all. But I actually
want to hear someone saying, I love to drum. And that's the person who's more likely to become the best
drummer of all time. Daniel, I'm curious what you think about this idea of Diet Coke. I asked for
strange theories or little things that you discovered as ideas. What is this Diet Coke idea? And why is
that relevant? I was just saying, I think it's a kind of interesting and abstract that you have
Elon Musk, Bill Gates, Lawrence Summers, John Carmack, all these different kinds of conditions.
across very different spectrums who all have at some point in their life, and some of them,
even to this day, seem to be guzzling Diet Coke. Like if I told you in abstract, there was a secret
black potion that no one knew the recipe of that was made in Mississippi that Titans of Industry
seem to drink. You'd say, well, maybe I should drink that too. Now, I know everyone's dietitian
told them don't have Diet Coke. It has aspartame and whatnot, and it's extremely chemical, but I don't
know. It seems to be working really well for these people. Well, you might say the rest of the country
also drinks Diet Coke, too, so I'm not sure how valuable that is as a metric. The more important,
interesting thing we were talking about before that the Diet Coke idea is getting at is just raw potential
energy. You come into our book and its podcast and more broadly wondering how to assess
talent, what to look for in people, how to get better at that. There's all sorts of frameworks
one can throw at with all sorts of fancy words and acronyms, Myers-Braves, MBTI, the Big Five Aspect
Scale. And those are important. We can maybe talk about those if we want. But the real thing to look
for is raw potential energy that someone has. There's something I find interesting about vigorousness
and vitality of people that seem to be consuming all sorts of chemicals, compounds, whatnot,
and it seem to be fine regardless versus someone that's very careful and specific about what they do,
don't want to have caffeine before bed, whatnot. The flip side, you meet the top salespeople at a certain
company and whatnot. And they're just pushing forward. They're having a double espresso after dinner.
And I find that sign of physical health and stamina to be something to look for that I think
people don't focus on that much because it's not that intellectually clever or cute.
But I think it's just a very basic thing.
If you recruiters I work with, first thing I ask people to do, they bring me a long list
of candidates and they're going to have to go through all sorts of the different signaling
mechanisms you get, like who went to what school and whatnot and who has a better get-up
profile.
I just asked some of your top three people just by energy, who is the most energetic person
to talk to?
And I think if we take our previous definition of talent and reapply it here, someone who just has
energy to try in many different ways to positively manipulate the universe to do their bidding
is just going to have more shots on goal.
I was going to ask you to quantify or discuss the nuance around energy because there's ram down
the wall energy.
There's subtle ever-present energy.
Tyler, in your mind, what type of energy is valuable as you think about talent?
People who always want to get to the next destination and achieve something.
And they're very focused on that.
And one reason why I tend to agree with Daniel on the Diet Coke question, Diet Coke is something
you can almost always get a hold of in the Western world. So if that's your fixation for your nervous
energy, you're not going to be frustrated that often. You can always get a Diet Coke.
So at some mix of extreme habit formation, a kind of impulse within yourself plus caffeine is how to model
that. And if you think, well, how many substances fit all of those three markers? Actually,
Diet Coke probably would seem to win. When I used to play chess when I was much younger,
The thing I would look at is, how does the person pick up the chest pieces? Do they seem energetic in their moves? Do they seem focused? Do they seem like they give a damn? In most areas that are quite non-physical, you can find physical parallels that you can look at to get a sense of energy, attentiveness, and focus. Even the non-physical world is intensely physical, as I understand it.
I think it's obvious why talent's an important topic, because especially in the symbol manipulation world that we live in in the world of business today, talent is outcomes. In most companies,
companies, especially modern technology companies. So I think it's obvious why we would want to search for
talent. My hesitance to go straight into the quantitative is important because I come from a quantitative
background. I try to jam everything through this lens. But I'm curious what you think about the sort
of moneyball-like approach to talent. Having investigated, Daniel, you listed off some of the
famous personality inventories. Can this be quantified? What is your view here? Are there useful
tools for us to say quantitatively, this person's more talented than this person? Or do we really need to
stick in the qualitative realm? I would say three things. First, I think the field of social sciences
has a lot to be discovered. I really think we are probably at day one. Our understanding today,
using the frameworks that people talk about in research and literature, as far as I can tell,
and Tyler, we'll know much more about this and we'll have some color in a moment, but we're really
staring at 1920s film. This is not 4K Marvel cinematic universe stuff. This is like really
low, low resolution stuff. In fact, we're trying to take an incredibly high resolution image
which is someone's personality and predicting how that actor will work in different environments
through a very, very, very now of constraining lossy compression filter called the Big Five Aspect
Scale. So it really does not capture a lot. It is what we have. And I know that statisticians will come in
and say, well, you know, we have all these surveys that show that there are a big five personality
traits and they don't correlate, but I really tend to not believe that. So I take one, the tools that
we have are incredibly coarse. You can kind of get a sense at the end of the day that it's much
more subtle because if you look at what machine learning does in other fields, like say, with
TikTok, you realize there's more than five graphs on TikTok. So there are more than five
different macro personality types. And that's just a bad way of thinking about things.
Second thing I'd say is outcomes measuring people by the outcome in the previous work they did
because our tools are so coarse, I think is a far better way to do it. So feel the software engineering
where I have the most experience, just looking at the code someone's written is going to be far
more predictive, I think of any type of IQ test or psychometric tests are going to get them.
And the really nice thing in the software world, by the way, is a lot of the code happens
out there in the open. You can actually figure out who the best software engineers are in the world
in open source, quantitatively, actually, just looking by their code. So I'd say if there was an
interesting quantitative thing to look at, it would actually be the proof of a work. Now, not everything
works this way. Obviously, if you're a physicist at Stanford, it's not the same as looking at your
C++ code. But assessing the prior body of work, I think, is far richer a thing to look at, and
pine on, then the results on the test. And the last thing, the final thing I'd say is fundamental
constraint, I think, of all personality tests, not IQ tests, is that they're all self-report at the
end of the day. These are people assessing their own personality. Obviously, you have gaming issues
where someone's assessing the personality they want to be as opposed to where they are. You have also
people just repeating the same test throughout the day, delivering you completely different results.
So I think that field is interesting. And I know I said three points, but maybe one final fourth
point. I think they are probably helpful in the way that they provide vocabulary for a team.
It might be true that you never want to use psychometrics really to measure anyone in your team or forget who to interview, but it's probably also helpful to have everyone on the team understand when you say openness exactly what you mean. When you say conscientiousness, exactly what you mean. They provide a language, and that is quite powerful. I think language was probably the original technology of our species in scare quotes. Tyler, I don't know if you have any related color to add on that or maybe disagree entirely. I would follow up on the money ball example. I'm a big believer in the best metrics. And sports has a lot of the very best metrics.
But the problem is, other people learn them. So Moneyball only worked for a few years or in the NBA
for a while. Three-point shots were underrated. That hasn't been the case now for decades.
So you need to learn those things that your competitors aren't learning. And over time,
those become more like a form of appreciation, almost like art or music appreciation.
And the NBA, the frontier question is, which of these tremendous athletes is actually going to
be a knucklehead and which will be a team player? And that's what you want to learn, because you've
measured everything possible. You have all the tape. So if you just stick with metrics, you will end up
behind your sector because those are easier for people to copy. I'd love me to riff, Tyler, on the pricing
of talent. If you think about it as a market, as you said in the NBA, the whole idea here was to
get talent for cheaper than what should be its market price. And there's an arms race there. Just like
in quantitative investing in public markets, signals have a half-life, generally speaking,
with maybe some exceptions, but in general, the signals have a half-life. So how do you think about the market
for talent. And if that is the goal to be able to hire people at the best price or at the right price,
how this should sit inside of a company. If a company is mostly going to be driven and thrive
or die based on its talent, how should a company think about the pricing of talent specifically?
In the talent literature, there's often a big confusion between what is good in absolute
terms, smarts, work ethic, conscientiousness, of course, and what is undervalued in the marketplace.
And if you simply pursue those things that sound good, like smarts and conscientiousness,
unless you have a comparative advantage at getting the smartest people to work for you.
So maybe Harvard has that comparative advantage.
But most of the rest of us do not.
So you have to look for the differential factors that you can either spot better or recruit better.
