E247: Why Wall Street Is Wrong About AI w/ Dan Ives

Speaker 1 I've always viewed valuation more as

Speaker 1 you have to look out three, five, seven years to ultimately think where you're going to market to it.

Speaker 2 Today's guest is one of the most influential tech analysts on the planet. Don Ives is the managing director and head of technology research at Wedbush Securities.

Speaker 2 And for the last 25 years, he's been the person the world turns to when they need to understand what's really happening in tech.

Speaker 1 I remember

Speaker 1 in late 2022 meeting with like a ton of engineers, you know, just part of the work that we do, talking about AI and where everything's headed.

Speaker 1 They say about late 22, yelling into an empty forest, right? But I was convinced like this was going to be the beginning in terms of everything NVIDIA was doing of the AI revolution.

Speaker 1 Microsoft does the open AI investment for 10 billion. And I think we put a note out where like the AI revolution's begun.
My whole view is like, it's not just about big tech. That was 23, 24.

Speaker 1 It's about who in software, who else in chips,

Speaker 1 the grid, infrastructure.

Speaker 3 Dad, I've been excited. Shout out to welcome to the How to Invest podcast.

Speaker 1 I'm so excited to be here and thanks for having me.

Speaker 3 So you're one of the most well-known Wall Street analysts. You're famous for your calls on Microsoft, NVIDIA, Palantir, and perhaps most notably being early on Tesla.
Let's start there.

Speaker 3 So why are you bullish on Tesla today?

Speaker 1 Well, I mean, today, it's because my view, along with NVIDIA, it's two of the best physical AI disruptive players in the world.

Speaker 1 Look, I've never viewed Tesla going back, you know, a decade as a car company. I always viewed everything Elon was doing was disruptive tech.

Speaker 1 And then today, what I think about the AI revolution, I don't think there's a better play outside NVIDIA.

Speaker 1 I'm thinking about the longer-term AI vision, physical AI in terms of autonomous robotics than Tesla. And that's why I think it's $2 trillion and ultimately a $3 trillion market.

Speaker 3 It may be a dumb question, but how is Tesla and AI playing? Maybe you kind of unpack that.

Speaker 1 Yeah, I mean, to me, when it comes to...

Speaker 1 true AI technology, I don't believe there's a better use case than autonomous. So I continue, it's my view that Tesla will dominate the autonomous world.

Speaker 1 And when I look out in the next three, five, seven years, Robotax, I think, is just the start, but I think no one can match their scale and scope.

Speaker 1 And I think when it comes to miles-driven and ultimately, really viewing Tesla as much more of a of an ecosystem. That's how I've always viewed the 10 million cars out there.

Speaker 1 I don't think there's a better AI use case than what I think about what Tesla is going to do over the coming years. And look, and I just say the last decade,

Speaker 1 and I've covered tech, what, 25 years? There's no more emotional bull bear story than Tesla. And now it's about Musk proving it out.

Speaker 3 You have kind of an art approach to your evaluation as well as a science, and you kind of marry these better than almost anyone.

Speaker 3 How do you go about figuring out the intrinsic value of something like a Tesla? Is it a DCF analysis 10 years from now, or just walk me through kind of your methodology?

Speaker 1 I've always said, right, like

Speaker 1 if you focus just on one year P here, one year valuation, you missed every transformational tech stock the last 20 years. So there's no doubt, like I've always viewed valuation more as

Speaker 1 you have to look out three, five, seven years to ultimately think where you think the market's going. So look, I mean, Tesla would be a good example.
Like it's my view that like

Speaker 1 20%

Speaker 1 of automotive is going to be autonomous by the year 2030.

Speaker 1 So when you think about Tesla today, just forget deliveries quarter to quarter and what they're doing. I mean, I could argue that

Speaker 1 Tesla's revenue today

Speaker 1 will ultimately potentially be double.

Speaker 1 when you look out over the next six, seven years relative to the opportunity. so when i look at eps can they do twelve fifteen twenty dollars of eps power yeah

Speaker 1 so i don't view it today as just a stock trading at xxx times next year earnings it's my view like what is robotics going to be what is autonomous gonna be look and palantir has been a perfect example of that right like the haters needed it at twelve despise at fifty yelling from the mountaintops at a hundred and i always say, like, you know, the bears, when they're in hibernation mode, and the Pinot Moirs, again, I like Pinot Moir, but they can't see AI in spreadsheets.

Speaker 3 One of the thought experiments that you told me is that you think about kind of freezing time, almost like private equity. You make the investment in Tesla today, you wake up in five years.

Speaker 3 What is it worth? Do you take kind of a private equity lens to it, or how would you describe that?

Speaker 1 Yeah, Dave, I think that's a great question.

Speaker 1 Yeah, I think it's much more of that approach that I've always taken, even though like obviously a lot of investors over time have disagreed with it.

Speaker 1 Because it's my view, like let's say, let's say a company like Palantir

Speaker 1 that's going from a government

Speaker 1 big data play, transforming to a commercial AI play.

Speaker 1 I don't think you could look at that in the next one, two years. You have to say, okay, their secret sauce.
What are they building out?

Speaker 1 What's this going to look like in the next three, five, seven years? And that's always how I've looked at, you know, especially disruptive technology plays. And given where we are, right?

