Jon: Welcome to the Venture Capital podcast. This is the second episode we've ever done with. Yes. As you know, Peter, the co host, but we also have David Frazier, raise your hand for those of you that are watching here on YouTube. And we have Kendall Frazier. And I think I've known them for 20 years now.
Jon: 20 years is a long time. So anyways, about once a week, Peter and I want to do every Friday record an episode where we're bringing outsiders in to kind of come and share insights from either the founders perspective or the the other side of the table, what it's like to be a venture capitalist. And so this episode is kind of like that, the first episode.
Jon: So if we make any mistakes, be patient with us. But first, David Kendall, do you want to talk about first without making any solicitations? What is the Frazier group? How is it different? I don't want to talk about your history at all, where you started in kind of like in secondary secondaries and now you've moved to primary investments if hopefully I'm saying that right.
Jon: David, give me this this weird, weird look. David also has one of the best sense of humor that around.
David: I wish you hadn't said that. I was about to say we guarantee 30% of your rock steady rock stable. So that's important. Yeah, we we've been a venture capitalist for 25 years working with our dad. And now we raised four venture funds from LP's and we put it into software.
Jon: What's the size of each fund?
David: 15, 20, 30, and then essentially 90.
David: And you're going up a little bit each time.
Jon: At what stage of your end stage a fund for you in Have you flown? Has it been fully deployed? 50% deployed, and it's mostly deployed.
David: So we're going to go raise again. So.
David: Thank you. Thank you.
Jon: What kind of deals? You guys typically look at the spread of the most common question. People are like, hey, who do I talk to? What is your ideal profile?
Kendall: we love to get into companies at the Seed or the Pre-seed stage. We like software as a service, we like AEI. We we love companies that are B2B and that's what we look for. And we we also do a lot of follow on as companies grow. So a lot of our capital will go into our existing portfolio as it matures.
Jon: And I feel like Kissick is also one of your your proud investments.
David: Yeah, we we like to say software, software, software. And then when people say what kind of companies, we always just tell him about his.
Peter: Softwares, software is boring.
David: They make software and they move numbers and do stuff for businesses. But his like makes pushes that you can step in.
Jon: So I think three of the four of us are wearing his X today, right?
Kendall: Yes, you are. Yep.
Jon: I think if you if you're connected to YouTube, you see it all. You have to be wearing a kissick.
Peter: Got your Cotopaxi jacket in your kids. That's right.
Jon: Well, let's kind of have this episode focus on air and your perspective in the changing landscape. And how do you think the startups or the companies your portfolio should be utilizing?
Kendall: I well, I think at a base level, everyone should be using it to increase their own. I kind of think of it in two different ways. So in the one camp, I think everyone should be using it individually for their own productivity and their their teams and the people they work with should be using it. But you're not going to get like a valuation bump or credit for that because you're using a I in kind of a supportive way for your company, but it doesn't mean you shouldn't do it.
Kendall: So you absolutely need to be doing that.
David: I see. I don't think I don't think I as a differentiate for most small companies, we saw the coolest company ever. They were doing AI driven insights for sales. They look at all the data on Salesforce, Hey, you know, when this happens, that tends to happen. If you want better results, do this, do this, do this, do this.
David: And it was really cool, really analytical, really powerful. And then we stopped and we thought to ourselves, this is exactly what Salesforce will want to do, because that's Salesforce. This whole job is to create data on your Salesforce motion and then like use it. And what I think is going to happen to this company, no offense, if you're that company is Salesforce is going to show up and eat your lunch because it's their data, it's their platform.
David: If they say, Hey everyone, we've got this great. We just built this air solution a year after this other small startup, but still we built it. A year later, we've got an army of engineers and we think everyone should use this. They're just going to eat the smaller companies lunch. So I don't think you should lead in saying, Hey, I'm going to build this tiny little niche air application.
David: I don't I don't think that's going to build you a competitive moat. It's the big ones that are going to swoop in and eat you up.
