My First Million - I asked Cathie Wood the question no one else will

Episode Date: October 30, 2025

Get the free investing playbook to invest like Warren Buffet: https://clickhubspot.com/rme Episode 760: Shaan Puri ( ⁠https://x.com/ShaanVP⁠ ) talks to Cathie Wood ( https://x.com/CathieDWood )...  about her fund’s performance, her biggest bets on AI, and the most misunderstood stock on earth.  — Show Notes: (0:00) McDonald’s to Managing Billions (8:54) A day in the life of Cathie Wood (17:29) ARK’s Performance Review (30:00) Cathie’s #1 stock pick — Links: • ARK - https://www.ark-funds.com/  • The MFM Newsletter Challenge - https://www.beehiiv.com/application/mfm — Check Out Shaan's Stuff: • Shaan's weekly email - https://www.shaanpuri.com  • Visit https://www.somewhere.com/mfm to hire worldwide talent like Shaan and get $500 off for being an MFM listener. Hire developers, assistants, marketing pros, sales teams and more for 80% less than US equivalents. • Mercury - Need a bank for your company? Go check out Mercury (mercury.com). Shaan uses it for all of his companies! Mercury is a financial technology company, not an FDIC-insured bank. Banking services provided by Choice Financial Group, Column, N.A., and Evolve Bank & Trust, Members FDIC — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth • Sam’s List - http://samslist.co/ My First Million is a HubSpot Original Podcast // Brought to you by HubSpot Media // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano

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Starting point is 00:00:00 manage more money than any other woman on earth. Across the company, we're closing in on $40 billion. She's called one of the most disruptive and innovative forces. Kathy Wood making some big headlines. The ARC innovation ETF soared over the early pandemic. If I'm a believer in AI, what's the number one stock that I should own? I think everyone knows about Nvidia. We always try and answer that question with stocks.
Starting point is 00:00:25 People are not thinking about in the right way. So here's the tough question. If somebody else had your track record, would you invest in them? Well. I feel like I can rule the world. I know I could be what I want to. I put my all in it like no days off on a road. Let's travel.
Starting point is 00:00:46 Kathy Wood, you're here. I appreciate you doing this. You're a pretty remarkable person. I've been watching you for a long time. And there's a good chance that you manage more money than any other woman on earth as a fun, as an active. fund manager. I don't know if that's exactly true, but you may be top five. Yeah, probably. I don't know. I don't know myself. I don't have those numbers. Yeah. I'm curious, actually, where, what's the humble origin? So what was Kathy Wood's first job? McDonald's. Cassier, what were you doing,
Starting point is 00:01:16 flipping burgers? No, I wasn't. I was at the register. I was 16. I also worked at a supermarket. First Girl allowed to push in carts at Vaughan Supermarket in Southern California. Do you remember roughly what you were making when you worked at McDonald's hourly? Gosh. I know. Well, right before that, I was babysitting for a quarter an hour. So you went from maybe a quarter an hour to managing something like $20, $30 billion in a fund. And I think this is interesting.
Starting point is 00:01:46 The reason I ask is because in the world of entrepreneurship, we always hear these hustle stories. And I don't think you go from McDonald's to, you know, the top where you're at without hustle. So what's the hustle story you pride yourself on? Well, the first big break was getting into the business. Art Laffer. I'm not sure if you know Laffer, Laffer Curve, Supply Side Economics, Rehganomics. He was my professor at the University of Southern California. He was like an advisor to presidents, right?
Starting point is 00:02:16 Oh, every president since Richard Nixon, except for president. Obama and Biden. And, you know, he was agnostic if anyone didn't matter what party wanted to hear what he had to say about taxes, deregulation, monetary policy. He wanted to give his point of view. And, you know, we've come full circle, Art and I, because I and my team introduced Art in 2015 to Bitcoin. And when he read our paper, he said, this is what I've been waiting for since the U.S. closed the gold window in 1971. A global rules-based monetary system. Wrong rule.