Speaker 1 I mean, we're in the biggest disruption phase in the last 40, 50 years in terms of AI revolution. And it's my view, like that's how you have to be able to look at these names.

Speaker 3 And easier said than done to kind of have this mental benchmark in your head of three to five years, very hard to kind of survive the turbulence.

Speaker 3 How do you deal with the turbulence and basically surviving the ups and downs of the public markets?

Speaker 1 I mean, I could go back to like my two worst years in 25 years, 08 and 2022, right? In terms of like, you're just giving the macro and then the re-environment.

Speaker 1 And it's, I think it's very easy as an analyst to just throw in the white powell.

Speaker 1 It's easier to kind of go with the pack. not fight sometimes the trends.
Stocks are selling off against you.

Speaker 1 But look i've traveled three million air miles 25 years an advantage that we've had is that just being around the globe

Speaker 1 you have such a sense in terms of like

Speaker 1 what things look like in taiwan what customers are talking about in the midwest what are the technologies emerging so it's my thesis that I've always built on is that like I'm going to do the work and even if stocks might not be reacting at that time favorably, or maybe even a quarter, right?

Speaker 1 Like we miss a quarter. Like the company didn't crush numbers and maybe the stock, but our checks are telling us other lies.

Speaker 3 But if you think about the markets kind of gaslighting you, telling you that it's a bad stock, and then your customers are telling you something else.

Speaker 3 So you have kind of almost this counterbalancing constant feedback. You're counterbalancing the market sentiment with kind of on-the-ground feedback.

Speaker 1 I'll give you like a really good example. Like,

Speaker 1 I remember

Speaker 1 in late 2022,

Speaker 1 meeting with like a ton of engineers, you know, just part of the work that we do, talking about AI and where everything's headed. They'll say about late 22,

Speaker 1 yelling into an empty forest, right? But I was convinced like this was going to be the beginning in terms of everything NVIDIA was doing of the AI revolution.

Speaker 1 Microsoft does the open AI investment for 10 billion. Everyone's like, why would they do this? This is crazy.

Speaker 1 At that moment we're like they would put a note out we're like the ai revolution's begun then the emails that i got from institutional

Speaker 1 which is i wouldn't repeat them here what are you talking about created this but that's a good example like the mark because i felt like the work that we did gave us confidence that we basically put a you know

Speaker 1 almost like you know a stamp or sort of pole on the ground saying like this is it things have changed.

Speaker 3 I think of memetic and herd behavior and I think of it as like different herds. There's like a Silicon Valley herd where certain things are accepted, certain things are haradoxical.

Speaker 3 There's like a public markets herd. And for example, like the public markets are much more later adopters, right?

Speaker 3 It's just a different, so saying something when you're with your Silicon Valley friends. could sound very different, could get you more isolated than you're with your public friends.

Speaker 1 Yeah. And then also, I'd say like, it's the, it's also the role that retail has played in this market.

Speaker 1 I think the way a lot of people on the institutional side have like missed, you know, I think a lot of these stocks is that they've been caught up in their echo chambers from New York to San Fran to Connecticut,

Speaker 1 and they've missed some of the underlying trends that are happening in Nimes. And whether it's Robin Hood or Palantir, it's some of the NVIDIA moves or whatever.

Speaker 1 I think it's a good example where

Speaker 1 you have to have a good understanding of sediment, whether it's Singapore or meetings in Florida. And also it's the work that we do in the field.

Speaker 1 I remember Palantir was selling off like massive after a quarter. Maybe I'm just from like $30

Speaker 1 to like 23. I'm just giving an example.
We're selling about around that. Everyone's like, that's it.
Stories, I can went from 12 to 30. This is it.

Speaker 1 But yet, like the work that we were doing at boot camps for Valentier with customers, it was unlike anything I've seen, you know, relative to the demand.

Speaker 1 So that was a moment where everyone's like, is this it? People are downgrading the stock. You're like, no, this is,

Speaker 1 we might have like missed the quarter from a timing perspective. This is a table pounder.

Speaker 3 moment. When we last chatted, you said that your alpha is are things that are not in the spreadsheets, which is very surprising for public companies.
What exactly is not in the spreadsheets?

Speaker 1 So, as I'm talking to a customer, and a year ago, they were,

Speaker 1 they thought AI was hype.

Speaker 1 They weren't allocating budget. It's a CIA.

Speaker 1 And today,

Speaker 1 after doing a bunch of demos, that customer is like all in. And now maybe it's a one or two priority in their budget.

Speaker 1 That's one, but that's important data point. Like, that's showing what's happening in the technology.

Speaker 1 So like if MongoDB misses a quarter and the stock's a disaster, but I'm hearing from customers and I'm in the work that we're doing at user conferences, we'll realize that they have a unique mousetrap.

Speaker 1 Well,

Speaker 1 why would that not be just the opportunity rather than throwing the towel? And I'm gonna say, like on the I think as an analyst on the sell side, it's easier

Speaker 1 to just stay with the herd.

Speaker 1 Don't go go against the grand.

Speaker 1 I've never dressed like that.

Speaker 1 I've never analyzed stocks like that.

Speaker 1 And I think that's been

Speaker 1 look, I think that's been part of our framework, right? Like part of our DNA. And also, like, I've learned the most from our failures too.
Like, maybe there have been stocks

Speaker 1 over time, like

Speaker 1 we were

Speaker 1 too early.

