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Speaker 1: This is Masters in Business with Barry Ridholts on Bloomberg Radio.

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Speaker 1: This week on the podcast, I have an extra special guest,

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Speaker 1: and what can I tell you? Kevin Landis has been

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Speaker 1: investing in technology companies I don't know, thirty years, thirty years,

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Speaker 1: both public and private. He runs Firsthand Funds. They have

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Speaker 1: a number of different mutual funds that specialize in technology companies,

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Speaker 1: including one that is one of the rare publicly traded

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Speaker 1: venture capital funds. Imagine an individual VC that itself is

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Speaker 1: publicly traded. Kevin not only survived the dot com implosion

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Speaker 1: but thrived. The funds have put up really outstanding numbers

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Speaker 1: over the past fill in the blank, five, ten, fifteen years. Uh.

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Speaker 1: He really is super knowledgeable about startups and technology companies,

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Speaker 1: both both new and old. And one of the things

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Speaker 1: that makes them so interesting is they're located right out

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Speaker 1: there in the heart of Silicon Valley. It's it's hard

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Speaker 1: to imagine that before first Hand Funds opened up in

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Speaker 1: ninety four, there were no mutual funds located right there

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Speaker 1: in the midst of tech Land. Really quite interesting. He

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Speaker 1: grew up out there, he went to Berkeley, that's his backyard.

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Speaker 1: Really a fascinating guy in a fascinating conversation about all

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Speaker 1: things technology related. I think you'll find this to be

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Speaker 1: an interesting conversation. I really enjoyed it. So with no

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Speaker 1: further ado, my interview of first Hand Funds Kevin Landis

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Speaker 1: vias is Masters in Business with Barry Ridholtz on Boomberg Radio.

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Speaker 1: My special guest this week is Kevin Landis. He is

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Speaker 1: the c i O of first Hand Capital Management and

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Speaker 1: president and chairman of first Hand Funds. Founded in four

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Speaker 1: with five hundred million dollars in assets under management, Kevin

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Speaker 1: has specialized in technology. The first Hand Technology Opportunities Funds

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Speaker 1: has been up a hundred and two percent over the

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Speaker 1: past twelve months. Kevin Landis, Welcome to Bloomberg. Thank you

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Speaker 1: very much for having me. So you spent your life

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Speaker 1: in Silicon Valley and are known as one of the

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Speaker 1: longest tenured technology investors. How did you find your way

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Speaker 1: into tech investing? Well, there's a there's a long, boring

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Speaker 1: story of how I, you know, touched every stone along

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Speaker 1: the path, or there's more of the moment in time

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Speaker 1: terable answer, And I'll give you the moment in time answer,

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Speaker 1: and that is when I was in the fifth grade,

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Speaker 1: I told my parents that I wanted to be a

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Speaker 1: historian when I grew up. Now, my parents were both

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Speaker 1: children of the Great Suppression, and so they were immediately

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Speaker 1: horrified that I was um unwittingly, I was pointing to

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Speaker 1: a profession that wouldn't make me very financially successful or secure.

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Speaker 1: And they really tried hard to talk me out of it,

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Speaker 1: and finally one of them said, you know, Kevin, if

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Speaker 1: you can figure out the history that hasn't happened yet,

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Speaker 1: then you're gonna be all right son, and the other

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Speaker 1: quickly agreed. And I thought about that on and off

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Speaker 1: ever since, that if you configure out the history that

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Speaker 1: hasn't happened, that's a really good thing. And I think

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Speaker 1: that's that's a pretty good encapsulation of what I do.

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Speaker 1: That's the definition of investing history that has yet to happen.

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Speaker 1: So I'm kind of intrigued by your background. You have

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Speaker 1: a BS degree. It looks like this is a double

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Speaker 1: degree in electrical engineering and computer science from UC Berkeley

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Speaker 1: before you got your m b A. The first question

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Speaker 1: is why not go directly to a tech startup? Was

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Speaker 1: there any ever any lure to that? There was, and

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Speaker 1: I considered that, but this was one of those moments

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Speaker 1: where fate sort of intervened. And my dad's business was

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Speaker 1: as a manufacturer's rep in Silicon Valley, meaning he was

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Speaker 1: the customer facing office. He and his partner with the

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Speaker 1: customer facing office for tech companies based outside of Silicon

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Speaker 1: Valley dealing with Silicon Valley customers. And his partner had

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Speaker 1: a heart attack and had to go in for cornery

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Speaker 1: bypass surgery during my senior year in college, and my

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Speaker 1: dad needed needed me to come and join the business

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Speaker 1: because he would have looked like a one man band otherwise.

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Speaker 1: So I spent the first four years of my professional career,

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Speaker 1: instead of learning more things about engineering, learning a lot

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Speaker 1: about business and human nature and how to deal with people. So, Kevin,

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Speaker 1: your first experience in the field was not anything that

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Speaker 1: encouraged you to want to become a an insider at

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Speaker 1: some tech startup. Well, that's right, but it I mean

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Speaker 1: it taught me a great deal about human nature and

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Speaker 1: about business and business strategy, and like you know that,

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Speaker 1: it led to the second job that I got out

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Speaker 1: after business school as an analyst at a high technology

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Speaker 1: market research firm which also began teaching me a lot

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Speaker 1: of the things that that I had thought that I

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Speaker 1: had learned in school that actually weren't true. Give us

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Speaker 1: an example of things you learned in school that turned

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Speaker 1: out to be not true. Well. One of the one

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Speaker 1: of the explanations for um efficient markets is that there's

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Speaker 1: a lot of just incredibly brilliant, gifted people doing perfect research,

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Speaker 1: and that everything that can be known about a company

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Speaker 1: is already in the stock price. But when you're an

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Speaker 1: analyst at again, at a high tech market research firm,

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Speaker 1: and somebody from a big name financial firm calls and

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Speaker 1: starts asking you a bunch of very naive questions, it

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Speaker 1: doesn't take you long to realize that the emperor has

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Speaker 1: no clothes, and that maybe you need to modify your

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Speaker 1: thought to realize that the world is not this perfectly

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Speaker 1: ordered place where everything's all worked out. There's actually a

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Speaker 1: lot of confusion out there, uh, and that information is

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Speaker 1: not really evenly distributed. And all of the forces that

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Speaker 1: finance professors will teach you about why markets tend towards efficiency,

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Speaker 1: they're all valid arguments, but things are usually changing fast

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Speaker 1: enough and people are imperfect enough that markets don't really

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Speaker 1: always have it, have it just right. I couldn't agree

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Speaker 1: with you more. I find markets are kind of sort

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Speaker 1: of eventually efficient, but that's the still leaves a lot

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Speaker 1: of riddle room and and hence the opportunity for some

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Speaker 1: investors to outperform right. Right, So you're an analyst for

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Speaker 1: a number of years. What else did you do before

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Speaker 1: launching firsthand funds? In so after being you know, starting

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Speaker 1: out as an applications engineer customer facing with my dad's firm,

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Speaker 1: and then being a junior analyst in a market research firm,

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Speaker 1: then I spent a couple of years as a product

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Speaker 1: manager at a little chip company in Silicon Valley, And

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Speaker 1: again it was it was a great just an example

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Speaker 1: for myself, uh, to realize some of the nitty gritty

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Speaker 1: stuff that I thought I understood as an analyst, but

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Speaker 1: even though I was close to the industry, it wasn't

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Speaker 1: in the industry. And that again, I just kept learning

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Speaker 1: more stuff that I thought I knew that I hadn't known,

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Speaker 1: and uh and that was where uh frankly though, I

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Speaker 1: I kind of realized one day that I was making

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Speaker 1: more money trading stocks than I was on my day job.

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Speaker 1: And maybe that was the wrong day job to have

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Speaker 1: h Maybe my crew calling was just to be a

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Speaker 1: detect investor. So you launched first Hand Funds in ninety four.

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Speaker 1: What was the process like of getting that off the ground. Well,

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Speaker 1: that was really daunting because you know a lot of

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Speaker 1: times when your pick, when you're you're young, starting out,

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Speaker 1: you have this feeling like you know the existing businesses,

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Speaker 1: there's some sort of a club and you need to

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Speaker 1: get an invite uh to get in, or somebody needs

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Speaker 1: to give you a chance, and you have to make

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Speaker 1: that leap that says you kind of have to make

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Speaker 1: your own looks and no one's going to hand it

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Speaker 1: to you. And so my partner and I UH basically

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Speaker 1: figured out how to form a mutual funds. At that time,

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Speaker 1: I couldn't believe there was no high tech neutral fund

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Speaker 1: based in Silicon Valley, and I couldn't believe that that

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Speaker 1: I couldn't find any examples of tech funds that were

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Speaker 1: run by engineers, and it seemed like, oh my gosh,

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Speaker 1: this is If I don't do this, I'm going to

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Speaker 1: regret it for a really long time. So we need

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Speaker 1: to figure out how to do this, and then we

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Speaker 1: basically just if we pulled a couple of million dollars

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Speaker 1: out of our address books, UH and and got in

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Speaker 1: touch with people that we had gotten to know who

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Speaker 1: believed in us, and said, here's this vehicle we're investing in,

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Speaker 1: and let's let's see if we can make you some money.

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Speaker 1: And that was That was basically our little startup states there.

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Speaker 1: I think the joke was that um our management see

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Speaker 1: was enough that uh we could each buy a sandwich

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Speaker 1: each day, and that was it. So what are the

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Speaker 1: advantages of running a tech mutual funds from right in

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Speaker 1: the heart of Silicon Valley? You know, you can't bump

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Speaker 1: into people and chit chat without picking up UH industry

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Speaker 1: scuttle butt. I mean, I did the best. I had

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Speaker 1: an example just the other day. We my wife and

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Speaker 1: I were working with this uh a dog rescue organization,

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Speaker 1: and and we took a rescue dog for a weekend

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Speaker 1: while the fosters were out of town. And you know,

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Speaker 1: the guy came back to pick up the dog and

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Speaker 1: we were chit chatting, and all of a sudden, before

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Speaker 1: you know, we're talking about what's going on at vm

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Speaker 1: ware and what's the matter with this company? In that company?

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Speaker 1: Where do you think about the CEO leaving there to

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Speaker 1: go to Intel, and all of a sudden, I'm in

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Speaker 1: the middle of a research meeting and I'm just handed.

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Speaker 1: This guy is dog so uh and you know the

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Speaker 1: same thing, you bump into somebody you know they haven't

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Speaker 1: seen in a few months at the grocery store. You

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Speaker 1: you're always swimming in it, and uh so people aspect

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Speaker 1: what's your you know, what's your process for going out

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Speaker 1: and and uh, you know, getting ideas and getting skulled button.

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Speaker 1: That's like saying, what's your process for getting wet when

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Speaker 1: it's raining? Just go out sitting and shopping, right, yeah, right,

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Speaker 1: that's pretty funny. You're also the CEO of the first

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Speaker 1: Hand Technology Value Funds, which is really interesting. It's a

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Speaker 1: publicly traded venture capital funds, obviously focusing on emerging technologies.

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Speaker 1: You were pre i p O investors in Facebook, Twitter,

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Speaker 1: Solar City, Yelp, Roku, leading to the obvious question, why

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Speaker 1: a publicly traded venture capital firm? Well, that's so that

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Speaker 1: was a great That was a great moment in uh

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Speaker 1: in time here. I mean, you're probably well acquainted with

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Speaker 1: how easy it was for companies to go public in

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Speaker 1: the late ninety nineties, and then the and then the

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Speaker 1: just the dramatic backlash against that. The pendulum swung really

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Speaker 1: hard the other direction. And it wasn't just people being

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Speaker 1: skeptical of of startups uh and and of IPOs, but

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Speaker 1: it was also Starbanes Oxley and a bunch of other

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Speaker 1: really draconian regulations that just made it really, really difficult.

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Speaker 1: That the I p O went from being uh, sort

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Speaker 1: of this rite of passage that people were striving for

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Speaker 1: to being just awful ordeal that people were avoiding at

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Speaker 1: all costs. And that's we just realized as we got

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Speaker 1: into you know, uh, you know, oh seven oh eight

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Speaker 1: or nine, that companies, by the time they went public, uh,

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Speaker 1: they were so well known and so expensive that a

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Speaker 1: lot of those early returns had already been and you

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Speaker 1: just couldn't get them in the public market. So, you know,

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Speaker 1: I had by this time already made a career out

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Speaker 1: of mocking and ridiculing companies that failed to adapt um.

