🎙️ 143: Why Playing It Safe Could Be the Riskiest Career Move (ft. Taylor Pearson)

David speaks with Taylor Pearson, an author, investor, and principal at Mutiny Fund. Taylor wrote The End of Jobs, a book about how work is changing and what that means for people building their careers today. These days, he focuses on decision-making, risk, and helping investors think about uncertainty through his work at Mutiny Fund.

They talked about:

📚 How ditching plans to become a lawyer changed Taylor's life

⚠️ How "safe" career paths often hide the biggest risks

💼 Why some jobs will feel secure until they aren't

🔒 Why job security and career stability are not the same thing

🧾 How to track your life balance sheet beyond money

🧠 How thinking like an investor can help with making smarter life choices

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📄 Show notes:

[00:00] – Introduction
[02:29] – How Taylor avoided law school and chose a different path
[04:11] – Why traditional careers aren't as safe as they seem
[08:11] – The hidden risks of staying on the “safe” path
[21:12] – Thinking in terms of a personal balance sheet
[26:16] – How Taylor built his skill stack across different jobs
[40:26] – Behind the scenes of publishing The End of Jobs
[45:27] – Will AI change how we work?
[51:35] – Why niche markets thrive on the internet
[54:11] – How AI might rebundle everything
[01:00:00] – Rethinking work in a world with AI
[01:07:48] – What is ergodicity and why it matters in investing
[01:12:45] – How to think about risk in work and life
[01:18:112] – Why diversification is more than just finance
[01:24:58] – The Helsinki Bus Station Theory explained
[01:24:05] – Apprenticeships, scenius, and creative growth

🗣 Mentioned in the show:

👇🏾

Full episode transcript below

👤 Connect with Taylor:

Twitter: https://x.com/TaylorPearsonMe
Website: taylorpearson.me

👨🏾‍💻 About David Elikwu:

David Elikwu FRSA is a serial entrepreneur, strategist, and writer. David is the founder of The Knowledge, a platform helping people think deeper and work smarter.

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📜 Full transcript:

How Taylor avoided law school and chose a different path

David Elikwu: So I think one place I'd actually like to start is, so from hearing you speak about your background in the past, I heard that first of all you majored in history, minored in Spanish, and you know, you went, you did some year abroads and then I think you did a year abroad in Argentina, then you moved abroad for work. So before we get to that, 'cause I also wanna ask about your time abroad. I would love to know, you ended up going down, you know, it's a chain of cascading [00:03:00] events that led you to doing marketing, but it started with you not wanting to do law and you were a history major, but you were thinking of going to law school and I found your decision making process here interesting. I'll let you talk about it and then I'll ask the questions after.

Taylor Pearson: Yeah. So, I don't know, I guess I wasn't particularly forward thinking in college. I studied history because I liked it. I just picked the thing I most enjoyed. I took a bunch of classes my first year in the first half of my second year. And I liked history, I liked writing papers.

I mean, mostly right, you just read books and talked about them and then wrote papers about them. And I thought all of that was really fun. And I got to, I think it was the sort of summer after my junior year, before starting my final year and kind of the default path, certainly at my college. I think this is probably true in the US broadly for the most part, is like, if you do a history undergrad, like law school is a very common path.

After that, I think there was like 17. I went to a small school. I think there were 17 history [00:04:00] majors in my senior year. And I think 13 probably went to law school or something like that. Like that was kind of like by far the most common thing. And, I'm curious what I've said in the past about my decision making framework.

Why traditional careers aren't as safe as they seem

Taylor Pearson: I think the, I just wasn't excited about it. I think that's where I got to. And it wasn't that risky to like, not do it for a year and think about it and like, go back and take the test or whatever. And so my parents thought I was like just about to go to law school every year for like five years after I graduated college that I would go back.

I think most of what I recall thinking about it was. I just like wasn't excited about it. And, you know, the way the sort of US university system evolved, like there was like a substantial amount of debt that I was gonna need to take on to do law school. So like, if I did it and didn't like it, it was like really hard to get off the path and do something else.

And so yeah, I just, I just kept delaying it and delaying it. And then eventually, I don't know, I got to a certain point where I delayed, you know, I delayed it so long and I had other opportunities and it was no longer something I was thinking [00:05:00] about.

David Elikwu: Yeah, that makes a lot of sense. And that's what you said is exactly it. But the thing that I'm interested in is first of all, loads of people going to law degrees. It's the exact same here in the UK and I know from lots of people in the US people end up going and doing law or doing medicine. But I find interesting about what you said and knowing that you have now spent a lot of time thinking about decision making frameworks and a lot of these other things. I'd be interested to know how you think about that same decision, maybe aside from the fact that you already knew you perhaps weren't super interested in it.

But the key part I'm thinking of is the fact that a lot of people probably rationalize themselves into doing in law or medicine or some similar degrees, simply because the way the kind of mental model works is that the expected value is quite high in a sense where you probably eat dirt for a few years, you are not earning that much, especially while you're doing law school, everyone's poor, if you're in medical school, you're gonna be poor for a number of years. And then suddenly your pay skyrockets and you are doing extremely well. And then now you are in a very [00:06:00] high paying career. And in some of those years, then you just suddenly very quite quickly pay off the debt that you incurred along the way. And I think a lot of people have that framework in mind, and that's how they rationalize themselves into making the exact same decision that you decided not to do. And people just think, you know, because doing some other degrees, you could also rack up a lot of debt for something else that doesn't pay well in, in the end anyway.

Taylor Pearson: I think, I don't know if I had like the presence of mind. I don't, yeah. I don't know if I thought this at the time, but I think, I mean, I think certainly one lesson I take from that is like, the options you know that are available to you are like, not necessarily all the options.

I grew up in Memphis, Tennessee. I went to like a small, you know, not particularly notable school in the southeast US and most people from that school went into accounting, legal, I guess, you know, somewhat standard sort of corporate, like working at Wells Fargo, like, you know, kind of that sort of trajectory. And so like, that's kind of what I thought, like, I don't know, like that was just what you did, right? That's just like kind of what I saw people doing. And so I think, I think the first thing I was like, [00:07:00] I'm gonna take some time and think about like, do a little exploration and like see what more is going on there.

And then I think I made a decision like pretty early on in my life to like, I wouldn't frame it in these terms, but like, not view myself as like homo economicus, like an economic agent, right? Like, oh, I do this and this is trajectory and this is the payoff, right? Because like, Paul Graham, the one of the Y Combinator founders and writer has a essay about wealth.

And like, one of the lines is like, wealth is what you want, right? So like if you had a magic machine and you just told that machine what you wanted and it gave it to you, you would have no use for money, like a dollar, whatever. It would be useless to you, right? You would just tell the machine what you wanted, whatever you wanted and the machine would produce that sort of thing.

So I think my goal was always to find something where I could do good enough financially, you know, with what good enough meant changing over time. But like, I've always put like a reasonable emphasis on like trying to enjoy my Day-to-Day work and career. I think everyone has certain parts of their work. I don't, I'm not blissful all day, every day [00:08:00] at work. And I think being, if I'm going like six months and I'm like really sort of miserable at work, like something has to change here. And if that's like economically to my detriment then try to figure out a way to make that work.

David Elikwu: Yeah, sure.

The hidden risks of staying on the “safe” path

David Elikwu: What scares a lot of people is essentially it's just risk, different flavors of risk. And I think, perhaps we'll talk a bit about abstractions and heuristics later, but very often people kind of get onto a path. You know, we both know Paul Millerd who has the book, The Pathless Path, and this idea of there is a track that you could very easily go on that leads you through university and then you do this job, then you do that job and, you know, life could all be so simple and straying off of that path opens you up to tremendous risk perhaps, or that's, that's what it seems to be. But I've heard you talk about this idea of simultaneously there's a silent risk of perhaps doing the expected or staying in a job too long.

Taylor Pearson: So, I think one of the writers that was very influential on me early on was Nassim Taleb. He has a number of books, Fooled by Randomness, The Black Swan, [00:09:00] Anti-Fragile. And Fooled by Randomness, I think is the best. It's his first book and I think the most straightforward introduction to his work. But he has this, this fun graph of the lifespan of a Turkey. And so, like, of course, like the American tradition is like on Thanksgiving, everyone eats a Turkey, right? And so, you know, if you are a Turkey, he shows this little graphic and it's a Turkey standing in front of a whiteboard and he's got this big chart behind him, and every day the turkey's life gets better, right?

So the farmer comes out and he puts the food in the trough and you know, the turkey's eat the food and then whatever, waddles around with his friends and it's great life is a turkey's great, right? You know, he's pointed at his chart and it's just going up into the right, right? Everything's getting better. All the days the Turkey comes in. And then of course, Thanksgiving morning, the turkey's life is not so good. All of a sudden everything goes bad.

And, you know, his point is, you know, if there's lots of things where like, you don't necessarily get like a warning sign, right? It's not like, things start to slowly decline. It's like, things are good, then things are bad, and it just, you know, it just changes very quickly.

And so I think, [00:10:00] you know, talking about risk, I think that's an important concept of, you know, yeah, I think I use the term silent risk, which is like, actually after, after my, my book, The End of Jobs came out, I had a guy reach out to me that I, I talked to a lot that was really interesting. He had worked at IBM for I think 30 years, a long time, 20, 30 years or something. IBM for some period of time had, I think they called it like a lifetime employment policy, but they basically said, we'll never fire you like you started IBM I think, you know, he started IBM at 22 or something for university.

And you know, at a certain point that changed. He got laid off, I think he was in his fifties, so he was around his like peak earning years. And he was in a really tough spot because a lot of his like career value and career knowledge was, he understood a lot of really specific things about working at IBM that weren't very transferrable to another company, right? It was how certain the hierarchy worked at IBM or certain IBM products or how to manage things politically or certain coworkers, relationships, all that kind of stuff. And so he'd had to sort of [00:11:00] go through this multi-year process of sort of reinventing himself and coming up with a new career and, and trying to figure things out.