Speaker 1 And then maybe lacked the confidence. But yet at that time,

Speaker 1 that was a huge

Speaker 1 momentous move opportunity. And I think I learned a lot of that, like

Speaker 1 being so bullish. And like, what's like when Nadella came to Microsoft?

Speaker 1 You know, if you go back at the time, everyone's like, oh, Mike, they should have gotten like an outsider. Like Michael Dell, I'm just giving examples, like, you know, Chambers, whoever it was.

Speaker 1 And Adela, I always viewed as the Yoda. Like he understood

Speaker 1 the time cloud better than anyone.

Speaker 1 But if you go back when he took over at 14, it was like, okay, like it didn't at first hit. And there were maybe moments in there where we're like,

Speaker 1 okay, we're fully confident in our vision, but maybe we're not going to pound the table.

Speaker 1 And

Speaker 1 that actually was the time to pound the table.

Speaker 3 You mentioned kind of how you dress and being outside of the herd. Is the dress a way for you to separate from the herd? Or are since you're separated from the herd, you dress differently?

Speaker 3 What is driving what?

Speaker 1 It's kind of like, I've always dressed funky. So that's always like been there.

Speaker 1 But I do think like my, it's like a little symbolism too. Like,

Speaker 1 because I'm not going to, like, I'm not going to like go to the beat of like a typical drone. Like I'll dress different.
I could care what others think. But it's just like the way that I call stocks.

Speaker 1 Investors that have like followed me for, you know, decades understand

Speaker 1 who I, they understand the way that we analyze. Like, just like our ETF, right?

Speaker 1 Like, they understand like how we pick stocks, why we pick stocks, and some could disagree, but I think over the years, like, we've proven out our

Speaker 1 success.

Speaker 3 I had Mike Maples, famous venture capitalists, and one of the things he really focuses on, especially early on, is kind of finding your true believers and finding your early believers and not focusing on the people that don't believe in you.

Speaker 3 How do you operationalize it? You seem to have operationalized this really good. How do you avoid the noise? How do you avoid conformity? And how do you find your early, early adopters?

Speaker 3 I guess two different questions.

Speaker 1 Yeah, I mean, like, look, it's like I found it like definitely on the institutional side, right? Like, there's a lot of people that

Speaker 1 believed in me early, like, you know, that were very influential, you know, on the institutional side.

Speaker 1 And

Speaker 1 that in those early days gave me like a lot of confidence.

Speaker 1 And then I think ultimately I started to realize like

Speaker 1 haters hate and to some extent understand the opposite side, like understand the bare argument.

Speaker 1 Like I like that sounds like it's very important to me to engage in the opposite side to understand the differing view because actually it's helped me a lot.

Speaker 1 And I think obviously with social and retail,

Speaker 1 it's one where it's kind of like, I'm an open book,

Speaker 1 people love it, people hate it.

Speaker 1 But the way that we do things has been very

Speaker 1 clear

Speaker 1 in terms of our view of stocks, terms of staying long and strong, terms of our view of like just this, you know, basically 20-year tech bull market, my view of ai

Speaker 1 so i don't i just don't get caught up in

Speaker 1 like noise

Speaker 1 because it's also confidence in like the work that we do

Speaker 1 how do you know when you're wrong you know when you're wrong more from the when the thesis changes like when all of a sudden like let's say

Speaker 1 like i'll give you example it's like adobe

Speaker 1 Like as being a very bullish in Adobe over the years, I was a believer that Adobe was going to be able to like pivot and AI was actually going to be like a tailwind for him.

Speaker 1 And then basically like after like six, nine months, a year, start to realize more and more from like customers and partners, like

Speaker 1 that wasn't right. Like it was actually the opposite.
Like AI was going from like a tailwind to actually like a headwind.

Speaker 1 So so that's a good example of recognizing like we were wrong.

Speaker 1 Maybe right, obviously on the call, but on the AI piece wrong, admitting we are wrong, and then

Speaker 1 ultimately taking out of our like, you know, our core AI index.

Speaker 3 Essentially, a customer says something that breaks your frame of mind, and then you start to build consensus on the bear case. You start to double click on the bear case.

Speaker 1 And also, so it's like not being.

Speaker 1 I think it's easy to where like, let's say if you're a kid, if you have a kid and your kid does something wrong, it's easy as a parent be like, oh, it's not my kid. It's the other kid.

Speaker 1 It's the parent. It's the coach.
So don't you have to be like,

Speaker 1 okay, like, yeah, like, it's my kid. Like, you got the ownership.
And I think it's very easy with stocks.

Speaker 1 You can kind of like not listen to things that maybe go against your thesis and rationalize them. And I think that's the other thing.
I've gotten like a lot better over the years

Speaker 1 to understanding like that input and being like, hey, I gotta like, this could be a red flag. Let me do more digging.
Like I think Oracle is an example, like

Speaker 1 about like two years ago, like stocks going like a really rough spot. Like I spent like two days basically just like at user conferences talking to customers.

Speaker 1 You know, it was one just to like solidify that my broader thesis, you know, was, was right at the, the foundation, even though the execution could be offered with time and perspective.

Speaker 3 I like the indecent horror with strong convictions loosely held. So it's this idea of having very strongly rooted theories, but being willing to very quickly change it.