And those again tend to be more subjective.
So does the question, how readily can a person figure out his or her role on a team?
Much harder to measure than smarts or conscientious.
It's an area where you might retain some kind of enduring comparative advantage.
So not to confuse absolute importance with what's underrated.
What do you think is most overpriced as a dimension of talent in today's labor marketplace?
Depends on the job.
For lower level jobs, everyone's looking for conscientiousness.
It obviously is important.
But if you're trying to hire away conscientious people from other organizations, the organization
knows they're conscientious.
They want to keep the good ones.
They let the lemons come to you.
So I would just say, be very careful when chasing after conscientiousness for its own sake.
Get without at all denying its absolute importance.
Daniel, what would you say?
One thing I've observed in both founders that I've had the honor and pleasure I guess I've
working with as well as just hiring people on my team is that you have a consensus mechanism
for hiring talent.
You end up optimizing for very even-keel people.
The most important thing to pay attention to the most kind of mispriced people, so to speak,
are ones where people on the team vehemently love them and vehemently hate them, because you often
get outliers in more than one dimension. You'll have people that are a typical example,
like incredibly productive but difficult to deal with, people that are incredibly extroverted and
fun to deal with, but very, very bad at dotting the eyes and crossing the T's.
Consensus mechanisms don't end up hiring those people because it's a bit painful to push through,
but I think those are the most important people. The best way, I think, to go about that is to have
an organization where you can structure it such that the Vaughnoyman is only doing math and it is
not doing any HR. Really, really focusing on specialization is good. And that really broadens your
lens because you can now start to think of, who can I hire that somewhat actually disfigured
in some ways and just have them focus on one specific thing. When you find those people and you can
get them out of the general big organization that they're in, if they're stuck there, it's usually a
great blessing for them too. Your prototypical example is the engineer that's really, really good,
but stuck in the cogs of a large company and you just let them go at a five-person team and they cut
through red tape and it's really amazing. Those people often again, when that company grows,
they don't work anymore because there's much interfacing with other people and they need to find the
next small team. Just searching for unevenness I think is really helpful and people don't do that.
I feel much better about a hire when I know what's wrong with the person.
Exactly. And part of the paradox, the people bringing me the hire just want to sell me on the person
and that's the wrong attitude. I try to beat that out of them a bit. I'm like, well, tell me why they're a
good match for us. How were they screwed up? How were they uneven? And then possibly the mental picture
can click. Once hired someone who on paper was perfect, in the interview was perfect. He showed up,
really just did no work, period, did nothing, had no ambition, really, had multiple advanced
degrees from prestige schools. It was a mistake. And ex-ante, I couldn't answer the question.
What's wrong with this person? Why does he or she want to work with us?
What do you think the relationship is between experience and or age and talent?
It's going to depend on the sector.
So if it's chess players, you can be washed up at 35 or 40.
But if it's novelists or philosophers or, in fact, people hiring talent, you tend to get
better at that with age up until some extreme point.
So a lot of the advice we give, it's highly context specific.
You might just want boring semi-low energy people if your product, say, is life insurance.
Can't take too much risk.
You're highly regulated.
Maybe you have some kind of favored market position, just to keep the ship moving, in essence.
So it's going to depend.
If you think about talent, back to that absolute versus relative, so you could be talented at a small, mid-level job.
But I think the talent that we're all interested in is people that are going to make some sort of strange, large, orthogonal impact on a domain around them that they're interested in.
What about then?
And do you think that age for someone that's going to make a massive impact, is there any evidence that you want them to start younger, that you want to back them when they're younger and less experience because they're less tainted by the normal ways of doing things in a given field?
Is there anything there if we're thinking just about talent as measured by like huge impact in building something new?
Of course, people live too at this point say most founders are young and then Juniper Networks and Jim Simons from Rentech and all these people that started their career actually relatively later on in life.
So I think there are examples both ways. I think it is a fair statement that by and large,
if you had to average the age of successful tech founders, you would school young. I mean, that is just the truth.
Now, part of it is that those people don't actually fit into any other part of society. So it's not something innate with the youngness,
although I think there's definitely something there. But also, these are outcasts that got fired from large companies,
didn't fit into college left. God bless the internet, because it provides not just a great employment opportunity for these misfits,
but also a way for them to make incredibly successful companies and obviously impact on the world.
You definitely have the flip side, though, in areas of management, say engineering management as an
example, a lot of the job is pattern recognition, both in the type of person that you're dealing
with hiring, I've seen that type of person before, seen this type of situation before,
and infrastructure decisions. The early stage companies with the early 20-year-old founder or whatnot,
I'm saying this as someone who was. I was very young when I started my first company.
You tend to succeed in spite of the age sometimes, not because of, because you make terrible infrastructure
decisions. You have no infrastructure taste. So you're just trying things left and right. You go through
nine different decisions where someone who's seen something before usually just helps you go to the
best path. Sometimes the best teams are one where you have a relatively young founder and one or two
people on the executive team that have seen things before now common. Pitfalls here is obviously you don't
want a bunch of suits in the room. The old Steve Jobs quotes, everyone's heard, whatnot. But it's helpful,
I think, to have a balance just because there are roles where taste matters. I used to work at Apple,
used to run searching machine learning at Apple. And one thing Apple thought of that I thought was
interesting, there's this little pamphlet I got at some point of basically why I'm not a senior
vice president. And the responsibilities people have all the way from the lowest rung of the organization
to the CEO. And the way it was constructed is the cost of making an erroneous decision,
how long of a time would take Apple to recover from that? A engineer, rank and file engineers,
maybe three to four hours, slightly more senior engineers, maybe a week. Managers, maybe two
to three weeks. A director is maybe a month or two. A vice president is two or three quarters.
And all the way up to senior vice president's two or three years. And if Tim makes a strategic error
could be a decade until Apple recovers. I think that's a good sense of also when you want a care
of age. How large is the penalty of making a mistake? You would certainly not want your
neurologist or anesthesiologist to tell you, hey, I just got into Ycombinator and I read a few good
Wikipedia articles and I'm ready to go. That's another helpful way to think about age, is basically
the cost of an error. For all the talk about youth, I still think that something like 14 to 19
year olds remain underrated. And in particular, I'm thinking about the realm I work in, which is
the world of ideas, where if you get something wrong, it can just be ignored. You're not throwing
all of Apple, of course, and that if you want to shape ideas that you should be talking to,
writing for, spending time with, people in that age bracket, 14 to 19, they're so smart,
they see things afresh, they're willing to take chances, can be just full of energy.
And I think the rest of the world still doesn't see that.
They put out their papers or their books for someone who's 47 years old and might review their book.
I mean, that's fine.
I'm not that those people don't matter.
But they don't quite grasp that some kid who's 16 is smarter than they are.
And that's the person who's really going to matter.
So I think we're still underrating that in many areas.
And finance and tech, in particular, music, chess, those are mostly the domains of youth.
All of those make me think of intelligence, just raw intelligence.
And so I'm curious what you learned about the utility of IQ or other measures.
I'm not terribly familiar with measures beyond IQ and their relationship to talent.
I'm thinking of David Rubinstein at Carlisle Group, who told me a couple weeks ago,
very often the biggest problems were the highest IQ hires that they made.
So there's an interesting question of should hire IQ be founders versus employees or managers.
But what did you learn about IQ and its usefulness or where it may steer you wrong?
I think it's very often overrated.
So for many jobs, you have to be at a certain level of smarts, but above that level,
it doesn't correlate well with success.
Let me just give you two statistical measurements.
First is a study of Swedish CEOs of the larger Swedish firms.
The median Swedish CEO is at the 83rd percentile of IQ, which is pretty good, smarter than 83%
of the rest of the Swedish people on average.
But it's not exceptional.
Before doing all the work for this book, I might have thought, well, that's going to be 95,
95, 96, 97, for a lot of them 99. But 83, it's a little underwhelming. Here's another number.
Lower in the distribution. If you move someone from the 25th percentile of IQ up to the 75th,
that's a big leap, 50 percentile points, they will on average earn 10 to 16 percent more.
Okay, I'd love to earn 16 percent more, but that's it. So smart people in particular,
I think they significantly overrate IQ with the caveat that for a whole,
whole bunch of jobs. Yes, of course, you have to be above a certain level to do it at all.
