How I Invest with David Weisburd - E247: Why Wall Street Is Wrong About AI w/ Dan Ives

Episode Date: November 21, 2025

Is traditional valuation dead for the biggest winners of the AI era? Or have investors simply been looking in the wrong place? In this episode, I talk with Dan Ives, Managing Director and Global Head of Technology Research at Wedbush Securities, and one of Wall Street’s most followed tech analysts. Dan has covered the software and technology sector for 25 years, becoming known for his bold, high-conviction calls on Tesla, Nvidia, Microsoft, and Palantir long before they became consensus. We break down why Dan calls Tesla the world’s leading “physical AI” company, why he thinks AI is the largest tech transformation in 40–50 years, what investors miss when they rely only on spreadsheets, and how his pattern-recognition framework helps him spot multi-baggers years before the herd.

I've always viewed valuation more as you have to look out three, five, seven years. To ultimately think where you think the market's one. 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. 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. I remember in late 2020, 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 don't see what, Lee 22 yelling into an empty forest, right?

But I was convinced, like, this was going to be the beginning in terms of everything Invidio was doing of the AI revolution. 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 old view is, like, it's not just about big tech. That was 23, 24. It's about who in software, who else in chip, the grid, infrastructure. Yeah, and I've been excited to shout. Welcome to the High Invest podcast.

I'm so excited to be here and thanks for having me. So you're one of the most well-known Wall Street analysts. You're famous for your calls on Microsoft, Nvidia, Pallenteer. and perhaps most notably being early on Tesla. Let's start there. So why are you bullish on Tesla today? Well, I mean, today it's because my view, along with Nvidia, two of the best physical AI disruptive players in the world.

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. And today, what I think about the AI revolution, I don't think there's a better play outside Invidia. I'm talking 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 $3 trillion market. Maybe a dumb question, but how is Tesla an AI play? Maybe you can unpack that.

Yeah, I mean, to me, when it comes to 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. And when I look out the next three, five, seven years, robot action, I think is just the start. But I think no one can match their scale and scope. And I think when it comes to miles driven and ultimately really viewing Tesla is much more of an ecosystem.

That's how I've always viewed 10 million cars out there. 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, you know, when I've covered tech, what, 25 years, there's no more emotional bull bear story than Tesla. And now it's about Musk proving out. You have kind of an art approach to your evaluation as well as the science, and you kind of marry these better than almost anyone. How do you go about figuring out the intrinsic value of something like a Tesla? Is it a DCF analysis 10 years so now or just walk me through kind of your methodology? I've always said, right?

Like, if you focus just on one year P year, one year evaluation, you missed every transformation of tech stock the last 20 years. So there's no doubt. Like I've always viewed valuation more as you have to look out three, five, seven years to ultimately think where you think the market's going. So look, I mean, Tesla, be a good example. It's my view that like

20% of automotive is going to be autonomous by the year 2030. So when you think about Tesla today, just forget delivery is quarter a quarter and what they're doing. I mean, I could argue that

Tesla's revenue today will ultimately potentially be double when you look out over the next six, seven years relative to the opportunity. So when I look at EPS, can they do 12, 15, $20 a EPS power? Yeah.

So I don't view it today as just a stock training at X, X, X times next year earnings. It's my idea, like, what is robotics going to be? What is autonomous going to be? Look, and Palantir has been a perfect example of that, right? Like, the heaters needed it at 12, despise it at 15, yelling from the mountain tops at 100. And I always say, like, you know, the bears, when they're in hibernation mode

and the Pinar's, I mean, I like Pina Moulars, but they can't see AI in spreadsheets. 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. What is it worth?

Do you take kind of a private equity lens to it, or how would you describe that? Yeah, Dave, I think, That's a great question, I think it's much more of that approach that I've always taken, even though, like, obviously, a lot of investors, you know, over time I disagreed with it. Because it's my deal, like, let's say a company like Palantir that's going from a government big data play, transforming to a commercial AI play. I don't think you could look at that in the next one, two years.