Speaker 3 And sometimes it just things change. A new CAO comes in, they change their strategy.
It's not that you were quote-unquote wrong. You were right at the time, but

Speaker 1 the thesis has changed. Stocks don't lie.
Sometimes it's like, okay, like stocks telling you something.

Speaker 1 What is it telling you? And it's like, look, and I'll be the first to say, like, our, if there was like a,

Speaker 1 like almost kind of like a

Speaker 1 great way to like sort of symbolize like our

Speaker 1 career, it would be like great at taking this inflection point,

Speaker 1 great at riding it. But probably like our fault is like not calling

Speaker 1 the top, right? Like if it was like staying on too long.

Speaker 1 And I think that was maybe like the thesis like you know there's many times on names where like we've kind of gone like this

Speaker 1 stay on

Speaker 1 okay then eventually like you know you're right but like it's hard when you're like on this part where it's almost like you're like okay I should have like I should have gotten more cautious should

Speaker 1 And I think that's something where it's always hard to see that, that inflection.

Speaker 1 And that's something that like, you know, we probably like, we spend like a lot more time trying to find that to make sure that we're not missing something

Speaker 1 and staying on stores too long.

Speaker 3 You've been doing this for decades. Have you ever had a situation where the company became more profitable, more intrinsically valuable, and the market just never caught up to it?

Speaker 1 Yeah, I mean, I think there are.

Speaker 1 And they're like a lot of the, but I think a lot of those examples were companies that ultimately ended up getting acquired by like private equity like sale point or like they may not have intrinsic value in public markets but they still have intrinsic value most of those examples were companies like they got bought

Speaker 1 and it was almost like the public market never recognized it whether it was like the management team or the consistent execution or whatever and then a lot of those companies ended up like getting acquired either private equity or strategic i think that's usually how that's played out.

Speaker 1 I feel like there have been some like,

Speaker 1 like I think Oracle is a good example where like

Speaker 1 that was happening, I feel like a year ago, but it took the market time to catch up.

Speaker 1 Like Oracle would be a good example where those dynamics were happening

Speaker 1 a year ago. nine months ago

Speaker 1 but only in this last six months has it truly caught up.

Speaker 1 Like another good example, let's say be like Google. Like,

Speaker 1 look, I'm of you. Like,

Speaker 1 anytime someone says, like, this lawsuit, this antitrust, this breakup, I'll always take, like, if we were betting, I'll always take like

Speaker 1 the over. Like, I always bet, I always bet, like, this is gonna be a lot better than the fear.

Speaker 1 So Google is a good example. I was like, search, search is going to kill, you know, AI

Speaker 1 done with search. The DOJ, it's going to get broken up, like New York City cab drivers barristering the stock.
But that was an example. Like, I see what's happening in terms of like Google Cloud.

Speaker 1 I see everything Kurion's doing. I see salespeople going from company X and Y.
So that was one where it was like, dang, okay, we're not right. We're not right.
Stocks telling you something.

Speaker 1 Like Salesforce, investors, like, you're wrong. You're up.

Speaker 1 And it happens.

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Speaker 3 There is a famous John Maynard Keynes quote, markets can remain irrational longer than you could remain solvent.

Speaker 3 And for somebody trying to operationalize being bullish on a single stock, what would your advice be to him or her in terms of the sizing?

Speaker 3 Because if you do size it too much, it becomes difficult to execute.

Speaker 1 So any guidance on sizing and how do you build a portfolio of these positions yeah i feel like it's almost like let's say if conviction level scale 110

Speaker 1 and let's say by definition if you're bullish you're always gonna be a conviction level like eight to ten when you're like an eight

Speaker 1 eight point five you're scaling it's still like

Speaker 1 toe in the water toe in the water but when it inflex from like an 8.5 to like in the nines, that's where you scale up. Like it's almost like, because I do think

Speaker 1 you're exactly right. Like, it's so, it's easy where you can be like right, but your timing is wrong.
And that in three bucks gets your coffee.

Speaker 1 So it's almost like trying to figure out like when it inflex.

Speaker 1 And just

Speaker 1 that's like there's, those are the moments to me where like the conviction level,

Speaker 3 it's, I think that's where you and the conviction and flex, not the stock.

Speaker 1 Exactly. Almost separate from the stock.

Speaker 3 It's like you're not trying to, and you're not saying that you, you could pick inflection points in the stock.

Speaker 3 You're saying you know how to position yourself so that when there's a, I guess, catalystic.

Speaker 1 That's exactly. And now you might be like, when that happens at first, like the stock might go the wrong way.

Speaker 1 But I'm fine with it because like you, you have conviction now. that that conviction could be from like

Speaker 1 the uh like you're seeing more companies go for like the stack that the company that the software company is selling

Speaker 1 or

Speaker 1 people are lining up for chip demand that maybe hasn't been reflected so much in numbers like that would be a good example of nvidia in like late 22 or early 23.

Speaker 1 sometimes it's very easy like the stock could go against you based on like macro whatever it may be But if your work tells you,

Speaker 1 that's where it's like, you. and look, and you're betting on yourself at the end of the day.

Speaker 3 You travel the world, you talk to many of the buyers. Are you ever having the buyers actually point you to a new stock that you might have never heard of?

Speaker 1 All the time, like

Speaker 1 it would be like there's been a lot of companies where maybe like they weren't even on my radar, but they're coming up like in bake-offs.