Starting point is 00:03:09 Quantity theory of money, you know, limited to 21 million units. But we'll get there. And of course, he was talking about stable coins. So now we have introduced him to stable coins, tether. circle and so forth. And he said, ah, the right rule. Have you seen this website? WTF happened in 1971? It's amazing. There's an entire website basically saying what the F happened in 1971. And it shows like a series of charts where something happened in 1971 and the world was really never the same. And it's just a, it's a very
Starting point is 00:03:44 compelling case. It makes you want to go look at it. And obviously, I think that's the year that we went off the gold standard, right? It's the year we went off the gold standard. and all hell broke loose in monetary policy. We went into massive inflation. So anyway, it was in the late 70s that while I was in his class that Art introduced me to Capital Group, I walked into Capital Group. I didn't even know what the investment business was. I had been a waitress.
Starting point is 00:04:11 I was interested in economics, but I didn't know this business. And Capital was the premier firm in Southern California at the time. Sounds like that might be a tough job to get. Art recommended me highly to Don Conlon, who was the chief economist of Capital Group. And I walked in there, and Don was losing a person who was going on to Harvard Business School. So this woman, her name was Claudia Huntington. She was so good at what she did. He was looking for one and a half people to replace her.
Starting point is 00:04:52 I was the half, but I didn't want to be the half. I wanted to be the one and a half. So let me ask you a question about that, because I think everybody in their career, you know, we'll have an opportunity. I had one when I moved to San Francisco when I was 24. I didn't know anybody, but I wanted to be an entrepreneur.
Starting point is 00:05:07 I wanted to be in Silicon Valley. This billionaire was hiring for this role. I don't know how I got the job. I was, they literally told me, you're not qualified for this, but we like you. We'll bring you on. We'll still hire somebody else qualified for that role,
Starting point is 00:05:18 but we want you here anyway. So I had like my foot in the door. and I think everybody has this opportunity to work hard, but there's one thing to put in hours. So I think there's a lesson in like first one to be there, last one to leave, like put in a sheer number of hours. But what else goes into kind of like making an impression during that like sprint phase of your career
Starting point is 00:05:36 when you can just like fully go full force? What else besides sitting in the chair for a lot of hours matters? Do you think? What's the mindset? Sitting in the chair maybe matters, but I think the most important, thing is, and my objective was to bring new technology into the firm. I was using economics time-sharing system. We were back in time-sharing. All the charts that you just brought up,
Starting point is 00:06:05 boom, boom, boom. Back then, each one would have cost in today's dollars, five to ten thousand dollars. So that just gives you a sense of how far we've come. But sparingly, I would able to use charts for, you know, ones we made up, so original, and then, you know, call them from people we trusted and really develop little economic books for, and presentations for Don to use. Yeah, you'll get what you want when you help other people get what they want. So the fastest way to getting what you want is just to give other people what they want. And I like what you're pointing out, which is that as a young person, you're coming in without the experience without the network, without maybe the track record, or any of those things.
Starting point is 00:06:55 Those are your disadvantage, but maybe your advantage is tech and new things might be easier for you to pick up because you have time and maybe you grew up with those tools and you're less set in old ways. And so you bring something to the table and that can be your thing. Hey, real quick, our sponsor for today, HubSpot actually did something pretty cool. If you like money stuff like this, you like investing wisdom like Warren Buffett or Monish Prairie, well, they actually put together a nine investment principle. document. There's a free document you can have of frameworks that they shared when they came on the podcast. You can get it right now. It's actually just a mental model that separates, I guess, the elite investors from the average investors.