I think that's right. I mean, these things tend to go in waves. If you listen to the Radio
Lab podcast of the early 2000s, their G, IQ is like a big deal. And now I think we've been
talking about it so much. We're in this countercyclical wave. We're kind of realizing there
are limits to the returns of focus on IQ. And I wholeheartedly agree with everything Tyler said,
with the caveat that I think anyone certainly in this podcast recording that we're on, but also
anyone probably listening to the podcast exists in a very special world where most of the people
they're surrounded by are very intelligent. When you leave that world, you realize there is a
baseline of IQ that matters quite a bit for the roles that we're talking about. Productive employment,
I think is possible at many different ranges of IQ. But for top tier talent, there is definitely
a baseline that matters that if you don't have, it's going to be difficult. I think it is probably
on the margins to something that people might focus on maybe too much instead of too little.
I think there are also some jobs that fit what I would call the multiplicity.
model. Take someone like a Bill Gates. Someone like that has to be in the very top tier of at least
seven or eight different qualities. One would be energy, another would be work ethic, another would be
IQ. And if even a single one of those falls away, Bill Gates can't be Bill Gates anymore.
Those typically are very, very high-level jobs. We've heard of the people who hold them.
And there, I think, a super high IQ is just an absolute prerequisite. But so are seven or eight other
things. In the marginal sense, it's not only IQ that matters absolutely. You've referenced this idea of
outsider or outcast or somebody that rejected some institution that they were in. How important is all
of that? What's beneath that as an interesting variable? Is it some set of early experiences? Is it a
personality characteristic? I guess it's sort of a nature and nurture question on outsiders and why they're
important. If you're an outsider, you take more chances. You're not surrounded by peers who want you to do a
specific thing. I think that's super important. If I think of the chances I took in my own career
that worked out very well, a large number, maybe all of them stemmed from the fact that I'm at
George Mason University and not Harvard. And what's expected of me is simply something totally
different. I'm allowed to define that for myself. No matter how independent-minded you are,
it's very hard to avoid conformism and getting locked into playing and winning a status game that
maybe isn't the game that can matter. So if you're at Harvard, you want to publish a great number of papers
and high-impact journals.
If you're talented, you can do very well at that.
But for a lot of people, it's a dead end in terms of actual influence or improving the
world.
And people from other places, on average, they're going to do much worse.
But some number of them will just do totally different things.
And they're not worried about, hey, what will my buddies at Harvard think of me?
I'd love to turn to the notion of evaluating talent.
Obviously, you've both done quite a lot of this and studied how others do it.
I've got a few topics that I'd love to hear what you learned as you investigated them.
Maybe the most interesting to me is this investigation of downtime, like what people do in their
downtime. I'd love you to outline why that's interesting and very specifically how you pull it out
of somebody. If you're interviewing them or doing a reference check or something, talk to me about
the utility of this variable. It's kind of similar to this idea of why looking at someone's prior
body of work is a bit better than a test, meaning given the universe of available options,
the real test is what you decide to do every given second moment and how you weigh your
opportunity costs. It's exceptionally interesting, of course, to ask what people do when they don't
have any particular obligations. So they're downtime. The movies they watch, the activities they do,
the books they read. You can just ask people what kind of movies, TV shows, books, subreddits,
links you find interesting. Tyler taught me which I think is a wonderful idea. There's many layers
to thinking about the answer. But the first layer that's quite important is looking for specific
answers instead of just generalizations. You ask someone about their favorite movies.
It's really helpful if they say, I really like The Matrix, I really like Pulp Fiction,
I really like Catch Me If You Can, versus action movies and stuff.
There's something about that, the person who's able to articulate specific proper nouns.
So that's definitely one baseline thing to work on.
Tyler, what do you think?
This is really an area where you're the master of this domain.
If the key thing you're trying to learn is how does the person work together in teams,
small teams, everyone is prepped with their examples of how great they are or the mistakes
they learned from, but ask them about a sports team, if they know basketball, the Los Angeles
Lakers, why didn't they do well this year? Now, you're not testing them about the knowledge of that.
You want to pick something you know they know, and they feel confident about. But if you get
vague generalities, like their morale was low, well, okay, it might be true, but what exactly
went wrong? Or if they know movies, well, in Star Wars, Luke Leia and Hahn, they seem to make a lot of
mistakes. What did they do wrong? Did they listen to Yoda too much? Like, talk me through that.
they can't prep for that kind of question, and you get their understanding of personal dynamics.
If they read a lot, ask them about their favorite Shakespeare play, Lady Macbeth, how evil is she?
What was her big mistake?
Whatever you think they can speak to and see how well they can speak to it.
And you want to look for the questions.
How well do they understand the hierarchies at work in the situations they're perceiving?
What kind of resentments come out when they're talking?
What level of detail can they show?
and how varied and complex is their understanding of other human beings' psychological mechanisms.
It's very hard for someone to fool you with that kind of test.
Is this all a study of their curiosity?
Is that what it boils down to?
That too.
So you can test their curiosity by seeing how many different areas they can talk intelligently about.
But surely they ought to have one.
Like you want to let them pick the area.
You have to know something about it.
But you're not testing their knowledge base.
You're testing how well they can think about what they know best.
Tyler, do you have a favorite on-ramp question to get into this part of an interview with somebody,
like a way to get down this path that you ask often?
I'll look at their age and where they're from and whatever clues I have.
And it could be books or movies or a travel spot or a sports team.
I'm comfortable with any of those.
Again, I'm trying to cater to their expertise.
It can't be something I know nothing about.
I can't say, well, who's the greatest player in Canadian curling and how does he train?
Right.
It's harder for me to draw information from that.
but I've hardly ever met a case where I can't ask them anything. Sometimes some other cultures
it's harder, Nigeria. But even there, I'll talk about the Kootty family, who were the generationally
best performers and why, and how did they organize their groups? There's always something.
When learning about somebody, it's become very popular to say that interviews are maybe necessary,
but not all that useful, whereas references can be incredibly useful at getting to know the underlying
person. To what extent do you both agree with that concept? Do you value references in the
is very much if you're trying to back somebody or invest in them or hire them. It's a specific context. But
do you think that references is an art that's way more important than actually interviewing and
getting to know the person directly? And if so, by how much? I think the correct answer is definitely
references are useful. One of the things Tyler, I think, asks people, not necessarily in interviews,
but in general is what one's equivalent of playing scales is. So if you're pianist, you can sit in front
of the piano every single day and play scales and just get better and better and better. And so finally,
you go to Carnegie Hall, you step in on the Steinway, and you play Moonlight Sonata and it all works.
I think a different field is an interesting question. What is the thing I can do every day, where I can just compound?
And one, in I think the particular area of talent is actually building a network in your field.
That is a compounding activity because that increases the value of the reference that you're going to get.
The signal that you're going to get from a reference is strictly a function of just how close you are to that person.
And obviously, the closer you are, the more honest to read you'll get.
And there's all sorts of things you could do.
You could force them to stack rank the individual somehow.
On the scale of 1 to 10, how good at Bob was at software engineering is a good question.
And then when they say eight and a half out of 10, you can say, well, why is 8 and a half the right number for them?
And that kind of gets a little bit of alpha that's kind of helpful because they might say things that aren't just effusively positive.
You'll just get more signal if you know the person better.
It's actually a very helpful thing is to have you or the recruiter and your team have a very, very strong network somehow.
Because references, yeah, are earlier we made the case that their prior body of work is really the best way to evaluate someone.
And us neurons have like code you can look at.
But in all honesty, all roles are interpersonal.
References are just their body of work in quotes that they've done, how fun they are to interact with.
The other final little anecdote I'll say about references is it's always a great opportunity to use that as a way to source candidates too.
People don't take advantage of this.
But let's imagine you're looking to hire someone to be a engineering manager of folks on your quant fund.
You're now on the phone with that person's manager, say.
And so it's an amazing time to both, A, try and hire them if they seem good,
but B, just ask them, who else would we be talking to?
It's a small trick I've used to grade advantage over the years.
I think references are essential for jobs requiring a lot of conscientiousness that are mid-level.
And then they absolutely rule.