Speaker 1 And I'm like, what? They're coming, like,

Speaker 1 yeah,

Speaker 1 oh, like, there's an example, let's say, like,

Speaker 1 like InnoData,

Speaker 1 small cap,

Speaker 1 best software company in New Jersey.

Speaker 1 You're like, stocks, like, no one cares about. Then all of a sudden, like, in a lot of these AI, I'm hearing about them a lot.
Like, in a lot of these AI deployments,

Speaker 1 no one cared about it. And

Speaker 1 that was a good example. Like, you know, we started covering the stock and that that's been one of our core,

Speaker 1 probably one of our best calls over the last whatever six months i think that's also where like

Speaker 1 talking to so many people whether it's investors customers partners

Speaker 1 and traveling a lot i think that helps you it's very easy to like be in your own like echo chamber and i think that's that's sometimes like

Speaker 1 i think there could be like a big negative

Speaker 3 There's this weird psychological phenomenon where you learn something and blows your mind and then your brain convinces you that now now you know everything about the topic so you're just constantly getting getting updates to your brain in ways that are very kind of non non-linear and then you still think that now you know everything so there's there's this bias that human beings have that they know everything you don't know what you don't know like i always view myself as like

Speaker 1 i never have like hubris

Speaker 1 Like I just, I'm always trying to like learn, right? So it's like, to me, that is,

Speaker 1 I think, I think that's one of the keys too. And it's just trying to learn about different things that maybe,

Speaker 1 you know, would just increase your ability to better understand the markets one way or another.

Speaker 3 Last time we chatted, you said that you make yourself a conduit of information. What does that mean?

Speaker 1 As a cognitive information,

Speaker 1 we view ourselves as almost like, very intertwined globally with investor feedback.

Speaker 1 And I think that's a big part of our value, right? Like when I'm marketing, no matter where it is, investors like, what's the sentiment on stock acts?

Speaker 1 Why?

Speaker 1 Do you think a lot of people are bullish into your end?

Speaker 1 What about valuation? What are people talking about?

Speaker 1 And I think cognitive information is like a big, it's a big role you play as an artwork.

Speaker 3 I kind of look at it as information bartering. We have conversations every day, three to four LPs, GBs.
They're telling us information all the time. We're telling them a market information.

Speaker 3 And it's kind of like this positive sum. As long as you have information to give, and as long as you're giving kind of at the margin, more, people will start feeding you information.

Speaker 3 Now you have more information to give to the market.

Speaker 1 And also, part of it is like that. Also, I'm very active in social, right? Like, in other words, like in terms of social media, speak at a lot of conferences.
Like, I'm, you know,

Speaker 1 just by traveling, I feel like you have a lot.

Speaker 1 You're meeting meeting like new people all the time, different perspectives. And I think like that's helped us.

Speaker 3 Mark Andreessen recently said that

Speaker 3 the top public investors that he knows look at public stocks as having power law type aspects.

Speaker 3 So power law is when your entire, you have a portfolio of 10, one of them returns more than everybody combined to an order of magnitude. That was a little surprising to me.

Speaker 3 But if you look look at Amazon's returns since IPOs and the thousands of X's and Google, Microsoft,

Speaker 3 are there still power law returns in the public markets today, or was this kind of a thing of the 90s and 2000s?

Speaker 1 More today

Speaker 1 because of what's happened with the AI revolution. And I think how

Speaker 1 a lot of investors are maybe not even seeing the second, third, fourth derivatives that are happening. I mean, I go, that's a whole part of like our ETF.
Like, my whole view is like,

Speaker 1 it's not just about big tech. That was 23, 24.
It's about who in software, who else in ships,

Speaker 1 the grid, infrastructure.

Speaker 1 And

Speaker 1 a lot of times, like, I'm looking for names, being like, okay, could this stock outperform? And then there's, there's the rare names where you're like, okay, like,

Speaker 1 no one cares about this.

Speaker 1 And I think this thing could be a four bagger a five bagger like i feel like sometimes you know

Speaker 1 when you feel like you uncover some of those

Speaker 1 and what i love is like when sentiment is like so negative

Speaker 1 and you feel like

Speaker 1 you know you feel like you've like stumbled onto something

Speaker 3 It's quite common, especially smart or among smart people to think of second order effects. So you have, you now need AI.
So now you need to build these data centers.

Speaker 3 Few investors actually think of third level, third order effects and kind of even just, it's only two derivations out, but for whatever reason, investors don't think about that or it's not commonplace.

Speaker 1 But it's even like

Speaker 1 G Vernova, like on as a power play, okay?

Speaker 1 Like that's in our like Ives AI 30.

Speaker 1 Like Nebesis, which is an infrastructure play there. Like Aqua, which is is a nuclear play there but david this is a big example like okay it's like i'm not talking about

Speaker 1 like we're talking about football not the cookie cutter for 15 scripted plays

Speaker 1 what are those like moonshot play and it's trying to sometimes

Speaker 1 see where the market is going that maybe at the time investors don't see like maybe even like if we're in a market now everyone's like

Speaker 1 nvidia open ai Like, is this a bubble? Like, does this remind you of things you know, froth, like maybe risk off in the near term? Whatever. So, I view it differently.

