You've been in hundreds of companies. What did you learn early that still shapes how you invest today? Before we started Hustle Fund, one of my co-founders, Elizabeth, and I were working at an accelerator called 500 Global. And the unique property of being in an accelerator is that you get to have access to tons of data. At the time, I think they had close to 2,000 companies that they invested in, even at that point in 2017. So it's a classic accelerator program. They get a batch every quarter or so, 30 companies, 50 companies sometimes. An interesting exercise that we informally did was we tried to stack rank the best companies from one to 30 or however many companies at the beginning of the batch, one month in, the very end. And then in some cases when we could do it one year later. And the shocking thing was our stack ranking about one month in did not change indefinitely into the future after that. And the reason why that was the case was once you're about a month in with these companies, you've had a chance to witness how they work, how they operate, see what kinds of metrics that they're going after and how successful they are in executing against those sprints. And that was really the genesis of Hustle Fund. We think that Hustle, which we define as great execution meets high velocity, is one of the best leading indicators of success. And that it actually penetrates through all the noise of other kinds of factors that a lot of other early stage managers try to judge teams. You are very focused on the concept of hustle. Obviously, it's in your name. How do you know so early on whether somebody is actually a hustler versus they're simulating hustling or they're trying to make it seem like they're a hustler? I'll tell a super quick story that is tied to the genesis of Hustle Fund. So a long time ago, 12 years ago, I was a product manager at Meta. And at the time, there was something like 270 product managers. All of us actually had to do one-on-ones with Mark Zuckerberg. And I was not a very good product manager at big companies, but I was obsessed in trying to understand the top 10% of PMs. I was like, why were they so successful? Why are they continually being rewarded so much for their efforts? And what I learned after talking to all these product managers was that they weren't necessarily smarter than me or anyone else in the organization. However, their throughput of code shipped was almost like 10 times higher than the rest of the population. And number of lines of code and the code base. You could actually literally see it. So for us, hustle is really about that kind of throughput, which is we want teams that are going above and beyond being able to ship, even beyond what seems feasible in any unit of time that you're measuring them. So if you're trying to judge hustle based on a pitch alone before you invest, you can't. You're basically guessing. You're trying to use your best judgment. But our model is to make that initial investment to teams where we're curious. And then the only way that we can truly judge hustle is by working with them on sprints over the course of eight weeks on a growth project. That's the process that follows afterwards. At that point, there really isn't any affect of trying to pretend that you're working. You're already an investor and you're already on the same team. It's that Stanley, Drunkenmiller, invest and investigate, meaning you write a small check and then you learn more about the investment. Every single person in the pitch claims that they're a hustler. And actually, I don't think that they're lying either. I think they truly believe that they're a hustler. But measurement through how they are tracking their throughput, how they are actually shipping their goals. That's harder to fake. There's also, I think, a little bit of the art behind this business because there isn't what we've learned, any standard metric, like number of lines of code or number of sales that you've closed, etc. It's really unique to the team. Why are you measuring the certain metric as your North Star? And how are you outperforming in terms of experimentation to try to drive towards that metric? And that's something that you just have to witness by participating in their sprints. Something that we really think about at my firm is this quantity equals quality. if you think about why is it the top 10% of PMs at meta were producing 10 times the code part of that is they're obviously able to work faster and their brains just functioning on a faster level they have more grits they're able to spend more time after hours on the weekends all these things like you know the anti-work-life balance but part of it is doing so much code and all the error and all the pattern matching that you get from making the errors actually makes you a top PM. So it's not just that the top PMs write a lot of code, it's the people that write a lot of code become top PMs. One of the hardest things of investing is seeing what's shifting before everyone else does. For decades, only the largest hedge funds could afford extensive channel research programs to spot inflection points before earnings and to stay ahead of consensus. 