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Speaker 1: And you know, when we started out in the nineties,

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Speaker 1: I made fun of Deck in data general, you know,

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Speaker 1: and then uh, you know, by two thousands ten, we

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Speaker 1: were all making fun of Yahoo and UH and and

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Speaker 1: plenty of others believe me. Uh. And I kind of

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Speaker 1: looked at that, and I said, well, I'm running a

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Speaker 1: what's a mutual fund, but in the industry is referred

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Speaker 1: to as a forty Act fund because that's the the

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Speaker 1: Investment Company Act of nineteen forty. And so one day

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Speaker 1: I just sort of looked in the mirrors, said, right,

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Speaker 1: I'm here in Silicon Valley making fun of people who

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Speaker 1: failed to revolve, and I'm running a nineteen forty Acts fund.

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Speaker 1: Uh And and I thought about that a little bit, said,

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Speaker 1: you know, I think we need to adapt. So um,

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Speaker 1: we realized that there was an obscure branch of the

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Speaker 1: forty Act that talked about business development companies b dcs,

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Speaker 1: and that had kind of evolved into this odd kind

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Speaker 1: of a credit granting model. But we went back to

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Speaker 1: the original version of that, which is, no always a

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Speaker 1: business development company. We can make this adventure capital portfolio.

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Speaker 1: And that was right around the time that companies like

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Speaker 1: SHA's Posts and Second Market, We're making it easier to

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Speaker 1: get shares in startup companies. So that was, uh, that

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Speaker 1: just sort of fell into place, and and we looked

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Speaker 1: around and said, Okay, we're just gonna buy Uh, we're

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Speaker 1: gonna look at We're not changing how we look at companies.

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Speaker 1: We're still looking for the same things right place, right

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Speaker 1: time markets that we like, this looks like the winner.

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Speaker 1: And uh, that allowed us to really kind of go

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Speaker 1: back to doing what we've always done. I always pull people.

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Speaker 1: You know, you don't need to pay me to go

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Speaker 1: buy Microsoft for you. You know you kind of already

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Speaker 1: discovered that one. Uh just today, you know, nobody needs

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Speaker 1: to pay me to go buy Apple. Uh, you can

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Speaker 1: buy it on your own. So but what you're looking

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Speaker 1: for those companies you haven't heard of yet. And so

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Speaker 1: that's why we made that shift. So why do that

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Speaker 1: in a vehicle that's publicly traded instead of just setting

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Speaker 1: up a separate venture capital fund that doesn't have to

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Speaker 1: go through all of the usual public listening things. Well,

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Speaker 1: I think that we've always had a bit of a

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Speaker 1: egalitarian dance here where it should be available for everybody,

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Speaker 1: and it shouldn't just see this, uh you know kind

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Speaker 1: of I don't want to say elitist, but you shouldn't

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Speaker 1: just be an investment vehicle that's only available for the few.

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Speaker 1: Should be available for everybody. And so I like the

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Speaker 1: idea of publicly listed vehicles. I mean, that's kind of

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Speaker 1: the reason that we didn't start out with a hedge

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Speaker 1: fund to begin with. We wanted the doors open to everybody.

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Speaker 1: And of course, you know, we're unconventional enough that, um,

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Speaker 1: I don't think we do very well on the on

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Speaker 1: the standard public road show that you'd have to go

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Speaker 1: through to do institution fundraising, So we're not really adapted

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Speaker 1: at at that game. So last question on the public

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Speaker 1: private issue, what do you think of the line being

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Speaker 1: blurred between these pre public companies and publicly traded companies

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Speaker 1: and all of the SPACs that have come out as

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Speaker 1: a sort of back doorway two I p O companies

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Speaker 1: that don't go through that road show you were describing. Yeah,

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Speaker 1: I think it's first of all, I think it's a

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Speaker 1: good thing that people get in the habit of looking

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Speaker 1: at companies through the same lens. You know, a late

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Speaker 1: stage public company, you ought to look at it the

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Speaker 1: same way you look at a public company. Uh. And

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Speaker 1: and I think that would uh that that level of scrutiny.

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Speaker 1: That's a good thing. But I'm also I'm a really

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Speaker 1: big fan of competition. I think it really brings out

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Speaker 1: the best in US, so I view direct listings and

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Speaker 1: fact as basic the other ideas coming in uh and

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Speaker 1: competing with the UH sort of this historical model of

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Speaker 1: I pos the standard S one and you know, I

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Speaker 1: would I don't know if I would say the the

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Speaker 1: old style S one process is broken, but it's certainly

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Speaker 1: bend out of shape and and doesn't work that well

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Speaker 1: because it is it is just it is really onerous, uh,

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Speaker 1: and it is really tough on the company. Uh. So

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Speaker 1: you really need to be um big with a lot

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Speaker 1: of resources before you do it. And um, that's unfair

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Speaker 1: to a lot of people. Uh. You should be able

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Speaker 1: to go public a little bit earlier, a little bit sooner,

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Speaker 1: and frankly, you know today there's that spack process allows

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Speaker 1: you to talk a lot more about where you're going

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Speaker 1: instead of just being uh restricted and only being able

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Speaker 1: to stay where you've been and where you're going is

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Speaker 1: kind of what matters for stuff. Huh. That's interesting. I

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Speaker 1: know quite a few other people out in your part

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Speaker 1: of the woods. Venture capitalists like Bill Gurley have been

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Speaker 1: big champions of the direct listening exactly because the I

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Speaker 1: P O process has become increasingly difficult over the past

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Speaker 1: I don't know twenty thirty years is that is most

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Speaker 1: of this a post dot com implosion effect. Was it

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Speaker 1: easier in the nineties, Yes, absolutely absolutely going public Going

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Speaker 1: public in two thousand's was still really really easy. But

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Speaker 1: you know, if you look at the scandals, if you

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Speaker 1: look at all all of the busted I pos, the

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Speaker 1: whole pet dot com generation. Uh, and then you combine

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Speaker 1: that with some of the corporate scandals i e. World Calm, Tycho,

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Speaker 1: and Ron, those are kind of my big three. Um,

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Speaker 1: you could say frauds. We're not afraid of the word

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Speaker 1: fraud here, right, those the reaction to those kind of

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Speaker 1: got conslated. Uh So corporate fraud and busted I. He

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Speaker 1: has kind of got conflated. And and everyone said, despite

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Speaker 1: the fact that those management teams thought went to jail

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Speaker 1: under existing law, uh and Justice Serve people still said

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Speaker 1: there ought to be a law, and so they made

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Speaker 1: Sarbanes Oxley. Um. And I think that's the equivalent of

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Speaker 1: you know, going home and kicking the dog because you're

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Speaker 1: because your boss is mean to you. Um. So the

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Speaker 1: dog they kicked there was you know, the next twenty

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Speaker 1: years of tech companies wanted to go public. Um. But

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Speaker 1: The other thing I'll say there is that you know,

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Speaker 1: the direct listing and and the Spack merger are actually

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Speaker 1: kind of converging on a on a similar UH path. Today.

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Speaker 1: UH there's usually a big pipe of public investment and

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Speaker 1: a private or private investment in public equity, and that

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Speaker 1: pipe investment UH is highly supportive as back transactions, and

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Speaker 1: it's almost becoming a standard part of it, like a

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Speaker 1: required part of it. That's kind of like building your

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Speaker 1: book on the I P O figuring out who is

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Speaker 1: going to own that stock afterwards. And it has a

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Speaker 1: lot of the lower costs associated with a direct listing.

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Speaker 1: So people are talking about the blended cost with your

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Speaker 1: pipe plus back transaction. So the market is trying to

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Speaker 1: find the right the right mix of that makes a

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Speaker 1: lot of sense in tech stocks. Right through the nineties

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Speaker 1: really a unique period in history. I always kind of

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Speaker 1: chuckle when I see some of the young guns compare

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Speaker 1: the current market to the era or the dot com implosion,

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Speaker 1: although I'm chuckling a little less these days than I

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Speaker 1: was a year or two ago. What's your taken on

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Speaker 1: this comparison? How did the twenties match up against the

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Speaker 1: late nineties. Well, first, let's talk about how they're the same.

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Speaker 1: You know. I think the feeling that one gets here

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Speaker 1: uh is we're reminded that a little optimism is a

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Speaker 1: great thing u uh and and too much optimism can

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Speaker 1: you can drive right off the road, and that can

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Speaker 1: be a really bad thing. So uh, it's good to

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Speaker 1: have people looking for looking towards the future, looking to see, well,

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Speaker 1: what could we do? What could this company do? Um?

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Speaker 1: What how do we change things for the better? Uh?

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Speaker 1: And it should be about that. I think somewhere along

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Speaker 1: the line, though, there's a segment that simply is saying, uh,

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Speaker 1: how do we just get rich? And uh? There's nothing

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Speaker 1: wrong with the profit motives. It's great, I'm a capitalist,

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Speaker 1: but um, you know it should be what how are you?

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Speaker 1: How are you making the world better? And what are you?

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Speaker 1: What are you really uh driving towards I'm actually kind

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Speaker 1: of encouraged that a lot of the sort of the

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Speaker 1: the striving and and the looking forward what can we do?

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Speaker 1: Has to do with solving really big problems. How do

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Speaker 1: we go to space again? How do we? Uh? You

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Speaker 1: know Elon Musk wants to go to Mars. That's good

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Speaker 1: for him, you know, how do we send lots of

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Speaker 1: other people there, how do we bring people back and uh,

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Speaker 1: and how do we sell climate change? There's there's some

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Speaker 1: really big things there were there's are no quote a

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Speaker 1: few years ago somebody said we were promised flying cars

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Speaker 1: and instead we got a hundred and forty characters. Uh.

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Speaker 1: To me, that was that was that was this great

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Speaker 1: encapsulation again of just how you can kind of get

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Speaker 1: off track if you're when you've got a bunch of

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Speaker 1: smart people working on something. You know. Uh, it's sort

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Speaker 1: of if you're working on on making crops grow on

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Speaker 1: some stupid online game, Uh, that has limited value. On

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Speaker 1: the other hand, if you're actually working on making crops grow,

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Speaker 1: maybe that's better. So I like that, uh. And I

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Speaker 1: like that people are are looking at companies and not saying, well,

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Speaker 1: what did you do over the last five years, but

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Speaker 1: what are you gonna do in the next five years.

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Speaker 1: That's the right way to look at It's the better

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Speaker 1: way to look at it. Um. I just I guess

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Speaker 1: I would cautume folks. A lot of these companies aren't

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Speaker 1: gonna make it. A lot of these companies are gonna

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Speaker 1: fall short their lofty goals. That's probably okay. I mean,

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Speaker 1: it's it's okay that pets dot Com blew up because

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Speaker 1: now you've got Amazon. So for better or for worse,

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Speaker 1: you've got Amazon. Somebody made it. Somebody made it work. Uh,

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Speaker 1: and somebody was actually right in all all the hype

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Speaker 1: that they were generating. And I think it'll be this

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Speaker 1: way again. Uh. And in the meantime, markets will do

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Speaker 1: their damned this to give us lots of opportunities to

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Speaker 1: hurt ourselves financially. So two thoughts about that. One is

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Speaker 1: pets dot Com might have been a disaster, but today

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Speaker 1: we have Chewy, which is doing really well. I'm intrigued

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Speaker 1: by the concept of genomic agriculture as the better bet

385
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Speaker 1: than Farmville. Discuss some of the things you see that

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Speaker 1: are really more along the flying cars progression than the

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Speaker 1: hundred forty character progression right right, In other words, the

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Speaker 1: sort of the John F. Kennedy called action momentum. It's

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Speaker 1: focused on duty instead of call of duty. So yeah,

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Speaker 1: I guess, uh, you know, UM, electrification of transport is

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Speaker 1: a big deal. Yes, you're still using power, but I

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Speaker 1: think that the part that UM people are kind of

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Speaker 1: learning from direct experience on their on their personal vehicles

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Speaker 1: is that the great thing about having an electric drive

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Speaker 1: train is that you can harvest all the energy uh

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Speaker 1: that's built up in your vehicle speed. And I always

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Speaker 1: you know, tell people, go stand out in front of

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Speaker 1: your house on trash day and watch this big heavy

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Speaker 1: truck going from zero to ten miles and back down

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Speaker 1: to zero, all the way up and down your block,

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Speaker 1: and think about all that wasted energy. And if if

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Speaker 1: that truck had an electric drive train, uh they wouldn't

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Speaker 1: have to hit the brakes, they they just ease off

404
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Speaker 1: the accelerator pedal and you would regenerate and store all

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Speaker 1: that energy each time they they come to a stop.