But especially if you're looking at very young people, I find references not useless,
but why should you trust their judgment over yours?
say someone who's a teenager. Who is that you think they know that has better judgment than you?
I think also for creativity, do their references have a high enough level of creativity to see
this person's creativity? I mean, they might, but you certainly shouldn't assume they do,
again, especially for the young. A simple thought question, say Mark Zuckerberg at age 18 or
Peter Thiel at that age, what are their references like? They're probably not negative,
but the people they know at that time, are those people good enough to see how good like Peter
and Mark would become, highly unclear. So there's some irreducible side of the equation,
especially for creativity, especially for the young, where you have to use your own judgment.
And if nothing else, you're ending up having to assess the referring person. So why not just
assess the candidate himself or herself in those cases, but do both? Do you think that there
are any beyond this idea of prior work and using the reference as the best way to understand
prior work for a lot of people? Is there anything else that you recommend people listening,
try to get out of a reference call as an objective?
Making the referer feel safe to criticize, which is very hard to do.
I wouldn't say you need to trick them, but you have to go overboard and ask something like,
would you work with this person or could you, in a ranked quantitative sense, compare them
to other people I might know?
You have to really force their hand to get a slight downgrade of comment and then take that
seriously when you hear that downgrade. And the amount you have to work is strictly a function of
how well you know that person or how well, you know, the friend that referred you to that person.
I think there's some type of composite function there. One of the interesting chapters in the book
is about disability. I find this area really interesting as it pertains to talent. We talked about
specialization a little bit already. What did you learn about different kinds of disability and their
relationship to talent, maybe to start with a simple one? The concept of ADHD comes up. I don't
know if you would call that a disability or not, but it's something that comes up a lot,
certainly in my world. And very often, some of the most successful people have this condition
and they've figured out how to control it or hone it or pointed at something specific.
What did you learn about disability and what led you to write that chapter specifically?
I would say what we call disabilities very often or not, maybe sometimes they would be
for your entire life. But in the workplace with division of labor, you can be more obsessive
have a very specialized talent. People with ADHD, often they hone it and they use it to propel
themselves forward. So one version of ADHD might be, well, you can ever finish a book or finish
a thought. I think that's less likely the case. If you use ADHD with, well, I'm done with this diet
Coke. I want another. I'm done with this page. I'm going to turn the page. I'm getting bored with
this book. So yes, I'm going to finish it, but I want to make sure I get to another book. It becomes
a positive, propulsive mechanism. And it's a high variance thing to have. But I think, again,
On average, it's correlated with success, not failure.
What about more extreme forms of disability, whether that's something like autism?
And again, maybe the same answer that you gave for ADHD in some ways.
But what other forms of disability are interesting as it relates to talent that you studied?
Extreme is a hard word to you.
So Elon Musk gets on Saturday Night Live and says he's Asperger's, which is essentially the same as autism.
He's the most successful, greatest entrepreneur of our generation.
Again, I don't know how happy he is.
but you need to take that seriously.
My goodness, look at what he's done.
His command of engineering is phenomenal, his ability to achieve, be out there in the public
arena, create memes, everything.
My goodness, how many major companies has you been a part of?
So I think high variance is the model.
It's not that everyone with the so-called disability is actually a superperson, but it's
assigned to look more closely.
What could this person do for me?
And because they might be weird or come off as weird, the chance you can hire them
is actually probably much higher.
If you understand what they're about, they may need some kind of special accommodation.
Well, we understand you, we'll give you that.
Your chance of recruiting them is higher too.
Do you think there's a relationship between happiness and talent?
Do you think very talented people are less or more happy?
That classification of happiness, type 1, 2, 3.
Type 1 is happy in the moment, going down a roller coaster ride for those leg roller coasters.
Type 2 is you're on a hike.
It's tough.
In hindsight, you reflect positively on it.
But in the moment you wish you could stop, type 3 is just, well,
just sucks both ways. My sense is certainly successful and I think talented people are more of the
type two happiness. I actually don't think Elon has in the moment an amazing life. I think he's going
to have years and decades and probably centuries of positive reflection on it. Look how cool it was.
But I think when you're at that last stage, what is it, the tending step on Everest and you're just
trying to make it to the top and not die. I don't think that's fun at all. I think the average day in Elon's
life is, there's a lot going on. I don't know how pleasurable it is. So maybe there's a difference
between happiness and pleasure in that sense. It's also not clear to me, and this is more of a
personal observation than one speaking that on behalf of literature, how much striving for happiness
is the exclusive thing one should be seeking. I think that's a very kind of Buddhist idea.
I'm not sure that actually gets you to happiness, so to speak, meaning I've often, if you really
strive for like constant pleasure happy, you do get a lot of type one happiness, but I'm not actually
sure how long that lasts, the circuitry in the brain is very much triggered not to want that 24-7.
So even if you're on a roller coaster every day, by the 10th day, it's not that exciting.
It's a bit of a meandering answer.
One final thing I will say, which is I do find talented people's default state, many, not all,
but it is something to look for.
Their default state giving, say, the same set of inputs, if you could say the same set of stimulus
to like 10 different people and whatever that you want to define stimulus as a series of Gmail messages,
some good, some bad, hike, whatever.
The default optimism I find talent people have is a bit greater.
The belief that things will be great, things are great, things will continue to be great,
that does seem to be a bit more present.
What I've always wondered is to the extent to which that is a biomechanical mechanism,
as opposed to it being something psychological,
I really do wonder if it's just a sense of liveliness and vitality.
And now we're really going off the rails.
But to what extent are folks that are just not happy by default,
to what extent is that something physical, some type of vagus nerve biome thing. And you certainly know
as an extreme if one is actually sick, if you have the flu, you're not happy. That's an extreme.
If you sleep really well and it's a great day and there's sunshine outside, you are happy.
Maybe that's not a zero to one. Maybe it's not a binary continuum. And so maybe you can be like
one percent of just sick. Maybe some people are like that a lot. There's all sorts of wacky evidence
to indicate the fact. But that's often what I really wonder when I meet people that are kind of morose
all the time is the extent to which I'm not a psychologist, but I really do wonder, is that really
some childhood trauma, whatever thing? Or is it something physical in the body that's driving the
mind to predict lower odds of good scenarios and higher odds of bad scenarios?
I would put it this way. I look for a positive sense of agency, ability to experience and
enjoy flow, and the person not being that content, that trifecta together, I think.
think is very powerful. I would second Daniel's remarks on the physical. And I feel this myself.
If I'm trying to write something, my body has to be able to squirm in the proper way for me to get
the writing done. And it doesn't make any sense. And I'm not saying it's the same setup for everyone.
But each person has his or her physical requirements. Are those satisfied in the person? Can they be
satisfied? Does the person understand how to mobilize them? Those are good questions.
Say more about the lack of contentment as your third thing that you said there.
Is this just something that we're unsatisfied at the presence or you're sort of compelled to continue
in exploration? Is that the general idea? What is it about contentment that's important or lack
there are, rather? For leadership roles, it should be there's never enough. It's partly something
that feeds into charisma, but it's also a belief you want for its own sake. If the person can be
made happy by some set of achievements, that to me is definitely a negative. Should never be enough,
a kind of restlessness, never happy enough with themselves, always questing for the next
thing, the new thing, the higher level. It depends on the sector. But it ought to be something
where there's not a plateau. When I was in Beijing as a ninth grader, there was a group of people
outside our hotel that were doing Tai Chi every morning. And at the time, I did a bunch of karate
and karate you do these cataas where you memorize moves and then perform this thing. I watched
them and then I tried to join them and an older woman slap me on the wrist and said, you know,
at your age, you shouldn't be doing Tai Chi because it will kill your ambition. You won't want to do
anything else. You'll be content and that's a problem. Does that spend?
speak to you at all. Do you think that? Absolutely. But that seems like a good thing. I'm against good
things. You're against good things. Say more. It's partly in jest, but the notion of a good thing is a little
too complacent for me. It's a challenging thing. And maybe in a deep way that makes you happier,
but don't focus on the happiness. Focus on the process. Focus on the thing. Focus on your quest.
Maybe you'll end up happy. Don't think too much about happiness and be suspicious of people
who think a lot about unhappiness. I think often they're miserable.
and they wallow too much in something or rather, and they end up as complainers.