You have to say, okay, their secret sauce. they build out 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? I mean, we're in the biggest disruption phase in the last 40, 50 years in terms of AI revolution. And it's my like, that's how you have to be able to look at these names. 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.

How do you deal with the turbulence and basically surviving the ups and downs of the public markets? I could go back to like my two worst years and 25 years, 08 in 2022, right, in terms of like you're just given the macro and then the re-environment. I think it's very easy as an analyst to just throw in the white towel. It's easier to kind of go with the pack, not fight sometimes the trends. stocks are selling off against you but look I've traveled three million air miles 25 years an advantage that we've had is that just being around the globe you have such a sense in terms

of like what things look like in Taiwan what customers are talking about in the Midwest what are the technologies emergent 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 like we miss a quarter like the company didn't crush numbers and maybe the stock but our checks are telling us other lies but if you think about the market's kind of gaslighting you telling you that it's a bad stock and then your customers are telling something else so you have kind of almost this counterbalancing constant feedback you're counterbalancing the market sentiment with kind of on the ground feedback I give you like a really

good example. I remember in late 2002 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 don't see what, Lee 22 yelling into an empty forest, right?

But I was convinced like this was going to be the beginning in terms of everything in Viti was doing of the AI revolution. Microsoft does the open AI investment for $10 billion. Everyone's like, why would they do? This is great. At that moment where I didn't even put a note out where like the AI revolution has begun.

Then the emails that I got from institutional, but just I wouldn't repeat them here. What are you talking about? Create this. But that's a good example. Because I felt like the work that we did gave us confidence that we basically put us, you know, almost like, you know, a stamp or sort of pull on the ground saying, like, this is it. Things have changed. 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 paradoxical. There's, like, a public markets herd. And, for example, like, the public markets are much more later adopters, right? 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 your... with your public friends.

Yeah, and then also, I'd say, like, it's also the role that retail has played in this market. I think the way a lot of people on the institutional side of, 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, and they've missed some of the underlying trends that are happening in names. And, you know, whether it's Robin Hood or Palantir, some of the NVIDium moves or whatever, I think it's a good example where 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. I remember Palantir was selling off, like, massive after a quarter. Maybe I'm just from like $30 to like 23.

I'm just giving an example. We're selling about around that. Everyone's like, that's it. Stories are. I can learn from 12 to 30. This is it. But yet, like the work that we were doing at bootcams for Ballanteer with customers, it was unlike anything I'd seen, you know, relative to the demand.

So that was a moment where everyone's like, is this it? People are downgrading the stock. You're like, no, this is. We might have, like, missed the quarter from a timing perspective. This is a table-bound moment. When we last chat, 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? So I was talking to a customer, and a year ago, they were, they thought AI was hype. They weren't allocating budget. It's a CIA. And today, after doing a bunch of demo, that customer is like all in and now maybe it's a one or two priority in their budget.

That's one cut. But that's important data. Like that's showing what's happening in the technology. So like if MongoDB misses a quarter in the stocks of disaster, but I'm hearing from customers and I'm in the work that we're doing to user conferences

or realize that they have a unique mouse shot, well, why would that not be just the opportunity rather than throw in the towel? And I'm saying, like, on the, I think as an analyst in the south side, it's easier to just stay with the herd. Don't go against a grant. I've never dressed like that. I've never analyzed stocks like that. And I think that's been, look, I think that's been part of our framework, right? like part of our DNA.

And also like I've learned like the most from our failures too. Like maybe like there have been stocks like over time like we were too early. And then maybe lack the confidence. But yet at that time that was a huge momentous move opportunity. And I think I learned a lot of that like being so bullish and like, like, It's like when the Della came to Microsoft. You know, if you go back at the time, everyone's like, oh, like, they should have gotten, like, an outsider, like Michael Dellum's giving examples, like, you know, Chambers, whoever it was. And Della, I always viewed as the Yoda.