And so I think that's, a lot of stuff when people talk about, oh, this is the safe path or this is the safe trajectory, I think it's like what depends on what your definition of safe is and like what is safe really, right? So like pointing to this thing has worked for the last 10 years. Okay, that's a data point, but like, can we necessarily say like, that's safe per se?

And I think, I mean, I think that's the case with like a lot of jobs. I know there's been, like the US tech sectors had quite a few layoffs and like most people in those layoffs, I don't think saw it coming, right? They weren't saying, they going, I'm probably gonna get laid off 12 months from now, right?

They thought, oh, this is great. I've got this great job, everything's going well. And it's, you know, maybe I'm not happy, but at least it's safe kind of thing. And so I think, I challenge that with a lot of people because I think, you know, especially if you're, if you love it and you're super passionate about it and it's the thing you wanna spend your life on, like, that's great. Maybe it is risky, but good for you. And if that makes sense given everything else you, your life. That's awesome. Lot of times the safety thing it's like a [00:12:00] way of sort of saying like, I'm afraid or I'm worried. And you say like, talking about that directly, you're just sort of like appealing to this notion of safety that like may or may not exist.

David Elikwu: I think what you were saying just now, well, just a moment ago about IBM made me think of when I, I spent some time a while ago working in China, working in Shanghai. And a friend of mine was telling me that, I think a lot of young Chinese people probably getting into their mid twenties by probably about 25 people start having existential crises. Because there are so many people, there are lots of jobs, but there's also a lot of people. And so whatever job you're doing, by the time you're 25, at least this is how people think about it. That's gonna be the job for the rest of your life. And you know, in Japan, for example, they won't fire you there either. And so it's not like you're going to lose your job, but it's also, it doesn't mean you can switch jobs. So it's almost the, the inverse risk of like, once you pick a path, you are stuck on that path. And that's, that's actually going to be it. [00:13:00] It's not even like you have the option to switch paths.

But just on what you were saying about just the idea of risk and how people can either the perceived risk that they see is too high or they, or they just don't fully appreciate the value of risk. I think this links to another thing that I've heard you mention in the past, but I think is also from Nassim Taleb, which is this idea that, I think the analogy that Nassim Taleb used was, I mean, it's links to Ergodicity and it's the idea that, jumping off a one foot wall 50 times is not the same as jumping off a 50 foot wall one time.

And the way I think about it as well, something that came to my mind, I think in the last week or so, I was at the train station, and you've been to London, you came last year. You know, sometimes on the London underground, you'll see there's gonna be the escalators, but there'll also be the stairs. And they put a warning on the stairs and they tell you exactly how many stairs they are, especially if it's gonna be long. So they'll say, this stairwell has X number of stairs just because you can't see it before you start taking the stairs. And that warning has to be there so people know exactly what they're signing up [00:14:00] for once they start taking the stairs. But I think the funny thing is that when you have to take the stairs in an emergency, people obviously end up hating it. But a big part of that reason is because people don't do the small hard thing that you could do every day, which is taking the stairs. And so when you are forced to do a much bigger, hard thing, it feels so much worse.

And I think in that same process, people take away the wrong lesson. So every day people avoid taking the stairs, even though, incrementally, like just day to day, it's not that bad. You could take the stairs on a normal day, but people will avoid the small inconvenience of taking the stairs on a regular day. And then on the one day that you are actually forced to take the stairs, it feels like the worst thing in the world. And then once you do that, you're like, oh, I'm not gonna do that again. And so from that point on, then you continue to avoid the stairs. Whereas if you took the stairs regularly on a normal day, just small stairs, then by the time if there's an emergency, there's a fire drill or you actually are required to use the stairs, [00:15:00] then you know, it feels relatively easier.

Taylor Pearson: Yeah. I like that example, and I think of like, you know, I have no data whatsoever to support this, but just like total anecdotal observation. Like, I meet some people that have, you know, talked to some people that are very intelligent people that have worked at like large companies for long periods of time and, you know, in a certain way they just by necessity, right?

Like you're working at Amazon or something, like your whole job is like two pages, managing two pages on like the seller central dashboard or whatever. You know, a lot of it just like isn't very transferrable to like other things, right? Like it's just extremely specific to that particular company.

And so I think there's a lot of situations like that where like, to me, I think I can make a reasonable case that that's like quite a risky thing to do, right? As you said, you know, if you start your career, you work for some period like at a, a small company or a startup or freelance or whatever, like the skills you get there tend to be a lot more generalizable, right?

You know, the equivalent of like jumping off one stair 50 times and like applicable to a lot of other [00:16:00] situations in a way that certain big companies. And I'm thinking of you get sort of like put in this really niche specific thing that's just like not particularly transferrable, and like that's a risky thing, right? Because like your economic value, right? Like maybe you're making a really great salary, but like your economic value is very tied to like this particular thing, right? Like one product on Amazon Web services, you know, whatever the thing, you're doing is.

So I think like, from my view, the important is like, it's not necessarily a bad thing, right? If you enjoy it or you know, you're making a ton of money, whatever, great. You know, good for you. But like, let's not say that this is like necessarily safe or smart or robust. This is like a risky thing that you're doing and you're sort of comfortable with that risk. I don't think that, that doesn't tend to be how people think about it, right? They didn't think about that's like the smart safe thing to do. And you know, something where you're gonna work at a smaller company or start your own thing or whatever it is, is a lot more risky. And I don't think that's like a really reasonable assessment of like career risk, right? That like, having a broad [00:17:00] experience of generalizable and transferable skills feels to me like, that's like a much less risky thing to do, right? That your ability you know, turn that do other things with that is much higher.

David Elikwu: Yeah. But what I find interesting about that though is, I feel like I can see both sides and the irony is that most people don't, and that's why they stay stuck. So the end question I wanna ask you is, you know, how you think people can functionally escape the sunk cost of whatever position they're stuck in or whatever role they're doing.

But I think, you know, just going off the back of what you were saying, I spent about five years in corporate law. And I definitely think that people severely underestimate how transferable some of the skills they're learning are, or at least how powerful some of the skills they were learning are if they applied them to other domains. But the problem is they are applying that exact same skillset to the exact same domain over and over again and just optimizing for getting better at that. Whereas if you took some of those skills and you applied them somewhere else, actually you would realize these feel like superpowers. And I guess the analogy that I would give is that it's a bit like [00:18:00] thinking that you have superpowers because you get really good at cultivating spiders instead of letting the spider bite you. And then you get to become Spider-Man, like If you took that little bit of risk of letting the spider bite you, the asymmetry of a future where your Spider-Man is far greater than, being the person that gets to grow the spiders. But you are, you still have the same proximity to that, the potential of having that alternate timeline.

I know that probably sounds a little bit complicated, but that's kind of the way I think about it, where,

Taylor Pearson: Not, I love a good Spider-Man analogy.

David Elikwu: But yeah, go on.

Taylor Pearson: No, I think there's, I don't know, you know, it's interesting, like I've hired people, like directly out of college. Like there are like a lot of work, like how to write an email, you know what I mean? It's like an underrated, an important work skill. Like, it's like a surprisingly non-obvious thing to do, or like, yeah, you know, how to manage your calendar and stuff like that, which like, this sounds like kind of pedantic, but like, it's actually not like if you're like, good at responding to your email and showing up at appointments sometimes, that's pretty good. You can do a lot with that.

I don't know. I'm like, there's, there's a bit of this like lionization of [00:19:00] entrepreneurship in the culture at the moment, and I'm always like really hesitant. I'm always about like sort of not playing into that kind of thing. And I think one thing I was like most people, this is again, my sort of experience, like most people that have like been successful, like working their way up some like competitive corporate career. Spinning that into starting a business or working a smaller company, like just a general like grit, competence, raw intelligence, you know, all those filters. Like you've kind of probably passed through all those filters at that point, I'm like, your ability to make that switch in my experience is like pretty good.

I think there's usually like a, I don't know, three year transition period or you, there is some transition period of like figuring that out kind of thing. But no, I think that's right. Like there is a certain transferability there. I don't know. I'm curious what you think, like, it seems like maybe the later you wait it's, it gets a little bit harder, especially like given earning expectations, you know, if you're at like 45 or 50 at sort of peak earning years and like trying to do that and get back to peak earning in a new career, that seems like it might be a little bit harder, but I'm not sure.

David Elikwu: Yeah. Yeah, no, I [00:20:00] absolutely agree. And that's where all my friends are stuck. I think that's the thing, right. Okay. So it is both in terms of your compensation and both in terms of the skillset, if you stay long enough just to pick up the skills and then you can take them and apply them elsewhere, I think that's the peak option. Well, that's what I did. I think that's the peak option we will see. Right now, I am still very much feeling jealous of some of my friends who will be listening to this that are still at the firm that I was at, who are earning, you know, very well and a lot of people from, from my cohort.

But I think the thing is that the longer you stay just applying the same skillset to the same problem, it almost starts to diminish. I think the potential upside diminishes because then you get trained too much to apply it very narrowly and you don't know it anymore how to apply that skillset broadly. And then on top of that, that's compounded by the compensation that you get. So then the benefit that you could potentially get by leaving and actually trying to, 'cause it does necessitate starting from the bottom a bit, taking that skillset and moving it elsewhere, you do have [00:21:00] to learn and you have to start pattern matching.

And that requires, yeah, there is the emotional risk there of actually having to, it takes some humility, it takes some, you have to put yourself out there to learn in other domains.

Thinking in terms of a personal balance sheet

Taylor Pearson: One thing I've been thinking a lot about lately is like the idea of like a personal balance sheet, right? So like a business will have a balance sheet that like shows all its assets, right? It owns a factory and a, a car and, you know, whatever, and it has this much cash in the bank and, and like those sorts of things. Or like, a person has a balance sheet too, and you can like, think of that in strictly financial terms. You have whatever money you have in the bank and you have a car and whatever you own and that kind of stuff. But like, I think there's like two other ways to like broaden the concept of balance sheet that are interesting.