Speaker 1 For me, it's like if some of the covered tech stocks that I need, I compare it dramatically different

Speaker 1 relative to the use cases, the spending, and everything I see.

Speaker 1 And I view times like when there's like sell-offs

Speaker 1 as maybe just times to just further my conviction

Speaker 1 in,

Speaker 1 you know, in

Speaker 1 tech names that I think are mispriced.

Speaker 1 My reputation's been built not when stocks go from here to here. Dude, like in that, my shih tzu

Speaker 1 or terrier could be the genius.

Speaker 1 It's when stocks are going like this

Speaker 1 and everyone's jumping ship

Speaker 1 and you're like.

Speaker 1 Like,

Speaker 1 you know, these are the opportunities.

Speaker 3 Do you judge yourself kind of as a venture capitalist would based on your big outliers, or are you kind of looking at your hit rate?

Speaker 1 It's a combo. It's my hit rate, but also a lot of times it's like my outliers, like my moonshots, like, was I right?

Speaker 1 Like, and I take it very personally in terms of like what I'm doing. Like, when I'm in an airport and some random person comes up to me and they're like, thank you so much.
Because you invest in this.

Speaker 1 Or if I'm in Europe and someone's like, my grandpa invests in this. See, I view it much more like personally.
This is not like

Speaker 1 client and just numbers and whatever money you make, whatever. I take it much more personally because people are

Speaker 1 putting their confidence in me.

Speaker 1 And I take that as a very heavy weight beyond just like a job.

Speaker 3 Why is investing in the public markets like batting 300 in baseball?

Speaker 1 It's hard to outperform.

Speaker 1 The alpha and the information flow is so hard to find things on the edges. So when you think about like batting 300,

Speaker 1 you know, and ultimately be about 300 over a career with some other stature in Cooperstown.

Speaker 1 Because I think it's about information flow.

Speaker 1 Like, I think it's just like harder and harder to distinguish, differentiate, and also the timing of things, especially in a market that's become so global, right? Like,

Speaker 1 I mean, today, if I stay at today already, I've talked to investors from Korea,

Speaker 1 Middle East,

Speaker 1 New York, California,

Speaker 1 South America.

Speaker 3 One of the keys to your success is you believe you could push buttons on a stock, and you said that you could push buttons on Tesla. What does that mean? How does that help you generate returns?

Speaker 1 Tesla is one where

Speaker 1 I feel like

Speaker 1 when you have a big following on a name,

Speaker 1 I feel like

Speaker 1 you can help change the narrative.

Speaker 1 And I think Tesla is one where it's very important to

Speaker 1 make sure the narrative is right. Because I think as an investor, it's very easy, just as an example, like if you look at the last year, so let's just say you looked at Tesla's

Speaker 1 numbers. So, all you know is just their quarter, what they report, and what street numbers have done.

Speaker 1 You'd right now think Tesla stocks 200 bucks,

Speaker 1 but instead it's whatever 430

Speaker 1 because it's about the narrative, it's about this the focus on Tesla is about

Speaker 1 the future back, autonomous, robotics,

Speaker 1 you know, and and and really them become much more of an AI play

Speaker 1 over the coming years. We view ourselves

Speaker 1 as very important in a lot of these names in terms of like

Speaker 1 the measure the narratives right,

Speaker 1 because I believe that's where the growth is. And I think it's very, it's very easy where a lot of names become very combative.

Speaker 1 You have a thesis and you have a mouthpiece

Speaker 1 and you have to be clear about that. I mean, look at Palantir as an example, right? Like the last $180,

Speaker 1 whatever, $170 of the stock move, people have just fought it every time, valuation, whatever,

Speaker 1 it's a services company and they just, and that's created the opportunity.

Speaker 3 When you say push buttons, you're able to contribute to the public discussion on the stock. You're able to influence the board.
What do you mean exactly?

Speaker 1 Yeah, like let's say, like, like from a board perspective, like I felt like the board needed to get a new pay package to Musk.

Speaker 1 I think there was also a groundswell among a lot of investors I was talking about. So, we put out basically like a three-point note to the board what they need to do in Musk.

Speaker 1 Now, again, like, I think that message was well received.

Speaker 1 The board ended up, you know, whatever, a month ago doing that stuff but that was a good example like that was an overhang in the stock like must needs to be with tesla he needs a new package he needs to get 25 ownership investors want more x ai and they want that ownership so also it's like it's playing a role in that way like it's trying to like weigh out what ultimately i believe is important not for me but for the story

Speaker 3 you mentioned Palantir. I was invested five years before it went public.
I had to sell a via lockup because of our provisions. But you were right on Palantir.

Speaker 3 And specifically, I just want to go back because oftentimes people change the narrative in retrospect. Oh, I know.

Speaker 1 I know the narrative.

Speaker 3 Yeah. At the time, everyone was saying it's not great because consulting, it's masquerading around as a tech company.
What did you see that other people didn't see?

Speaker 1 Well, first of all, and I started off like messy of AI, whatever, it was like $12 or $15, $13.

Speaker 1 Well, first of all, it was my view of CARP.

Speaker 1 Like,

Speaker 1 I'm also a believer, whether it's Saler, MicroStrategy, or Strategy, or

Speaker 1 Nadel at Microsoft, or CARP. I think

Speaker 1 you're betting on the leaders. You're betting on Jensen Nvidia.
So I'm a huge fan, huge believer in everything CARP is doing.