Like, he understood it's a time cloud better than anyone. But if you go back when he took over a 14, it was like, okay, like, it didn't at first hit. And there were maybe moments in there where we're like, okay, we're fully carved in our vision, but maybe we're not going to pound the table. And that actually was the time to pound the table. 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 since you're separated from the herd, you dress differently? What is driving what? It's commonly, I've always dressed funky.

so that's always like been there but I do think like my it's like a little symbolism too like because I'm not gonna like I'm not gonna like go to the beat of like a typical drone like I'll dress different I could cow or others think

but it's just like the way that I call stocks investors that have like filed me for you know decades understand who I they understand the way that we analyze Like, just like our ETF, right? 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 success.

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. how do you operationalize this really good how do you avoid the noise how do you avoid conformity and how do you find your early early adopters i guess two different questions yeah i mean look it's like i found that like definitely institutional side right like there's a lot of people that believed in me early like you know that were very influential you know on the institutional side

and that in those early days gave me like a lot of confidence And then I think ultimately started to realize, like, haters, hate, and to some extent, understand the opposite side. Like, understand the bare argument. Like, that's something like it's very important to engage in the opposite side to understand the differing view. Because actually, it's helped me a lot. And I think, obviously, with social and retail,

it's one where it's kind of like I'm an open book people love it people hate it but the way that we do things has been very clear in terms of our view of stocks in terms of staying long and strong in terms of our view of just this

you know basically 20 year tech bowl market my view of AI so I don't I just don't get caught up in, like, noise, because it's also a confidence in, like, the work that we do. 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, like, I'll give you example, it's like Adobe, like, as being very bullish

in Adobe over the, like, I was a believer that Adobe was going to be able to, like, pivot and AI was actually going to be like a talent for him. And then basically like after like six, nine months a year, start to realize more and more from like customers and partners. Like that wasn't right. Like it was actually the opposite. Like AI was going from like a talent to actually like a headwind. So so that's a good example of recognizing like we were wrong.

Maybe right obviously on the call, But on the AI piece wrong, admitting we are wrong, and then ultimately taken out of our, like, you know, our core AI index. Essentially, a customer says something that breaks your frame of mind and then you start to build consensus on the bare case. You start to double click on the bare case. And also it's like not being, I think it's easy too where like, let's say 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, it's the parent, it's the coach. So then you have to be like, okay, like, yeah, like, it's my kid. Like, you got the ownership.

And I think it's very easy with stocks. 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 than I've gotten, like, a lot better over the years to understanding, like, that input and being like hey i got to like this could be a red flag let me do more digging like i think oracle as an example like about like two years ago like stocks going to like a really rough spot like i spent like two days basically just like at user conferences talking to customers you know it was one just to like solidify that my broader thesis you know was was right at the at the foundation even though the execution could be offered with time and

perspective i like the indrecent 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 and sometimes it just things change the new ceo comes in they change their strategy it's not that you were quote unquote wrong you were right at the time but the thesis has changed stocks don't lie sometimes it's like okay like stocks telling you something what is it telling you and it's like look and I'll be the first of it like our

if there was like a like a like almost kind of like a great way to like sort of symbolify like our career it would be like great at taking this inflection point

great at riding it but probably like our fault is like not calling the top right like it was like staying on too long 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 stay on okay then eventually like 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 and i think that something where it's always hard to see that, that inflection. And that's something that like,

you know, we spend like a lot more time trying to find that to make sure that we're not missing something and staying on stores too long. You've been doing this for decades. Have you ever had a situation where the company became more profit, more intrinsically valuable, and the market just never caught up to it? Yeah, I mean, I think there are, And there, like, a lot of, like, but I think a lot of those examples were companies that ultimately ended up getting acquired by, like, private equity. Like, like, sale point or, I got, like, they may not have intrinsic value in public markets, but they still have intrinsic value. Most of those examples were coming as, like, they got bought. And it was almost like the public market never recognized it, whether it was, like, the managing 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. There have been some, like, I think Oracle is a good example where, like, that was happening, I felt like a year ago. But it took the market time to catch up.