One is thinking about like, as you said, like human capital, right? So like, if you're learning very fast, right? You're acquiring a lot of new knowledge, you know, hopefully that's like somewhat transferrable. Like even if you're not making that much money, like you could factor that into the balance sheet too, right?

Like, okay, maybe I didn't make that much money over this period, or I did that, I made a lot of money and I learned a lot of skills. Okay, [00:22:00] that's really interesting, right? But I think, how I'm interpreting what you're saying, right? It's like, you also getting these periods where like maybe you're earning a lot of money, but like the human capital part of your, so like the financial balance sheet looks good, but at a certain point, maybe the human capital side of the balance sheet isn't that much more interesting than it was five years earlier or isn't that much more compelling than it's five years earlier. And like there's a cost associated with that, right. That's a trade off that's being made maybe, I think a lot of people don't think about explicitly. And then I think you could even broaden the concept more and say there's also like, you know, how you feel about your life that's like part of that balance sheet, right? Like, is it, whatever, am I enjoying what I'm doing? Is this meaningful to me? Like all those sort of like existential questions start to come in.

And so I think it's like, I think about that a lot. I think one, one sort of interesting in investing analogy is, if you're investing in a company, people often do something what's called a discounted cash flow analysis, right? So you'll try and project out the cash flows of the company and its earnings and its cost and all this kind of stuff, and what the profits gonna be, and you'll work backwards from that to determine like what an appropriate valuation [00:23:00] is today, right? What I'm willing to pay for this company, and like one of the biggest variables in that calculation is how long you expect those earnings to persist for, right? So if you have a company that's making a lot of money but doesn't have much of a competitive advantage, and those earnings go away in three years, the present value is a lot less than a company that has pretty good profits, but has a very durable competitive advantage and can last over a long time. And so I think, you know, in principle that's true of an individual as well, right?

It's like if you do something where it's reasonably valuable and you're reasonably good at it, and you can do it for reasonably long time on your, you know, discounted cashflow analysis. It's actually worth a lot. 'Cause it can persist over a long period of time. I think some people get, you know, folks saying like, oh, I can make a lot of money doing this for the next year or two years, three years, five years, whatever.

But actually, you know, maybe it's better to think about what could I do for the next 20 years? or what would that look to think in that timeframe? You know, and like, what would that look like and how would I do things differently?

David Elikwu: Yeah, that makes a lot of [00:24:00] sense. I'm gonna mix analogies here, but the way I'm thinking about it in my mind is, okay, so on one hand it's a bit like the 80 20 of, in most jobs and in most careers, you spend 80% of the time getting good and then 20% of the time getting griped. But you have to get good first. And once you get good that you've got the 80% and the 20% is just optimizing.

And so the other way of thinking about it is getting good at the skill and getting good at the game. The skill is the 80% but that is just onboarding slightly beyond onboarding, but like getting to a point where you are competent and you know you are good enough to be dangerous. That is the 80% and then the 20% is the game. So first you get good at the skill, then you get good at the game. But the problem is that the actual time allocation is the inverse of that. So how long does it take to get the 80%, 20% of the time? And then you spend 80% of the time on the remaining 20%, and that is the rest of the career.

And so using law as an analogy, but it applies to other careers as well, is that people within the first few years of being in that career, you do [00:25:00] the 80%, you get good at the skill, and then the rest of the entire time span of that career is like working your way up to partner.

That's getting good at the game, that's the only 20%. And so I think that's the part where in your analogy, that goes on the other side of the balance sheet where you're not actually building the skill anymore in terms of the human capital. You are just optimizing for the game and just getting good at applying it within this very specific domain. And that is useful as long as you keep playing the game. That is super useful. But once you stop playing the game, you actually realize that you've spent however many years just optimizing for the final 20% and the rest of that time you haven't actually spent that developing on the other side of your skillset.

Taylor Pearson: Right. No, I like that. That's very interesting, like at that point your trajectory becomes very path dependent, right? You have to stay on that path and keep playing that game for it to sort of be successful in the long run. Yeah, I think there's a, a, blogger I like, his name's Venkatesh Rao.

He has a blog post, I think it's called the compass in the gyroscope, or that's the sort of analogy he uses. There's the idea of like a, an external [00:26:00] versus an internal coordinate system, right? So like a compass is an external coordinate system. You know, you have the north, southeast, west, and you look at a map and you sort of navigate it. And a gyroscope has sort of an internal system, right? It's rolling downhill. I'm not gonna describe very well mechanically how a gyroscope works, but I think people can sort of, visualize it. And I think about that analogy a lot too, because I think sort of to your point of like the skill versus the game is like, it's the more sort of like clear the map is in general, I think it's just like more competitive, right? Like getting to partner at a law firm or being a renowned surgeon in a particular, like, it's really hard. It's just really, it's like being, you know, being a professional athlete, right? Like what percentage of kids wanna be a professional athlete when they're like 10 years are like, it's really hard.

And so this idea of like a gyroscope or maybe you're, you know, you're picking up some skills here and some skills there. You're sort of following an internal coordinate system that's not leading down a necessarily known map or known road. Paul's like Pathless Path idea, but does still have a certain logic [00:27:00] to it, right? Things do stitch together in a certain way in which those skills are complimentary and useful. They are not in a way that is easily explained to someone on the outside in the same way that you know, you may partner to a law firm or you went to go to law school, or you did this or that sort of, specific accomplishment.

David Elikwu: Yeah, so I'm interested to apply this too. Going back to your career path.

How Taylor built his skill stack across different jobs

David Elikwu: So after you left college, I think you spent some time working abroad, and you've mentioned that, or maybe this was, I think actually before that, in your second year of college you had a year abroad and then coming back you had like a reverse culture shock that made you want to go back out again. And I'd love to know more about how you felt in that moment and what felt like the most impactful. Like what did you see that felt, I dunno, life changing or paradigm shifting, that you then came back and felt like, huh, something's different, something's missing.

Taylor Pearson: I think for me, that experience, yeah, I did. It was my, my third year, my junior year, I spent a year in Argentina. I was a Spanish, at least I was a Spanish minor and my Spanish was not very good. And so I thought if I went and spent a year Argentina, you know, my Spanish would have to be good. I lived with like a host [00:28:00] family, like an older woman. I lived in like a spare bedroom in her house and went to the university there.

And I think, yeah, that was impactful for two reasons. I think one, when I got there, my experience was really bad. Like really bad. Like, I don't know. I can't stress how bad, embarrassingly bad. And the first, I'm depressed is a strong term, but like the first month or two were like really hard like, my classes were in Spanish it's like, imagine if you know but or didn't speak any Russian, you're like, chain down in Russian University. And like, I literally didn't know what they were saying, you know what I mean? Like literally I couldn't understand the words that were coming outta their mouth.

And yes, it was really tough. And so I would like go home with my like host mother and I would like sit there with like my Spanish English dictionary open and like try and talk to her you know, and I'm like looking up words and like we're pointing, you know, she's pointing at stuff and she's telling me what the word, like, you know, like I'm a 4-year-old basically, right. You know, like a, a young child. And by the end of it, my, I don't know, my Spanish was decent. Like I was conversationally functional.

But like I could like go to a university class and like in Spanish and like get, you know, 98% of what they were saying and be a [00:29:00] functional thing.

And so I think that was just like a huge confidence boost for me that I had done this hard thing that I was clearly very bad when I showed up and I was like reasonably competent when I left. And so I think that gave me like a lot of courage to like try something else, you know, to do something a little bit different and not necessarily go to law school or kind of go down the default trajectory.

And I think the other thing relates back to what I said earlier, which is just like, it was a different experience in like ways I couldn't have imagined, right? There's, you know, you talk about like there's the known knowns and the, the known unknowns, and the unknown unknowns, right. So this was a, and it was, it was an unknown, unknown, right? It was different culturally, historically, sort of all those different components in ways I hadn't even really thought about. And so I think that gave me a certain, like maybe there's other things I haven't thought about that are different about how the world works.

Like, I wanted to explore that some. And so I think, yeah, I think I wanted to go live abroad again after that. Just because that, for me at that point, like that was one way in which that was very visual. Just living in a different culture, people speaking a different language, and like seeing what that was like.

David Elikwu: Yeah, [00:30:00] sure. That reminds me a bit of, like I mentioned, I went to to China as well, and it was a very similar experience, although I had studied Chinese a bit and that was kind of the point. So originally, actually before going to university, my original plan was I wanted to go and work at a Chinese university. I got like two offers through my Chinese teacher to go and, you know, teach English at a university there, and my dad said no. So I didn't get to do it. But, but then during university, then I had an opportunity to go and I was actually working at a law firm there, so to connect two of our, two of our lines. But in the first month, I was doing half days. So I would go to work for the first half of the day and then go to language school for the second half of the day. And at the language school they did not speak English, they would only speak to you in Chinese. And then at work, obviously people are only speaking in Chinese and it was so hard. And particularly that first month was just grueling because you know, people also, like culturally, they would have lunch together at work. And so, [00:31:00] yeah, first of all, I didn't even know how to use chopsticks, so I had to learn that in front of everyone. So it's like hugely embarrassing, everyone's sitting around this big table having lunch together and I'm trying to figure it out, it actually took a while. And then going from there to language school where they're only gonna speak to you in Chinese, but you actually get better quite quickly.

And I remembered one situation, 'cause you mentioned Russian. They sent me to go and meet with some guys. Obviously the whole point under is 'cause I speak English, right? And so I'm meant to be really good at English, that's how I got the job. I had some of the best exam grades in the world at English. And so they sent me to go and meet these, you know, white people. They were from Russia. And the joke was when I actually got there to meet them, they did not speak English. They spoke Russian and they also spoke Chinese. And so and so, the only language I could speak to them in was Chinese because I was, you know, I'd been learning Chinese. This guy spoke Chinese and also Russian, I know no Russian. And so I was just stuck there trying to try to figure out how to negotiate things. [00:32:00]

But the other thing, how I was gonna tie that back was you had mentioned this idea that I think also connects to something we were talking about, which is when you go to a new place, you kind of get to try out some different versions of yourself, right? You are unconstrained by your typical environment. People usually know you as one person and in one way, and when you move somewhere else, you get to, not that you have to be different, but you get to try to be different. You get to be a bit more explorative and you can push some of the boundaries that you might typically be stuck within.