Jon: Peter, you're like nodding your head.
Peter: I mean, I'm curious to hear what the Frasers think from, like, where the opportunities are. And I but a lot of the things I've been thinking about lately is that I think there will be big opportunities for air infrastructure, and I think there'll be big opportunity is for companies that have unique data sets. And I think all the companies that are essentially AI wrappers are.
Peter: There might be a couple of winners in there. Who knows? There'll be hard to like pick out. So I think about some will get by. I think of them like Canva. Like Canva is like an interesting like product market led growth UX, But there's nothing really special about Canva, right, from a technology perspective. So there could be some winners there.
Peter: But I think they'll be really hard to pick. and I think the big thing is that the incumbents who already have the customers already have the data, they're just going to be implementing LMS from larger players and leveraging their own data, set their own customer. and frankly, like if you look at every single customer that's out there or every single company, SAS company that has access to these data sets, they all have an AI play right in process.
Peter: They're all thinking about it because you have to know. And so that's where like I'm thinking about where the opportunities are and where we're focusing as either unique data sets or infrastructure when it comes to like pure play AI.
David: Or just have a really cool business and say, Hey, AI, we were already planning to do this.
David: It was already going to be so awesome. And now this AI is is helping us make customers them happier, I gather. I like those kind of pitches, but if they come in saying, Hey, we're different because as we use a large language model, to me that that kind of puts me off a little bit.
Jon: In that sense, do you look at AI as it's something that everyone has to implement to be competitive? As you look at like the economies of scale, everything is going to shift from an economic standpoint and that if you don't do it, you just like like let's say you're you, you sell widgets. Widgets are now 5% cheaper. If you can enable AI, you can stay competitive.
Jon: If you don't, aren't able to enable and to your business, your ERP, then you're going to be at a huge disadvantage.
David: I think in the long run. That's 100% true that it's kind of table stakes like this isn't what you do as a business, but if you're just less efficient, then you just you just won't make it. So.
David: I think you're hundred percent right there.
Jon: What kind of investments have you guys made in the air space so far?
Kendall: So the investments we've made are not large language model related A.I., but a couple of them come to mind. One of them we did, and now these were kind of done pre AI hype, so we're kind of lucky on some of them. One of them uses visual AI to help identify cancer. That one's doing well, one of them.
Jon: And you want to give a shout out.
Kendall: Yeah. Pathology what.
Kendall: So they're doing well and but again it's not really related. Now they do incorporate some large language models just for helping write up notes and annotations when they identify cancer, but that's not their bread and butter. So I'm glad they're they're relying on that. They're integrating it in that. That's not what makes them interesting. And then the other would be Twin thread, which is one of David's companies.
David: They are super cool. They do machine learning for industrial plants. So if you are Procter and Gamble and your plants, some days they're more energy efficient and other days they're less energy efficient. They create a digital twin of the whole plant, a model, every machine, every interaction, and then just machine learning. They just say, Hey, you've got 10 million data points to figure this out.
David: And it turns out, you know, when things behave this way, they kind of affect those things that way and and builds a big, big giant machine learning model. So they're really cool. And we also have an investment in file line. They do case management software for law firms. And I think law firms are a great place for a couple of things we've seen that are really cool.
David: One, they can generate demand letters, not just, hey, here's a generic, here's a regular kind of demand letter, but it'll ingest all the documents and all the interactions with a given party and say, Hey, David Frazier has this lawsuit going on with so-and-so, and it pulls out of all the different documents this happened that happened, your pain levels, your medical records, everything.
David: So pretty cool. Or another one we saw was they would do redlining for contract. When you see two contracts and they're a little different, this one kind of like DocuSign sign says, Hey, click here to find the next point where something's different from your contract, where they changed it. And then the API can also say, Hey, 80% of the time this change, your boss finds that acceptable.