Like, Oracle would be a good example where those dynamics were happening a year ago. nine months ago but only in this last six months is it truly caught up I like another good example what's it be like Google

like look I'm of you like anytime someone says like this lawsuit this antitrust this breakup I'll always take

like if we're betting I'll always take like the over like I always bet I always bet like this is going to be a lot better than the fear. So Google is a good example. It was like, search. It's going to kill, you know, AI done with search.

The DOJ, it's going to get broken up, like New York City cab drivers, barris in the stock. But that was an example. I see what's happened in terms of Google Cloud. I see everything Currian is doing. I see salespeople going from company X and Y. So that was one where it was like, hey, okay, we're not right. It's stocks telling you something. Like sales for, as investors, like, you're wrong.

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Not all applicants will qualify. Plus 500. It's trading with a plus. There's a famous John Maynard Keynes, quote, markets can remain irrational longer than you could remain solvent. 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? Because if you do size it too much, it becomes difficult to execute.

So any guidance on sizing and how do you, build the portfolio of these positions? Yeah, I feel like it's almost like, let's say if conviction level scale 110. And let's say by definition of your bullers, you're always going to be a conviction level like 8 to 10. When you're like in 8, 8.5, you're scaling, it's still like toe in the water,

toe in the water. But when it in flecks from like an 8.5 to like in the nuns, that's where you scale up. Like, it's almost like, because I do think you're exactly right. Like, it's so, it's easy where you can be like right, but your timing was wrong and that in three bucks gets your coffee. So it's almost like trying to figure out like when it inflats and just that's like those are the moments to me where like the conviction level it's, I think that's where you're. And the confection inflex, not the stock. Exactly, almost separate from the stock.

It's like, you're not trying to, and you're not saying that you could pick inflection points in the stock. You're saying you know how to position yourself so that when there's a, I guess, catalystic. That's exactly. And now you might be like, when that happens at first, like, stock might go the wrong way. But I'm fine with it because it's like you have conviction now. That conviction could be from like, the. Like, you're seeing more companies go for, like, the stack that the company, that the software coming to sell it.

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

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 all the time like 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 Beakoff And I'm like, what, they're coming, like, yeah, like, there's an example, let's say, like, like, you know, data, small cap, best software company in New Jersey, it's a joke, you know, like, stocks, like, no one cares.

They don't 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. No one cared about it. And no, that was a good example. like, you know, we started covering the stock and that's been in one of our core and probably one of our best calls over the last, whatever, six months.

I think that's also where like talking to so many people, whether it's investors, customers, partners, 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,

I think there could be like a big negative. there's this weird psychological phenomenon where you learn something and blows your mind and then your brain convinces you that now you know everything about the topic. So you're just constantly getting updates to your brain in ways that are very kind of non, nonlinear. And then you still think that now you know everything. So there's this bias that human beings have that they know it. You don't know what you don't know. Like I always view myself as like, I never have like hubris.

Like I just, I'm always trying. like learn right so it's like to me that is i think i think that's one of the keys too and it's just trying to learn about different things that maybe you know would just increase your ability to better understand the markets one way or another last time we chatted you said that you make yourself a conduit of information what does that mean as a cognitive information we view ourselves is almost like very intertwined globally with investor feedback. 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? Why? Do you think a lot of people are bullish into year end? What about valuation? What are people talking about? And I think kind of information is like a big, it's a big role. you play as an hour worse?