Starting point is 00:07:32 So you can get it right now, scan the QR code or click the link of the description. All right, let me get back to the episode. I'm just curious, like, what is a day in the life of Kathy would look like? What's your actual day-to-day main thing that you focus on? I hold sacred in terms of from the moment I get up in the morning until 10.30, that time is all about research. And so we have our research meeting from 9 in the morning to 10.30. First half of it is just the entire research team together and investment team, portfolio management teams, together. really sharing information. And then we focus on, in the last half hour, on one of the four teams. So we're broken up into autonomous technology
Starting point is 00:08:29 and robotics team, AI and cloud, which has forked another team, which is consumer internet and fintech. Then we have our model. multi-omics team, which is really all about life sciences and how profoundly AI is going to transform healthcare. And I think that's the most inefficiently priced part of the market. And then we have our blockchain technology team. On Fridays, at 1030, we have a brainstorm. And the brainstorm is all our teams coming together or staying together. But we have another, I'm going to say another
Starting point is 00:09:15 40 people who have followed us over the years and are passionate about innovation and we invite them to what's called a brainstorm. And that is where we try to get out of this not invented here. We really want pushback. So these are venture capitalists,
Starting point is 00:09:36 they're entrepreneurs, they're retired engineers, they're retired professors, they're people teaching in universities, today, and they are very vocal because all of us, they're probably more for their personal accounts, but we're all trying to figure out how the world is going to work. And we're trying to push the frontiers of knowledge forward as fast as we can, anticipate what the next set of topics are going to be that people are discussing and trying to figure out where we should position ourselves.
Starting point is 00:10:12 That's pretty interesting. Is that common? Do you do other? firms do this kind of Friday open-door brainstorm with like external folks? That sounds pretty unique. No, they don't, and I've done this since 2001 when I was at my last firm. I just thought it was really important not to get stuck in our own research, but to have it battle tested. And we took that to another level when I founded ARC with this notion that we're going to give our research. away. We're going to give our research away, not when it's finished, because it's never finished, but as it is evolving, and we push it out. Now, at the time, 2014, Twitter was for tweens, teens, and celebrities, right? So I didn't think that was going to be our primary social network. We thought
Starting point is 00:11:05 maybe LinkedIn would be, instead, X has become the most important social network, even for crypto. I thought Telegram was where all of that was going to live and yeah, there are all kinds of conversations, but the ones that we need and that I need to see, they are on X. And sometimes we
Starting point is 00:11:26 stir the pot, you know, with our research and get debates going. So I feel that the world is moving so quickly today. It's not like it was in 1977. Back in 77, as I described,
Starting point is 00:11:42 It was really expensive to get information and to travel places to pull information for management. And so research departments, like the one at Capitol, they were closed and that was their secret sauce. Today, information is ubiquitous. It is all over the place. In fact, you have to figure out, is it real or fake? So that takes another skill. So I thought, you know, the closed world is probably not where we are best suited for what we want to do. And that is focus exclusively on technologically enabled disruptive innovation.
Starting point is 00:12:29 That's all we want to do. Well, there's so much information out there. And we knew we could harness it. And it's how you put it together. and what you place priorities on in terms of the kind of information and the kinds of assumptions that you're making that become more important. And you, this might be a dumb question, but like you will go on TV and you'll say, I think Tesla's going to $2,000 a share or whatever your target price is,
Starting point is 00:13:00 and everyone says, oh my gosh, that's really bullish, and you say, here's why we believe, here's what we believe the future looks like. And I hold Tesla and I hope that that all comes true. But you are very active. Like you're buying and selling Tesla all the time. I looked at the last like 24 hours your firm has made like 20 trades or something like that. Like millions of dollars in and out of these positions. If you believe Tesla's going to, you know, some $2,000 a share, why don't you just buy it and hold it?
Starting point is 00:13:28 What is all the active trading for? And like, are you day trading? I mean, I'm not from the investor world. So I'm trying to understand. Yeah. You know, you have sort of the Buffett mentality. and then you're very, very active. I don't really get that.
Starting point is 00:13:40 Yeah, that's another great question. I know it must seem confusing. And we often do describe ourselves, a few people believe this, but we believe it, as a deep value manager, like a Warren Buffett, if you give us five years. And, you know, Warren Buffett, he was the first to admit,
Starting point is 00:14:05 I don't invest in technology. He made a few good ones. Like Apple was great, IBM not so, but he knew where his strengths were, or he knows where his strengths are. He's still with us. And he did not feel that technology was where he had an edge. That's where we do have our edge. And so you can say we're a great compliment to the Warren Buffett strategy if you give us a five-year investment time horizon. So, why do we trade so much? Well, because of what has happened to the markets, really since I got into the business,
Starting point is 00:14:46 I think more than 75% of the trading is algorithmic and high-frequency trading. There's a huge amount of volatility in the market itself, but especially in our stocks. So if you look at our trading in Tesla, we are using it, we're using the volatility to our advantage. So rarely has Tesla dropped below the number one position in our flagship portfolio, ARKK.