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The best part, these proprietary channel checks integrate directly into AlphaSense's research platform, trusted by 75% of the world's top hedge funds, with access to over 500 million premium sources, from company filings and brokerage research, to news, trade journals, and more than 240,000 expert call transcripts. That context turns raw signal into conviction. The first to see wins, the rest follow. Check it out for yourself at alpha-sense.com slash how I invest. It's a pretty interesting interpretation. I largely agree with it. Probably 90% of what product managers back in the day at meta were shipping in that era didn't work. It just, you know, you tested it, it just failed, right? But it was that 10% that kind of worked or really worked super well. And when you just have so many shots on goal, You just tend to find that the metric that you're trying to track against just goes up into the right because of sheer throughput. It's like a brute force kind of methodology. Yeah, we figured this out on the podcast. We've gone to five episodes a week. And my biggest fear, the thing that kept me up at night, I'm like, is the podcast quality going down? I would look at every metric every morning. I'm like, just waiting for the podcast quality to go down. And not only did the podcast quality not go down, these are like objective metrics in terms of like how much people listen to every episode, how many people finish the episode, all these things. It actually went up. And the reason for that is because I myself was learning, I was getting more reps. But beyond just myself, I was getting better at asking questions, I was getting better research, getting better doing pre interviews. Also, the editors were getting better, they were getting better at everything. And even so much so that the actual guests and the guest selection was getting better. So again, it's one of those things where you want to, we want to think that we could jump on a podcast once a week or once a month and have this masterful performance of excellence. But excellence oftentimes is these small little things that just improve over and over. It's a accumulation of 10, 20 different things that together compound and have a 10x return. But on its own, they're quite unremarkable. Many of the top GPs that I've interviewed, the best of the best of the best, there's a tendency to be more concentrated, to be more bold in their bets. You have this enormous portfolio. Why are they wrong and why are you right? The wonderful thing about venture is that everyone can be right. There's always different paths up the mountain. And I think for us as pure pre-seed investors, our entry point is always at the pre-seed stage. And 70% of the companies that we've backed, we're the very first investor, even before mom and dad. The longer that I'm in this game as a pre-seed stage investor, the more I'm convinced that all of us are just sheerly guessing Full stop It just sheerly guessing We making an intuition bet in that first check that we writing And the reason for that is there no data to really assess You can look at inputs like do they have really good pedigree? Do they go to like a Stanford or MST or something or work at Meta? That's all good too. But the ability to create a huge company from absolute scarcity with no resources from the very beginning, connecting the dots between that inception stage all the way to the scale business is so unique and singular that it's almost impossible to predict. But we do think that hustle starts to show you that indicator because it's about understanding the process by which these teams are learning and being impressed by the rate of learning. And if it's paired with a great market, that's great. So when we started Hustle Fund, we tried to intersect two fairly far distance theories of venture capital. One was concentrated portfolios, right? This is what we're discussing. And this is the classic model. Like we raised a bunch of money. We're only investing like 30 or 40 companies, maybe less, you know, lots of ownership in a given business. If we're right, we're really right. And then we can all make a ton of money, but it's a relatively small N, you know, N of 20, 30, whatever. That's a small sample size. So there's a high failure rate. Marrying that with, let's call it spray and pray, honestly, right? Like this notion that let's create an index on these early companies. We don't really have great data as to which ones are going to succeed, but we know that this is an outlier's business, right? So let's cast a really wide net. This is a very derogatory term in venture, I think the spray and pray notion, but actually love it. So the intersection of the Venn diagrams is hustle fund, which is let's cast that wide net and then do some level of concentration into the ones after we've had a chance to work with them and see that hustle firsthand, because we think our due diligence is very different. But for us, we're a lot less ownership sensitive than any other fund. At a small size, we never raised more than $50 million at a time. This is a long tail bet that you only need like a handful of companies, maybe like three, four or five that truly will pull up the entire value of the total portfolio. So this works