And it was funny, there was a post that I came across on Reddit that was reshared on Twitter. So unfortunately the person that shared it didn't get to see the, the revelation that occurred, but the person that was making the post was talking about his life and basically he was miserable, right? He had this job, washing dishes, working early hours of the morning, he was just working in this restaurant washing dishes, it wasn't fun. He was arguing with his girlfriend all the time. I think [00:33:00] they'd recently broken up. He had these friends that he, he wasn't really friends with them anymore, and they've kind of disconnected and none of them were really doing anything well, either. He'd been trying to save some money to move, but not enough that he could. He hadn't saved enough to move. He had saved enough. What he did was he stopped renting the apartment he was renting. He got a van, he was living in the van, and he managed to save about 15,000, but he didn't feel like he'd saved enough to move.

And the comment that I saw, which was now on Twitter, where this post had been re shared, is that this guy is completely miserable, but how happy would he be if someone whacked him over the head and he completely forgot everything about his current life. All the constraints that he sees to the girlfriend that he argues with the job that he, he's supposed to show up at. If he didn't know he had to show up at that job, he just woke up with no memories. Like Jason Bourne, he has a van that he could stay in. He has $15,000 in the bank. Like that is actually a pretty great fresh start. You know, if you didn't know anything else and you have $15,000, you've got a [00:34:00] van, you've got some clothes, some belongings, that's actually a much better position to be in than, than a lot of people. But when you are stuck in that position, you can't really see that, like you can't climb out of the situation that you are already in to see things with fresh eyes.

Taylor Pearson: I know, I think that's hard. For me, that's been perpetually hard, right? You just don't, I think there's a, there's a David Foster Wallace bit where he is talking about, there's two fish swimming that like, just swimming at each other and they swim past each other in the water, and one fish turns the other fish and goes, water's nice today. And the other fish looks back and goes, what the fuck is water? Right? And it's like, well, you know, he's in bits of fish. Why water is nothing? It's like, why would you even comment on it? You know, you're in water all the time, right? Yeah. I think it's, it's hard to see those things and see like, oh, you know, this is like, this is water.

David Elikwu: Yeah, so in The End of Jobs, your book, you talk about this idea of developing skill stacks and, you know, using that as a way of traversing through the working world. And I think, well, a big part of the emphasis of your book was becoming more entrepreneurial and kind of [00:35:00] using the skills that you developed to become more entrepreneurial. I would love to know about your personal skill stack, because you are, you've had a really interesting background and I think, so maybe there's two layers with the question. The first layer is how do you think you've gone about building your skill stack? Is there any way that you've thought about learning things in particular that you found useful?

Just because, I mean like tracking some of the things you've been interested in. First of all, okay. Starting with majoring in history, minoring in Spanish, getting into marketing and learning all the skills you need to get there without going through any real formal process. You kind of did that very manually. Going from there to becoming a writer, both publishing your book and also writing quite prolifically online. Then going from there to being an investor. I think at one point you got interested in complexity studies. You seem to have taught yourself a lot of things along that path, so I'd love to hear you talk a bit more about that.

Taylor Pearson: Yes. Let me see if I can answer sort of both levels of the question at the same time. I think, there's a, a paper I wrote a summary of some years ago, I believe it's called Optimize for Interesting. I think that the guy that wrote, I believe was [00:36:00] an AI researcher, and if you think about why emotions exist, right?

Like why does the emotion of interesting exist? Why do we, like, why don't, you know, you get interested in something, right? Like, why is that? Why evolutionarily, psychologically, like why would we develop the emotion of interesting. And, his theory was basically something that is interesting is an area in which you have a great capacity for what he calls compression progress.

So your ability to like take the different components of that and compress it with your existing knowledge and like make something more efficient and useful and interesting is higher. And that's why the emotion interesting exists because it would make sense evolutionarily that you wanna pursue these things which you find interesting because it's an emotion that's indicating sort of a fruitful way to take your skill stack as you described it.

And so I think, that's always sort of been the way I've tried to think about it is like, okay, what am I doing now? And like, what is interesting? That is like somewhat adjacent to that and like, I'm gonna go, that's gonna kind of how be I'm gonna spend my free time. You know, that's what I'm reading about, that's what I'm interested [00:37:00] in, that's what I'm looking at. And even though it's not directly applicable to maybe what I'm doing now, it's interesting to me. And so I'm, I'm just gonna sort of take it on some faith that there's some ability for compression progress, that there's something I can do in, in that direction.

So I guess sort of my career progression, my first job was a, I was a Spanish interpreter. That was my one marketable skill coming out of university. I took a night class my senior year to get, I don't know if I was officially licensed. I had some badge or something but I was doing interpretation. So I did that. It's like, that was sort of my first freelance gig. And then I got a job as an English teacher in Brazil. I said I wanted to go abroad again, so I moved to Brazil and I taught English for a while. I didn't love teaching English for a number of reasons. And so I had gotten interested in digital marketing and, and I just think this was sort of early 2010s, and like search engine optimization, all this stuff was kinda coming online. And I, I went to Amazon and I bought every book on search engine optimization at the time, which I think there were three books. I think there's probably 30,000 of them now. And I built some websites to basically teach myself [00:38:00] SEO, I think my most successful website was collegefurniture.net.

And it was like reviews of like furniture you would use at college, so like futon reviews and nightstand reviews, whatever. And I think at its peak, I think I made like $300 a month or something, and I was like pretty jazzed about my $300 a month from the site. But that sort of set me on like my initial career trajectory, I was able to parlay that $300 in a month wasn't sustainable. So when I left my English teacher a job, I got a job in a marketing agency and I basically, I cold emailed a bunch of marketing agencies and said, Hey, look, I know SEO here's my website, here's all the SEO stuff I did, you know, will you give me a part-time job?

And so I got a part-time job that turned into a full-time job. I worked there for a little while. I started doing, you know, sort of other digital marketing agency things, email marketing, pay-per-click, a bunch of stuff like that. That got turned into, I got a job at a e-commerce company that was based between Southern California, some in East Asia. We had a team in like the Philippines and Vietnam and China. And so I moved out, I was in Vietnam for a couple years working for them. And I started [00:39:00] progression just doing marketing, they had a number of different hospitality equipment brands, so we sold like parking equipment, bar equipment, stuff like that.

And I ended up running one of those brands. And so I kind of got outta marketing, I was doing more operational stuff. I was kind of overseeing the whole brand and sort of not just the marketing piece of it. And then, that company got sold and at that point's when I sort of wrote my book the End of Jobs and started doing, basically consulting, freelancing stuff around battleship e-commerce, marketing and e-commerce operation stuff.

And at that time I just got like, really interested in finance. So I just started like reading like a bunch of finance books. I was doing like a little bit of investing like nothing particularly crazy. I got very interested in the cryptocurrency bitcoin stuff. I thought that was very fascinating as like a blend of technology and finance.

And so sort of my consulting progressed to be a little bit more focused around financial services companies, that sort of industry. And sort of in that process I met my now business [00:40:00] partner who was trader by background or a finance person by background and we started a small fund. So that's what I sort of run day to day now.

But the trajectory there, there's a certain linearity to me looking back, I think, sort of as you mentioned, some of these ideas from like complexity and anti fragility have always been really interesting to me. And I've in different areas thought about how those things apply, but I felt was always sort of on this trajectory of like, kind of what's interesting and how can I sort of incorporate that more into what I'm doing.

Behind the scenes of publishing The End of Jobs

David Elikwu: What was the process like of publishing the end of jobs?

Taylor Pearson: So the self-publishing, I know you, you've had Eric Jorgenson on the podcast. He's the CEO of Scribe now. So I was one of scribes very early customers. I don't know how early I was, but it was before it was called Scribe. They had a previous name. So I had, when I published the book, I don't, I've always enjoyed writing, I liked history. I started blogging when I was at my e-commerce job, kind of on the side. And so that was kinda what enabled me. That was like my Saturday project for like three or four years. You know, I would wake up Saturday morning and I would go to coffee shop and I was like working on my blog. And that was, I guess people work on newsletters now, not [00:41:00] blogs, but kind of same concept.

So I had a blog and I had done a fair amount of writing about these ideas of just like, future of work and how the internet was affecting careers and, you know, it was at some level just sort of like a reflection on my own career, my own path, right? Like how did I sort of end up in what was very different from a sort of a law school trajectory that I was like a brand manager in e-commerce company in Vietnam, right? It's just a very, it was a very different trajectory than sort of like where I'd, I'd expect it to be if you asked me five years earlier. And so, yeah, I just decided, it would be cool to like write a book. I had, I'd written a lot about it and so I was like, let's kind of take these things and I'll stitch them together into a book.

Yeah, I was very fortunate. I had like, some friends that helped me promote it and, it got a bit of traction and did a lot better than I expected, honestly. And I really enjoyed the, I liked writing, so it was painful at times, but overall enjoyable.[00:42:00]

David Elikwu: If you were to write an update to the book now, what beliefs would you update? So what's changed in your thinking from what you previously wrote? Or is there anything new that you've learned since?

Taylor Pearson: I think that I have like a whole chapter, like railing on accountants and a month before I published the book, I met my now wife who's an accountant. So I would probably, I would probably change that chapter. There's one major update I would make. My views on the [00:43:00] future of accounting have become more nuanced and sophisticated over time. Certainly there's roles for good accountants in the future.