Starting point is 00:15:18 What has happened, it has gone from $100 to $500 and becomes, you know, 13, 14% of the portfolio from a portfolio management point of view, we are effectively rebalancing. That's a lot of hard work, 100 to 500. And we know, we know, we know, we know. Tesla is a controversial stock. Elon Musk is a controversial individual. And we are going to have opportunities at lower prices
Starting point is 00:15:54 to move back in. And so that's the kind of trading that you see around our high conviction stocks. Okay, so let's take what you just said. So you said, give us five years, right? Because we're betting on these sort of long-term technology S-curves that we think are playing out. So here's the tough question.
Starting point is 00:16:14 Over the last 10 years, you've been making hundreds of millions in fees, but haven't outperformed the simple index like QQQ. Do you think that's a fair criticism? So can I give you a reset here? love the question. You're giving me an opportunity to answer a question that I know is on many people's minds, even if they don't ask it. So thank you. So our objective as a firm is to deliver a minimum 15% compound annual rate of return over five years. So you are absolutely right. We have not done that.
Starting point is 00:16:57 we have done that since inception. So since inception, our compound annual rate of return is over 15%. Now, what happened in the middle there? Because you're focused on endpoint sensitivity, and I understand why people use five years, ten years, all of that. If you use ten years and you look at Morning Star and just their quantitative metrics, which have no human input. They just have their rules-based system. Based on the benchmark, they selected for us.
Starting point is 00:17:35 We didn't choose the benchmark. We are benchmark agnostic. We are in the fourth percentile of performance for that benchmark. Now, that benchmark is mid-cap growth, which kind of fits because we consider ourselves all-cap, but, you know, if you average, you'll get mid-ish cap, let's say. So that's good. You know, that's actually saying something.
Starting point is 00:18:06 The space we've been in, anything less than large cap, and especially mega-cap growth, especially in the tech space, has been very tough. Okay, so that's another marker. Now, what about the last five years? Well, we had COVID in 2020. Because this is when we blew up. I'm not sure if you know this part of the history, but because we were the only investment firm
Starting point is 00:18:39 putting our research out on social media, and the only one posting our trades every day, we went viral during COVID because everyone was sitting in front of their computers trying to figure out what to do with their time, right? And their extra money, by the way. Yeah, and their extra money. We were actually really one of the few out there teaching people about investing, bringing them along on our journey.
Starting point is 00:19:10 In 2020, we were up 150%. And at the end of that year, remember, we're five years away from that. This is what we're comparing against. At the end of that year, I was on Eric Schatzker's. show on Bloomberg. It was a holiday show, and they gave us a lot of time. And one of my main messages was, hey, keep some powder dry. This, we know what goes up like this is going to come down. It's just too much capital chasing the opportunity perhaps too soon. And that last point, I probably should have said more loudly to myself and to our team.
Starting point is 00:19:57 Right. Because even though our modeling, stock by stock, got us to a 15% compound annual rate of return over the next five years, which was very low. Normally we're, normally we're expecting 25% to 40% compound annual rate of return. So it had dropped because of the appropriate. in stocks to 15%. But what also had happened and what we did not appreciate enough was many people think, oh, the interest rate increase, that wasn't as much the problem. The problem was supply chain bottlenecks. Our models are driven by unit growth.
Starting point is 00:20:44 and when there's an interruption in unit growth, our model, the rate of return expectations come down. And I thought, and we thought, we were going to come out of this crisis in a V-shaped recovery. And we did. That was correct. But we didn't catch how long it was going to take supply chains to, to, reorient and that that I think was a big big lesson for us if I had just focused on that one variable I would have said all right let's move more into larger cap tech stocks with a big cash position that are innovating and it would have been the mag six
Starting point is 00:21:38 and all of that we did not do that what we did we owned them and as we because we had started doing that in the bull market. We always diversify as a bull market extends because our stocks do tend to go crazy to the upside. So we were already doing that. But then in 21, those stocks kept going up, and our stock, so smaller cap and mid-cap stocks, started going down.