for us at a very small size. I would say though, David, that if you and I were raising a billion dollar multi-stage fund, concentration is going to really matter as well as like your product all the way through like the IPO, because that's just how the portfolio mathematics works for larger funds. But for smaller ones, we can focus less about ownership target and like a concentration of ownership. Instead, focus on the multiple by which we can achieve great success from the entry point valuation for the company for that first and second check, that can actually drive all the performance versus the ownership. And that's something, frankly, that a lot of LPs today still push back on and don't believe. They have this bias for concentration. Rightly so. I mean, I think this has been the mental model of venture capital since the 1970s, right? It's this idea that, you know, I'm smart. I can see the future. My name's Eric. You know, bet on me to put in these incredible investments. And sometimes it does work. You know, you do find those outlier successes like the John Doors and Michael Morton's, et cetera, right? They sure have their fair share of failures, but their performance on the ones that really worked out are really great. I think that this is a hustle funds approach is a more intellectually honest approach to venture, which is just like, look, I precede who the hell knows, right? They might seem smart. We can get disappointed. They might seem a little bit risky, but we might get really surprised by the performance. Let's just cast that wide net and then use our skills for our collecting data and observation along the way to then make more informed decisions on how to double down. And you said before that pedigree is not that predictive, which sounds like a fun saying to say. But if you look back at what pedigree is, Stanford, Harvard, MIT, but also Meta, Google, today, OpenAI is Anthropic. You'd think being in those talent clusters should be predictive of future startup success. Why is pedigree a weaker signal than most people assume? For us, we think that this is an edge. This notion that great hustlers look like anyone and come from anywhere. Our belief is that if we expand our funnel very widely, have a really inclusive approach of anyone that we want to assess, and then really focus on the mid part of the funnel, which is judging their hustle, we can get better results because pedigree, I think, is really problematic in that I think it presumes a de-risking, which I just fundamentally don't believe in. But because it also presumes a de-risking, there's a different kind of problem that you have to manage now as a fund, which is entry point valuation, right? If David has been working 15 years as an engineering leader at Meta, he's not going to ask for a $3 million post-money valuation, which is where we often invest. He's going to ask for a 30, 40, 100 million. I interviewed Abe Othman, who's director of data science at AngelLess and now runs essentially fund of funds. And he has one of the most interesting data sets to play with, like tens of thousands of startups. And what they figured out is these obvious signals are actually priced into the valuation. So yes, Stanford engineer will have a better outcome than non-Stanford engineer or Harvard Business School founder, which a lot of people like to say that they're not more successful. Of course, they're more successful, but it's priced in at the entry point. So as an investor, maybe even as an employee of that company, you're not necessarily getting more, you're getting smaller amount of maybe a bigger pie. Venture, it is a game theory where you're competing with other people. So it used to be that places like Waterloo or McGill and all these other engineering, that was where the alpha is. And now that alpha has contracted away as a engineering center becomes known for several exits, that alpha is now gone, just like in the public markets. As information becomes more dispersed, that alpha goes away. So you're not necessarily saying that pedigree is not a predictor of success. You're saying maybe that it's just a higher valuation, almost like a later round than an earlier round. And what you're really looking at as hustle is not priced in. You're looking to really ascertain the alpha via this work sample that you call hustle. What I found with also our very best performing companies, regardless of whether they great pedigrees or not, is that especially at the early stages, the teams that do best are the ones that are just doing the gritty, nasty work in the beginning. For example, picking up the phone, trying to make 100 phone calls into prospective clients a day, or even like doing feed on the street kind of work. So, you know, I find that it's more of a, almost like an emotional intelligence exercise, which is quite democratized. You know, those who have great pedigrees or come from less great pedigrees, whatever, you know, but are willing to do, I think the things that other founders aren't willing to do in terms of just feed on the street sales, just being really gritty in terms of just nasty throughput of kind of boring work in the beginning to gather data. Those are the ones that do really well. And maybe this is a