The basic thesis of the book was basically like, the internet opens up a lot of these new sort of like, niche business opportunities that don't work in geographic worlds. So one of the brands at the e-commerce company I worked for was, we sold like, sort of like high-end boutique, well-designed cat furniture. It would be like your cat litter box would fit into like it looked like a mid-century modern, sort of side table, right? So you could like, put it next to your nice mid-century modern couch. And, you know, the cat could go in and like use the litter box or whatever. And that business only makes sense on the internet, right? There's no geographic location. Where there's just a sufficient quantity of people that want to buy enough mid-century modern cat furniture to like, make that a viable business, right? Like maybe New York or London or Tokyo. But it's not that, like the business works a lot better on the internet because across the world they're like, are enough of those people, right? That have that particular design aesthetic and have a [00:44:00] cat and want their, you know, want their place to look nice or whatever.

And I just thought that was like, so fascinating. Like that was a viable, like that was a real business. Like, it, it was a multiple six-figure business that could sustain a person and, you know, the head of manufacturing and all that kind of stuff. And sort of through that process, I just met a lot of other people running similar types of businesses, right?

That there were all these sort of, we kinda get called like long tail, if you will, businesses relatively, niche businesses that were economically viable in sort of the internet era. And yeah, I mean, I think broadly like that's still true. Like there's still a lot of podcasting is certainly one thing that's exploded right in the last 10 years. Like the number of things, there's podcasts for that like are real businesses now is like insane, right? Like, all these really niche, there's a particular like college football team in the US that I like, that's like the team I grew up and like, there's like people that like run a full-time job. It's like there, it's a podcast for people that are fans of this one college football team in the US right? And there's a, you know, whatever, there's a thousand people that are willing to pay $10 a month to like hear the [00:45:00] commentary about this team, right? Because they're super into it and they want to hear the latest of what's going on in the recruiting and that kind of stuff.

So I think that's sort of like core, sort of core thesis intact. I think like the specific examples have probably like evolved. Some like how those businesses get started and where you get into it. But, I wouldn't like change a lot. Like, I think sort of like core concepts are pretty decent and still work. I'd probably just sort of update it, take out the accounting stuff so I don't have to hear my wife tell me about how I was wrong about that.

Will AI change how we work?

David Elikwu: Do you think AI changes much of what you were previously thinking about? I think of it in two ways. So one is, going back to the the Turkey problem, there's a potential way in which, you know, people give advice, oh, here's what you should do, here's the fields you should go into, et cetera. Loads of people are still, I think there was definitely a much bigger movement at one point of getting people into tech and saying, I remember people saying on the internet, plumbers are gonna be dead. All these other careers will die out and everyone needs to start coding, you know, code or die, or whatever it was. And the [00:46:00] irony is, it seems like that's probably one of the things AI is gonna be best at is completely replacing a bunch of, especially the junior coders.

And actually, I think this ties to a framework I've heard you mention, which is something along the lines of a simple work, complicated work, and then complex work. Where complicated is, I can't remember the, precise words that you used, but complex work is kind of like heuristic work where it's not so much just getting good at a certain skillset, but it's more thinking in an abstract way and that seems to be what will survive. Whereas if you're doing something wrote, something that can be taught, something that can be, you know, you can essentially just train an AI to do, Hey, coding has a language. If it has a language similar to chess, chess has a fixed number of moves. If you can teach someone to do that, then you can teach an AI to do it, and maybe you don't have it as a job in the same way. And perhaps people will only do some of these things for entertainment purposes.

Taylor Pearson: Yeah, I think the simple complicated complex is a good way to talk about it. So the idea [00:47:00] is, sort of a simple job or a simple system is something that can be broken down into like very clear discrete steps. So like putting together a Lego set, right? Like you open the instruction manual, there's 42 steps of where you put the blocks on a certain Legos. You follow the steps, if you do it correctly it looks like whatever the boat or whatever it's going to be.

A complicated thing is something that tends to require some level of like, expertise and experience. So I would say like, you know, like a mechanic for example, right? It's like, you can try and fix your car just like following some instructions on YouTube. But like, for a number of things, you probably want someone with some expertise, they can go like, well, if you take that off first, the bolt could fall down here and that causes this thing to explode, right? Like, you need some sort of expertise. But ultimately, like there's a number of good enough answers, right? In a simple system, there's a correct answer, there's one best solution. And a complicated system, there's a discreet set of good answers, right? If your car is broken in a particular way, maybe there's three different ways you could fix it [00:48:00] that are one's more expensive, but maybe last longer or whatever.

A complex system is one in which you have emergent properties and there is no discreet set of good answers that, it's constantly evolving. So, like, sort of distinction between complicated and complex. The example I like is like the difference between like repairing a car and repairing a horse, right? So a car, as we said, of discrete parts, right? So you can take the tires off the car, put a new set of tires on. If you take the liver out of the horse, you cannot put the liver back in the horse, right? It all works together. It's all integrated. You know, once you take the liver out, you take the heart out, the horse is no longer functional. It all requires a sort of integrated system.

I think it's an interesting way to think about work, right? Like you can say certain type of work a given role or a given task that someone's doing, right? Like there's certain things they do on a day basis that are simple things, right? It's four steps, whatever. Making my coffee in the morning, like it's four discrete steps. There's a correct way to do it. There's a wrong way to do it. There's also complicated things I [00:49:00] do that are, you know, slightly more whatever. And then there's also complex things I do that there's not a clear right answer. It's hard to do.

And sort of the way I talked about it in the book is, you know, if you think of these things sort of as a pyramid, there are these two kinds of forces. One is globalization, I use the word machines. I debate on this a lot about, but like technology more broadly. I would sort of like lump AI into this thing, but these two forces of sort of globalization in machines that are kind of eating their way up the stack, right? And so like a lot of maybe the early stages of globalization was a lot of this simple work that got eaten by one of those two things effectively, right? That things got outsourced. They got to moved overseas for a lot of people in developed countries, manufacturing from the US of China, kind of that classical stuff or it got automated.

I did a tour of the Toyota production plant in San Antonio, Texas, right? And it's like, there's got about a lot of big machines, right? There's people there that are doing stuff as well, and like the people are important. They've automated a lot of that, like how that sort of, production works.

And so my thesis around, I think I might have used the term AI. I certainly [00:50:00] wasn't like knowledgeable about AI to like make any sort of interesting predictions. But like to me, it's like a part of that machine group that is just like eating up that stack, right? So now I think, a lot of things software did a lot of simple things, right? Like, if you can write a deterministic, if you can write a set of steps for this thing, the software can do those steps in a deterministic way. And AI, I think is when it starts to get into that complicated stuff, right? That you can have things that require certain expertise and heuristic decision making. And you know, it seems plausible that the trajectory that AI is on will get to where it can do that kind of work, right? Like, I guess my sort of mental model for AI is like, it can like let anyone be mediocre at anything.

You know, if you've seen like AI write a history paper or whatever, like it writes a pretty good freshman, sophomore, level history paper of the impact of Napoleon on Russian culture or whatever, right? Like, it's like a pretty decent attempt at that. But it's not like really good, right? Like, I don't like, I don't like have chat GPT write me an essay on, like write, you know, something and like be like, oh, this is like really not, it's like, [00:51:00] it's fine, it would probably get you, I don't know, a B or a C if you like, turned it in and your teacher didn't know, know what it was or whatever.

So I guess that's the way, you know, I talk about in the book, like becoming more entrepreneurial. Like, I think another way of saying that is like, getting better at dealing with complex environments. Emerging things are changing fast. How do you do that kind of work? Because that is the thing that is, that's what's scarce, right? That's what's hard to do for people, that's what's hard to do for machines. And so getting good at that is making yourself more valuable, I think in the long run.

David Elikwu: Okay. Yeah, that makes sense.

Why niche markets thrive on the internet

David Elikwu: I think the other part that links to what you were saying that I think is interesting is, so Naval Ravikant has, I think at one point, essentially the quote from him is something like, there's two ways to make money bundling and unbundling. And I think part of what made the internet age really great is that it unbundled so many things, right?

In order to make money and for a business to be successful, it no longer needed to corner a market. [00:52:00] You could make money, just like you were saying, in loads of niche ways. You could have your podcast in one corner of the world, which is just about one particular US football team or college football team. And you could have your business that sells mid-century modern cat furniture. Like you could do all of these very niche things. Because the internet allows you to find all of the people distributed around the world that make money doing that thing.

And I think I heard someone else say something similar today, but I think he was just commenting on when people talk on the internet about how, okay, starting an e-commerce business, you can make millions and things like that. A lot of people think it's a scam. And a lot of people, I mean, there's definitely plenty of scams, so I'm not saying there's no scams, but I think the point is when you hear about, okay, all of these e-commerce businesses that are making 7, 8, 9 figures, it seems incredible, but it's because, okay, so I just finished reading a book called Flatland. I'm not sure if you've come across it. It's really good. I'd highly recommend it. It's a, it's an old book and it's a bit weird. It's basically [00:53:00] just about a world of a flat world that is two-dimensional and someone comes from a three-dimensional world into the two-dimensional world and explains to someone in that two-dimensional world that there are other dimensions. So they take them up into the three-dimensional world and they're like, whoa, you guys have spheres here. Because in their world, everything is just flat, right? So things are just straight lines or things have points, but you can't really figure out that they're points. 'Cause if you are actually flat, then you don't know how many sides of shape has, anyway, it gets a bit complex.

But the point is, it just made me think of that where, when you think of the internet, what that allows you to do is go up another level. 'Cause when you are in Flatland and you can only see the world in one way, you think of things as local. And so when someone explains a business that makes a lot of money, you're thinking, oh yeah, like within this local sphere. But actually the internet is up a level and you can go down into, you know, Japan and China and you can make money in all places in the world. And so it's actually super easy to have a [00:54:00] seven figure business because it's so distributed. Like it's not in one place. If it was in one place, it'll be a very different type of business. But because you are able to come up into 3D land, you can make money from all around the world and it's very different.