Starting point is 00:22:08 And so what we always do is rebalance. We took profits there. we bought. That was just way too soon. It worked out, and I think history will show that everything is fine. We had to have people stick with us, and there are so many people who piled in at the top, even though we're saying, hold your horses, and who left us at the bottom, which is classic. It's classic. And so we're going to be out there in this cycle a lot more saying along the way, rebalance, sell, take profits, so that when our strategies go through a weak spot, a sinking spell, then you'll have the psychological wherewithal to buy. It's called rebalancing, and it's a basic
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Starting point is 00:23:22 Betting against you as betting against a combination of things that I would never want to bet against. It's betting against AI. It's betting against crypto. It's better against innovation. And it's betting against Elon Musk. And those are just, that's not who I, you know, that's like the Mond Stars and Space Jam.
Starting point is 00:23:36 I'm just not trying to bet against that. You might even be right on some, on any, one of those individual things, maybe for a period of time. It's just not where I would want to be positioned against long term. At the same time, like, I'm a normal person, and it's pretty crazy when, like, this is In venture capital, too, by the way. In venture capital, VCs, it's a rigged game. I heard this a long time ago, and it never left me, which is venture capital is a rigged
Starting point is 00:24:00 game. You make 2% annually on your fees, regardless of whether you make money or lose money. And I think what you do is very similar, right? Like if you have, like, I don't know, let's just use a round number, 20 billion in assets across your ETFs. Is that about right? Across the company, we're closing in on 40 billion. Okay, that includes the digital assets, private funds, everything. So we do have a venture fund.
Starting point is 00:24:23 So I know what you're talking about. We're doing ours a little differently. We don't have a carry so that anyone with $500 can get onto the cap tables of SpaceX, OpenAI, Neurlink, and so forth. You don't have carry, so how do you make money in that? So what we do is we do have a high fee. So I think it's 2.75%. And what we did to arrive there is we said, okay, what do the best venture capital firms in the world deliver over time
Starting point is 00:25:00 in terms of compound annual rate of return for their clients and how much of the benefit do they derive? And the best ones, and maybe they're going to be north of 2.75% per year on average, and especially in this kind of a market where AI is just out of sight. But the best ones, if you do a very long-term historical retrospective, historical is retrospective, 2.75% was the, the landing point. But we are offering direct-to-cap table. These are not SPV. Right. Not SPVs. So there are no fees or pump-fee's upon fees. Right. And so, you know, I think that the challenge is basically on a 20 or
Starting point is 00:25:48 $40 billion in total assets. There's a guarantee as a, this is why finance and fund management is like one of the best businesses in the world is you get, you know, hundreds of millions in fees guaranteed, regardless of whether you're up, whether you're down. And then, you know, like the more you go up, maybe you have additional carrier. There's other things that, you know, in venture capital that you benefit from. And so I think that's the challenge, right? Like, Munger used to say, you know, show me your incentive, I'll show your outcome. It's like, I think all finance and fund management is generally suited towards grow assets under
Starting point is 00:26:21 management. We make money either way. And then, like, try to do your best in terms of performance. And in the long run, you know, you will be judged on the performance. But in the short run, it's hard to tell, right? like what's what's working and what's not, which is why when Buffett, I think, started, he basically said, I'll take nothing for the first 6%, which I think was like kind of the sort of the index standard at the time. And he said, but if I beat market, then I want 25% of profits.
Starting point is 00:26:46 And I thought, like, you know, that was a great structure. And I think the world of finance has moved away from that. Because why would you? I would do it too. If I could take the guaranteed fees, I'm going to take it. Well, you know, it's interesting from the, I'm going to say from the 80s on, when I I saw hedge fund structures and venture capital, I said, I'm an economist. I said, oh, that game's going to end.