little bit of a bias. But when I was working at some of these fame companies earlier in my career, that was an area of pushback from some employees, which is just like, hey, like, you know, this is kind of beneath me to be doing like customer service work, like in this manner, you know, this may be a little bit of an unfair stereotype. But I think that's kind of what I'm more excited about is like this emotional intelligence test. Like, are you just really gritty? It's a contrast signal. Correct. Yeah. That used to be one of my philosophies early on when I was running startups is you hire somebody from Cal, not preferred. Basically almost the same intelligence, if not the same intelligence, but the Cal student would be slightly grittier, less egosensitive. Obviously I love Stanford, but it's just a fact that on average, especially in the top engineers, the Cal engineers were willing to work harder and basically had the same exact skill as a Stanford engineer. They're just less entitlement. I think that there's something to this. I do a lot of mentorship at Stanford. That's where I went. And I see a lot of hesitation. Nothing personal about the observation. A hundred percent. A lot of times I encourage people in their early journey to do a lot of customer discovery. I said, when we come back next week, I want you to talk to a hundred people about this idea. It could be even other students about whatever you're building. Very few Stanford students that I've ever worked with are good about that follow up. I've also done a lot of work with Michigan State. So I grew up in Michigan and had some connections there. Those students have a far higher likelihood of taking that kind of customer discovery step of like yeah okay Like I just called like a bunch of people and here what I discovered So there could be something to that In fact I believe that GE was really famous for this Like they wanted to recruit from state schools for their leadership programs because they felt like maybe if you have a little bit of a chip on your shoulder, you're going to be able to work harder and you want to prove yourself. And I think that model did succeed for a period of time. I think the way that I look at all of this are factors. IQ is a factor. Grit is a factor. Ego is a factor. You're really looking to line up all these different factors together in this like super entrepreneur. And when you have that, then it's fireworks. Couldn't agree more with that. So your firm behaves almost like a media and community platform alongside a fund. What's the genesis of that? And how does that help you in the marketplace? There's 26 other people that are working on knowledge and networks at Hustle Fund. So that manifests as things like we have an eBooks business, YouTube channel, but we also have a rapidly growing newsletter that reaches 500,000 mostly founders each month. We host 50 events per year globally. A lot of them here in San Francisco, New York, LA, but also Singapore, Tokyo, Seoul, some other markets that we're tracking. Almost all of them are for founders. And then we have a large angel investor community called Angel Squad, which has 2,600 members. They're all deep operators. A lot of them are senior folks at Snowflake, Meta, Google, et cetera, but also doctors and lawyers and nurses. So the value prop that we offer for founders when they asked a question of like, hey, what are you going to do besides money to help me out? Is our response is, well, the first thing we're going to do is we're going to begin promoting through our newsletters. It's a channel that we entirely own that reaches 500,000 people. So why don't we just drive your first revenue this way? In some cases, we were able to drive the first million in revenue for free on this channel. So distribution is a big one. If you're looking for fellowship and local communities of other great founders, come to our events. We'll feature you as a fireside chat speaker so that we can build a little community around you. If you're looking for specific mentorship from your industry, this diverse community of angel squad, these deep operators, we mine that all the time to try to find mentors and advisors for you to unblock your questions specific to your industry. So that's how all these flywheels work together. And I think there's also a question that we're often asked by our LPs and our community, like, how do you pay for this as a tiny fund? And we can explore that too, if you like, David. I'm too intrigued. How do you pay for this as a smaller fund? So this is something that I'm really proud of. And I do think that this is where venture is beginning to evolve as a services-based business for founders. And I credit A16Z. They're the one that sort of changed the social contract initially to say like, we have a services model to serve our founders, like with recruiting or something else, right? That's their genesis as well. And we are building on top of that. So this is what we're trying to fight for. We like staying small. We think that small funds have better mathematical levers for outsizing returns than big funds. And we also just enjoy the pre-seed stage, which usually means you have to write smaller checks. We're not writing like $10 million