Speaker 3 Is that also not

Speaker 3 in the spreadsheets? The leadership is essential.

Speaker 1 There's no INN, right?

Speaker 1 It's like AMD. It's like this past year.
AMD, it's a disaster. Dude, Lisa Sue, if she's flying an airplane, I'm in 3A drinking a cab feeling really good.

Speaker 1 So then there's other managing teams that I would spray like Using Bolt away from that stock. They're so bad.

Speaker 1 So I do think that's something that you have to have a very good sense for like which managing teams to bet on. Proofpoint, okay? Like Gary Steele.

Speaker 1 I remember when I met Gary Steele at Proofpoint, I'm like, this guy's all famer. Like he might be the best CEO of a small cap manager I've ever seen.

Speaker 1 Proofpoint ended up becoming like a 40 bag or whatever, but it was betting on Gary Steele and now he's at Splunk. I do think that that's important.

Speaker 3 One of the most mispriced things in the public markets is founder-led companies

Speaker 3 because there's this three-month quarterly reporting. Now

Speaker 3 they're trying to change that to every six months, but this disconnect between playing for a quarter and playing for eternity or forever long the founder is alive. It seems like it's not priced in.

Speaker 3 Is there any credence to that?

Speaker 1 Yeah.

Speaker 1 And also, I think founder-led, like CEO, you know, there's, there's all differing views, right? Like sometimes like,

Speaker 1 you need

Speaker 1 maybe other managers come in and they could go to chairman or whatever because because they could actually lead it. Other times, you know, they're the ones to actually lead the vision.

Speaker 1 I always think sometimes like companies get to a certain scale, especially a lot of times like when companies go from like 500 million to a billion,

Speaker 1 you know, in software, that's like a huge whip.

Speaker 1 And there's a lot of management teams where, like, okay, you know what? They were great to get into there.

Speaker 1 Now it's like it's time to

Speaker 1 hand over the

Speaker 1 reins, right?

Speaker 1 So,

Speaker 1 but that's why to like not in the spreadsheets. Like, I think that is something,

Speaker 1 like, I think in this job, having like EQ

Speaker 1 is as more important than IQ. I don't know how much it's innate, you're born with it or taught, but sometimes it's like sitting down with individuals being like,

Speaker 1 is this someone I want to bet on or not? And I do think, like, some of like the best investors,

Speaker 1 they have just their genius level EQ.

Speaker 3 So another way the IQ is in the spreadsheet or the numbers are there, the EQ is almost inherently not in the spreadsheet.

Speaker 1 That's like, that's like a really, really important thing that I think gets like overlooked very often.

Speaker 3 People will fact check me, but I believe the first time that there were super voting shares in these founder class was Google when it went public now alphabet. I think

Speaker 3 Mark Zuckerberg has since done that. Obviously Elon has a lot of control.
Do you think net net, that's a good thing? And how is this kind of 20-year experience played out?

Speaker 1 I think it's, I actually think it's a great thing.

Speaker 1 for those companies. Like in other words, like I could say Sailor has done very similar things in MicroStrategy.

Speaker 1 Like that's another, because look, it's like you're betting on that pilot to fly the plane.

Speaker 1 If you get too caught up, investor boards, rep quarter, quarter, make some missteps, rep.

Speaker 1 So I do think like

Speaker 1 in order to have like a wartime CEO, like a Zoc or a Musk or

Speaker 1 a Salerm,

Speaker 1 I do think you need that because I think it's very easy to get caught up in gyrations,

Speaker 1 boards, and other investors.

Speaker 3 It's like an insurance against an activist short-term takeover. So said another way.
And it's not only that activists can't come in, it's that the team knows that activists can't come in.

Speaker 3 So therefore, they could plan for the long term.

Speaker 1 I think that's right. And I think, like,

Speaker 1 if you look like what Zucks does with Meta,

Speaker 1 go back to like Metaverse,

Speaker 1 that disaster quarter in October, stocks, 85 bucks, whatever.

Speaker 1 It's like,

Speaker 1 it would have been very easy to

Speaker 1 like, should we change course throughout? And then what what is he to bam, bam, bam, change course in the rest of history?

Speaker 3 It's very easy to criticize Zuck, but he has been managing Facebook truly and meta truly like a startup. What does that mean?

Speaker 3 Taking large, big bets in every cycle, knowing that maybe 50% or maybe even one-third of them will play out. But if similar to the recent bet on AI, if that winner is going to be kind of a power loss.

Speaker 3 So

Speaker 3 he's like investing $100 or $200 billion

Speaker 3 almost on a venture-like bet, which is extremely bold. And I think rationally is the right thing to do, even though many, the first couple of times you'll be wrong and everybody will ridicule you.

Speaker 3 And then on the third, you'll be a genius.

Speaker 1 Exactly. But then if you don't have that structure, it's hard to do that.

Speaker 3 If you could go back to 1996, when Dan Ives graduated at Penn State, what would be one piece of timeless advice you would give yourself to either accelerate your career or avoid some of those mistakes?

Speaker 1 There were a lot of times earlier in my career where, like,

Speaker 1 whether it was like

Speaker 1 not getting jobs or maybe even at jobs, like, you know, different failures, where it was very easy to let that get you down, you get caught up in it.