How AI might rebundle everything

David Elikwu: So I went on off on a bit of a tangent there, but bringing it back to AI, the thought that I had was, there's a sense in which AI kind of rebundle things. Because before, for example, you know, you would go to Google to search for text, you would go here to read something, you'd go to your library or you, you'll go to blogs or research papers or wherever. Then you go somewhere else to create images like, you would be multimodal in how you approached life, how you approach research, how you approach learning, how you approach entertainment. And there's a potential future where a lot of these things just coalesce and actually open AI or choose your tool of choice. They begin to aggregate a bunch of different services. And I think, you are already starting to see that there's some AI tools that could generate characters, they can generate images, they can generate potential movies.

And I wonder what [00:55:00] happens when you no longer need to go to different websites, to different places to see what you need to see. Like if you could just type and the entire film was generated on your laptop, like within the same screen here's a film that you can watch. You know, what does that do to, I dunno, to creativity, to entertainment, to books. So the things that you could be doing as an entrepreneur, I wonder how much of that gets eaten up by the AI.

So all of that's on one side, and then on the other side is this idea that a lot of this comes at the price of our cognition. And I wonder what happens when, if you never need to, like I think we've already lost one set of skills, which was, for example, mental maths. You don't need to learn to do mental maths if you have a calculator. And then what you currently use a calculator to do, if you just ask chat GPT, what is this? What's the percentage of this? It's just gonna tell you, you don't even need to learn that. And in a similar way, at least in our generation, you still have to do some research. Maybe you could use the internet for some of that research, but you don't have to go to the library and learn how to look for books. You could maybe do some research on the [00:56:00] internet, you can look for webpages. What happens when you no longer need to learn to look for webpages? All you have to do is just type a search.

So all of these different functions just coalesce into such, such function and, just being able to think of what you want is all that you need to be able to produce a vast amount of things. So I just wanted to know what you thought of the coming together of all of those ideas.

Taylor Pearson: My wife and I like those like, like every year Netflix has like five, like sort of C grade Christmas rom-com movies where like the script feels like AI generated. Like if it's not AI generated, it could totally be, you know what I mean? It's like the same cliche plot line where you could like predict the thing or whatever. So whoever's producing those is screwed because that for sure can be turned over to AI.

David Elikwu: Yeah, hallmark

Taylor Pearson: complex I've seen that movie five times every year. Yeah, exactly. Exactly. Hallmark. Hallmark better have some good AI engineers because yeah, someone is coming for them.

I think that's interesting. And I, you're talking about like the flatland thing, and I like the bundling on [00:57:00] unbundling framing because right. It captures a sense in which like nothing is novel, right? Or like, we're just like recapitulating certain things. So it's like, in a certain sense, I think about, it's not that there's no local businesses on the internet, it's just the way you define local is different, like local might mean a forum or a subreddit, right? Like, that's the thing that happened. Like in the ways someone would be well regarded in their local community of, you know, 5,000 people, it was like in their neighborhood because they were a good plumber, right.

That same phenomenon exists on the internet. It's just like you're a common poster on whatever the personal finance subreddit, and you have helpful things to say about, you know, how people should do their budgeting, and you're a trusted and valuable member of that community and that gives you access to certain opportunities that people will trust you and whatever. And then you have an online course that you sell about how to, you know, get your budget right, or you do some consulting or you write a book or whatever. So I guess I have that, like, same intuition about the AI thing is like, It's just gonna change sort of the definition of like what local means or like how that work like, instead of being local, [00:58:00] you know, I think about like the cat furniture business. I tried to, I tried to draw this image at one point. Maybe I could see if I could get an AI image of like, instead of like New York City, you have Amazon, right? And like, you live on the outskirts of Amazon and you're on the border of like Amazon and Google. And like, that's how people, you know, people find you through those two channels. And like, that's the local place that you occupy on the internet. And you know, instead of selling plumbing, you're selling, you know, selling a plumber, you're selling cat furniture or, sort of whatever it is.

I guess that's the intuition I have that like, it bundles and unbundles in a different way. Yeah, I don't know, right. And I think, like, maybe a good answer to your question, like, what would I change about the book now is I think I like, I like probably overestimated the extent to which the internet would like remain like, somewhat decentralized or like somewhat distributed.

And I think right. Instead we've ended up with a bit more of like this wall to garden phenomenon. You know, like, if you, if you like Sci-fi, there's a book by Neal Stephenson called Snow Crash that was like, I think he coined the term Metaverse in that book. It's like from the nineties.

It sort of like imagines this [00:59:00] future, where it's like Ready Player One, if you enjoyed that book. It's like sort of a conceptually similar book. It like imagines this future of, like, nation states have kind of collapsed and you kind of have this like reutilization. And so I think, I think the protagonist lives in, I think it's called like Mr. Lee's Greater Hong Kong, like now encompasses like the west coast of the US and like Vancouver, Canada, right? That's this sort of like new jurisdiction of like greater Hong Kong, you know, I don't know. I just thought that was like such an interesting concept, right? It's like we're just redrawing the lines here, we're we sort of doing it.

That's my intuition about AI is like, it just sort of like redraws the lines in a different way. And like, maybe it is something that's like a lot more centralized, right? Like maybe there's huge economies of scale to it because access to certain data sets, chip production becomes, you know, you can't make a good AI model without using one of four play, you know, open ai, Google, Facebook without having access to one of these four sort of players and that, you know, yeah. You end up in some different sort of jurisdiction.

So that was a long-winded answer. I'm not sure like really got the heart your question, [01:00:00] but the unbundling bundling seems directionally correct way to think about it.

David Elikwu: Okay.

Rethinking work in a world with AI

David Elikwu: Tying this slightly back to what we talked about before, do you think it changes the heuristics that people might have? So, you know, we talk about like navigating with compasses or gyroscopes and, the Turkey problem of people typically may have had heuristics of this is the part that you go on, here is how you get a career, here's how you get a job. Do you think it changes anything about that process of how people find what kind of things to work on?

So for example, just using the example we just gave, maybe you don't think about, you know, going and working at Hallmark right now. Maybe, maybe you think of a different company or a different industry to work in. Do you think it changes any of that at all? Or like any mental models that people might have for picking a career or picking a field?

Taylor Pearson: That's, I'm not sure I have a good answer that question. I think, I think it's certainly worth thinking about. Douglas Adams, the author of The Hitchhiker's Guide, the Galaxy Series, which is one of my favorite fiction series. He has like a great quote or something like, everything that exists in the world when you're born is normal and the way the world [01:01:00] should be, everything that's invented between the time you're zero and 35 is new and exciting and you could build a career in, and everything that comes into the world after you're 35 is unnatural and against the way things should be and should be stopped or whatever.

And you know, right. there's a lot of truth to that observation. Yeah, I feel like it's certainly worth thinking about, like what extrapolate the AI thing outwards and like, what is that? What does that look like? Like I, I mean, I think one thing is like, to our conversation earlier about like what is safe and what is not safe, right? Like you have certain careers that look safe or, you know, may look safe to most people now that in fact aren't super safe, right? Because, you know, you're having this sort of changing landscape of what is valuable and like how the economy is structured. But I guess I think about through the same ones I mentioned earlier, it's sort of like the first wave of machines, technology, globalization, sort of ate away at the sort of the simple type of work. Like, I think AI like, it starts to eat away at the more complicated. They're like a junior coder is a good example, right? Or there's probably like lots of like, junior legal professions. Like we think of like, sort of [01:02:00] mid-level or junior levels in like a lot of fields where like, it's not as defensible as it used to be, right? Like, you know, I moved into like a older house and I'm like learning about home maintenance and all this kind of stuff, and like, chat GPT is awesome for that, right? Like, I can get to like a three out of 10 plumber knowledge, like pretty fast.

Does that make me a good plumber? No. Like, you know, I mean, I'm not qualified to do something, but like, I can get a basic understanding, I can get to like mediocre at something like a lot faster than I used to be. You know, that like first half of the learning curve I think is a lot faster. But yeah, I'm not sure it like affects that much on the second half of the learning. You know what I mean? Like being truly exceptional is something feels as or more valuable as it used to.

David Elikwu: Yeah, that makes sense. And actually I'm very glad that we talked through this part 'cause it's also helped me to solidify some of my thoughts on certain things. I think that some of the stickiest jobs will also be the ones with the highest risk asymetry.

Literally just came off the back of what you were saying where, okay, so thinking about law [01:03:00] specifically from when I worked in law, people were already talking about, this is before we were talking about ai, but tech was already starting to be incorporated into law.

And there were already these murmurings that, oh my gosh, you know, some lawyers might be replaced by technology. And that seemed like nonsense to me because, and my reason why has changed from now, but at the time it was because, I worked at a firm where, I mean, we'd had a merger with a US firm. So now it was a much bigger firm, but the original version of that firm, we had people that I worked with where, so there was one guy, I think he was almost 80 or something, and he had been a trainee when the first, so that's like a first or second year associate when the first Star Wars film came out. And the person that he worked with that he trained under was also still at the firm. And the person that he trained was also still at the firm. Like you have like three generations of really old people that all one, one trained the next all at the same firm.

And when they were first and second year associates, they didn't have email. There were no email, there were no computers, there were no type of writers. Secretaries used to write [01:04:00] by hand what a partner dictated to them. So first of all, imagine how hard that job was. And then, and then trying to get everyone trained on email or trained on typewriters first, and then trained on email. And you think at some point, oh, you know, you're not gonna need all these secretaries. People are worrying about what's gonna happen to trainees. Because for example, I think trainees used to have to like, write things out behind or, or to copy documents. They would just type them out again. And that was how you made extra copies of documents that you needed to take with you. And you would think, oh, we're not gonna need all these trainings. And now before you would have like two or three, now you have dozens. The same in the US you have some associates and you have first and second year associates. You have so many more of them because there's actually way more work for them to do.

But I think, the reason my thinking has changed, I still come to the same or similar conclusion, was just off the back of what you were saying, where I think it's just a function of risk. And it's the same reason right now. People are still not accepting self-driving cars. If you drive your car and you kill someone, you can say sorry, and it's like, ah, you know, at least there [01:05:00] was a human that you can either forgive or hate for the rest of your life. If an AI, is driving a car and kills your child, what do you do? Like the anger that you have, you have nowhere to direct it. And I think that's a big reason why people hate it.