Tyler, from the cheap seats, you seem maybe content's the wrong word.
You seem extremely enlivened by the things that you do, intellectual investigation,
conversations, writing, ideas.
Is that not contentment?
What am I missing there?
Well, I always want to do more.
Typically, I've always been starting some new project, but it helps me maintain a very high
energy level.
Let's write another book.
Let's do another podcast.
The old Ernie Banks sang, let's play two, right?
He meant double headers, but it's a general idea. It's part of my life philosophy. Let's play too.
It's interesting. Before we have recorded, I said, what's a book that is your favorite looking
back and you said the next one. So it stands up pretty cleanly.
But I asked Daniel about me. He'll give a better answer than I would or ask me about him.
Yeah, what do you think? What do you think, Daniel?
Well, I think Tyler has a very unique ability to consistently produce writing output,
which I think is a more mature version of the same mind that excelled playing chess early on
in life. It's a very taxing cognitive thing to do. Most people have the dread task of, oh, I need to go
write the thing. And maybe I'll get to that tomorrow, not today. Tyler's the opposite mode of that
where he's effectively writing every day. So I think that is a mixture of mental stamina and mental
ability. It's an interesting question for someone to ask Tyler that I've certainly asked in the
past. You have that experience where you're writing something and it starts out good. And then as
you're writing, realize halfway through everything I wrote doesn't make sense. And that original point
actually didn't ever connect to us. I'll get back to it tomorrow. But he's working through that puzzle
every day, which I think is very impressive. It just takes a certain sense of fortitude. In reality,
probably the most interesting thing is the fact that I don't think it's a huge kind of
jaco-willing David Gaghan's struggle for him that he's pushing through some type of
courage and fortitude and attaboy stuff. It's the thing it kind of happens. And when you meet people
who are really excellent in a particular field, I always find it fascinating where some of them are
just not trying that hard. They just are. That photo of Usain Bolt running that nine second smiling and
making it look easy at Kipchoga, breaking the marathon record, also making it look easy. There's a related
thing going on there, which is people that truly excel at something. They're not trying that hard.
They just are good at it. Tyler, how do you see Daniel as most talented?
Combination of things. First, an extreme intelligence from birth, which is important for him,
but a willingness and desire to see things differently and see and articulate an angle to
a problem that the other very smart people around him just do not see. So on the surface,
he's relatively quiet in a group, but is thinking more, calculating more than the other people
there, and will come up with something they haven't thought of. And then he combines that with the
desire and ability to build something from that. So not just, well, I saw that, people like that on
Twitter. Oh, I'm so great. But it has to be converted into something quite tangible and
physical. So I think the physical is a big part of Daniel's excellence. He's run marathons in Antarctica.
That's not an incidental fact about him. What he's trying to do with those smarts, assessing
projects, people, is to turn it into some real-life equivalent of running the marathon in Antarctica
and his ability to integrate the software of his mind with the hardware of the concrete ambition.
I think Daniel's just an A-plus. How's that, Daniel? Pretty good. It's a great excuse to talk about
the physical. Daniel and I have talked a lot about running in the past. Usain Bolt thing is a great example.
You mentioned this physical restlessness you need, Tyler. What is the prescription or the RX coming
out of this research for how should people think about the physical side of their lives,
even if I think most of the book and most of what we're talking about and thinking about here is
mental talent? What is the supporting physical infrastructure beneath that that's interesting,
if anything? I think everyone should exercise every day, if only for investment reasons,
but at a deeper level to understand your own physicality and how it interacts with your mental
output is a great way to become more productive.
And there's not going to be any single answer that's going to hold for everyone, but that
I need to squirm on the couch in a certain way.
Well, kind of unique to me, but I understand that.
And it helps me write better.
So to figure out what for you is like me squirming on the couch, I strongly recommend.
Daniel, what have you gotten out of running?
Why is this so important?
It's funny.
I'm smiling because the pursuit of maximizing the self-approvedment, quantified self-stuff,
I find it's a funny scene where zero interest in the field is a bad sign.
110% interest in the field is just as bad a sign.
In reality, I find most productive people have very deep, very private, a kind of secret interest in the field.
Would never ask someone all those Tim Ferriss, although I think Tim Ferriss is great,
but that kind of style of what's your daily routine, do you take cold showers, but secretly are
wondering if they should be taking cold showers. That's kind of where I sit. Running happens to be the
thing I've chosen to self-identify as and do every day, almost every day. It is funny how actually
productive people, when you meet them behind the scenes, there's a veneer that they're really not doing
much. Some of them are. Some of them just do sleep fend magnificently every night and really don't
work out and actually seem very healthy and vibrant, but find a lot secretly in the QS.
seen, but don't really want to talk about it too much. And I think that's probably the healthy
balance to have. So I'm not here to reveal any daily routines I have. I'm like 1% of successful
of the guests that you've had on your show. So I'm not the person you should be asking.
But yeah, if you do manage to get Ken Griffin to talk about his sauna cycling, I think that'd be
helpful. Were there frustrating aspects of the research part of this project, meaning things that
you wanted to learn that just didn't have answers or hypotheses that were just totally wrong
or unsatisfying things? What was frustrating about this book? I'll say one thing. I'll let Tyler
comment, not just with this book, but in general, I have been a bit frustrated with the disconnect
between the world of social sciences and the most cutting edge machine learning that we have
available to us today. I think there's a bit of a selection effect of who goes into what field in
industry, but you read a study that's purportedly showing results. And studies are truth. That's what
we learned over COVID, right? This is a study. It's true. Expert checkers and experts agree. It's
true. But in reality, these things are, we got 40 people in the room and we asked them to fill out
a Google form four times. But there's so many obvious experiments you would look for.
If you were running this as a machine learning team at TikTok, you just say, well, can we take the
text output people have and put it into different clusters and heaps, not label them, but put it into
different clusters and heaps so that we can figure out the different writing styles people have.
Maybe you do the same with video. Maybe you do the same with images. The profile of pictures,
If people select for themselves on social media, gosh, that's got to be predictive in different ways.
And there are a few things here and there about it, but nothing really that's gone deep.
No one's really brought the arsenal of tools that machine learning offers to social science with the correct level of depth.
I run a small company that's doing a little bit of this, but I'm disappointed that there's no open AI for psychology, so to speak.
Tyler, what's your take?
I would second all that.
There are just very few papers, research papers, in these areas that I trust.
And the ones I trust the most tend to show, well, Factor X is only so important, like IQ is only so
important. Conscientiousness is only so important. Those actually seem to replicate. The papers that
make bigger claims about something being very important tend to fall apart, or they're so context-specific.
You have to be very careful with them. But more and more, I think of the quest for talent as a kind of art.
Now, in the arts, you can understand works of music or painting or movies far better or far worse,
but it's hard to give people fixed rules. You wouldn't say, well, always buy the paintings
with red in them or paintings with dogs in them. That'd be pretty crazy. But if you look at
enough paintings and talk about paintings with other smart people, you'll understand paintings
much, much better. And you can do that with talent. There's something ineffable about the
success. And if you look at some of the biggest successes, such as Peter Thiel, who has this
incredible record, Peter is not a formulaic talent searcher. It's highly intuitive. It's almost a
kind of moral judgment. His own background is in the humanities, not in number crunching,
and that is itself interesting. When building good models, the size of the dataset, we've learned
from modern AI research is incredibly important. You both have huge, what I'll call reference
classes of people and talented people, and you both actively are searching for talent all the
time, whether that's to invest in or interview or write about or back through grants. This is
something that matters greatly to both of you. What has changed, if anything, the most about how you
evaluate talent from before beginning this project to now as a result of the work?
I would say where the person has ended up, not where they come from, but geographical location
predicts talent more than I had thought, and I find this actually somewhat discomforting,
since it could have dangerous political implications that you have talent so concentrated,
say, in South England, near New York City, Bay Area, some other places, parts of India,
but the people who are really talented actually are able very often to make the efforts
to get themselves to those places, more than I had thought, and I already had thought that.
For me, the big model update has actually been one that I got from Tyler. I started an organization
that built our own IQ test. We built our own psychometrics test. We went really deep and really climbed
all the way up, but now all the way down the Dunning Kruger chart of belief in that stuff.