Speaker 1 The thing that I would tell myself back then would be

Speaker 1 embrace the failures let them make you better

Speaker 1 and and and it's belief in yourself like it's just like all the success that you've had right

Speaker 1 like

Speaker 1 i'm sure like if you went back like 20 years and showed what you're doing there you're like whoa

Speaker 1 but part of it is that like it's a learned behavior and i think for me it's like once the once like the bell went off or be like look

Speaker 1 stop like getting focused on like,

Speaker 1 you know, failures you've had and let them get you down. Cause it's a true story.

Speaker 1 I'm at FBR, like, you know, and Freedom Billings Ramsey, you know, that was a core part of my career.

Speaker 1 I remember I initiate on three companies

Speaker 1 and

Speaker 1 I'm like, so excited like, you know, it's like, maybe it's like 2002 or something like that.

Speaker 1 And three companies, in the next three weeks, they all go down 50%.

Speaker 1 And they were all buy-oid.

Speaker 1 And I remember I'm sitting there stuck in like Pittsburgh airport a Friday night. And I'm thinking, like, what am I going to do for my next career? You know what I mean?

Speaker 1 Because it's like disaster blow-ups. My head is sales at the time.
John Billings calls me and he's like,

Speaker 1 you're going to let this conviction just go. who cares if the stocks were, and they all pre-announced negative.
He's like, if you have conviction, that's what meets you.

Speaker 1 And it was like a Vince Bombardier type speech. And that weekend, like, I wrote this like crazy piece, like, this is like temporary.
These companies get bought.

Speaker 1 It's like, you know, just confidence in the thesis.

Speaker 1 And actually, like over the next like, I think nine months, all those companies got bought and they became like all of them were like four or five baggers.

Speaker 1 But that was like a defining moment in my career where it's like, just stop like, stop feeling sorry for yourself if you're wrong and just have conviction in yourself.

Speaker 3 It's not just the failures. It's having people around you that interpret the failures in a certain way.

Speaker 3 The Zucker example is actually a pretty interesting one because he essentially tarnished his reputation for five, six years, even though he had made the right probabilistic bet in order to do what's right for meta.

Speaker 3 And if he had been around people that were very herd-like or insecure, they may have said, Well, you've made these two wrong bets. Don't do the third one.
But

Speaker 3 who you're surrounded with is as important as your own mental state.

Speaker 1 And for me, just being on Wall Street 25 years, like there's like thousands and thousands of adults. Like they just,

Speaker 1 you know, they disappear like, you know, like the wind or whatever, right?

Speaker 1 So it's like, I've been lucky that like I, like at FA, you know, at FBR and then like a web bus, like I always like worked at places where like they understood who i was and they gave me that

Speaker 1 time for the calls to to play out but maybe if i was like at different firms that didn't have they didn't understand like this funky dresser and like you know they just looks at stocks differently or whatever then maybe like you know like it never would have never would have worked right

Speaker 3 is there something in your childhood or background that allows you to be kind of

Speaker 3 out of the herd and eccentric?

Speaker 1 Part of it is like my dad always said, like, people are always going to be better looking, wealthier, and smarter. Just accept it.

Speaker 1 Like, there were certain things like growing up in like Log Island in the 80s, right? It was just like, I think that was like a great place to grow up.

Speaker 1 And just like living, like, in my household, it was one where it was like, just be your own self.

Speaker 1 So, I think that was like a big thing where like it rooted back to those days.

Speaker 3 What would you like the audience to know about you, Webbush, or anything else you'd like to share?

Speaker 1 Webbush, obviously, you know, doing great things from a tech perspective in terms of AI. You know, we have our IZ ETF, which is we've been super excited about launched in June.

Speaker 1 Option's been really good because that gives investors the opportunity to basically bet at AI.

Speaker 1 And then, you know, very similar to the theme, we recently became chairman of Orbs, you know, ECO, which is a company that's really focused on Sam Altman's world.

Speaker 1 You know, I think Sam's going to be a great partner, everything he's done. I think there's going to be a single sign-on for the AI future.

Speaker 1 You know, I think authentication is going to be more and more important in terms of human proof. And look, for people who know me, I do a lot of different things.

Speaker 1 The clothing line may be a little different, but it's all centered around. the AI revolution.
It's my passion for where that's happening.

Speaker 3 A mutual friend told me to ask you about snow milk and and your clothing.

Speaker 1 Tell me about that. So,

Speaker 1 Snow Milk, you know, an awesome designer in Williamsburg in Brooklyn. They came to me and wanted to do a collab.
So, we did a Dead Eyes collab with DeadEyesClothing.com.

Speaker 1 And look, this is something where I have so many people. These are for men, women, for whoever.

Speaker 1 Different colors, funky designs. We start off with shirts.
We're going to go in sweatshirts and hats. It's been great working with them.
And the demands are really,

Speaker 1 it's been obviously a lot higher than I ever thought.

Speaker 3 Well, Dan, you're truly a one-of-one. I've never met anybody like you and I'm so lucky to have spent time and

Speaker 3 looking forward to continuing this conversation.

Speaker 1 No, and I'm just happy that you invited me and all the success that you've had. It's just great to be alone here.

Speaker 3 Thank you, Dan. That's it for today's episode of How to Invest.

Speaker 3 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.

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Speaker 4 Thank you for your continued support.