And so it's the asymmetry function there where, if the risk could involve AI killing someone, people are not necessarily gonna be on board.

And similarly with law, if the risk is your company's gonna lose millions because this AI didn't think to check this other thing, good grief. Like the, the lawsuit for the first you know, law firm that tries to employ AI on something serious is going to be astronomical. I can't imagine being the partner that decides, oh yeah, we're gonna take this risk, especially on something serious.

And so I wonder how, how long it will take for some of these things to be sticky. Whereas if the risk like plumbing, Hey, I can just say what's gonna happen? The risk is maybe I can't use the toilet for a little while. You know, the risk is, okay, now I have to call a real plumber to come and do the thing that I just messed up. I made it even worse.

So I think that's how some people might do the [01:06:00] math.

Taylor Pearson: I use chat GPT, for writing stuff, and I find it's just like it, to your point about the bundling unbundling, like there's just certain things, like it's really good at like analogies, like help me. I'm trying to, I'm trying to explain this concept, like throw out some analogies for me or like, I was trying to do something with like a sports metaphor and I was like going back and forth with it, trying to come and it was like, great at that.

But yes, it's certain, like I would never use it for something where I needed to be like 99% confident right. Like something where I'm happy with where 70% accuracy is sufficient. Great. That's fine. Like, I'm gonna do some sort of like, brainstorming exercise, but I, I just, yeah. About law for searching. I wouldn't, I do, I have a chat GPT bot that like, have a little prompt in there for it to be a lawyer or whatever, and like I'll talk to it or whatever. And it actually is, it is useful for like me coming up like, before I have a call with a lawyer, I will come up with the you know what I mean? Like I'll use like, come up with the questions and get like, be mediocre, you know, be three out of 10 or whatever to like be able to participate in that call. I wouldn't like make a major financial [01:07:00] decision on the basis of that thing.

David Elikwu: Yeah, exactly. I think same. And I don't want this to turn into, you know, we're just talking about law, Here is one maybe to connect to your investing, which is probably one of the, the main things that you do now running the Mutiny Fund.

But there's an obvious, tell risks that people talk a lot about with ai, which is that it's gonna come and kill everyone. And so maybe not specifically to talk about that, but I would love to know how you think about tail risks in general. 'Cause I've heard you talk a little bit about the way that you do investments, but actually, you know, maybe taking a step back from that, why would you even do investments by yourself? Why would you invest, there is a safe way potentially to do money where you just spread the risk out in a non ergotic way across the entire market. And you just say, Hey, I'm just gonna put all my money in ETFs. Why would you choose to do anything more complicated than that?

What is ergodicity and why it matters in investing

Taylor Pearson: Yeah, so I think, you've mentioned ergodicity couple times, so maybe it's worth like talking about that because I think that sort of, plays into what we're talking about with the career stuff and also the sort of investing stuff. So, ergodicity the term from physics, but [01:08:00] basic idea of ergodicity is, when you have two scenarios.

So, one is, I'm gonna use my own terms necessarily technical terms, but what you call like an ensemble average. One is we'd have what's like called like a time average. So you can think about it, you know, does one person doing a repeated action over time get the same outcome as many people doing one action, right?

So, in the case, if you flip a coin, you have a hundred people flip one coin, and you count how many heads and tails there are, or you have one person flip a coin a hundred times, statistically it's gonna work out to be the same distribution, right? You're gonna have the same thing.

If you have a scenario where, the fun example is Russian roulette. If you have six people play Russian roulette once, as opposed to one person playing Russian roulette six times, you get a very different outcome, right? If six people play, once one person loses, five people win, and five people are very happy. If one person plays six times in a row, they're guaranteed to lose eventually. So in a not necessarily, you know, a situation where the ensemble and the time average are, or path are not the same as said to [01:09:00] be non ergotic.

And so, it's interesting with respect to like, careers and technology and paths and stuff, right? 'cause it's like, just because it worked for someone else at another point in time doesn't necessarily mean it will work for you now, right? It depends what path and what director you're on.

But then I think also very interesting in a finance, and investing context because, you as an individual do not get the average returns of the market. You get what you get based on the path that you're on. So, if you have a child that gets sick, if you need to support a parent, if you have get laid off, if you wanna start a business, right? You have all these sort of inflows and outflows that matter, you know, impact the trajectory.

So like, You know, one example I give, this is like The Dow Jones Industrial Index from 1966 to 1997 returned on average 8% a year. But it did that in two very different ways. So the first part of that period, not remembering these dates exactly, but let's call like 66 to 82, it was basically flat. There were no returns. And for the second part of that period, that's called 82 and 97, it had 15% a year returns, right? So it had 8% on average over this 30 year [01:10:00] period. But the trajectory of those really matters, right? So if you are 65 years old and you retire at the start of that time period, you are drawing down that whole period, right? You're sort of spending your money and so you don't get the average returns because by the time the sort of the strong period of returns comes in, you've already withdrawn a lot of your wealth. If you do the inverse scenario, you know, you get strong returns. So that I don't remember these numbers off head, but are off the top of my head. But something like a, you know, let's say a couple that retires with $3 million and they're planning to spend $180,000 a year in their retirement. If they get that bad period first they go broke after like 12 or 13 years, right? Because their investments aren't appreciating and they're just drawing down on it. If they get the good period first, they get the strong returns. Their retirement account grows a ton, right? They're only withdrawing a portion of it, it's going up 15%. You know, it peaks at 12 million and their retirement savings last them for 70 years or something.

And so, sort of central to the way I think right in investing is like, we don't know the future path of returns, right? Like we don't know what the trajectory of those are. We don't even know the average. But even if [01:11:00] we did know the average, it's not enough to know the average. You also need to know sort of the sequence and the path. So I think this is interesting and relevant to most people in the sense that, a lot of times when people get financial advice, they talk about, oh, you know, the stock market returns 7% on average. Which is a correct statement, that's a roughly true statement from the historical data I've seen.

One of those things is that you can drown in a river that's two feet deep on average, right? If it's shallow along most of it and has one very deep channel, you can still drown in the channel. So, you know, you can withdraw 4% a year from an investment strategy that earns 8% a year on average and still go broke, right? Because it depends on the trajectory, the path of sort of what those investment returns are.

So that's kind of the central idea I've been interested in and sort of, I think how that applies is. I think a lot of investing advice, investment education doesn't tend to make that delineation about like, path and ensemble or, like averages can be deceiving in that sense.

And so, sort of part of my [01:12:00] philosophy and how I think about it is, it's not just trying to maximize whatever your long-term expected return is. It's also thinking about like the possible path and trajectory by which you get there, right? That if you're, you know, you have a down period or 15 year flat period or whatever it is, and you need to withdraw funds at that time, you're not going to get the averages right, because you have inflows and outflows over that period.

So, yeah, again, been a long-winded thing, but I think that's, I think that's a really important concept that does have a lot of impact on how most people think about their investments. That's not broadly understood.

David Elikwu: Okay, so how do you avoid that then? Because I think this connects to some of the other things we've talked about. We've talked about tell risks to an extent, you know, something that seems wildly unpredictable, but it can also happen.

How to think about risk in work and life

David Elikwu: It's ergotic in the same way that you could have, I mean the Russian roulette analogy is a perfect example. There's six bullets in the chamber. If you get the bullet on the first one, you don't get to live the rest of the five empty ones, right. And so the [01:13:00] losses are irreversible.

And in a similar way, with careers, with a lot of different things in our lives, if you, okay.

So you could say careers are non-ergotic in a sense where, if you have a company that works their people really hard, grinds them to the bone, you could have a lot of people that potentially burn out. But the thing is, the odds for the individual are not the same as the odds for the company. For the company, they are playing the ensemble. They have a hundred people and every single one of them is gonna work however many hours. And a few of them burn out, but they still get the rewards at the end of that for the individual, each individual they get the time series average where they actually have to work through every single hour and day after day.

And the thing is, let's say you have X odds of burning out. If you burn out early on, that could irreversibly change your ability to work the rest of those hours. So you don't actually get to live the rest of that timeline. Applying that to investing just like you did, if you take a big loss early on, even though the average result over time is different, you don't actually get to live the rest of [01:14:00] that, that time period.

So I'd love to know how you think about. Because the thing is with tail risks, a lot of people don't necessarily want to hedge against them. Like if I said, oh, once in a hundred years there's going to be a global pandemic. We just had one a couple years ago. I'm gonna think, Hey, you know, that gives me a good, you know, 97, 98 years, no need to worry. But the thing is, one in a hundred that could actually be five years from now, and suddenly it's a very different picture. So how do you balance these two ideas?

Taylor Pearson: I like the company and employee thing. I like between venture capitalists and, like startup founders is, they don't like the venture capitalist gets the ensemble return. So oftentimes their incentivized to say, yeah, go big or go home, see if you can do this really good.

Whereas the individual does not, they get the return of their particular company's trajectory, right? Well, maybe let's be a little bit more conservative and we'll take a path that's more likely to work, but maybe isn't as, as high. So I think, yeah, it is an interesting distinction as well with the company, right?

But I think sort of like in the, investing context, and I think it's actually, it's harder to talk about with an individual in investing it's a little bit [01:15:00] simpler that like, the idea is just thinking more broadly about diversification is like basically the main way to think about it or thinking more realistically about sort of, you know, what to expect on the future.

So like, again, I'll give like rough numbers here in the case of like, you know, say the average returns of stocks is, is 7%. Well, the 50th percentile is like 5% and the 25th percentile is like 2%. And average returns per year or compound annual growth rate. And so like, yeah, I guess it's like a bit unintuitive, but like the average is highly weighted by the very good outcomes, right? So you have some very, very strong periods and those bring up the average. But like, you don't know where you're gonna be in those periods. Like, are you gonna be invested in that period or are you not? Is that period gonna happen in your, in your lifetime sort of thing? And then, you know, I think to your point about tail risk and sort of, how do you think about the appropriate tail risk?