And I've greatly reduced my priors on all of those things, with the exceptions that I mentioned
earlier, so as a way to provide taxonomy and language to a team and whatnot, and
increase my belief, yeah, to Tyler's point on the prior body of work. You know, it's funny,
my sister is an organizational psychologist, and I remember coming up to her after I learned about
the Big Five Aspect Scales and started to work on implementing our own version of it. She said,
oh, you know, you're in the Big Five Aspect Scales, Halo. Come back to me in a year, let's check in
and see where you are, and she was totally right. I do think when people first learn
about it, they have a tendency to believe that it is the ultimate utensil for understanding
people and whatnot. Again, it's useful as language, but I rate that stuff far lower because
I've realized how the sausage is made and the factory doesn't look great.
Until we have better tools, the work is the way to go.
Another revision I have had is to focus a bit more, not on whom can I find, but who will find
me? And it's thinking about the problem in reverse. You don't want it to be either too hard or
too easy for someone to find you, at least for what I'm doing. That is at least as important
as me showing up, talking to a person, meeting them, reading their work, whatever, and making
my judgment, who's attracted to me? If you're not going to get that right, it's hard to do well.
I'll call that the bat signal effect. What have you learned about doing that well? What represents
a good bat signal? When I interview candidates for emergent ventures and they say, oh, I'm your
biggest fan, I've read all your this, heard all your podcasts, they are not usually the best candidates.
They're usually smart, curious people who don't have that much to do. The very best candidates tend
to be, I have a friend who loves your stuff. I listen to one of your podcasts before this.
interview. They've learned who I am. They have some mental model, but they're not a fan. And I find
that very interesting. It shows it's about your soft network. You can't rely just on your hard network,
but who your hard network will bring in as your soft network, you need to be out there in some way
with an image that corresponds to what you're trying to pull in and help fund hire, whatever
the case may be. Daniel, have you learned anything about this through Pioneer in terms of
throwing up the right signal to attract the right people, the sort of pull versus the push?
You definitely come across folks who really admire the individual to the point where you realize
the fact that you are filling some type of heroic protagonist role model in their life
speaks to something that they're missing more than something they have.
Something I saw at YC2, we've come to hear those people.
The best people are trying to use your platform to their advantage.
It's a great feeling to feel like I'm being slightly taking advantage of.
You are a step on the staircase.
I'll be stepping on you now to get over here.
And it's great.
We'd love to invest in people like that.
And as they step on us, we buy a little bit of equity and they continue on.
You're really something that they're using as opposed to being the destination.
Probably it is a thing that as we become more successful, we get worse and worse.
And you kind of see the extreme of this super successful businessman seem to attract around them,
these kind of silver tongue types that really like them and admire them.
And it does start to distort the thinking of some of these folks when your entire audience
or these court gestures that really needed a hero in life. You are that hero. They're trying to
to appease you. I think it's a very unhealthy psychological cycle to fall into. You always have to
really make sure, first, when you come across someone like that that compliment you and whatnot,
it takes a while to develop T-cell immunity to that. At some point, I think it's very important
to become highly allergic to those dynamics and really focus on people that might know you and respect
you, but there's a specific goal that's not you that they are trying to achieve, that you might
be helpful to get them to another planet. And you need to be very careful. If there's
compliments are true, it can be worse. The people who BS you and say things nice about you
that aren't true, there's actually maybe a greater chance they're the ones who want to use you.
So if you say to yourself, well, that person flatters me, but the things he or she says are true,
so that's a good channel of information. That's a very dangerous path to go down. In fact,
it's maybe more dangerous than having some pure BSers by you. There's a section of the book.
I've intentionally avoided the area of these personality inventories. You've referenced them a few
times. And I think as you go down this path, you sort of are enamored with them originally because
there's this physics envy that exists in the non-physics field. You want stuff to jam into a formula,
but still, if they're useful as a language, is there one, whether it's MBTI or Ocean or
anyogram or whatever it is, is there one that you recommend people check out just to develop that
sense of language, that descriptive language around personality characteristics or types?
I think the least bad is the big five aspect scale. And it's only.
five, thank goodness. There's a version of it, the big 16. It may have a higher R squared in statistical
terms, but you can't use 16 concepts with your team. So big five, it is with a ton of qualifications.
You mentioned this notion of geography, which makes me think a little bit of the frictions that might
exist between someone talented and getting to one of these hubs of creativity or cities or whatever
that might lead to something really interesting because they're a talented person.
Say a little bit about the frictions that you investigated. That could be areas of
bias that are big topics today, whether that be gender bias or racial bias or something else,
what factor did these sorts of frictions or biases play in talent achieving its highest possible
success rate? The most obvious is immigration law, but the one that maybe you can change that is
still way under discussed is it is much, much harder for women, especially younger women,
to develop mentors in today's world. There's a number of ways you can put it with different
valances, depending on, say, how feminist you are. But one is the risk the woman may be harassed.
Another is the risk that the man will feel vulnerable because the woman can charge he was harassing her
or just create some kind of negative impression. But no matter how you want to frame it,
I'm convinced that is a major, major factor holding back, especially younger women,
that we're not doing a very good job of addressing. Arguably, in some ways we're making it worse.
by making the issue more fraught. You do definitely want to protect women against harassment,
but I don't feel right now we have very good institutions for men mentoring women.
Anything you'd highlight, Daniel, in that area?
I think an interesting open question is whether Zoom makes things better or worse.
I've heard both sides of this. Tyler, actually, what do you think in terms of, say,
mentor development for women, the reality of remote work. Is that a plus or a minus?
I hear from a large number that it's a plus. I'm not sure I know enough to have my own judgment,
but I take those reports seriously from women. And that in a broader Zoom conversation,
they feel they're cut off less and that it's more egalitarian. I hear that a lot too.
Yeah. In a recent conversation with Antonio Gracias, who was the first big institutional backer
of Elon's company, SpaceX, and Tesla, we were talking about the sorts of talent, the supply of
which are a rate limiter on progress in the world.
It's tightened a little bit here, but there's abundant capital, financial capital.
That doesn't seem to be a major rate limiter in innovation or great new companies or institutions
being formed.
So talent seems to be the rate limiter.
And I was interested to hear Antonio say, look, it's actually probably not that we need
a hundred more Elon's, that we need the layer of talent beneath that enable the rare genius
like an Elon to do more and create more leverage for that type of person.
I was surprised by that answer, given that he was Elon's big backer and I think would agree
with us all that he's a remarkable entrepreneur. What do you guys think is the most important
supply-constrained type of talent today that if you could just snap it into existence would make
the world a much better place? On the Elon point, I think it's an interesting question. There's a bit of a
reflexive loop there where it's someone with the intellectual gravitas and then subsequent market
success like Elon that then attracts the executive bench underneath him. So you kind of have this
chicken and egg dynamic where I think a lot of what's going on for Elon today is he can attract
talent, no one else can attract. It's part of the star power moat that he has, along with some other
regulatory benefits. I don't know that that would actually be the shortage. I think there's some
basic base rate of how many humans there are in the world that we were creating every year
that are both very talented in the world of engineering with numbers and shapes and code and with other
people. For reasons that are pretty deep that I don't really understand, we're pretty decent at
creating outliers in either direction. It's very rare to find someone that has both. That's actually a
real constriction. Not only do we not create enough of them, but we also don't slot most of them,
I think, into the right roles. There's a very big inefficiency that will probably only realize
once we have it fully figured out. And I don't know if this is going to be some type of whimsical
techno punk future where the AI is routing jobs. I'm certainly not signing up for that first.
That'd be turned into a professional garbage can collector probably. But I think there's a lot of people
that are not sorted into the right jobs. I think that's a raison de etre for the book. At the end of the day,
it is not a capital problem, but there's a significantly outdated operating system running on the
minds of the different people around the world who are responsible for finding the right person for the right
job. I think if we could route people more appropriately, we would get more SpaceX's and more
Teslas and more apples than Googles. The free market has this awesome process of grade of destruction
that kind of has that happen occasionally. A different way of saying is, startups should have a much
lower failure rate if we were able to route everyone properly to do the right thing. We have high
failure rate. People kind of celebrate it because successes are so big, but things can be much
better. Many more startups can be successful if you were able to route people to the right jobs.