checks into a single deal, right? The problem though, with small funds is that there's small management fees. We take our 2%. It's not that much for 30 people. So, and in addition to that too, there's another problem that we're trying to solve here too, which is if we were to grow AOM just because we could, and our management fees grow, there's an inverse fear that I have that we're going to get lazy. You know, at a certain point, like if you're like a billion dollars, that's a $20 million management fee for doing nothing, right? So you can sit on your ass and get rich. There's internal struggle where, well, do I want to do the incremental meeting? It's always the incremental thing. You always put in people with billion dollars, $10 billion funds. They're always working eight hours a day, but will they go? Will they work on the holiday? Will they travel to their customer? Will they do all these things that it takes to be elite in these hyper-competitive spaces? That's really the question. This is a really important point here too. I worry about myself. Right. Like, don't cry for me. Like I did fine as a founder. So I have some savings to allow me to have this life. But like, you know, if you're making too much money, I do think that there is an inverse quality that we can start to get too lazy. We're not working as hard. We're not fighting as hard as we should. We're not we're not hustling as hard. That's a really big fear. So in order to reconcile all these concepts that I just shared with you, our GP is capped at a $210,000 salary per year. So don't cry for me, but that's pretty much a middle-class salary here in Silicon Valley, enough to sort of pay the bills, right? And our knowledge and networks teams, the ones that are building the media business, as we call it, generates about 3 million in revenue per year, primarily through sponsorships like OpenAI, Google, et cetera, that want to get in front of our early founders. This allows us to underwrite our large team. But the only way that we can make substantial wealth from hustle funds specifically is if our founders get rich, then our LPs and us through carry. And I really like this checks and balance system, but it's all possible because we have this huge team that can produce amazing throughput of experimentation and building out this great reach for our founders, but we're not reliant on the management fees. And increasingly, I'm starting to see peers in the venture capital space creating other kinds of value-added, monetized solutions for their founders that are aligned with their founders so that they can also remain small. And I think that this is a great evolution to where our industry is heading. It's sort of like a negative CAC. You're getting paid to strengthen the network, to strengthen the founder experience. Instead of paying for it, you're actually getting paid for it. And that allows your funds to stay small. Previously had Henry Shee from AI Startup Leaderboard on the podcast, and he tracks the seed strapping companies, these companies that raise one, $2 million and then are profitable until they're like a billion dollar company, most famously mid-journey. Yeah. Became a billion dollar company, a $10 billion company, I think 40 employees or so. As AI starts to bring down the costs of starting companies, how do you see that playing out in the seed space specifically and also venture in general? I love talking about seed strapping. And a funny thing about this is that it's quite polarizing in our industry. Some VCs are like, I hate this term. I think it's dumb. And good on them. I can see that. But I love it. But it works for a very specific set of companies. So if David and Eric were starting a boom supersonic competitor or something like that, or something that requires a lot of capital expenditure, it doesn't work, right? You just need to like buy things for physical atoms and they cost what they cost, right? That's just hard. So for me, this really isolates down to pretty much only software, maybe a little bit more B2B oriented, perhaps consumer, but like B2B, I think because you can monetize a little bit faster, right? And I think this is fantastic because I'm always happy when founders make a lot of money. Selfishly, I'm also pretty happy as a pre-seed investor because if I'm writing a friendly 150,000 and then $200,000 check into a team, That's pretty easy for a founder to ingest. And we're well suited to actually still be a part of this journey for the seed strappings where they keep growing until they're acquired for a gazillion dollars or something like that or IPO. That said, there is a downside to seed strapping when it comes to being a general partner. You don't get marked up. And this is actually something that dings us quite a bit. We have a lot of founders who are sort of in the seed strapping mindset where they haven't raised in like four years, but they're doing like 50 million in revenue. right we have held them at cost from their last race because that is our audit policy and sometimes when we're raising capital lps are like are you guys like kind of dog shit investors here because like there's no markups happening like in your best positions over the last like three or four years and