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Speaker 1: Uh So, in other words, one of the biggest untapped

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Speaker 1: sources of energy out there is the momentum uh in

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Speaker 1: these vehicles. And uh so, the mania you electrify you

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Speaker 1: you start to harvest that. Basic ideas like that are

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Speaker 1: really a big thing. And um so, I think, yes,

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Speaker 1: taking a lot of the waste out of the system

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Speaker 1: and a lot of the wasted energy that's going to

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Speaker 1: get us a long ways towards climate change. And there

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Speaker 1: are gonna be a lot of other great examples. I

415
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Speaker 1: think we go we go to space again, We're gonna

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Speaker 1: find better ways, uh and better materials for insulation. You know,

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Speaker 1: heat shields are serious business in uh in space, and

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Speaker 1: you know, I think ten years from now we'll have

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Speaker 1: much better insulators. That means we're going to be much

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Speaker 1: more energy efficient and again that's going to help with

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Speaker 1: with global warming. So there there's a lot that we

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Speaker 1: can do. We have really, really some daunting challenges, but

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Speaker 1: we think it to work on them. Let me jump

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Speaker 1: in here and ask you this question because I started

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Speaker 1: out trying to do a twenty twenties comparisons in the

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Speaker 1: nine nineties, and what I'm reading between the lines is

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Speaker 1: the technology that you're looking at today seems to be

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Speaker 1: much bigger, broader impact, more significant both politically, socially and

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Speaker 1: economically than some of the let's call them more frivolous

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Speaker 1: dot com technologies that were Investor Darling's in the nineties.

431
00:25:34,119 --> 00:25:36,920
Speaker 1: Is that a fair compare and contrast. I think so.

432
00:25:37,400 --> 00:25:41,119
Speaker 1: You know, UM, if you look back at the one

433
00:25:41,119 --> 00:25:44,440
Speaker 1: of my favorite examples is uh, you know, sort of

434
00:25:44,520 --> 00:25:49,520
Speaker 1: creative destruction, was we disintermediated travel agents. If there were

435
00:25:49,520 --> 00:25:51,680
Speaker 1: a lot of people who worked in the as travel agents.

436
00:25:51,720 --> 00:25:54,080
Speaker 1: There are still a few, but they're really kind of

437
00:25:54,160 --> 00:25:57,920
Speaker 1: high end concierge folks. Everybody can go online and book

438
00:25:57,960 --> 00:26:01,040
Speaker 1: their own travel right. Uh. And in fact, you know,

439
00:26:01,080 --> 00:26:05,320
Speaker 1: when I fly on Southwest Airlines, I just intermediate Travelocity

440
00:26:05,359 --> 00:26:07,760
Speaker 1: and just go straight to state to the southwest side.

441
00:26:08,160 --> 00:26:13,520
Speaker 1: So um, that's a great efficiency. But yeah, and it's

442
00:26:13,560 --> 00:26:17,000
Speaker 1: not just the late ninety nineties with everyone wanted a website,

443
00:26:17,520 --> 00:26:19,840
Speaker 1: having a website for certain things, that was really really good.

444
00:26:20,320 --> 00:26:23,080
Speaker 1: But even since then, you know, look at what the

445
00:26:23,160 --> 00:26:28,080
Speaker 1: tech industry did with transportation. The right hailing services lift

446
00:26:28,119 --> 00:26:33,040
Speaker 1: in uber Um fix a really really daunting problem, which

447
00:26:33,160 --> 00:26:34,800
Speaker 1: was that there's nothing wrong with the cab. It's just

448
00:26:35,080 --> 00:26:38,600
Speaker 1: that it's not here. Uh, that the cab dispatch function

449
00:26:39,000 --> 00:26:41,440
Speaker 1: just never never evolved to wear it all to be.

450
00:26:41,600 --> 00:26:44,240
Speaker 1: So now that we have GPS in our phones, we

451
00:26:44,359 --> 00:26:46,600
Speaker 1: can we can we can hail a cab no matter

452
00:26:46,640 --> 00:26:49,399
Speaker 1: where we are. That's great, it solved some problems. But

453
00:26:50,160 --> 00:26:51,920
Speaker 1: you know, I I think a lot of us are

454
00:26:52,040 --> 00:26:54,879
Speaker 1: just uncomfortable with the idea that a lot of this

455
00:26:55,040 --> 00:26:59,320
Speaker 1: amazing technology is really useful in keeping current on our

456
00:26:59,359 --> 00:27:03,399
Speaker 1: Instagrams and posting selfies all over the place. That's not

457
00:27:03,520 --> 00:27:05,480
Speaker 1: a good look. I mean, even if you look good

458
00:27:05,520 --> 00:27:08,120
Speaker 1: on your Instagram, that's not a good look. Just being

459
00:27:08,160 --> 00:27:10,560
Speaker 1: all about that makes a lot of sense. So let

460
00:27:10,600 --> 00:27:15,080
Speaker 1: me finished by circling back. Do you think the current

461
00:27:15,280 --> 00:27:22,159
Speaker 1: environment is a late nineties bubble like market? And if not,

462
00:27:22,720 --> 00:27:26,560
Speaker 1: do you see pockets of bubbles in any areas in particular?

463
00:27:27,160 --> 00:27:29,119
Speaker 1: You know, somebody asked me the other day about do

464
00:27:29,240 --> 00:27:32,000
Speaker 1: you see bubbles? And I, I well said, of course

465
00:27:32,080 --> 00:27:36,119
Speaker 1: I do, And I realized, Uh, there's there's the Haley

466
00:27:36,200 --> 00:27:39,120
Speaker 1: Joe Osman character in the movie The sixth Ens where

467
00:27:39,160 --> 00:27:43,879
Speaker 1: he finally contesses to uh. He says, I see dead people, right,

468
00:27:43,920 --> 00:27:46,040
Speaker 1: and he's he's very scared as he says that I

469
00:27:46,400 --> 00:27:50,000
Speaker 1: kind of feel like I see bubbles everywhere I look,

470
00:27:50,320 --> 00:27:54,680
Speaker 1: and that that's what I'm realizing is that's just the

471
00:27:54,840 --> 00:27:58,400
Speaker 1: normal natural part of the environment. There are bubbles all

472
00:27:58,440 --> 00:28:04,560
Speaker 1: the time everywhere, and um, you're just uh, you're you're

473
00:28:04,600 --> 00:28:07,280
Speaker 1: not noticing them because when they pop there, each one

474
00:28:07,359 --> 00:28:10,600
Speaker 1: isn't necessarily big enough to take down the whole system. Um,

475
00:28:11,280 --> 00:28:16,280
Speaker 1: but you know, most companies fail, Most companies don't get there. Uh,

476
00:28:16,520 --> 00:28:20,400
Speaker 1: the actual survival rate is a lot lower, uh than

477
00:28:21,440 --> 00:28:23,520
Speaker 1: then you think it is when you do the real

478
00:28:23,560 --> 00:28:26,480
Speaker 1: accounting of it, and working with startups teaches you that

479
00:28:26,720 --> 00:28:31,280
Speaker 1: pretty quickly. That's okay. Lots of stocks are overpriced, That's okay,

480
00:28:32,040 --> 00:28:34,960
Speaker 1: because the benefit to getting a few companies to be

481
00:28:35,080 --> 00:28:39,280
Speaker 1: really successful in solving it, getting it right. Um, those

482
00:28:39,360 --> 00:28:43,280
Speaker 1: benefits are worth it. Quite fascinating. So let's talk a

483
00:28:43,360 --> 00:28:48,400
Speaker 1: little bit about We'll start with the technology funds. Doubling

484
00:28:48,720 --> 00:28:51,680
Speaker 1: your benchmark is quite an achievement. But what I'm more

485
00:28:51,800 --> 00:28:59,440
Speaker 1: fascinated by is you're up that much without owning Amazon, Alphabet,

486
00:29:00,040 --> 00:29:03,520
Speaker 1: Apple or Facebook. How did you? How do you accomplish that?

487
00:29:04,000 --> 00:29:06,440
Speaker 1: I thought you had to be in the giant big

488
00:29:06,560 --> 00:29:11,400
Speaker 1: cap tech stocks to put up triple digit returns like that. Well,

489
00:29:11,880 --> 00:29:16,040
Speaker 1: you know, it turns out that a twenty billion dollar

490
00:29:16,160 --> 00:29:19,360
Speaker 1: market cap you can go to forty billion just as

491
00:29:19,400 --> 00:29:21,920
Speaker 1: easily as a one trillion market caps can go to

492
00:29:22,000 --> 00:29:25,080
Speaker 1: two trillions. Uh, and in fact, in some cases even

493
00:29:25,080 --> 00:29:29,200
Speaker 1: a little bit easier. Um. You know, it is true

494
00:29:29,280 --> 00:29:33,320
Speaker 1: that there are moments, and you know, we saw these again,

495
00:29:33,560 --> 00:29:36,200
Speaker 1: you know, in the nineties and at other times when

496
00:29:36,320 --> 00:29:39,160
Speaker 1: people just want to pile into tech and they pile

497
00:29:39,240 --> 00:29:42,840
Speaker 1: into the names that they already know, and because they

498
00:29:42,880 --> 00:29:46,000
Speaker 1: get comfort in those names, they feel like they understand

499
00:29:46,040 --> 00:29:48,760
Speaker 1: them because they're familiar with them. Um, turns up, those

500
00:29:48,760 --> 00:29:51,960
Speaker 1: aren't actually the same thing. But okay, fine, there are

501
00:29:52,080 --> 00:29:56,080
Speaker 1: moments when when when people do that. But taking a

502
00:29:56,200 --> 00:30:01,400
Speaker 1: longer view, uh, there is a better moment when people

503
00:30:02,280 --> 00:30:06,560
Speaker 1: are craving growth and they're seeing that to go get

504
00:30:06,640 --> 00:30:10,440
Speaker 1: a company that has a robust growth for years to come. Um,

505
00:30:11,040 --> 00:30:13,320
Speaker 1: you can't take the people who are already worth a

506
00:30:13,400 --> 00:30:16,760
Speaker 1: trillion dollars or more and populate your portfolio just with

507
00:30:16,840 --> 00:30:20,880
Speaker 1: those names. Um, you need to find companies that you know.

508
00:30:21,080 --> 00:30:26,520
Speaker 1: Maybe they're maybe they're only only twenty billion in market cap,

509
00:30:26,640 --> 00:30:29,080
Speaker 1: but they're on their way to a hundred billion. That's

510
00:30:29,120 --> 00:30:31,800
Speaker 1: a better way to return. But you've got to be

511
00:30:31,880 --> 00:30:34,560
Speaker 1: comfortable that you've done your homework and it's not a

512
00:30:34,640 --> 00:30:37,280
Speaker 1: household name. And people might look at your funny if

513
00:30:37,320 --> 00:30:40,400
Speaker 1: you tell them that you own this crazy stock named

514
00:30:40,440 --> 00:30:45,320
Speaker 1: cheg or roku h. And that's okay. What about Tesla?

515
00:30:45,400 --> 00:30:48,040
Speaker 1: I know you owned it briefly, but it really was

516
00:30:48,160 --> 00:30:52,760
Speaker 1: never a significant part of this portfolio. Why not own

517
00:30:52,800 --> 00:30:56,000
Speaker 1: a Tesla? Is it you mentioned earlier? Hey, you don't

518
00:30:56,040 --> 00:30:58,560
Speaker 1: need me to tell you to go buy Microsoft. Is

519
00:30:58,720 --> 00:31:03,560
Speaker 1: Tesla in the in category? You know, test was a

520
00:31:03,640 --> 00:31:08,160
Speaker 1: great example of when you're right, even if you forget

521
00:31:08,240 --> 00:31:11,280
Speaker 1: why you're right. If if the stock is working, um,

522
00:31:12,280 --> 00:31:13,880
Speaker 1: maybe the best thing for you to do is just

523
00:31:14,080 --> 00:31:16,280
Speaker 1: turn off your computer and go to the beach uh

524
00:31:16,400 --> 00:31:19,800
Speaker 1: and let it be working for you. Uh. And and

525
00:31:20,040 --> 00:31:22,560
Speaker 1: so you know, shame on me for thinking that I was,

526
00:31:23,000 --> 00:31:25,520
Speaker 1: you know, overly clever when the market the market was

527
00:31:25,560 --> 00:31:28,200
Speaker 1: really really frothy, and so I thought I'd get cute

528
00:31:28,480 --> 00:31:31,880
Speaker 1: and on a really really down day, I would uh

529
00:31:32,680 --> 00:31:34,880
Speaker 1: buy some beaten up Tesla shares and then write some

530
00:31:34,960 --> 00:31:37,040
Speaker 1: covered calls against it. And the worst I could do is,

531
00:31:37,120 --> 00:31:40,239
Speaker 1: you know, makes x percent. And and of course then

532
00:31:40,320 --> 00:31:42,280
Speaker 1: it rallied right past that, and I got taken out

533
00:31:42,320 --> 00:31:46,440
Speaker 1: of the stuck. Um. And that was just me trying

534
00:31:46,440 --> 00:31:48,320
Speaker 1: to prove to myself once again that I'm not a

535
00:31:48,400 --> 00:31:51,920
Speaker 1: very good trader. Uh. And I should stick with investing. Um.