And I think that's true over the whole economy, a middle manager at some Fortune 500 company,
as well as a VC picking the next startup. I think there's failures at every level. And it's interesting
for me to look at the pandemic. Some of our public health institutions failed pretty badly.
the CDC, the NIH, they failed at every level. They're on a kind of automatic pilot. And we only really
saw that when there was a particular discrete emergency. Now, when it comes to talent, while I would say
there's an emergency every moment, there's not from one month to the next, some obvious new emergency
that pops up. So we don't see what we saw as the failures of, say, the CDC in the world of talent.
But imagine the talent allocation process as being like the CDC. And the failures are just always there
at multiple levels, and we continue down the path on bureaucratized solutions that are actually good
enough for maintaining our current level of GDP. Most years, it doesn't go down. We could do much,
much better. And people who are worried about income inequality as a problem, that is simply the other
side of the coin of talent allocation. I would say talent misallocation. What would you redesign,
Tyler, about what I'll call the attractors or the filters for talent, whether it's, let's take
colleges as an example that are designed to first attract, then evaluate, and then foster talent
at different levels. What's most broken about them or said differently? Like, if you were designing
one of those institutions, YC is interesting in this regard for founder talent, if you were designing a
new talent filter institution, what would it look like relative to the ones that we mostly rely on
still today, especially colleges? Well, if you take universities where I work, it's striking to me
how slowly they react. So as we know, right now, there's a crisis in Ukraine.
a university should be raising its hands and saying, we're going to open up 10, 50, 100, even just five,
even just one slot for a super talented Ukrainian student, pay their way, take care of their visa problems,
and bring them in.
The number of schools that have actually done that, as opposed to the press releases,
which I've read and looked into who's actually doing what, is remarkably small.
Schools are not set up to adapt quickly.
To make, say, 10% of education at a school online can take schools many years to do.
if they get there ever. That's a way of attracting talent that doesn't want to show up every morning
to take classes. In general, flexibility and speed of reaction or poor across most of our larger
institutions. If you were designing something as a filter, any ideas there for what might make?
I'm always struck by Paul Graham's original, I think it was Russ Roberts that interviewed him
back in 2008 or 2009. And he described YC as this assembly line that they were trying to make the
throughput of the factory as efficient and fast as possible, as high a throughput as possible.
Are there ways that we could do this in a more self-served way?
Like I think of the CFA exam and finance is an interesting one of, yeah, if you get through
that thing, you definitely have the ability to work really hard and you're smart enough.
It says something about you and it's sort of self-serve in a way.
Should we have more of that designations or tests or filters that are more scalable?
I'm all for competency testing.
But there's so many layers at which the problem has to be fixed, just another simple one from
my area universities.
Mid-century, it was not so unusual to have American university presidents at top schools
in their late 20s.
Now, if you're 60, you might be considered too young.
That is crazy.
It's only one thing.
Fixing that one thing may not change matters.
But if you realize there's 30, 40 things like that, and to get on the path of fixing each
and every one to make our key institutions more dynamic, faster to change, better at allocating
talent.
What is the biggest open question for each of you about talent at large?
This is super practical for me selfishly. I'm not saying it's the biggest social problem,
but in the context of a brief interview or interaction to assess who has durability,
I find that much harder than assessing energy or smarts or even conscientiousness.
Durability. They'll stick with it. They'll persist. Very hard for me to get a handle on that.
Obviously, older people, you just look at the records, basically going to tell you younger people,
there's not a record. How do you know?
In physics, we have a pretty good understanding that seems to only change in quotes every 200 years or so about how the universe and the world works.
But we have pretty good frameworks now that Plank and Einstein to Newton to some extent put in place.
We don't really have that physics blueprint for assessing someone in an interview.
I'd like to have something that's as durable, meaning it's a science that will last at least 100 years.
truths are reinvented even in physics every couple hundred years or so.
So something to last at least 100 years of just how to give in a set of inputs and say 60
minutes of interaction with a human predict how they would respond to different environments
over the course of multiple years.
And if we had a greater ability to do that, whatever metric you want, global economy,
technological progress, a lot of things would accelerate much faster.
So this particular Torah we don't have yet.
And the book is really the beginning of a conversation that hopefully will result in
the creation of this science. I think that's the real thing missing from the world.
Daniel, do you think that the reason why that's hard is that it's almost like a priced marketplace
for talent, that it is more of a relative game than an absolute one? And therefore,
that science can never exist because it'll always be changing because it's so competitive
versus a ball dropping that can be measured. It's going to be the same every time.
Nature doesn't respond to you at the same speed that other humans do. I think it's a fair counterpoint.
But if we look at markets as an example of this, there are quant funds you would
know better than me, that outperform the market consistently, some of them for a very long time.
So there are ways, even in reflexive dynamics, to have some sense of real truth. I agree with you that
it's harder said than done, because Earth is not changing gravity based on whether you're dropping
a ball. But there's still, I think, a way we can probably get there. And it does not have to be
adversarial like markets, by the way. No one wants to be sorted or selected for a job that they do
not enjoy. And people seem to be at their best when they enjoy what they do. So I think there's a way
to make it happen in the win-win dynamic. I'll definitely remember the book for this idea of
energy, durability, and curiosity really is the three things that I personally took away from it as
things to screen for, think about test for, ask questions around. Highly recommend everyone
check out the book. I think this conversation is critical for everyone listening. Daniel, you know
my traditional closing question. I've already asked it of you last time we talked. So I'll ask it
of Tyler this time. Tyler, what is the kindest thing that anyone's ever done for you?
My mother was an incredible and loving mother. And I think that is still underrated in our society.
And she drove me around to chess tournaments when I was 10 years old and couldn't get around by
myself. That was formative for my later development. And she never asked what was in it for her.
It's got to be mom. Love it. Simple, wonderful answer. Guys, thank you so much for your time today.
Thanks for writing the book. I hope there's a sequel. Really appreciate it. Thank you.
Thank you for having us.
Next, you'll hear my conversation with Canalist customer Giuseppe Coco of LK advisors.
We talk about the good, the bad, and the ugly around proprietary models and how Giuseppe has made
Canales a key component of his investment process.
So, Giuseppe, I think the place to start is with the concept of a deep economic model
on a business.
You've got a unique background in banking where I think you spent, God knows how many hours
building complex models.
And I'd love to just begin there.
Talk us through your early experience building models, sort of the good, the bad and the ugly.
Yeah, so, you know, we started out with investment banking, which is very much on the private side.
And there, obviously, you have a lot more information.
And so you can go in a lot more detail.
So you would look at the models that we were building for deals were frequently 20, 30, 40, 50 taps, thousands of lines long, only like to get to a very simple output.
And, you know, you would spend hours just changing this, changing this, updating this.
It would literally take forever and it was very difficult, almost like to audit.
You would find something, okay, you know, this number should be this, this number should be that, right?
And you would literally go back and spend hours and hours and nights just trying to reconcile that.
Just because most of the times people are just adding more and more complexity to those models
and always ask for incremental complexity.
What do you think is the most useful and the least useful part of how those complex models are built on the banking side?
Obviously, precision is good if you can get to it, but false precision is bad.
What do you think the good and the bad is of that style of model building that's so complicated?
I think to a lot of people that provides false comfort because it's more like the more of the merrier,
but it's actually not the case.
It's more sort of, you know, what are the relevant things?
What are the key things that actually make a difference?
And frequently, that unfortunately just gets lost in the detail.
On the good side, to be frank, I don't think there is actually much because we think
of a solution like Canales, which the first time I opened a Canales model, I was amazed by
the level of detail and precision that they could get basically into their one-tap models.
I was totally amazed by that, that it was even possible.
Until that point, I mean, that hasn't even crossed my mind that it was really possible
to build such a detailed and sophisticated yet simple model in a manner that they do.
If you think about those early days and what Canalist does or when you first encountered it,
What did you like about the service when you first encountered it?
Like, what did it replace for you?
And because you didn't no longer have to do those things,
what did it open up or unlock for you with your time?
When I first started on the by side, we started out by the sort of models manually.
My former boss asked me, you know, to build out like models manually into this and
that.
I mean, obviously, like your work basically piles up.
And I mean, it just takes hours.