Starting point is 00:27:08 That's, you know, those kinds of excesses, excessive return, shall we say, they go away with competition. But in the venture world, and there is a huge amount of competition, but if you look at where the real money is made, it's in the top, you know, 10. The top 10 is where a disqualmie, you know, proportionate amount of the returns are. And of course, that's what we're aspiring to. And of course, everyone is aspiring to it. But there's some kind of network effect. And I think it has to do with the network effect is not a viral app. It is the community. Well, venture has one different
Starting point is 00:27:49 property than what you do outside of your venture stuff, which is in startups, it's the only asset class where the security selects the investor. So, you know, for Buffett or any public stock market, I get to just pick what I want to be in and I push a button, I'm in the stock. Whereas in venture, the hot startups want to be with the hot funds and only the hot funds get to be on the cap table. So the security selects the investor, not just the investor selecting the security. So it has this like, that's where the network effect comes in. That's where the brand effects come in. And that's why Sequoia and Benchmark and these other guys will keep showing up in the top because if I'm one of the top startups, I want them. And so they get the
Starting point is 00:28:27 access. Even if another investor was totally right in their thesis, they just can't get Yeah, it's a self, yes, there is self-selection. You're seeing in the hedge fund world big changes, though. In that world, the fee structure is changing. Because passive, the indexes were outperforming active. It was a self-fulfilling prophecy because the pendulum was swinging there. I believe that that pendulum swing, I think that, and consider the source, Right. But I think the pendulum swing, the final swish in that direction, was in the last few years towards the MagSix.
Starting point is 00:29:12 And now they're so – one of the reasons they're such concentrated parts of the – now are they all going to benefit from all of these new technologies? You know, our focus on robotics, energy storage, AI, blockchain technology and multi-omics. Some of them will. Apple, we've been watching for a long time. Finally, it's out. They don't know what they're doing in AI. Now I think they're scrambling a bit, so we'll see what happens. Each one of them has a weakness. Each of the Mag6 has a weak spot.
Starting point is 00:29:45 Sure, they'll participate in the wave, but they also have some weaknesses caused by the disruptions associated with these new ways of doing things. And I think we're at the beginning of that pendulum swing in the other direction. As I just said, consider the source. That would be great for us because we don't own the mag six in our top ten. It's not like we won't on them, but we don't own them for the most part in the top ten. If I'm a believer in AI, what's the number one stock that I should own to benefit from the oncoming AI wave? Well, I think everyone knows about Nvidia.
Starting point is 00:30:27 We always try and answer that question with stocks, people, either they don't know or they're not quite thinking about them in the right way. Yeah, misunderstood. Maybe not unknown, but misunderstood or mispriced. So, yes, as we were selling in Vivida and we got all kinds of flack, nobody bothered to notice that we put it in the portfolio in 2014 because of autonomous driving at, I think, 20 cents on the cost. current stock's basis at 20 cents per share. And we held it for years and no one would listen to us. No one. I talked about robotics. Talked about autonomous driving. Talked about, nope, it was a PC gaming chip company and that's all it was. And then it explodes with chat GPT and we start selling it and and we sold it too soon in the in the flagship. I mean, meaning we exited it.
Starting point is 00:31:26 We're back in it now when it dropped during tariff turmoil. But what did we put the money? In portfolio management, you have to not look at just what was sold. But what did you do with the proceeds? How about Palantir, which I think from that point has done better than Nvidia? I don't know. It was, that was the case at one point. How about Coinbase when the SEC was suing it?
Starting point is 00:31:51 That's one of the, that's what we use some of the Nvidia for. It has done pretty darn well, I think, almost as well as NVIDIA. So you have to do it. So today, of course, NVIDIA still has a very important role. Palantir still has a very important role. It is the premier platform as a service company. We think embodied AI is underappreciated. What is that?
Starting point is 00:32:18 Embodied AI is physical AI, physical and digital world's meeting. You know what I'm going to say next. Tesla is the largest AI project on Earth, and it's not just robotaxies anymore. It is humanoid robots. It is humanoid robots, and according to our research, while the robotaxy opportunity, globally for everyone, including China, is an $8 to $10 trillion revenue opportunity in the next five to 10 years from maybe a billion now. So think about that, a billion to $8 to $10 trillion.