536
00:31:53,120 --> 00:31:59,120
Speaker 1: You know, when you see a company like this that

537
00:31:59,360 --> 00:32:03,280
Speaker 1: becomes just absolutely unsupportable on the valuation side, that the

538
00:32:03,360 --> 00:32:08,640
Speaker 1: numbers just don't seem to work. Um, you can you know,

539
00:32:08,800 --> 00:32:11,880
Speaker 1: you can pull your hair out. Uh. You can shake

540
00:32:11,960 --> 00:32:13,560
Speaker 1: your head, or you can just say, all right, well,

541
00:32:13,640 --> 00:32:16,800
Speaker 1: that's the power of optimists. That's the power of when

542
00:32:16,840 --> 00:32:19,280
Speaker 1: people really believe in something, they will really support the

543
00:32:19,320 --> 00:32:23,040
Speaker 1: hell out of it. And UM, find other examples of that,

544
00:32:24,080 --> 00:32:26,760
Speaker 1: uh that you could put in your portfolio that haven't

545
00:32:26,800 --> 00:32:30,720
Speaker 1: been discovered yet and that haven't gotten all of that

546
00:32:30,960 --> 00:32:34,080
Speaker 1: psychology behind them just yet. Huh. I love this quote

547
00:32:34,120 --> 00:32:37,400
Speaker 1: of yours quote. I like to remind people that the

548
00:32:37,560 --> 00:32:41,160
Speaker 1: time to invest in Netflix was when you never heard

549
00:32:41,200 --> 00:32:45,640
Speaker 1: of Netflix. Explain the thinking behind that. Well, you know,

550
00:32:45,760 --> 00:32:51,000
Speaker 1: the the argument is that pick any great um investment

551
00:32:51,080 --> 00:32:53,480
Speaker 1: in technology, and what you're going to see is that

552
00:32:54,240 --> 00:32:57,360
Speaker 1: those stocks performed best when people were just figuring it

553
00:32:57,440 --> 00:33:00,520
Speaker 1: out and adding it to their portfolio. There's a there

554
00:33:00,600 --> 00:33:03,280
Speaker 1: was a moment where somebody would stay in a ABC corporation,

555
00:33:03,400 --> 00:33:05,720
Speaker 1: never heard of him, and then I think I figured

556
00:33:05,760 --> 00:33:08,080
Speaker 1: them out. Oh yeah, I'm I'm in on that idea.

557
00:33:08,160 --> 00:33:11,120
Speaker 1: I like that, and I just if I look back

558
00:33:11,200 --> 00:33:15,240
Speaker 1: over the years, some of our best years performance wise

559
00:33:15,440 --> 00:33:17,840
Speaker 1: were when other people were following in love with this,

560
00:33:18,120 --> 00:33:20,040
Speaker 1: falling in love with the stocks that we already owned.

561
00:33:20,360 --> 00:33:23,600
Speaker 1: But we made those investments in years where we didn't

562
00:33:23,640 --> 00:33:27,680
Speaker 1: necessarily perform that well. So you know, you you you

563
00:33:27,800 --> 00:33:30,480
Speaker 1: make your best investments, you know, a year in year

564
00:33:30,560 --> 00:33:33,280
Speaker 1: two and maybe you get all the return out of

565
00:33:33,360 --> 00:33:35,440
Speaker 1: it in year four when people catch up to your

566
00:33:35,480 --> 00:33:38,360
Speaker 1: way of thinking and start to agree with you. Quite interesting.

567
00:33:38,920 --> 00:33:43,080
Speaker 1: You know, you launched the tech funds some sometime late

568
00:33:43,200 --> 00:33:47,960
Speaker 1: in that cycle, and the returns despite that timing, they've

569
00:33:48,000 --> 00:33:51,760
Speaker 1: been top decile for over ten years two percent a

570
00:33:51,880 --> 00:33:56,600
Speaker 1: year or for fifteen years a year And I'm looking

571
00:33:56,640 --> 00:34:00,239
Speaker 1: at your five year return is a year. What are

572
00:34:00,280 --> 00:34:03,960
Speaker 1: you doing that is garnering these sorts of returns? Is

573
00:34:04,040 --> 00:34:10,960
Speaker 1: it simply finding these currently unloved but future loved tech companies?

574
00:34:11,080 --> 00:34:14,360
Speaker 1: Is that the secret? Sauce? The shortest answer that I

575
00:34:14,440 --> 00:34:16,160
Speaker 1: can give you to that question is what are we

576
00:34:16,239 --> 00:34:20,120
Speaker 1: doing being right? Um? And that's going to happen a

577
00:34:20,160 --> 00:34:23,359
Speaker 1: fair amount of time, a fair amount of the time anyhow. Um.

578
00:34:24,360 --> 00:34:28,040
Speaker 1: You know, I go back to my early days as

579
00:34:28,120 --> 00:34:32,040
Speaker 1: an analyst at a market research firm, and um, when

580
00:34:32,160 --> 00:34:34,080
Speaker 1: when people said, well, how big is this market going

581
00:34:34,120 --> 00:34:35,960
Speaker 1: to be? And how do you just determine how big

582
00:34:36,040 --> 00:34:38,959
Speaker 1: this market is going to be? Nobody knows? Nobody really

583
00:34:39,040 --> 00:34:43,160
Speaker 1: knows how big upside is and the markets that you

584
00:34:43,280 --> 00:34:48,320
Speaker 1: can understand really really well are already establishment. Do you

585
00:34:48,360 --> 00:34:50,520
Speaker 1: want to know how big is the market for automobile tires,

586
00:34:50,760 --> 00:34:53,120
Speaker 1: There's somebody who's got all that data. You want to

587
00:34:53,160 --> 00:34:55,640
Speaker 1: know how big is the market for dental floss and toothpaste.

588
00:34:55,840 --> 00:34:58,160
Speaker 1: Somebody's got all that data. And you know what, that's

589
00:34:58,160 --> 00:35:00,640
Speaker 1: not where you want to invest. It's really boring. Uh.

590
00:35:00,920 --> 00:35:04,960
Speaker 1: If you want to know the market for a new

591
00:35:05,080 --> 00:35:10,560
Speaker 1: generation of small satellite, nobody really knows, uh, And that's

592
00:35:10,600 --> 00:35:14,000
Speaker 1: what makes it so interesting. And so having worked on

593
00:35:14,080 --> 00:35:16,719
Speaker 1: the job many many years ago as a young kid

594
00:35:16,800 --> 00:35:19,239
Speaker 1: and realizing that I was supposed to come up with

595
00:35:19,280 --> 00:35:24,680
Speaker 1: a number, I kind of understand now that, Uh, it's

596
00:35:24,760 --> 00:35:27,399
Speaker 1: it's not all about buttoning up your spreadsheets. Sometimes it's

597
00:35:27,400 --> 00:35:30,160
Speaker 1: about leaning back in your chair and staring up the

598
00:35:30,200 --> 00:35:33,080
Speaker 1: ceiling and asking yourself, just how big could this market become?

599
00:35:33,520 --> 00:35:39,560
Speaker 1: How big is this opportunity? And um, that's that's the

600
00:35:39,680 --> 00:35:42,200
Speaker 1: key thing there. Where when you see a company that's

601
00:35:42,360 --> 00:35:44,239
Speaker 1: in the right place at the right time, they're on

602
00:35:44,320 --> 00:35:47,600
Speaker 1: the right track, then the question is just how much

603
00:35:47,680 --> 00:35:51,440
Speaker 1: bigger could this market become? How much? How high is up.

604
00:35:52,200 --> 00:35:55,920
Speaker 1: And Um, if you've got a good feel for answering

605
00:35:56,000 --> 00:36:00,480
Speaker 1: that question, Um, then you're gonna be in some really

606
00:36:00,520 --> 00:36:02,440
Speaker 1: promising stocks and a few of them are gonna work

607
00:36:02,480 --> 00:36:05,680
Speaker 1: well for you. And that's that's what's gonna make that difference.

608
00:36:07,280 --> 00:36:11,760
Speaker 1: So so last of these questions. You're a board member

609
00:36:11,920 --> 00:36:15,440
Speaker 1: at several Silicon Valley startups. I have to think that

610
00:36:15,560 --> 00:36:18,759
Speaker 1: helps you keep a close eye on trends that are

611
00:36:18,800 --> 00:36:24,040
Speaker 1: developing in the private sector. Does this translate directly to

612
00:36:24,640 --> 00:36:28,719
Speaker 1: ownership in the public sector, Yes, absolutely, because in the

613
00:36:28,800 --> 00:36:32,880
Speaker 1: commercial world, Uh, it's not that you know, public companies

614
00:36:32,920 --> 00:36:36,200
Speaker 1: only transact with public companies and private companies only transact

615
00:36:36,239 --> 00:36:40,680
Speaker 1: with private companies. Right, it's all mixed together. And one

616
00:36:40,680 --> 00:36:42,239
Speaker 1: of the things, of course that being on a on

617
00:36:42,360 --> 00:36:45,960
Speaker 1: a startup board teaches you is that, well, it gives

618
00:36:46,000 --> 00:36:47,960
Speaker 1: you sort of a peek behind the curtain and you

619
00:36:48,040 --> 00:36:52,800
Speaker 1: see how much chaos is actually president most companies, and

620
00:36:53,200 --> 00:36:56,080
Speaker 1: how you know, there how many fires they have to

621
00:36:56,120 --> 00:37:00,319
Speaker 1: put out every week while still focusing on the big pictures. Um.

622
00:37:01,520 --> 00:37:03,239
Speaker 1: And so you'll you'll you know, you'll learn a few

623
00:37:03,360 --> 00:37:06,960
Speaker 1: a few things that are really important. Uh and uh,

624
00:37:07,040 --> 00:37:09,640
Speaker 1: and then along the way. Yes, you will get valuable

625
00:37:09,680 --> 00:37:12,640
Speaker 1: scuttle buds. Um. You know, one of my one of

626
00:37:12,719 --> 00:37:17,399
Speaker 1: my favorite is, um, my favorite observations is you ask

627
00:37:17,440 --> 00:37:20,360
Speaker 1: people their opinions on things, You'll get much more valuable

628
00:37:20,400 --> 00:37:22,439
Speaker 1: information than if you're just ask them for a data point.

629
00:37:22,880 --> 00:37:25,959
Speaker 1: You know, everyone thinks that insider inside is all about

630
00:37:26,000 --> 00:37:28,200
Speaker 1: who's going to make their quarter, who's gonna miss their quarters?

631
00:37:28,640 --> 00:37:32,400
Speaker 1: I really couldn't care less. Uh, that's that's that's the

632
00:37:32,480 --> 00:37:34,799
Speaker 1: wrong game to play, and get in trouble for playing

633
00:37:34,840 --> 00:37:37,120
Speaker 1: that game. Anyway. What you really should be doing when

634
00:37:37,120 --> 00:37:39,200
Speaker 1: you're talking to somebody is to ask yourself, this person

635
00:37:39,320 --> 00:37:41,600
Speaker 1: is an expert, is something they know a lot of

636
00:37:41,680 --> 00:37:45,120
Speaker 1: things that I don't know? Um, what can I learned

637
00:37:45,120 --> 00:37:48,520
Speaker 1: from this person? And usually it's not about them divolving

638
00:37:49,200 --> 00:37:54,600
Speaker 1: some facts and figures, it's about them sincerely, honestly sharing

639
00:37:54,640 --> 00:37:57,800
Speaker 1: their opinions. Those guys over there are a bunch of bosos.

640
00:37:58,200 --> 00:38:00,520
Speaker 1: These guys over here are the right guys. By the way,

641
00:38:00,560 --> 00:38:02,640
Speaker 1: the real talent is leaving company X and going to

642
00:38:02,719 --> 00:38:06,080
Speaker 1: company Y. That's the kind of stuff I like to get.