It can easily take a few hours until, you know, if we don't want to,
potentially even like three weeks, depending on the degree of complexity,
to build a proper and running a fully integrated.
model for any of the companies. What Canales does is basically condense all of that process. So
it's as simple as downloading any PDF file just from the internet. And you have the whole
model there with all the relevant KPIs, with all the relevant drivers, so you can overlay basically
your inputs. I think from all the tools I have been using on the BISD and I'm using today,
it is the one that reduces friction the most. Giuseppe, I'm curious, where did you first hear of
Canales? Funny enough, I actually heard about Canales on
your podcast in an ad. And, you know, it was one of those evenings. It was at home listening to a podcast.
And like, you know, I heard automated models out updating. I was like, oh, my God, this is exactly
what I need. And I'm curious if you've interacted with others in the investing industry, too, that
are using it more and more? Like, are you seeing more colleagues or even competitors or friends
using it? Is that part of the growing network of it? Here in the UK, my previous firm, I started using it,
and then, you know, a team that was sitting like next to it was like, okay, hey, what are you
place doing, you know, how are you doing this so fast? And then they started using it as well. So it became
sort of viral. And then when I joined here, so RCIO, funny enough, you know, when we first met,
we talked about it. It's like, you know, hey, there's this amazing solution which I'm using as part of
my process. He was like, oh, yeah, he's ex-fidelity. One of the catalyst founders is also ex-fidelity.
So he had it very much on the radar. And, you know, it wasn't even a discussion to get up and
running when coming here. Maybe just talk about your day-to-day life at LK advisors. What exactly is it
that you are doing, what is the daily workflow so that we understand how it slots in?
Depends on the time of the year.
Currently, you know, we're going into earnings season.
So what we're doing right now is lining up our numbers across the models for the
companies that we're holding, seeing where our estimates are.
And then obviously, there's just like preparation work at the moment.
The rest of the time is screening for real ideas, speaking to management teams, attending
conferences, setting up calls.
And for all of this, Canada, it's extremely helpful because, you know, you always have
a single source of truth, which we can refer to look at the numbers and to get a better sense
for where that is and how, you know, something that a management team may say, something that we
learn may impact our estimates and where and how they could potentially translate into true
value.
That single source of truth thing is interesting.
How historically in firms like yours or in your experience, knowing other analysts and PMs,
how is ownership of the model typically handled?
Because it seems like one nice thing like you said about catalyst is it's a single source
of truth. It's almost its own ownership. You don't have to worry about it as much. But how,
in the absence of something like Canalist, are models typically shared and responsibility for them
shared between teammates? Maybe like even going back to the previous experience, I think generally
in finance and I think most people will agree that models are sort of view, the model on a company
on the idea, whatever it may be, is sort of viewed as the holy gray, the numbers that people
use based their estimates on of value. And it's sort of like the most things, sort of, you know,
what is the impact of fill in the blank get X, Y, Z.
So people hold it a very, very high regard,
and people are very, I want to say, almost jealous of their model.
And everybody thinks that if you own the model,
you own the process and you ultimately like have to do.
But the model also is, it's usually in pre-canalist type of times,
it is extremely time-consuming and inefficient to maintain.
The way it's normally like shared among sort of like teammates is usually it's quite
easy for mistakes to sort of sneak in. Canalyst is great because there are no mistakes in their
models. If you want to have something added, right, you can just read out to the support team and
product analysts and they will mend it to your satisfaction. So thereby using Canales,
you don't need to worry about maintaining your single source of true. How would you compare how you
use Canalyst from your sort of hedge fund days to what you're doing at LK advisors? Is it different? Is it
similar? Is it highlighted anything for you about the product or products?
It's a bit different. I think in my previous role, the coverage universe was a bit more fixed,
a bit more Europe focused. So it was more about updating, maintaining, forming a rolling view.
I think in today's role, it's very different because our coverage and our universe is basically
global. So when I came in, I had to think of, okay, so how can we actually like leverage this?
And one of the thinking was, for instance, I was very keen to build a what I would call a quality scorecard, which would allow me basically to, when you have to think about across developed markets, what is what most of what we do, potentially even like some emerging markets.
How do you compare, cross-compare companies on a qualitative basis?
So we started building out this process, which looks at more than 250 KPIs to help us build sort of a scorecard, which has to score any company along those cases.
APIs from one to 10. And this is a process that we found very well working for us. And that without
Cannibalist, I mean, it would have been virtually impossible. Taking years or something.
Yeah, it would have taken multiple years, multiple years. What do you think is interesting about
where you sit? You know, you're in London. Obviously, a global coverage in universe is probably a little
bit more important to you sitting there than if you sat in New York or something. How does that transfer
into the use of Canales and the global nature of what you do.
Canales over time, since I started first using the product, they have expanded massively,
you know, and wider into, especially like European companies as well as EM and developed
Asia's companies. So the universe has expanded tremendously. The other great thing is, you know,
we work closely with their product team to make suggestions on sort of, you know, companies that we
care about and companies that we know, sort of, you know, people here in Europe care about.
And they are extremely reactive to initiating and launching on new models when we ask them to that gets put on sort of like a wait list.
So yeah, we continue doing that as we, you know, take an interest in different companies here in Europe.
And I think the roadmap is sort of, you know, to get to like sort of 10,000 companies slash models, which is a pretty wide scope.
What do you still do that's, I'll call it very manual that you don't think is too high value and you wish could be automated?
Another way of asking is like, what do you hope is on candleless products?
roadmap. I think it would be nice to have something what I would call a by-site consensus.
If you ask many people in the industry today, by-side consensus is this very elusive concept
of whisper, what some people may even call, right, second, sort of unformed expectation,
and it may vary. What would be amazing would be to have some sort of panelist user-weighted,
anonymized average of what actually the users on the other side thinking and then, you know,
sort of providing an opt-in or an opt-out whether you kind of think you want to participate
in that. I think that would be amazing. The other thing is they are currently working on this
KANIS platform and we have like an internal developer who's working with their team to scale
this scoring mechanism that I have just mentioned to you through a Python-enabled web platform
to basically run that even at larger scale through the entirety of their platform.
And as that becomes basically more life and more consumer-friendly as their website,
I think it could open up very exciting opportunities and use cases down the line.
I'm curious, Giuseppe, if there's anything that you think is lost in the process of outsourcing
some of this model updating, another way of asking it would be, you know,
if you're updating these things manually, does that give you some sort of felt sense for the business
that you can't get just by looking at the numbers.
And do you think that's worth that at all?
I mean, obviously you're a big catalyst user, so I can guess your answer.
But I'm just curious whether there is a downside to, I'll call it, outsourcing some of this manual work around updating the models.
I think the first part is that once, you know, when I remember when I open my first candidate,
you see all these things and it's more like, okay, how does this work?
Right?
You look like an introduction.
It's like, hmm, you know, I like it, do I trust it?
And I think it's more when you have your sort of, you know, the companies that you know and you follow them and you have a sense,
for the history. Obviously, you know, you need to look at the numbers and you just
anecdotally get a feel for what it is. But I think the beauty of catalysts is going to mention,
right? So you open a cannabis model, there are five tabs and they have these like beautiful
summary sheets. And I almost find it a lot easier to just look at those trends and get a sense
for how something has performed, what is driving X, what is driving Y. They actually enhance,
in my view, that process of understanding what is going on. I had this debate with multiple friends
and my view is that it's totally overrated to say, sort of, you know, you need to build the
model to entirely understand the business. I think you just need to like look at the numbers,
understand and how they flow, which is, you know, what Canada helps you with and do.
I think the other thing that I found super helpful that initially wasn't as intuitive is their
custom templates. So Canada's has like standard templates for,
an LBO or a DCF, coms, all these usual things.
We have our sort of proprietary process of how we look at things, how we value things,
the score cut that I've mentioned to you.
So we spent, we invested a decent amount of time into building our own templates
that correspond to our process that work exclusively on the kind of platform.
Once we scale, we put in that, you know, it incrementally helps us understand and make sense
of a business and wise we can, you know, continue to comply with, you know, how we
do things and how we think about things. Awesome. Well, Giuseppe, thanks so much for taking the time
to do this today. Really interesting career arc that you've obviously done a lot of modeling,
so a great set of experience to understand why this is valuable. Thanks so much for your time.
Thank you.
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