Like the number one way to be successful is to not die. The precondition for living is not experiencing death. Both like literally and metaphorically. And so eliminating or [01:16:00] severely reducing that possibility is very valuable, because it allows you to continue to play the game, right? If you can like mitigate that sort of sequencing thing.

So I think that's where it gets, I think people get tripped up or it's not exactly intuitive. They're like, oh, this thing is very unlikely to happen. Which may very well be true, but like, if the impact is sufficiently negative. It's still extremely problematic to sort of what that long-term growth rate is.

David Elikwu: Okay, that makes sense. I've heard you mention before Herschel Walker Syndrome. Could you explain that?

Taylor Pearson: Yeah. So, Herschel Walker was a running back American football player. He was most famous, he played for the Dallas Cowboys. He was like the great running back of the era of generation. And well, I don't, 1990, I'm trying to remember what year it was, he got traded to the Minnesota Vikings and the trade is like now called the Great Trade robbery.

And basically the Minnesota Vikings like, gave up a ton to get, you know, they gave up like four first round draft picks. I can't remember. [01:17:00] Basically, they were saying, okay, Herschel Walker's the greatest player of all time of his generation, and if we get Herschel Walker, we're gonna win a Super Bowl. And that's, sort of that's the number one thing. And Dallas was speaking about it much more from like a portfolio perspective. They're like, all right, we're giving a Herschel Walker, but we're getting four number one drastic picks and all this other stuff. And that was sort of like the peak of the Dallas Cowboy. I think they won three Super Bowls over like a five or six year period. And like a lot of the players from the Super Bowl teams were like the draft picks they got from the Herschel Walker trade.

And I think a lot of people tend to think about investing in the same way that like the Minnesota Vikings side about Herschel Walker is, it's like, oh, I need to pick the best thing, right? I need to get the number one thing that's gonna do the very best. But like, what really matters is like how the whole team plays together, right? It's how all the different things, all, all the assets in the portfolio interact, right? And so, you know, did the Dallas Cowboys get any players that were as good as Herschel Walker? Probably not. but in aggregate they were better, right? And that's what the, so, you know, they could have all those [01:18:00] players in the field, and that was sort of the trade.

So that, that's my observation about a lot of people tend to think of investing as, like, it's, I need to pick the winner, or I need to pick the best thing. And they don't think about the overall portfolio and how all the pieces work together.

Why diversification is more than just finance

Taylor Pearson: So like, coming back to our ergodicity and, and talking about sequencing risk it's like, sometimes it may be better to add a investment to a portfolio that doesn't have as good of strong returns, but is a diversifier against the rest of the portfolio, right?

So tail risk stuff would be something that may, like, is it gonna have the best long term returns. Not necessarily, but that's necessarily the point. The point is how does it interact with all the other elements in the portfolio.

David Elikwu: Yeah, that makes a lot of sense. How much does it make sense to hedge against these big risks? Because, for example, okay, I can think of a few different models or a few different people have said things about this. You know Charlie Munger said, okay, we don't try and be smart. We try and avoid being stupid.

I think even in this conversation we talked about the idea of the best way to survive is not to die. So if you want to be able to [01:19:00] live long and benefit from all the experiments you could take, you have to avoid being completely wiped out.

I had Luca Dellana on the pod a little while back, and he talks about a similar idea where, you know, again, instead of trying to win, you trying not to lose. I think he used the example of Elon Musk where, Elon Musk has survived going bankrupt so many times that if you imagined all the other alternate universes where Elon Musk exists, he's probably broke in quite a few of them. And actually we are living in the one universe where Elon Musk gets to be the richest person in the world simply because he is taken so much risk. And actually it might be better to optimize for you know, I think the Model Luca uses is, how could I create a situation so that in the maximum number of alternate worlds I am equally happy? And so I am kind of like cruising along at any equal pace in, in multiple universes. And so I'm not taking on too much risks that I could be wiped out, which means I don't get to benefit from future attempts.

However, going back to what we discussed earlier, [01:20:00] there is such a thing potentially as playing it too safe and not taking enough risk. And actually if you don't take any risks or you take risks too infrequently, you are not used to risks when they arise. And so the big risks that you do feel are so much more painful because of that.

So how do you think of the balance there, both in investing and in life in general of balancing? Okay, we need to build some muscles of learning to take risks, but then also you don't want to take so much risk that you could be potentially wiped out.

Taylor Pearson: Yeah, I like the exercise example you gave, like jumping off a wall is nice, right? Like you want more moderate stressors are more moderate risk and less significant tail risk, right? So like, I think, someone's like running a small business or working small business. You have a lot more moderate risk, this client doesn't pay, this thing doesn't happen. but you're a little bit more in control of your destiny, right. Like you're sort of like directly interfacing with the market. So, you don't want to eliminate risk. It's that you want to eliminate the very, very big risk and you want to take more of the appropriate [01:21:00] medium term risk.

So like, one of the concepts I had in The End of Jobs, this idea of like stair stepping in your career that like, you want to try and do something that's like reasonably adjacent to your skillset as opposed to like, you know, oh, I'm gonna leave my corporate law job and I'm gonna go do like an AI startup where I have no experience in AI and whatever, right. Like. It's a lot harder than like, I'm gonna leave my whatever job and I'm gonna do something that's like reasonably adjacent to it, where like my existing network and skills or whatever are somewhat transferrable and do it right. Like it's still a risk, but it's not like I'm gonna start from scratch kind of thing.

So that tends to be the way I think about it career-wise.

David Elikwu: So from your time running the mutiny fund, is there anything that you've learned from your time as an investor that you can apply to the rest of your life in terms of whether it's the level of risk you undertake or the way that you approach starting certain projects? You know, has that changed the way that you think about any other aspects of life?

Taylor Pearson: That's a good question. I'm not [01:22:00] sure. I think, like I do think about the ergodicity stuff a lot and like the path dependency stuff a lot more. I'm not sure I like any like, great concrete examples other than just like, those things tend to be on my mind a lot more when I'm like thinking about particular decisions. Like what is the sort of like trajectory or, or the path here.

I'm a big fan of Lucas' work that same way of like okay, across multiple universes, like how do I maximize the probability, maximize the number of them in which things work out pretty good. I think that's maybe one shift in my thinking as a result of it. And I think.

Yeah, I don't know. I think that that's the main thing that comes to mind.

David Elikwu: Okay. Fair.

The Helsinki Bus Station Theory explained

David Elikwu: Just because it came to my mind from what you said, could you explain the Helsinki bus station theory?

Taylor Pearson: Oh, yeah. No, I would love to, I think it was a commencement address at a, a photography school, an arts and design school. So the Helsinki bus station, the way the bus routes are designed is there's sort of a central station, and I've actually never been to the Helsinki bus station, but this is how it goes in the story at least.

And all the bus routes start leaving along the same path. You know, [01:23:00] they're leaving the main road out of the bus. And you can think of each of these steps as like a year in your career. And so everyone, whatever gets done with high school, graduate from university and like, you kind of start off on the same trajectory, right?

And you get, you know, oftentimes you'll get a year or two in and you'll look around and you'll say, I'm kind of doing the same thing everyone else is doing. You know, you're an artist, you're looking around at you're working, you're going, oh, this is derivative, right? I'm doing this. Like, I'm copying some other artist that I like, right? I'm doing some sort of copy derivative thing. And what a lot of he'll do is they get off the bus and they go back to the bus station and they get on another bus, and then you go two or three stops and you look around and you get into the same scenario. Everyone else is at this bus stop. Everything's going different, everything looks the same and starting to go back to the bus station. And so the Helsinki bus station theory is, you stay on the bus because the further the bus gets out from the bus station, you know, the paths start to diverge, right?

And you're sort of, you know, in the context of like, if you're an artist, you're doing photography, right? Your work starts to evolve, it starts to get unique, you start to develop your own sense of taste. [01:24:00] First, it's maybe a blend of two or three artists that you admire. And like, now you've taken that, you've incorporated and you've done something slightly different like, in the same in your context of your career. Like, I think, you know, most people three to five years in their career like, I don't know how much novel stuff are they doing? Like, probably not that much.

I mean there's research on this as well. Like, I think there's some, like, they sort of like average age of like Nobel Prize winners and like, I think it's usually like 12 to 15 years into their career or something. Like, there's something like that, like it takes them a while to get to the edge of whatever they're working on, right?

Like the third year PhD student is usually not doing something groundbreaking. They're doing something derivative just like getting them closer to sort of the frontier of their field. So like, I guess coming back to like our compass and our gyroscope it's like, what is that sort of gyroscope down the bus path look like and sort of how do you stay on the bus of like, how can you take what you've already got the skills, the assets, the relationships, all those sorts of things and weave them into the next thing.

David Elikwu: Yeah, that makes a lot of sense.

Apprenticeships, scenius, and creative growth

David Elikwu: And just the last thing you [01:25:00] were saying made me think of. What you talk about also in your book, which is this idea of apprenticeships and because, okay, you mentioned the Nobel Prize winners, you might also know that a disproportionate number of Nobel Prize winners worked for or with other Nobel Prize winners.

And you can find some, you know, almost like factories, unintentional factories where there are two or three different Nobel Prize winners that all worked at one point within the same university working with one particular person. That person themselves may not even have a Nobel Prize, but at least there was a starting point where all of them kind of diverged from.

And I think that's also a another underrated aspect of life building or career building, which is just kind of learning from other people as well.

Taylor Pearson: Very much it. Kevin Kelly, he has a term he uses called the Scenius that I like, you see this in history a lot that like how creativity emerges in certain groups, so, like Paris in the twenties or the Vienna Circle. Someone was telling me about this, like this is an AI thing that like a lot of the sort of most for AI people were the same. They were [01:26:00] like, there was like two labs 10 years ago, right? There was like two people that a lot of them were working for that, like that was sort of the promising approach that they all came out of.

David Elikwu: Yeah, exactly. Wow.

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