Starting point is 00:32:54 whole ecosystem with the platform companies like Tesla getting half of that. So that's $4 to $5 trillion. That's a big market. According to our estimates, the humanoid robot market will be a $26 trillion market in the next, I'll say, seven to 15 years. So me and Tyler, the CEO of Beehive, came up with a little challenge for you. It's the newsletter challenge. Now, if you know me, you know that I'm a big fan of newsletters.
Starting point is 00:33:28 I got my own newsletter. I also had a business that was a newsletter business that was amazing. I wrote this newsletter about crypto. We grew it to quarter million subscribers. And we ended up selling it after a year for millions of dollars. And I want you to be able to do the same thing in your business. So we're doing a challenge. 10 grand is on the line.
Starting point is 00:33:43 Plus, me and Tyler will actually be in your corner as growth advisors. You just need to go to Bihive.com slash MFM and you either start a new newsletter or you move your current newsletter over there. And five finalists will get picked to pitch me and Tyler, sort of like Shark Tank, and the winner gets 10 grand. So go to Behive.com slash MFM. That's Bihive.com slash MFM to enter the challenge today. I wanted to ask you about this because you put out this great deck or Ark put out a great
Starting point is 00:34:07 deck. And I love this slide. So if you're on YouTube, you'll be able to see this if you're on audio. Sorry, you know, go to YouTube or Spotify and check this out. So on this slide, I'll just describe it. So it's basically the cost per mile. Like how much does it cost to travel, to transport a, human being one mile. And you started like in the 1800s, like horse and carriage and,
Starting point is 00:34:29 you know, adjusted for inflation and all that. It's not, it looks like it's $2.10 to travel a mile when you're on horse and carriage. Then, you know, you get the Ford, you know, Henry Ford era, and you're at a dollar 10. And basically for like, I don't know, almost a hundred years, it's been roughly the same number. It's been a dollar 10 to travel a mile. And then your estimate is that with self-driving cars where you don't have a driver in there and you're on electric self-driving car, that the cost per mile could drop to, your estimate is a quarter. So, you know, four times cheaper than what it currently costs and what it has cost for the last hundred years. Did I summarize your slide correctly?
Starting point is 00:35:07 That is correct. That is correct. And, you know, when we first did this research, we too were astonished with that, wait a minute, it cost the same inflation adjusted. And one of the reasons for that is because the automobile matured fairly quickly, right? And we're all about rights law. Rights law tries to understand, okay, you've got this new technology. You're starting from a low base. For every cumulative doubling in that base, so from 1 to 2, 2 to 4, 4 to 8, for every cumulative doubling, cost decline at a consistent percentage rate for each technology.
Starting point is 00:35:47 Well, the internal combustion engine is mature. And so it has no shot against EVs. Even though I know that's not the prevailing wisdom in this political climate, or I'm just using economics and learning curves, so technology. Sorry, what do you mean by it has no shot? You mean like no shot in what sense? cost comparative compares in or just? Nope. Because of the chart you just showed. You can't get that cost down any lower. There are no more cumulative doublings. Everybody's got one. You know,
Starting point is 00:36:25 it's a bit of an exaggeration. And the emerging market, they don't. But they're not going to be paying up for, for internal, they're going to be looking for the cheapest solutions to cars, and those are going to be electric. And the part that I didn't get was, so, okay, great, the cost is going to go down because it's a self-driving electric vehicle. okay, I get that. I could see why the cost goes down. And I assume when the cost goes down, the demand goes up. It's cheaper to travel, more people travel.
Starting point is 00:36:50 It gets selected over all the other more expensive ways to travel. Yes. But the estimate you have, where it's like the cyber taxi revenue, I think you have the autonomous revenue is sort of like in the, what did you say? You said 10 trillion or something like that. It's a global. Yeah, yeah.
Starting point is 00:37:06 So right now, if I just take Uber, Lyft, DoorDash, like kind of the But the revenue of all those companies, which today, I would say ride sharing is not like a new idea. It's pretty prevalent. I think Uber's at $40 billion. You add Lyft, that's another $6 billion. And then Doordash, it does about $10 billion. So, like, the total of all three of those companies is only in the like $50, $60 billion range. But you're saying that that is even different from what we're talking about here.