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

information. Now you have more information to get to the market. And also part of it is like that also like I'm very active in social, right? Like in other words, like in terms like social media, speak at a lot of conferences like I'm like just by travel I feel like you have a lot you're meeting like new people all the time different perspectives and I think like that's helped us Mark Andreessen recently said

that the top public investors that he knows look at public stocks as having power law type aspects. So power law is when you have a portfolio of 10, one of them returns more than everybody combined to an order of magnitude. It was a little surprising to me. But if you look at Amazon's returns since IPO and the thousands of X's and Google and Microsoft, are there still power law returns in the public markets today or is this kind of a thing of the 90s and 2000s? We're today because of what's happened with the AI revolution. And I think how a lot of investors are maybe not even seeing the second, third, fourth derivatives that are happening.

I mean, that's a whole part like our ETF. Like my whole view is like, it's not just about big tech. That was 23, 24. It's about who in software, who else in ships, the grid, infrastructure. And a lot of times, like, I'm looking for names being like, okay, could the stock app? perform and then there's there's the rare names where you're like okay like no one cares about this and i think this thing could be a four bagger a five like i feel like sometimes you know when you feel like you uncover some of those and what i love is like when sentiment is like so

negative and you feel like you feel like you've like stumbled on this it's quite common especially 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 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 it's not a common place But it's even like G. Vernova

I got it as like a power play okay like that's in our like Ives AI 30 like nebesis which is an infrastructure play there

like Aqua which is a nuclear play there but David these are the example like okay it's like I'm not talking about

like we're talking about football not the cookie cutter first 15 scripted plays what are the those like moon shop play and it's trying to sometimes 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

invidia open ai like is this a bubble like does this remind you have think you know if roth like maybe risk off in the near term whatever so i do it differently for me it's like if some of the covered tech stocks than I need. I compare it dramatically different relative to the use cases, the spending and everything I see. And I view times like when there's like sell-offs

as maybe just times to just further my conviction in, you know, in tech names that I think are mispriced. My, my reputation's been built not when stocks go from here to here. Do you like in that,

my Shih Tzu or Terrier could be the genius. It's when stocks are going like this and everyone's jumping ship and you're like, like, you know, these are the opportunity. 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? It's a combo. It's my hit rate, but also a lot of times just like my outliers. by moon shots like was i right

like and i take it very personally in terms of 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 of you invest in this or if i'm in europe and someone's like my grandpa invest in it see i do it much more like personally

this is not like client and just numbers and whatever money you make whatever I take it much more personally because people are putting their confidence in me. And I take that as a very heavy week beyond just like a job. Why is investing in the public markets like batting 300 in baseball? It's hard to outperform. The alpha and the information flow is so hard to find things on the edges.

So when you think about like batting 300 or 100, you know, and ultimately about 300 over a career with some other stature in Cooperstown, because I think it's about information flow. Like I think it's just like harder and harder to distinguish, differentiating also the timing of things. Especially in the market has become so global, right? Like, I mean, today, if I just think about today already, I've talked investors from Korea, Middle East,

New York, California, South America. 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? Tesla is one where I feel like when you have a big following on a name, I feel like you can help. you can have changed narrative.

And I think Tesla is one where, like, it's very important to, like, 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, like, you looked at Tesla's numbers. So all you know is just their quarter, what they report, and what street numbers are done. You right now think Tesla stocks,

200 bucks but instead it's whatever 4 30 because it's about the narrative it's about this the focus on tessa is about the future about autonomous robotics you know and and and really them become much more of an a i play over the coming years we view ourselves as very important a lot these names in terms of like the measure the narratives right because I believe that's where the growth is and I think it's very

easy where a lot of names become very combative you have a thesis and you have a mouthpiece and you have to be clear about that I mean look at Palantir as an example right like the last $180

or whatever $170 hours of the stock move, people have just fought it every time, valuation, whatever, it's a services company, and they just, and that's created the opportunity. 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? Yeah, like, I could say, like, from a board perspective, like, I felt like the board needed to get a new paid package to Musk. 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. Now again, like, I think that message was well received. The board ended up, you know, whatever, a month ago doing that stuff. But that was a good example. Like, that was an over and the stock.