then we have to explain to them just like you know this notion of markups is quite arcane in many cases you know the fundamentals of these businesses are really really good if i can explain it to you but it just doesn't map to the old mental models of how venture works and how we track value. As they start up timelines now, some of these companies take 10, 15 years in extreme cases to go public. We saw that even in last generation with Palantir and now SpaceX is only now starting to talk about going public. Are you looking at alternate liquidity options like secondaries or even continuation vehicles, which has made its way from private equity to the venture space Absolutely In fact this is the primary way that we have to extract liquidity at this point Here a fun trivia question for you David Are you familiar with the notion of four vesting for employees Yes Yeah So the idea that I give you a job give you like 1 of the company you have to vest that over four years, right? With usually a one-year cliff. Do you have a sense of the history of how it came to four years as the norm? No, I do not. So what I learned was this was actually a standard that was set in the 90s because on average, it took four years for companies to IPO from inception back then. So there was no point in actually something longer because you're only going to be around for a couple of years before you get your liquidity. So damn, the 90s, right? And so I've been an investor in Stripe for like 16 years at this point, and I'm still waiting for that IPO. I'm not sure it's ever going to happen at this point. So IPOs are taking longer. M&A is getting more complicated. You're seeing these exotic maneuvers of like, we're going to buy 49% of the company, that kind of stuff lately. And secondaries really does seem to be the very best route by which you can extract liquidity. Now, the good news for early managers like ourselves is that this is a category of private equity that is growing so quickly, right? The number of entities that approach us on a weekly basis, looking at portfolio offering to buy is pretty high. And we've actually done some deals with royal families, family offices, really, really robust institutions that are only focused on secondaries that allow us to have that kind of optionality. So I think one of two things have to change for early managers who are in venture. One is that they just model and find the right partnerships for secondary outcomes. And they just make that work. That's part one. I think part two is change the standard by which fund lives are set from not just 10 years anymore, which is the standard to something that maybe is a little bit more evergreen, like 15 years or something, or 20 years, even one of our LPs is laundry group. And I remember Lyndall Eakman saying to me, you know, look, we're investing. I know it's a 10 year fund, but we assume it's gonna be 18 years before we get liquidity from this. I was like, damn, that's crazy. I had previous guests, Brent B-Shore, they market a 30-year fund and they do buy out and allows them to be much more long-term focused. Obviously, the opposite of long-term focus is short-term optimization, to your point. If you had to liquidate that position that was seat strapped, that could be a very costly mistake in five years. Well, let me ask you a question about Brent's 30-year fund. Who is he serving, actually? Because that doesn't make any sense. He actually has institutional investors in there. You have to listen to the episode, But he creates alignment with them and they're evergreen. There is an opportunity for them to get out earlier as well. But the assumption is he had a lot of success early in his career. So he got to kind of set the terms if he wanted to take in money. But he's able to align longer and he holds these companies. He doesn't put leverage. It's a different philosophy. But he actually does have institutional investors in there. In fact, some institutional investors are going into... Yeah, I only think it does. Because if you're a sovereign wealth fund or institution that's trying to manage like 50-year horizons for the entity, then that makes sense. I don't really love serving institutions. The people I love to serve are like family offices, maybe ultra high net worths, you know, people that kind of get closer to normal people. Like those are the, and they frankly are the best fit for tiny funds as well versus like a big institution. So the idea of an evergreen 30-year fund is really exciting, but I don't want like my buddy David to wait until he's 65 or 70 in order to extract his value. Like he's got to like put his kids to college and things like that. Those are the kinds of constituents I think that are underwriting early managers like myself. So that's actually like a paradox I can't really reconcile. You've been in Silicon Valley for 25 years. You've been into it, meta, you're at 500 startups. You're now running your own fund. What is one piece of advice you'd love to go back 25 years ago and give a younger Eric that would have either accelerated your career or helped you avoid costly mistakes? This is something that I discovered after I graduated from college. And this is something that I really pound the table