Starting point is 00:37:35 They are not autonomous. And they are not in the pole position. I mean, DoorDash will harness autonomous. That's very interesting one because we think delivery is, especially with drones and rolling robots and everything, is very interesting use case. But Uber and Lyft are not in the pole position for this new world. Right, right. But I guess what I'm saying is that's what's spent today on taking rides from a ride, like a push a button, get a ride service. Why would, why is self-driving going to be 20 times more revenue generated?
Starting point is 00:38:08 Why is it going to be 10 trillion when all of those add up to 60%? Right. What we're doing is moving from a very narrow subset of transportation called ride hail today to all of transportation. So we're moving the entire market to autonomous to get that number. They're a very small slice, very, very, very small. And in fact, was so interesting in San Francisco, I think that Waymo were finding, we're finding. research is showing that people are willing to wait longer and pay more for a Waymo than for an Uber or Lyft. And I believe this has already happened the number of miles, even though in San Francisco, Waymo is geofenced and Lyft is not, the number of miles in San Francisco, the San Francisco metropolitan area,
Starting point is 00:39:04 that Waymo is driving per day, has surpassed Lyft and is heading. for Uber. Isn't that remarkable? People are willing to pay up. Now, that's not in our 8 to 10 trillion. We assume that, sure, they'll start maybe right at or below the prevailing prices for Uber and Lyft, but they will drop over time to that 25 cents. So starting in the $2 and at surge pricing, you know, it can be $8 per mile, starting. $2ish dollars, $250 maybe, and dropping to $0.25 cents. $25 is at scale, right?
Starting point is 00:39:50 So that's the $8 to $10 trillion. And, you know, just think about it. I mean, I would prefer to take an Uber today, even though I have two Teslas and I love them, but I still have to pay some attention on the road, right? Right. I'm curious. how much of the Tesla market cap?
Starting point is 00:40:12 I think Tesla's $1.3 or $1.4 trillion. How much of that is Elon? Meaning, if I took Elon off the company, if Elon went to sleep for the next 20 years and we weren't going to have Elon running the company, would you keep your position the same way? And I guess just pie chart, right, of that $1.3 trillion,
Starting point is 00:40:28 what do you think that number goes to if there's no Elon? Well, if you had asked the question like five years ago, the answer would have been different. But I think what has happened, And one of the reasons Elon has spent so much time doing other things, some of which people didn't agree with, is because I think he feels they have pretty much solved the last mile in FSD. And if they have done that, then they're going to capture the robotaxy opportunity. They're going to be able to scale. We would not, however, start incorporating humanoid robots in the way we.
Starting point is 00:41:08 We haven't done much yet in our $2,600 price target. And we'll update that. We usually update it each spring for public consumption. And so we have very little for humanoid. We'd probably be much less optimistic on humanoid robots. And so we wouldn't put as much in as we perhaps will with Elon at the helm. Right. Wonderful.
Starting point is 00:41:36 Well, Kathy, I appreciate you coming on. It's fun to hear. some of your stories. It's good to hear your take on some of the tougher questions. So I appreciate you doing this. Yeah. Thank you, Sean. And thank you for the tougher questions. They're important. Thank you for giving me a platform on which to answer those questions because it is important. It is important. Great. Well, thank you. I hope to do it again. I feel like I can rule the world. I know I could be what I want to. I put my all in it like no days All right, let's take a quick break because, as you know, we are on the HubSpot Podcast Network,
Starting point is 00:42:11 but we're not the only ones. There's other podcasts on this network too, and maybe you like them. Maybe you should check them out. One of them that I want to draw your attention to is called Nudge by Phil Agnew. And whether you're a marketer or a salesperson, and you're looking for the small changes you could make, the new habits you could do, the small decisions you could make that will make a big difference. That's what that podcast is all about. Check it out.
Starting point is 00:42:30 It's called Nudge. And you can get it wherever you get your podcasts.

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