David: You said net 30 payment terms and they're saying net 45 and that's pretty cool. That's fine. And the air can say, Hey, but you know, this other change they asked, we've never seen it before. And other companies never accept it. And it's pretty outrageous. So it's a pretty cool software.
Jon: Is this what file Vine's doing?
David: Yep, they're doing they're doing a lot with they.
Kendall: Are doing a ton. They kind of just started selling it in June and it's already like a really sizable portion of the new revenue and not so fast.
David: I mean, don't don't quote me and don't listen pile vine, but literally, I suspect probably half of their value might be I really had not happened. They'd be worth half of what what they'll be worth event.
Jon: Can you say what they're worth right now.
David: No but but they raised a couple of years ago they raised at 700 million so they're they're big and and you know they're they're good at what they do. So it's not like a song and a prayer and a wish. It's like a is is very big to them.
Peter: And they kind of go back and reemphasize the point we made earlier, which is they have access to these unique data sets and they have the customers. And so if you are going to start like in a legal tech company today, you don't have those two things. Those are the things that matter, not the ability to tap into an alarm.
David: You have a bigger point. They don't have the data, so they can't train it to be quite as good creating documents and then b, they don't own the workflows of the customers. So yeah, if someone makes a different demand letter API product, they have to say, Hey dear customer, I want you to export all the interactions you've ever had with the client.
David: Yep. To our system, move all the data out which people don't love, and then we'll produce a demand letter and then all we give back is just the demand letter. Whereas if it's done inside file design, where they already own the workflows in the data, they can reuse what they figured out from that demand letter five more times, they can say, this is medical records, this is, you know, whatever.
David: So I think the advantage that the big companies have is pretty strong.
Jon: Do you think that I could be an innovator dilemma scenario to in effect, the very unit economics of the SAS industry? So for example, a lot of fast companies like Salesforce and HubSpot are built around the model of we are going to sell C, but potentially I could change it to, Hey, we are now going to be charging for the output or the contribution, not just a generic.
Jon: Do you see a affecting like subscriptions in a major way?
David: I think in the long run it's going to displace a lot of things and people will have to get really creative. Like, like for me not to go off topic, but related to this, I feel like CEO where if if everyone in the world started using chat to search like you don't search, you just ask chat and it gets way smarter.
David: It's way better. Then eventually the whole SEO market is disrupted because you don't have to go check people's websites. People don't have to make great content because is the air just kind of disrupted, circumvented the whole system? And I think they're all solvable and they'll all get solved over time. Like Salesforce will find a way. If they're adding value, they'll find a way to extract it.
David: And you know, if SEO gets broken, then maybe the maybe that I bought has to, you know, send money back to the successful websites or, you know, they're not sending traffic now, they're sending money, who knows? But I think it will all figure it out, though. But I think it's all going to break in the mean it'll all break and they all get fixed.
Jon: When you're looking to make an investment into an AI company, what are the other things that you're looking for? I know like with Running Air Utah, there's things that I look forward to see if they're a wrapper or they're really doing something foundational. For example, I look for statisticians, I look for data engineers, I look for people with longevity in the space.
Jon: There's a lot of startups that are starting right now that don't work. I feel like there's not anyone on the team who has any statistical analysis training, and I feel like that's a core part of any of these labs that are currently being rolled out. So even if you're going to modify it or provide a wrapper, I don't think I question how all the teams understand that and I think that's the current push and start ups.
Jon: Ten, from my perspective, are missing that. Are you seeing that as well?
Jon: I think well, that's a mouthful.
Peter: I think that that stuff is interesting and important. But I mean, if you're if you're going out to build a true alarm, I mean, you need to raise a ton of money.
Peter: I mean, I mean, look at like open a I look at Anthropic, look at cahir, look at, you know, some of the big alum businesses. They spend hundreds of millions of dollars, in some case billions of dollars on the processing to build these these large language models. So I don't know. I get really skeptical that, you know, a random startup is going to have the technical talent and much less so the capital available to build those types of complex models.