643
00:38:06,680 --> 00:38:10,800
Speaker 1: And so yes, working close superstartup companies gets you that

644
00:38:11,960 --> 00:38:16,000
Speaker 1: quite fascinating. Let's talk specifics about some of your favorite

645
00:38:16,040 --> 00:38:21,480
Speaker 1: investments today. What sectors and types of businesses have you

646
00:38:21,600 --> 00:38:26,080
Speaker 1: most excited. Well, you know, there's always a collection of

647
00:38:26,280 --> 00:38:29,640
Speaker 1: revolutions that are sort of underway within tech, and you know,

648
00:38:29,760 --> 00:38:32,480
Speaker 1: you hear about what's getting disrupted today and what's in

649
00:38:32,880 --> 00:38:38,040
Speaker 1: mid disruption and what's in early disruption. Um So, despite

650
00:38:38,080 --> 00:38:42,799
Speaker 1: the fact that Netflix has been at it now for many,

651
00:38:42,880 --> 00:38:46,320
Speaker 1: many years, um we're still kind of in maybe the

652
00:38:46,400 --> 00:38:49,600
Speaker 1: middle innings of streaming. And the fact that cable companies

653
00:38:49,640 --> 00:38:52,720
Speaker 1: are still in business and still pushing the old business

654
00:38:52,800 --> 00:38:56,000
Speaker 1: model is evidence that there's more to come. You know,

655
00:38:56,160 --> 00:38:59,920
Speaker 1: the the old thing is history doesn't repeat. But Ryan,

656
00:39:01,160 --> 00:39:05,080
Speaker 1: what I would say is that today Roku rhymes with Netflix.

657
00:39:05,600 --> 00:39:08,520
Speaker 1: Roku was that company that when I talked about it

658
00:39:08,800 --> 00:39:11,280
Speaker 1: three or four years ago, I got a blank stare.

659
00:39:11,760 --> 00:39:14,600
Speaker 1: And today more and more people recognize the name and

660
00:39:14,680 --> 00:39:17,200
Speaker 1: kind of understand what they do, and they fit that

661
00:39:17,320 --> 00:39:20,279
Speaker 1: pattern of the company that fights with no one and

662
00:39:20,360 --> 00:39:24,200
Speaker 1: wants to be everybody's partner. Uh And it gets themselves

663
00:39:24,239 --> 00:39:27,040
Speaker 1: in the middle of that trend. It kind of find

664
00:39:27,320 --> 00:39:33,359
Speaker 1: there their niche within that ecosystem. And uh So I'm

665
00:39:33,480 --> 00:39:37,680
Speaker 1: excited about the move too, sort of the on demand streaming,

666
00:39:37,920 --> 00:39:42,800
Speaker 1: and I'm excited about Roku's position on what's still a

667
00:39:42,920 --> 00:39:46,960
Speaker 1: really really big wave. So that's one example. Another great example,

668
00:39:47,000 --> 00:39:49,480
Speaker 1: I think is when we look at e v S

669
00:39:49,760 --> 00:39:52,719
Speaker 1: electric vehicles. One of the things that you have to

670
00:39:52,800 --> 00:39:55,360
Speaker 1: dig a little bit to get this appreciation is the voltage.

671
00:39:55,400 --> 00:40:00,640
Speaker 1: And the current requirements for electric vehicles are different, and

672
00:40:01,120 --> 00:40:05,800
Speaker 1: that requires UH different different materials technology, and so a

673
00:40:05,920 --> 00:40:10,560
Speaker 1: lot of the more efficient UH electronics they're not built

674
00:40:10,600 --> 00:40:14,000
Speaker 1: on silicon, but they're built on silicon carbides. And it

675
00:40:14,160 --> 00:40:17,120
Speaker 1: just happens that there's this company that's been struggling since

676
00:40:17,400 --> 00:40:21,000
Speaker 1: I kid you not the late nine It's called Cree

677
00:40:21,640 --> 00:40:26,279
Speaker 1: and based in North Carolina, and they have been struggling

678
00:40:26,360 --> 00:40:30,520
Speaker 1: their way down this really difficult learning curve of how

679
00:40:30,560 --> 00:40:34,400
Speaker 1: do you work with this exotic material, and they have

680
00:40:35,160 --> 00:40:38,560
Speaker 1: finally found themselves in the exact right place at the

681
00:40:38,600 --> 00:40:43,400
Speaker 1: exact right time. Because power electronics made with silicon carbides

682
00:40:43,640 --> 00:40:46,920
Speaker 1: perform much better and give you better electric vehicles. So

683
00:40:47,080 --> 00:40:49,279
Speaker 1: you don't need to decide if you want to buy

684
00:40:49,440 --> 00:40:52,440
Speaker 1: Tesla or you want to buy Lucid Motors, where you

685
00:40:52,480 --> 00:40:54,840
Speaker 1: want to buy Neo, you want to get exposure to

686
00:40:54,880 --> 00:40:58,040
Speaker 1: this trend, uh, you can buy Cree and we have,

687
00:40:58,600 --> 00:41:02,480
Speaker 1: and that's one of those stocks has performed really well

688
00:41:02,560 --> 00:41:05,200
Speaker 1: but still has a fairly modest market cap and still

689
00:41:05,239 --> 00:41:08,239
Speaker 1: has plenty of headroom. And we're really excited about that.

690
00:41:08,800 --> 00:41:11,880
Speaker 1: I recall Cree is one of the big innovators in

691
00:41:12,320 --> 00:41:14,840
Speaker 1: LED lights. I don't know twenty years ago, is this

692
00:41:14,960 --> 00:41:19,719
Speaker 1: the same company came up with the chip or or

693
00:41:19,880 --> 00:41:23,000
Speaker 1: something like that. Absolutely right, So this falls into the

694
00:41:23,080 --> 00:41:26,640
Speaker 1: category of a solution in search of a problem. What

695
00:41:26,840 --> 00:41:29,880
Speaker 1: Cree developed was the ability to work with silicon carbides,

696
00:41:30,239 --> 00:41:32,799
Speaker 1: and they struggled for years to try to figure out

697
00:41:33,040 --> 00:41:37,240
Speaker 1: what's the end market. We're silicon carbide really really taste,

698
00:41:37,880 --> 00:41:40,800
Speaker 1: and they thought it was l e eds for a while.

699
00:41:41,520 --> 00:41:44,320
Speaker 1: But then what they found was that you didn't have

700
00:41:44,440 --> 00:41:48,840
Speaker 1: to make the perfect LED using silicon carbides. UH, you

701
00:41:48,920 --> 00:41:54,360
Speaker 1: could make a cheaper LED using other technologies and other materials,

702
00:41:54,920 --> 00:41:57,600
Speaker 1: and you could do it in China and so never

703
00:41:57,719 --> 00:42:01,120
Speaker 1: mind all that. And that was a really daunting challenge

704
00:42:01,160 --> 00:42:05,120
Speaker 1: for them to get through that, but they did quite interesting.

705
00:42:05,760 --> 00:42:09,880
Speaker 1: So are all these changes that are coming slow iterative

706
00:42:10,040 --> 00:42:14,759
Speaker 1: changes or are some of these more revolutionary than evolution.

707
00:42:15,560 --> 00:42:19,480
Speaker 1: I think that it's somebody once called a successful startup company,

708
00:42:20,320 --> 00:42:24,840
Speaker 1: an overnight success, ten years in the making. Uh, this, this,

709
00:42:25,200 --> 00:42:27,320
Speaker 1: this often. And if you think about how long we

710
00:42:27,440 --> 00:42:30,360
Speaker 1: had cell phones before one day you look around and

711
00:42:30,480 --> 00:42:34,080
Speaker 1: noticed that everybody had a cell phone. Um, you know,

712
00:42:34,280 --> 00:42:37,759
Speaker 1: for me, that was uh gosh. You know, in the

713
00:42:37,840 --> 00:42:40,800
Speaker 1: early nineteen eighties when I was a college student, nobody

714
00:42:40,880 --> 00:42:42,960
Speaker 1: had a cell phone. By the end of the eighties,

715
00:42:43,200 --> 00:42:45,160
Speaker 1: anybody in sales had a cell phone, but that was

716
00:42:45,200 --> 00:42:47,440
Speaker 1: about it. Um. And by the end of the nineties,

717
00:42:47,480 --> 00:42:49,440
Speaker 1: it seemed like everybody had a cell phone, but all

718
00:42:49,480 --> 00:42:51,320
Speaker 1: they were doing on their cell phones was talking. So

719
00:42:51,520 --> 00:42:54,279
Speaker 1: you can see that the big, big, important changes they

720
00:42:54,360 --> 00:42:56,880
Speaker 1: take years to unfold, but when you look back at

721
00:42:56,960 --> 00:43:00,919
Speaker 1: it or you can't believe just just different things were,

722
00:43:01,760 --> 00:43:05,400
Speaker 1: you know, from one decade to the next. So obviously

723
00:43:05,719 --> 00:43:09,920
Speaker 1: evs are a longstanding trend that has nothing to do

724
00:43:10,040 --> 00:43:13,680
Speaker 1: with the pandemic. But you've mentioned some things that seem

725
00:43:13,719 --> 00:43:17,120
Speaker 1: to be a little pandemic related, obviously streaming being one

726
00:43:17,200 --> 00:43:21,360
Speaker 1: of them. What about things like distance learning and remote work?

727
00:43:21,960 --> 00:43:25,840
Speaker 1: Are these pandemic trends or do they have legs? Are

728
00:43:25,920 --> 00:43:29,960
Speaker 1: they going to continue once things start getting back to normal.

729
00:43:30,760 --> 00:43:33,760
Speaker 1: I think those those examples are both trends that were

730
00:43:33,880 --> 00:43:39,400
Speaker 1: happening already, UM, but the pandemic accelerated them. One of

731
00:43:39,440 --> 00:43:42,759
Speaker 1: the things that's happened here is that our daily lives

732
00:43:42,800 --> 00:43:47,520
Speaker 1: have been so disrupted that almost anything is on the table.

733
00:43:47,880 --> 00:43:50,320
Speaker 1: We're willing to rethink things, and we're willing to go

734
00:43:50,800 --> 00:43:55,400
Speaker 1: try new things. And so that's UM. Overcoming the inertia.

735
00:43:55,440 --> 00:43:58,759
Speaker 1: I mean, inertia is really that's really tough. You've got

736
00:43:58,880 --> 00:44:02,920
Speaker 1: something that's not broke, Why fix it? Uh? And and uh,

737
00:44:03,200 --> 00:44:04,879
Speaker 1: you know that's why you pay your cable bill every

738
00:44:04,920 --> 00:44:07,640
Speaker 1: month and figure the next month, I'll work the other

739
00:44:07,719 --> 00:44:13,360
Speaker 1: thing out. Um. And you know that's really true with education. UM. Unfortunately,

740
00:44:14,320 --> 00:44:19,000
Speaker 1: the state of education, it's such that you've got people

741
00:44:19,080 --> 00:44:22,560
Speaker 1: who have, through no faults of their own, are our

742
00:44:22,680 --> 00:44:28,719
Speaker 1: great advocates of supporting education and find themselves being defenders

743
00:44:28,760 --> 00:44:33,279
Speaker 1: of the status quo. And so I guess one of

744
00:44:33,320 --> 00:44:35,960
Speaker 1: the one great commentary I heard about a company one time,

745
00:44:36,000 --> 00:44:38,320
Speaker 1: as they said, the guy said, this was a great company,

746
00:44:38,400 --> 00:44:41,680
Speaker 1: they just forgot to evolve. UM. I would look at

747
00:44:41,719 --> 00:44:44,160
Speaker 1: our educational system and say they kind of look like

748
00:44:44,280 --> 00:44:50,600
Speaker 1: they forgot to evolve, and this pandemic now is maybe

749
00:44:51,239 --> 00:44:53,520
Speaker 1: maybe going to give them the necessary kick in the

750
00:44:53,560 --> 00:44:56,680
Speaker 1: pants to hurry up and evolve and and figure out

751
00:44:57,680 --> 00:44:59,799
Speaker 1: how to make it better. I mean, my old alma mater,

752
00:45:00,080 --> 00:45:04,319
Speaker 1: UC Berkeley, they've got students living on campus or living

753
00:45:04,440 --> 00:45:08,880
Speaker 1: off campus close by, but doing distance learning from their apartment, um,

754
00:45:09,280 --> 00:45:11,160
Speaker 1: rather than moving back to their parents house. But that's

755
00:45:11,160 --> 00:45:14,680
Speaker 1: a little odd. It's clearly a workaround, uh, And I

756
00:45:15,200 --> 00:45:18,040
Speaker 1: think that's causing a lot of people to ask some

757
00:45:18,920 --> 00:45:22,480
Speaker 1: very good questions and figure out what's the better way

758
00:45:22,520 --> 00:45:24,640
Speaker 1: to do this and how are we are we just

759
00:45:24,719 --> 00:45:26,920
Speaker 1: getting stuck in our old ways of doing things or

760
00:45:27,400 --> 00:45:32,360
Speaker 1: or not. I think with college there's the whole social,

761
00:45:33,040 --> 00:45:37,880
Speaker 1: physical interaction aspect of it that gets a little lost,

762
00:45:38,680 --> 00:45:43,399
Speaker 1: um with distance learning. But they're obviously room for both, right,

763
00:45:43,520 --> 00:45:46,839
Speaker 1: They're not mutually exclusive. Oh, absolutely right. You could argue

764
00:45:46,880 --> 00:45:49,600
Speaker 1: that the university experience a lot of it is about

765
00:45:49,760 --> 00:45:51,480
Speaker 1: learning in the classroom, but a lot of it is

766
00:45:51,520 --> 00:45:54,479
Speaker 1: about getting on with life and you know, leaving the nest.