with current college students. When you're a current college student, let's sort of focus on that, you have a superpower. You have the ability to cold message pretty much anyone, email, LinkedIn, whatever. And the response rate is absurdly high. If I reach out to David as a college student and say, hey, I'm a freshman at Stanford and I'm just really curious about your journey for how you became this amazing LPE with this great media company. Can you give me 20 minutes? That's an absurdly good response rate. So the advice I have for young people is try to gain a lot of mental models by building relationships early with people. And don't be afraid to just cold message people. If you just do the white knuckling throughput of like 20 messages a week, maybe you can even automate this with an AI agent on LinkedIn at this point and try to do at least one of those chats. Those people can become your ally in helping you in the future. They might come work for you. They might invest in you. They might give you a solid piece of advice that becomes that small hinge that swings that wide door in your life. And I think that I've benefited from the thousands of people who have raise your hand at very key moments in my life to say, I'm going to help you out. One thing that I wish I would have told myself is to really lean into my comparative advantage. So you mentioned earlier on with VCs, like what's their differentiation? They're all top 1% IQ. They all went to top Ivy League school. It's not that they're not special. It's that they don't necessarily have a comparative advantage. They're very absolutely good, but comparatively they're not in the right market. And leaning into that comparative advantage, where do you get and their intersection of different skill sets that makes you uniquely talented to do a specific thing. And I think upstream of that is actually being around people that see the strengths in you. So how could you be around people that see more in you than you see yourself, that see more potential in you than you see in yourself? It's a very small percentage of the population that is able to see that in others and surrounding yourself around people that see your strengths and not just constantly beating you down for your weaknesses is something that I wish I would have done earlier. It's a funny arc that you find so common in life, right? Which is when you're young, you're, you obsess around how can I shore up my weaknesses? How can I be a better speaker or better engineer or whatever it's going to be? And then as you've aged, and I'm in my mid forties at this point, it's usually just an acceptance of like, ah, my weaknesses are just things that are, you know, I'm not as interested in trying to fix at this point. Like, what am I actually super good at? And how do I kind of design my life as well as my work to isolate more on the thing that gives me joy and I'm really good at, right? And then, and that's where I've seen kind of the exponentiality of the career happen is when you sort of recognize that within yourself. But to be fair to young people out there, including younger version of Eric, if I go back in time, it's not easy to see what your strengths are at times, right? Like that takes a while for you to sort of just discern within yourself. If you look at the smile curve, which is life satisfaction, it dips actually in the thirties, mid thirties. And one of the reasons is that is the exact time where you see your limitations. And the working theory right now is that the reason people start to go off is because they accept their limitations. So there's like this lag between the, between the realization of your limitations, the acceptance of your limitation that leads to that kind of happiness curve. And then if you take it to the extreme, the 70, it keeps on going up until the end of life, pretty much until like the last year when people have health issues. But basically even into your 80s, you just gain more and more acceptance. And that just leads to more and more life satisfaction. I remember actually at my last college reunion, hanging out with some 70 year olds and 80 year olds and just hanging out with them for a while. And they were amazing because they have given up all fucks. Like they're talking about their sex lives and just like stuff that's happening in their life. And I It's just like, it's amazing to see such liberated people who just are unapologetically themselves. It just made me really excited for the exact thing that you're saying, which is like, I can't wait to continue aging. Like it's just discovering yourself more and just losing those fucks. And it seems like a very beautiful exercise of life. On that point, Eric, it's been an absolute pleasure. Didn't disappoint. Thanks so much for jumping on the podcast. Looking forward to doing this again soon. I appreciate all you do, David. That's it for today's episode of How to Invest. If this conversation gave you new insights or ideas, do me a quick favor. Share with one person in your network who'd find it valuable or leave a short review wherever you listen. This helps more investors discover the show and keeps us bringing you these conversations week after week. Thank you for your continued support.