Like, Musk needs to be with Tesla. He needs a new package. He needs to get 25% ownership. Investors want more XAI 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 or for the story. You mentioned Palantir.

I was invested five years before I went public. I had to sell a via lockup because of our provisions. But you were right on. Palantir. And specifically, I just want to go back because oftentimes people change the narrative in retrospect. Oh, I know. I know. 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? Well, first of all, and I started off like messy of AI, whatever, it was like $12 or $15, $13. Well, first of all, it was my view of cart. Like, I'm also a believer, whether it's sell or

micro strategy or in the Dell and Microsoft or CARP, I think you're betting you're betting on the leaders. Like you're bet on Jensen NVIDIA. Some of a huge fan, huge believer in everything CARP is doing. Is that

also not not in the spreadsheets, the leadership is a sense of there. There's no line at right. It's like AMD. I let's like this past year. AMD it's a disaster. Dude, Lisa's Sue, if she's flying an airplane, I'm in 3A drinking a cab, feeling really good.

So then there's other managing teams that I would spread like Lusine Bolt away from that stock. They're so bad. So I do think that's something that you have to have a very good sense for like which managing teams to better proof point, okay? like Gary Steele I remember like when I met Gary Steele proof point I'm like this guy's all famer like he might be the best CEO of a small cat manager I've ever seen proof point ended up becoming like a 40 bag or whatever but it was betting on Gary Steele and now is it splunk I do think that that's important one of the most mispriced things in the public markets is founder led companies because there's this a three month quarterly reporting now that 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's alive it seems like it's not priced in is there any credence to yeah and also i think founder led like see you you know there's there's all different views right like sometimes like you need maybe other men engine to come in and they could go to chairman or whatever because they could actually lead it other times you know they're the one was to actually lead the vision i always think sometimes like companies get to a certain scale especially at times like when companies go from like 500 million to a billion even software that's like a huge whip and there's a lot of

managers teams where like okay you know what they were great to get them to there now it's like it's time to hand you know hand over the the reins right so but that's why to like now in the spreadsheets like i think that is something like i think in this job having like EQ is as a 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 is this someone I want to bet on or not and I do think like some of like the best investors they have just their genius level EQ so another way the IQ is in the spreadsheet or the numbers are there the EQ is almost inherently not a not in spreadsheet that's like that's like a really

really important thing that I think it's like overlooked very often People will fact check me, but I believe the first time that there were super voting shares and the founder class was Google when it went public now Alphabet. I think you're right here. Mark Zuckerberg has since done that. Obviously, Elon has a lot of control. Do you think NetNet that's a good thing? And how is this kind of 20-year experience played out?

I think it's, I actually think it's a great thing for those companies. Like, in other words, like I could say sellers done very similar things in micro strategy. Like, yeah, that's another, because, look, it's like, you're betting on that pilot to fly the plane. If you get too caught up investor boards, report a quarter, meeks and missteps, so I do think, like, you know where to have, like, a wartime CEO, like a Zoc or a Musk or, you know, a seller, I do think you need that. Because I think it's very easy to get caught up in gyration. boards and other investors. It's like an insurance against an activist short-term takeover. So set 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, so therefore they could plan for the long term. I think that's right. And I think, like, if you look like what sucks though with Meta, go back to like Metaverse, that disaster quarter at October, stocks, $85, whatever. it's like it would have been very easy to

like should we change course throughout and then what is he to bam bam bam change course in the rest history it's very easy to criticize zuck but he has been managing facebook truly and meta truly like a startup what does that mean 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 bat on a.m., if that winner is going to be kind of a power loss. So he's like investing $100 or $200 billion, almost on a venture-like bet, which is extremely bold, and I think rationally is the right thing to do, even though the first couple of times you'll be wrong and everybody will ridicule you,

and then on the third, you'll be a genius. Exactly, but then if you don't have that structure, it's hard to do that. If you could go back to 1996, when Dan Ives graduated Penn State, what would be one piece of timeless advice you would give yourself to either accelerate your career or avoid some of those stakes?