767
00:45:55,000 --> 00:45:59,440
Speaker 1: You can also argue that for elementary school, a lot

768
00:45:59,520 --> 00:46:01,400
Speaker 1: of it is about learning, but a lot of it

769
00:46:01,560 --> 00:46:05,200
Speaker 1: is simply daycare so parents can go to work. Um,

770
00:46:05,840 --> 00:46:09,320
Speaker 1: you could argue that in a lot of zip codes

771
00:46:09,840 --> 00:46:14,400
Speaker 1: that it's actually about making sure kids are not food

772
00:46:14,520 --> 00:46:18,799
Speaker 1: insecure and and it's actually a great way to make

773
00:46:18,840 --> 00:46:22,960
Speaker 1: sure that you're you're investing in more ways than one

774
00:46:23,360 --> 00:46:27,040
Speaker 1: in the next generation. So one of the things that's

775
00:46:27,080 --> 00:46:29,680
Speaker 1: happening is is people are stepping back and looking at

776
00:46:30,640 --> 00:46:32,960
Speaker 1: as the educational system and saying, well, there's more than

777
00:46:33,040 --> 00:46:36,120
Speaker 1: one function going on here. Which of these functions can

778
00:46:36,160 --> 00:46:39,560
Speaker 1: be done better and differently? And are these naturally bundled together?

779
00:46:40,120 --> 00:46:45,160
Speaker 1: Is a right to bundle daycare and food with learning?

780
00:46:45,200 --> 00:46:49,520
Speaker 1: Your ABC probably seems to work. Uh. Is it natural

781
00:46:49,760 --> 00:46:54,200
Speaker 1: to bundle together learning differential equations and organic chemistry with

782
00:46:55,360 --> 00:46:57,040
Speaker 1: learning how to go out and do your own laundry

783
00:46:57,040 --> 00:47:00,279
Speaker 1: and shop for your own groceries? Maybe? But you know

784
00:47:00,480 --> 00:47:03,120
Speaker 1: just which part of this picture needs to be disrupted

785
00:47:03,160 --> 00:47:06,640
Speaker 1: and rethought and which part of this picture is working

786
00:47:07,360 --> 00:47:10,680
Speaker 1: just fine and ought to be preserved. That's a great

787
00:47:10,880 --> 00:47:13,600
Speaker 1: exercise for all of us to go through. So let's

788
00:47:13,640 --> 00:47:18,240
Speaker 1: stay with that idea around remote work. Obviously they're slack

789
00:47:18,400 --> 00:47:22,760
Speaker 1: and zoom and all the other technologies. The enterprise companies

790
00:47:22,840 --> 00:47:25,919
Speaker 1: like Google and Microsoft and even Apple for that matter,

791
00:47:26,600 --> 00:47:30,680
Speaker 1: have been big winners in this space. But I personally

792
00:47:30,760 --> 00:47:35,320
Speaker 1: find the groundhog day effect of seeming every day is

793
00:47:35,400 --> 00:47:39,080
Speaker 1: the same. You're not what you describe as the person

794
00:47:39,160 --> 00:47:42,480
Speaker 1: who you're dog sitting for or going to the supermarket.

795
00:47:42,920 --> 00:47:45,319
Speaker 1: You very much miss that. And I think it's as

796
00:47:45,400 --> 00:47:48,400
Speaker 1: true for work as it is for school or your

797
00:47:48,480 --> 00:47:52,839
Speaker 1: local community. What do you think stays from the work

798
00:47:52,920 --> 00:47:56,960
Speaker 1: from home phenomena once we get past the pandemic? What

799
00:47:57,280 --> 00:48:00,279
Speaker 1: changes are taking place and and how will the world

800
00:48:00,360 --> 00:48:03,920
Speaker 1: look after things get back to quote unquote normal if

801
00:48:04,040 --> 00:48:06,799
Speaker 1: if we ever do, we're certainly not going to return

802
00:48:06,880 --> 00:48:10,400
Speaker 1: to pre pandemic world. But what does normal look like

803
00:48:10,520 --> 00:48:13,520
Speaker 1: in the future. Well, one thing that I think changes

804
00:48:13,600 --> 00:48:15,520
Speaker 1: that the you know I look for I'm looking for

805
00:48:15,640 --> 00:48:17,880
Speaker 1: silver linings, right, So one thing that I think the changes,

806
00:48:17,960 --> 00:48:21,800
Speaker 1: it's a really good thing, is that people are focused

807
00:48:21,800 --> 00:48:25,000
Speaker 1: a lot more now on deliverable. So when we're just

808
00:48:25,080 --> 00:48:26,480
Speaker 1: going to have a zoom meeting and we're going to

809
00:48:26,560 --> 00:48:28,239
Speaker 1: talk about X, Y and Z, we're gonna get to

810
00:48:28,280 --> 00:48:29,879
Speaker 1: the end of that zoom meeting and we're just gonna say,

811
00:48:29,920 --> 00:48:32,320
Speaker 1: all right, well, we're gonna come back around, you know,

812
00:48:32,680 --> 00:48:35,120
Speaker 1: in three days and meet again. And this is exactly

813
00:48:35,200 --> 00:48:39,279
Speaker 1: what people need to have achieved or brought back to

814
00:48:39,360 --> 00:48:43,360
Speaker 1: the table here. So I guess the the co worker

815
00:48:43,400 --> 00:48:45,480
Speaker 1: who just sort of hangs around and ship chats with

816
00:48:45,600 --> 00:48:48,040
Speaker 1: everybody and tries to look busy and tries to be

817
00:48:48,160 --> 00:48:51,839
Speaker 1: in meetings and all that doesn't actually contribute that much.

818
00:48:51,920 --> 00:48:54,319
Speaker 1: But it's just trying to make sure he gets his job.

819
00:48:55,120 --> 00:48:57,520
Speaker 1: That guy's in trouble because in the age of zoom

820
00:48:57,600 --> 00:49:01,360
Speaker 1: meetings and all of this, and and working from a distance,

821
00:49:02,600 --> 00:49:04,759
Speaker 1: you can't hide the fact that you're not delivering the

822
00:49:04,840 --> 00:49:08,680
Speaker 1: good um or it's much harder to hide that. So

823
00:49:09,239 --> 00:49:12,239
Speaker 1: I like that, you know. I guess this kind came

824
00:49:12,520 --> 00:49:15,600
Speaker 1: partly from a conversation I had with a woman who

825
00:49:15,760 --> 00:49:18,760
Speaker 1: was they went from being a consultant to an employee,

826
00:49:18,800 --> 00:49:21,200
Speaker 1: and she said, you know, actually consultants do really well

827
00:49:21,239 --> 00:49:23,759
Speaker 1: when they get hired because every time that they have

828
00:49:23,840 --> 00:49:26,440
Speaker 1: a meeting or a project, they're looking for what's the

829
00:49:26,480 --> 00:49:28,440
Speaker 1: deliverable at the end that they always come through with

830
00:49:28,600 --> 00:49:31,040
Speaker 1: something and they forced people to define what it is

831
00:49:31,120 --> 00:49:32,640
Speaker 1: they need and what it is they want that. That's

832
00:49:32,640 --> 00:49:35,000
Speaker 1: not the only thing. Um, there's a lot of other

833
00:49:35,080 --> 00:49:39,080
Speaker 1: stuff that maybe the softer sides are more creative side. Um,

834
00:49:39,640 --> 00:49:42,440
Speaker 1: we're just hanging around other people and thinking about things

835
00:49:42,520 --> 00:49:46,879
Speaker 1: and bouncing ideas off each other. That's really great. UM.

836
00:49:47,760 --> 00:49:50,440
Speaker 1: I guess that maybe the journalistic equivalent of that is

837
00:49:50,600 --> 00:49:53,719
Speaker 1: where the where the good story ideas come from. Um

838
00:49:54,719 --> 00:49:57,759
Speaker 1: they get you know, ideas get tossed around and people

839
00:49:57,800 --> 00:50:01,640
Speaker 1: think about things and magic some time somehow happened. But

840
00:50:01,880 --> 00:50:05,480
Speaker 1: that that takes place in any workspace where um, the

841
00:50:05,760 --> 00:50:09,640
Speaker 1: people make each other more creative by this sort of

842
00:50:09,719 --> 00:50:12,880
Speaker 1: relaxed interaction. That's the thing that I think we're going

843
00:50:12,920 --> 00:50:15,680
Speaker 1: to find has been missing. And all this work at

844
00:50:15,719 --> 00:50:18,560
Speaker 1: home stuff, so we need to get we need to

845
00:50:18,600 --> 00:50:21,480
Speaker 1: get the right mix of that. So I think there'll

846
00:50:21,480 --> 00:50:23,759
Speaker 1: be a lot of offices that'll tell you that you

847
00:50:23,840 --> 00:50:25,320
Speaker 1: only need to come in a couple of days a

848
00:50:25,400 --> 00:50:27,080
Speaker 1: week and you can work from home some other days.

849
00:50:27,560 --> 00:50:31,360
Speaker 1: Makes a lot of sense. Last pandemic related question, So

850
00:50:32,000 --> 00:50:37,120
Speaker 1: casinos are closed, sports scambling seems to have all but disappeared,

851
00:50:37,360 --> 00:50:41,440
Speaker 1: and a lot of people are replacing it with trading.

852
00:50:41,640 --> 00:50:44,080
Speaker 1: What do you think of the whole robin hood TikTok

853
00:50:44,280 --> 00:50:49,640
Speaker 1: reddit community actively day trading for lack of a better word,

854
00:50:49,760 --> 00:50:53,120
Speaker 1: Is this anything significant within the market or is this

855
00:50:53,280 --> 00:50:58,600
Speaker 1: just a small niche of visible but not especially market

856
00:50:58,680 --> 00:51:03,360
Speaker 1: moving participants. Well, you know, first, I'll just comment that

857
00:51:03,719 --> 00:51:07,360
Speaker 1: as as an active investor. As active investors, we can't

858
00:51:07,480 --> 00:51:11,319
Speaker 1: complain that the market gets gets it wrong from time

859
00:51:11,400 --> 00:51:15,000
Speaker 1: to time. I mean, if markets were always right, then

860
00:51:15,760 --> 00:51:17,839
Speaker 1: we would have to go find a way to make

861
00:51:17,840 --> 00:51:23,400
Speaker 1: an honest living somehow. Uh So the a's for the

862
00:51:23,560 --> 00:51:26,439
Speaker 1: you know, the robin hood crowds. I love those guys

863
00:51:26,520 --> 00:51:29,680
Speaker 1: when they're buying stocks that I already owned. Um and

864
00:51:30,120 --> 00:51:31,719
Speaker 1: uh but you know, I don't get to have it

865
00:51:31,800 --> 00:51:35,680
Speaker 1: both ways. Uh. If people get over excited about something,

866
00:51:37,200 --> 00:51:40,440
Speaker 1: there could be a harm and you know the and

867
00:51:40,880 --> 00:51:43,880
Speaker 1: you could or you could pay in all sorts of scenarios. Right,

868
00:51:43,960 --> 00:51:47,239
Speaker 1: what if you what if the robin hood crowd did

869
00:51:48,000 --> 00:51:51,640
Speaker 1: your favorite stock right through the steeling up to a

870
00:51:51,719 --> 00:51:54,160
Speaker 1: point where you just absolutely can't justify it, and so

871
00:51:54,280 --> 00:51:57,520
Speaker 1: you do the rational thing and sell it, and then

872
00:51:57,560 --> 00:52:00,879
Speaker 1: it keeps going up, so everyone thinks about like, oh,

873
00:52:01,000 --> 00:52:02,880
Speaker 1: this is gonna crash, It's gonna be terrible and all that.

874
00:52:03,400 --> 00:52:06,040
Speaker 1: I look at this and think how many people got

875
00:52:06,120 --> 00:52:09,800
Speaker 1: forced out of test Lack because that crowd pushed that

876
00:52:09,920 --> 00:52:12,759
Speaker 1: stock up so fast, and and they'd have been better

877
00:52:12,840 --> 00:52:15,920
Speaker 1: off if the stock didn't look so explosive to the upside,

878
00:52:16,480 --> 00:52:18,160
Speaker 1: and they just made a lot, a lot of money

879
00:52:18,200 --> 00:52:22,200
Speaker 1: over time. You know. I I think we all look

880
00:52:22,280 --> 00:52:25,320
Speaker 1: back with certain things with regret. And I mean I

881
00:52:25,680 --> 00:52:28,480
Speaker 1: look back at Amazon. You know, that's been out of

882
00:52:28,520 --> 00:52:31,040
Speaker 1: my portfolio for the last ten years. You know, I

883
00:52:32,040 --> 00:52:36,279
Speaker 1: would be even even happier today if if if I

884
00:52:36,360 --> 00:52:38,920
Speaker 1: hadn't let that that stock just run right out up

885
00:52:39,000 --> 00:52:46,440
Speaker 1: from out of my grasp. Um. So yeah, one one

886
00:52:46,520 --> 00:52:49,880
Speaker 1: scenario here is that that crowd um takes some of

887
00:52:49,960 --> 00:52:52,279
Speaker 1: my best stocks out of my hands by making them

888
00:52:52,320 --> 00:52:57,920
Speaker 1: too expensive. Interesting, let's talk about those downturns and those recessions.

889
00:52:58,239 --> 00:53:01,600
Speaker 1: You've said those are usually seen as bad times for

890
00:53:01,719 --> 00:53:07,080
Speaker 1: growth stocks, but they also reveal the best opportunities for

891
00:53:07,239 --> 00:53:14,759
Speaker 1: what stocks are doing well and what's just been coasting explained. Well, look, um,

892
00:53:15,560 --> 00:53:20,920
Speaker 1: somebody said once that um, you know, calling something a

893
00:53:21,000 --> 00:53:24,160
Speaker 1: commodity that is not a dirty word. You know, certain

894
00:53:24,200 --> 00:53:27,560
Speaker 1: commodities you know, Uh, there were times when you really

895
00:53:27,600 --> 00:53:30,359
Speaker 1: wanted to own oil. There were times when you really

896
00:53:30,400 --> 00:53:34,920
Speaker 1: wanted to own cotton futures. Um. If you think of

897
00:53:35,040 --> 00:53:40,120
Speaker 1: growth as a commodity, then growth is most valuable. Like

898
00:53:40,239 --> 00:53:44,040
Speaker 1: any commodity, it's most valuable when it's scarce. Well, in

899
00:53:44,120 --> 00:53:48,160
Speaker 1: the midst of a recession, growth is really scarce. And

900
00:53:48,280 --> 00:53:52,520
Speaker 1: a lot of the mainstream companies, uh that were you know,

901
00:53:52,640 --> 00:53:55,839
Speaker 1: where a good year was when they grew uh four,

902
00:53:56,400 --> 00:53:58,359
Speaker 1: and a bad year was when they you know, didn't

903
00:53:58,360 --> 00:54:01,320
Speaker 1: grow at all. Those face might be shrinking, and a

904
00:54:01,400 --> 00:54:04,040
Speaker 1: lot of the other companies that you know, uh thought

905
00:54:04,120 --> 00:54:06,040
Speaker 1: that they could grow ten percent every year are struggling

906
00:54:06,080 --> 00:54:10,560
Speaker 1: to grow one or two percent um. That's that's when

907
00:54:10,600 --> 00:54:13,480
Speaker 1: growth really is the most valuable. And if you can

908
00:54:13,600 --> 00:54:18,200
Speaker 1: identify growth and see it where other people don't get appreciated,

909
00:54:19,239 --> 00:54:21,680
Speaker 1: you're going to be making some of the best investments

910
00:54:21,719 --> 00:54:26,759
Speaker 1: of your career right during those times. And so yeah,

911
00:54:27,080 --> 00:54:29,600
Speaker 1: you look at O eight No. Nine, that was probably

912
00:54:29,600 --> 00:54:31,759
Speaker 1: a really good time to get into Netflix, probably a

913
00:54:31,840 --> 00:54:35,840
Speaker 1: really good time to get into Apple. Yeah, in in

914
00:54:35,960 --> 00:54:40,000
Speaker 1: boom times, everybody looks like a growth story, and that's

915
00:54:40,239 --> 00:54:43,839
Speaker 1: that's wrong. And uh yeah, during a bust. It looks

916
00:54:43,880 --> 00:54:47,120
Speaker 1: like no one's growing. That's also wrong. Huh. Quite interesting.

917
00:54:47,719 --> 00:54:50,239
Speaker 1: So I only have you for a finite amount of time.

918
00:54:50,680 --> 00:54:53,719
Speaker 1: Let me jump to some of my favorite questions that

919
00:54:53,840 --> 00:54:57,000
Speaker 1: I ask all of my guests. And since we've been

920
00:54:57,040 --> 00:55:00,880
Speaker 1: talking about Netflix, let's discuss what have you been streaming

921
00:55:00,880 --> 00:55:06,400
Speaker 1: these days? Give us your favorite lockdown entertainment? You know, Um,

922
00:55:07,440 --> 00:55:09,400
Speaker 1: I have to say that, like a lot of people

923
00:55:09,440 --> 00:55:17,120
Speaker 1: who like complex business and drama and true crime stories, um,

924
00:55:18,120 --> 00:55:21,120
Speaker 1: that Breaking Bad put us all on a really dark path.

925
00:55:22,040 --> 00:55:25,360
Speaker 1: And for me, that path went from Breaking Bad to

926
00:55:25,600 --> 00:55:34,839
Speaker 1: Narcos to Ozark too uh zero zero zero two gomra uh.

927
00:55:34,960 --> 00:55:37,719
Speaker 1: And so currently I'm screaming Goma, which has got me

928
00:55:37,840 --> 00:55:40,759
Speaker 1: thinking of that I can almost speak Italians and and

929
00:55:41,840 --> 00:55:45,120
Speaker 1: it's just very dark. And so I need to break

930
00:55:45,160 --> 00:55:48,880
Speaker 1: out of that rent because because you know, um, that's

931
00:55:49,000 --> 00:55:50,920
Speaker 1: that's that's not a good place to be. So the

932
00:55:51,000 --> 00:55:52,600
Speaker 1: other great thing that I saw the other day was

933
00:55:52,800 --> 00:55:57,360
Speaker 1: a biography on Ulysses S. Grant, and it was a

934
00:55:57,440 --> 00:55:59,759
Speaker 1: wonderful look. When most people look at that periody and

935
00:55:59,800 --> 00:56:02,640
Speaker 1: you have history, they focus on Lincoln Um. Grant was

936
00:56:02,719 --> 00:56:06,919
Speaker 1: a wonderful strategist, uh and um. It was a great

937
00:56:06,960 --> 00:56:10,680
Speaker 1: example two of of an individual who wasn't really a

938
00:56:10,760 --> 00:56:14,880
Speaker 1: big success in life until he found his role. And

939
00:56:15,000 --> 00:56:17,960
Speaker 1: when he found his role, he became a U a

940
00:56:18,040 --> 00:56:21,600
Speaker 1: big success and that was that was wonderful. Man. I'm

941
00:56:21,680 --> 00:56:26,200
Speaker 1: a big fan of the Planet Money uh podcast over

942
00:56:26,560 --> 00:56:31,040
Speaker 1: over on NPR UM. But of course I did listen

943
00:56:31,160 --> 00:56:34,879
Speaker 1: to Odd Lots the other day on their their story

944
00:56:34,920 --> 00:56:36,759
Speaker 1: on t SMC and I thought that was well done.

945
00:56:37,840 --> 00:56:43,160
Speaker 1: And yeah and and I and I love there's one

946
00:56:43,200 --> 00:56:47,160
Speaker 1: called Cautionary Tales that talks about disasters and how they happened. Um.

947
00:56:47,360 --> 00:56:49,239
Speaker 1: And then finally, hardcore history is a kind of a

948
00:56:49,360 --> 00:56:53,479
Speaker 1: niche uh sort of a military history uh um game,

949
00:56:53,560 --> 00:56:57,160
Speaker 1: which is it's great too, you know, to to get

950
00:56:57,280 --> 00:57:02,239
Speaker 1: your strategic gears turning quite interesting. Tell us about your

951
00:57:02,239 --> 00:57:06,520
Speaker 1: mentors who helped to shape your career. Well, I you know,

952
00:57:06,640 --> 00:57:09,640
Speaker 1: I didn't. I didn't work at uh you know, at

953
00:57:10,080 --> 00:57:13,120
Speaker 1: the elbow of Da Vinci or Nicolangelo or anything like that.

954
00:57:13,239 --> 00:57:18,080
Speaker 1: But I did read a lot um from uh specifically

955
00:57:18,120 --> 00:57:21,720
Speaker 1: in investing from Peter Lynch and Warren Buffett. Um. You

956
00:57:21,800 --> 00:57:23,720
Speaker 1: know Peter Lynch when he wrote one up on Wall

957
00:57:23,760 --> 00:57:28,960
Speaker 1: Street kind of gave people permission to uh realize that

958
00:57:29,080 --> 00:57:31,240
Speaker 1: they have an edge. You're an expert at something, you

959
00:57:31,320 --> 00:57:33,680
Speaker 1: just need to figure out what it is. Uh. And

960
00:57:34,040 --> 00:57:37,440
Speaker 1: so as an engineer who was looking at tex stocks

961
00:57:37,480 --> 00:57:40,919
Speaker 1: and wondering about the efficient market hypothesis, that was a great,

962
00:57:42,080 --> 00:57:44,800
Speaker 1: a great way of a framing things. That was very helpful.

963
00:57:45,440 --> 00:57:51,280
Speaker 1: And I I just loved the home fund wisdom of Buffett.

964
00:57:51,520 --> 00:57:55,000
Speaker 1: He's great at actually being a bit of a disruptive

965
00:57:55,120 --> 00:58:00,440
Speaker 1: radical and disguising it as being a very conventional kind

966
00:58:00,440 --> 00:58:04,200
Speaker 1: of homespun of uncular guy. Um. But both of those

967
00:58:04,240 --> 00:58:08,560
Speaker 1: people gave really well reasoned explanations for why it was

968
00:58:08,720 --> 00:58:12,680
Speaker 1: that the Emperor has no clothes. And that's that's one

969
00:58:12,720 --> 00:58:14,560
Speaker 1: of those great lessons in life that they don't tell

970
00:58:14,600 --> 00:58:16,160
Speaker 1: you when you're a kid growing up, is that the

971
00:58:16,200 --> 00:58:17,880
Speaker 1: adults are kind of making a lot of this up

972
00:58:17,920 --> 00:58:20,680
Speaker 1: as they go. Um. And it's not quite such an

973
00:58:20,760 --> 00:58:23,600
Speaker 1: orderly place as you're led to belief, to say the

974
00:58:23,720 --> 00:58:27,520
Speaker 1: very least. Let's talk about everybody's favorite question. Tell us

975
00:58:27,840 --> 00:58:30,040
Speaker 1: some of your favorite books and what you might be

976
00:58:30,160 --> 00:58:34,200
Speaker 1: reading right now. A couple of books that are really

977
00:58:34,440 --> 00:58:38,160
Speaker 1: enjoyed early on had to do with individuals overcoming adversity.

978
00:58:38,320 --> 00:58:42,120
Speaker 1: So the Count of Monte Cristo and h The Old

979
00:58:42,200 --> 00:58:44,480
Speaker 1: Man in the Sea. The Old Man in the Sea

980
00:58:44,520 --> 00:58:47,480
Speaker 1: is still kind of my favorite, and uh made me

981
00:58:47,640 --> 00:58:50,200
Speaker 1: enough of a Hemingway fan that I later on I

982
00:58:50,320 --> 00:58:52,680
Speaker 1: read several of the other books and the one that

983
00:58:52,720 --> 00:58:55,160
Speaker 1: stuck with me was for Whom the Bell Tolls that

984
00:58:55,400 --> 00:58:58,960
Speaker 1: in the Spanish Civil War and had a great lesson

985
00:58:59,040 --> 00:59:00,960
Speaker 1: that there are times when you need to be decisive

986
00:59:01,040 --> 00:59:03,200
Speaker 1: and you're going to regret doing the thing you know

987
00:59:03,360 --> 00:59:06,600
Speaker 1: you need to do. I like reading strategy books, so

988
00:59:07,040 --> 00:59:10,560
Speaker 1: you know, Michael Porter's Competitive Strategy is a classic. You

989
00:59:10,640 --> 00:59:13,800
Speaker 1: know it. It provides a great framework for a lot

990
00:59:13,840 --> 00:59:17,000
Speaker 1: of your competitive thinking. But if you've already read that,

991
00:59:17,080 --> 00:59:21,200
Speaker 1: I recommend The Art of War, kind of a classic. Um.