It were a lot of times earlier in my career where like, whether it was like, you know, not getting jobs or maybe even at jobs, like, you know, different failures, where it was very easy to like let that get you down, you get caught up in it. The thing that I would tell myself back then

would be embrace the failures, let them make you better and it's belief in yourself. Like it's just like all the success that you've had, right? Like, I'm sure,

like if you went back like 20 years and showed what you're doing there, you're like, whoa. But part of it is that like it's a learned behavior. And I think for me, it's like once the when the bell went off

or be like, look, stop like getting focused on like, you know, failures you've had and let them get you down. Because it's a true story. I'm at FBR, like, you know, and Freedom Billings, Ramsey

you know, that was a core part of my career. I remember I initiate on three companies. And I'm like so excited like you know it's like maybe it's like 2002 or something like that and three companies in the next three weeks they all go down 50% and they were all byriad and I remember I'm sitting there stuck in like Pittsburgh airport or Friday night and I'm thinking like what am I going to do for my next career you know because a disaster blow

My head of sales at the time John Billings calls me and he's like, you're, you're going to let this conviction just go, who cares at the stock? And they all pronounce negative. He's like, if you have conviction, that's what meets you. And he was like a Vincent-Bardi type speech. And that weekend, like I wrote this like crazy piece. Like, this is like temporary. These companies get bought, it's like, you know, you just confidence in the thesis. 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 fatbaggers. 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 yourself. It's not just the failures. It's having people around you. that interpret the failures in a certain way. The Zuckian example is actually 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. 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 who you're surrounded with is as important as your own mental state. And for me, just being on Wall Street 12 years, like there's like thousands and thousands of adults like they just like you know they disappear like you know like the wind or whatever right so it's like I've been lucky that like I like at FBR and then like a webber's like that I always like worked at places where like they understood who I was and they gave me that time for the calls to play out but maybe if I was like at different firms that didn't have they didn't understand like this focus. dresser and like you know they just looks at stocks differently or whatever then maybe like you know like it never would never would have worked right is there something in your childhood background that allows you to be kind of out of the herd and eccentric part of it is like my dad always said like people are always going to be better looking wealthy and smarter just accept it like there were certain

thing is growing up in like Long Island in the 80s, right? It was just like I think that was like a great place to grow up and just like living like in my household. It was one where it was like just be your own self. So I think that was like a big thing where like

it rooted back to like those days. What would you like the audience to know about you? Wedbush or anything else you like to share? Wedbush obviously you're doing great things from a tech perspective in terms of AI. You know, we have our I's ETF, which is we've been super excited about lunch and June.

Optionson's been really good because that gives investors the opportunity to basically better the AI. 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. You know, I think Sam's going to be a great part of everything he's done. I think there's going to be a single sign on for the AI future. I think authentication is going to be more and more important in terms of human proof. And look, for people to know me, I do a lot of different things. The clothing line may be a little different, but it's all centered around the AI revolution.

It's my passion from where that's happening. A mutual friend told me to ask you about Snowmilk and your clothing. Tell me about that. So Snowmilk, you know, an awesome designer in Williams, were in Brooklyn. They came to me and wanted to do a collab. So we did a day and Ives collab with day and eyes clothing.com And look, this is something where

I have like so many people and these are for men, women, for whoever. 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 and really, it's been, yeah, obviously,

a lot higher than I ever thought. Well, Dan, you're truly a one-of-one. I've never met anybody like you. And I'm so lucky to have spend time and looking forward to continuing this conversation. No, and I'm just happy that you invite me and all the success that you've had

and it's great to be able in here. Thank you, Dan. That's it for today's episode of How I 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 a valuable or leave a short review wherever you listen.

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