992
00:59:22,040 --> 00:59:27,840
Speaker 1: And on the economic side, I think a great book

993
00:59:27,880 --> 00:59:32,160
Speaker 1: for me was UH, Free to Choose by Milton Freedman,

994
00:59:32,760 --> 00:59:37,160
Speaker 1: But I guess close runner up behind that is pre Economics,

995
00:59:37,360 --> 00:59:41,480
Speaker 1: which is just a wonderful way of of just being

996
00:59:41,640 --> 00:59:44,480
Speaker 1: being creative and how you frame the question is really

997
00:59:44,520 --> 00:59:46,200
Speaker 1: really important and I got a lot out of that. Now,

998
00:59:46,280 --> 00:59:48,800
Speaker 1: the next book, I have to tell you one of

999
00:59:48,840 --> 00:59:53,640
Speaker 1: those silver lining from the pandemic was, um, getting in

1000
00:59:53,640 --> 00:59:55,720
Speaker 1: a healthy habit of going for long walks and listening

1001
00:59:55,760 --> 00:59:58,240
Speaker 1: to books on tape. Um. So I've listened to The

1002
00:59:58,280 --> 01:00:02,440
Speaker 1: Great Gas Being Now finally, and UH enjoyed that a lot.

1003
01:00:03,440 --> 01:00:06,720
Speaker 1: But when I was a senior year in college, I

1004
01:00:06,800 --> 01:00:08,920
Speaker 1: got into an argument with a guy who was a

1005
01:00:09,000 --> 01:00:12,960
Speaker 1: sociology major and and you know, sciences versus humanities, and

1006
01:00:13,520 --> 01:00:18,040
Speaker 1: I made the case that, um, you know, really you

1007
01:00:18,120 --> 01:00:20,040
Speaker 1: couldn't if you're gonna learn the sciences you have to

1008
01:00:20,080 --> 01:00:23,080
Speaker 1: do while you're at university. And I think the way

1009
01:00:23,120 --> 01:00:24,720
Speaker 1: I won the won the argument, at least in my

1010
01:00:24,800 --> 01:00:28,240
Speaker 1: version I won the argument, uh, was that I said,

1011
01:00:28,720 --> 01:00:31,720
Speaker 1: I can always go read Moby Dick. Good luck five

1012
01:00:31,800 --> 01:00:35,440
Speaker 1: years from now getting your head around quantum physics. Uh.

1013
01:00:35,800 --> 01:00:37,840
Speaker 1: And so you know, I never went back and read

1014
01:00:37,920 --> 01:00:39,960
Speaker 1: Moby Dick. And the next book I'm reading will be

1015
01:00:40,080 --> 01:00:42,560
Speaker 1: a you know, going out for a walk, a long

1016
01:00:42,640 --> 01:00:46,720
Speaker 1: walk for a a podcast, and and Moby Dick is

1017
01:00:46,800 --> 01:00:51,000
Speaker 1: up next. That's interesting, to be fair to the sociologist.

1018
01:00:51,600 --> 01:00:56,960
Speaker 1: I recently took a course on astrophysics online. It's not

1019
01:00:57,200 --> 01:01:01,720
Speaker 1: the same as having those exam coming up each quarter,

1020
01:01:02,480 --> 01:01:07,160
Speaker 1: but you do get broad exposure to an area you

1021
01:01:07,840 --> 01:01:11,360
Speaker 1: you might be interested in. Not the same as the class,

1022
01:01:11,480 --> 01:01:16,840
Speaker 1: but but certainly uh intriguing. And I had the same

1023
01:01:16,920 --> 01:01:19,800
Speaker 1: experience with that you did with Old Man in the Sea.

1024
01:01:20,240 --> 01:01:22,880
Speaker 1: I started reading it on a on a flight to Florida,

1025
01:01:23,320 --> 01:01:25,040
Speaker 1: and by the time we landed, I was done and

1026
01:01:25,080 --> 01:01:28,680
Speaker 1: it was just an absolutely you know, you're it's one

1027
01:01:28,680 --> 01:01:31,280
Speaker 1: of those books you're sad when it's over and you

1028
01:01:31,400 --> 01:01:35,800
Speaker 1: immediately want to reread. Yeah, yeah, and you really want

1029
01:01:35,840 --> 01:01:38,720
Speaker 1: to meet the great DiMaggio that was that was the great.

1030
01:01:38,800 --> 01:01:41,200
Speaker 1: But the hero of the story has his own hero

1031
01:01:41,400 --> 01:01:44,160
Speaker 1: and this great DiMaggio that he hears about on radio.

1032
01:01:44,560 --> 01:01:47,280
Speaker 1: What sort of advice would you give to a recent

1033
01:01:47,480 --> 01:01:52,280
Speaker 1: college grad who was interested in a career in either

1034
01:01:52,400 --> 01:01:56,280
Speaker 1: technology or investment management. Well, I think I would give

1035
01:01:56,320 --> 01:01:59,560
Speaker 1: the same basic advice no matter what your career interest is.

1036
01:02:00,040 --> 01:02:02,280
Speaker 1: And that is so much of life, whether it's you

1037
01:02:02,360 --> 01:02:05,760
Speaker 1: know it is, you know your career and your in

1038
01:02:06,040 --> 01:02:08,600
Speaker 1: what business you're going to be in, it's not really

1039
01:02:08,640 --> 01:02:14,800
Speaker 1: about money. Money is a construct that any economics professor

1040
01:02:14,880 --> 01:02:18,080
Speaker 1: will tell you. It's only there to facilitate ever more

1041
01:02:18,200 --> 01:02:22,920
Speaker 1: complex bartering and you're well, you're always bartering what it

1042
01:02:23,080 --> 01:02:25,240
Speaker 1: is you can do for somebody and what it is

1043
01:02:25,320 --> 01:02:27,360
Speaker 1: they can do for you, and you're making all of

1044
01:02:27,400 --> 01:02:32,120
Speaker 1: these trades. Uh. And so before you start sitting down

1045
01:02:32,160 --> 01:02:36,000
Speaker 1: and figuring out how to barter, you need to understand

1046
01:02:36,040 --> 01:02:37,880
Speaker 1: what it is that you have to offer other people.

1047
01:02:38,400 --> 01:02:40,840
Speaker 1: You need to get to know yourself and figure out

1048
01:02:40,960 --> 01:02:44,680
Speaker 1: what it is that you can offer others. And if

1049
01:02:44,760 --> 01:02:47,080
Speaker 1: it's not enough, then you need to cultivate that. You

1050
01:02:47,200 --> 01:02:52,560
Speaker 1: need to work on what can you become? Um And

1051
01:02:53,480 --> 01:02:56,720
Speaker 1: once you figured that out, then you can, uh, then

1052
01:02:56,760 --> 01:02:58,160
Speaker 1: you can make your way in life. So I think

1053
01:02:58,160 --> 01:03:03,160
Speaker 1: a lot, a lot more effectively UM and I UM,

1054
01:03:03,680 --> 01:03:06,520
Speaker 1: But it's not about finding a job that you can

1055
01:03:06,600 --> 01:03:09,600
Speaker 1: get that pays. Well, that's only one component, right. I mean,

1056
01:03:10,520 --> 01:03:13,720
Speaker 1: the perfect job is one where or the perfect career

1057
01:03:13,840 --> 01:03:17,760
Speaker 1: is one where you you enjoy it um and uh

1058
01:03:18,320 --> 01:03:20,720
Speaker 1: So even when it's not paid, you still enjoy going

1059
01:03:20,760 --> 01:03:24,120
Speaker 1: to work, you're good at it, and other people valuate

1060
01:03:24,440 --> 01:03:26,160
Speaker 1: if you can if you can get those three things

1061
01:03:26,240 --> 01:03:29,320
Speaker 1: to line up for you, um, it's going to click.

1062
01:03:29,440 --> 01:03:32,360
Speaker 1: But you can't do that unless you really know yourself.

1063
01:03:32,800 --> 01:03:35,640
Speaker 1: I think that's pretty good advice, and our final question,

1064
01:03:36,280 --> 01:03:38,480
Speaker 1: what do you know about the world of investing in

1065
01:03:38,640 --> 01:03:42,400
Speaker 1: technology today that you wish you knew twenty five or

1066
01:03:42,480 --> 01:03:47,560
Speaker 1: so years ago when you were first getting started. Uh.

1067
01:03:48,320 --> 01:03:50,360
Speaker 1: I guess what I would say is that the world

1068
01:03:50,520 --> 01:03:54,280
Speaker 1: is a much bigger mess than you realize. Uh. It

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01:03:54,400 --> 01:03:57,240
Speaker 1: really is chaos out there, and there's a lot of

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01:03:57,360 --> 01:04:01,680
Speaker 1: things that are far from perfect. And that's actually a

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01:04:01,760 --> 01:04:04,000
Speaker 1: good thing because it means that you can go out

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Speaker 1: there and you can find ways to improve it. Uh.

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Speaker 1: And I think that the example that everyone can relate

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01:04:10,080 --> 01:04:14,040
Speaker 1: is that um generations of people complained that they couldn't

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Speaker 1: get a cab and then somebody created a right hailing

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01:04:16,680 --> 01:04:22,160
Speaker 1: service where you could and got rich doing it. So, yes,

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01:04:22,560 --> 01:04:24,840
Speaker 1: it is. It is a big mess out there, and

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01:04:25,200 --> 01:04:27,680
Speaker 1: we can't complain about it. Our job is to say

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01:04:27,720 --> 01:04:30,560
Speaker 1: to ourselves, with the conventional wisdom is usually wrong about something,

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01:04:30,840 --> 01:04:33,640
Speaker 1: maybe more than one thing. Our job is to figure

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01:04:33,640 --> 01:04:37,360
Speaker 1: out what they're prevailing with and is wrong about and

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01:04:37,440 --> 01:04:40,760
Speaker 1: then act on that. Quite intriguing Kevin, thank you for

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01:04:40,840 --> 01:04:43,560
Speaker 1: being so generous with your time. We have been speaking

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01:04:43,880 --> 01:04:47,320
Speaker 1: with Kevin Landis of Firsthand Funds. He is the c

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01:04:47,520 --> 01:04:50,600
Speaker 1: I O. Of Firsthand Capital Management and President and chairman

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01:04:50,640 --> 01:04:54,880
Speaker 1: of Firsthand Funds. If you enjoyed this conversation, well be

1087
01:04:55,000 --> 01:04:57,840
Speaker 1: sure and check out any of the other four hundred

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01:04:57,960 --> 01:05:02,160
Speaker 1: or so we've done over the past seven almost eight years. God,

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01:05:02,280 --> 01:05:07,080
Speaker 1: that's pretty insane. Um. You can find that at iTunes, Spotify,

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01:05:07,400 --> 01:05:11,240
Speaker 1: wherever you find your favorite podcasts. We love your comments,

1091
01:05:11,320 --> 01:05:15,760
Speaker 1: feedback in suggestions right to us at m IB podcast

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01:05:15,840 --> 01:05:18,200
Speaker 1: at Bloomberg dot net. Be sure and give us a

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01:05:18,240 --> 01:05:21,440
Speaker 1: review on Apple iTunes, and you can sign up from

1094
01:05:21,480 --> 01:05:24,880
Speaker 1: my daily reads at Dholts dot com. Check out my

1095
01:05:25,000 --> 01:05:29,240
Speaker 1: weekly column at Bloomberg dot com slash Opinion. Follow me

1096
01:05:29,360 --> 01:05:33,040
Speaker 1: on Twitter at rid Holts. I would be remiss if

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01:05:33,080 --> 01:05:35,200
Speaker 1: I did not thank the crack staff that helps put

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01:05:35,280 --> 01:05:39,720
Speaker 1: these conversations together each and every week. Reggie Bazil is

1099
01:05:39,800 --> 01:05:44,000
Speaker 1: my audio engineer. Attica val Bron is our project manager.

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01:05:44,560 --> 01:05:47,600
Speaker 1: Michael Boyle is my producer. Michael bat Nick is my

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01:05:47,760 --> 01:05:51,560
Speaker 1: head of research. I'm Barry Reholts. You've been listening to

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01:05:51,680 --> 01:05:54,120
Speaker 1: Masters in Business on Bloomberg Radio