David: But but what you were saying earlier, they could corner some data that would be valuable or they could corner some customers.
Peter: Well, and a lot of grow in a lot of cases, they're going to use the alarms that have been built and trained, you know, by others. They'll ingest their own data into those and be able to come up with unique insights.
David: I want to hear what you guys think about whether the large language models are even going to be differentiated or special at some point. Are they are they all just going to kind of seem kind of similar and one day anthropic is the best and then four months later GPT five comes out and then, you know, are they going to be very special or are they going to be a bunch of, you know, American Airlines versus Delta Airlines versus Southwest?
Peter: So, I mean, I think.
Peter: I don't know my viewpoint on it, having looked at several as a large online business, is that to a certain extent they will converge, they'll have like their unique differences. but honestly, I think over time, compute cost will come down, the alarms will be more or less commoditized. What I think is more interesting is will those companies be able to build the infrastructure, the will those companies be able to build the infrastructure that makes it easy for other companies to build on top of them, much like there's nothing special about having a server farm, right?
Peter: That's not what makes AWB special. What makes it special is all of the software that's layered on top of the servers. And so I think that is where like the bigger opportunity comes from. And so if you're looking at like an open I, I think open air is like an interesting company largely because like everybody uses chat, you know, and because everybody uses that and everybody, you know, they're able to wing to engage with and integrate with so many different companies that they're building out this incredible tech stack that will I think, allow them to have long term longevity in the space.
Peter: but, you know, I don't know, like five years from now, if you're going to start like a brand new alarm business, I, I think it'll be more or less commoditized on that side. I don't know. That's my view point. I'm, I'm curious what you guys think.
David: I like that answer.
Kendall: I like that answer to actually, I was pitched by someone who wants to build an LEM to compete with open air and anthropic and trying to think what the differentiator was going to be. I think it was going to be he claimed that it would it wouldn't have all the the safety controls.
David: Was going to raise it from Saudi Arabia, right?
Kendall: Yep. He was going to raise it from Saudi Arabia and it wasn't going to have all the guardrails. I'm like,
Peter: That's going to happen, right? But but I don't know if that's the one that you want to invest in from like a business perspective because like.
Kendall: And how often do those guardrails really, like, hamper your businesses ability to utilize the model anyway, Like is that hurting pipeline because like, dang, you know, the line we're using isn't letting us red line the documents the way we want.
Peter: Well and frankly, guardrails are good, right? I mean, you think about like Twitter slash X. Yeah. Got rid of a bunch of guardrails and got rid of a bunch of customers as part of it. Right.
Jon: So fascinating stuff. So what about the back to the site company that pitched you? If you look at like what's happening in crypto there, there's a competitor, maybe Sam can we find it for us He's ah he's our helper producers. We call it the producer.
David: Sam are things happening in crypto?
Jon: Well so I was listening to was the on podcast and they were talking about how a lot of the markets like the, like the next weeks they think is going to come out of the web and because of the regulations and they're making it easier, more predictable for people to work with. And do you see the center of I if the U.S. is so focused, like if companies like Google are so focused on being politically correct, having all these guardrails out of the gate, a company could go to the UAB, have an infinite amount of cash, it could come from there.
Jon: And do you think that makes it tough for your portfolio companies, your investments to be competitive?
Kendall: I don't think so. Only because of how much brainpower, capital and like dpu time you need to like make these huge AI models. I've read that like China is just struggling now. They're not allowed to have the best, but I think it just has to be centered in the United States and probably even San Francisco for the next like year or two, because that's where all the smartest engineers live.
Kendall: It's where the capital is. You can get GPUs here. I think if you had a model that was trained without any of the guardrails that like the U.S. might just restrict it and say, sorry, we're not going to let you, you know, and maybe the people who provide it, like in video and the data centers here, would just cut them off.
Kendall: And I think even just the risk of that would be too great for them to attempt it. And then I'm not sure, like I said before, that like taking the guardrails off just unlocks all this. Our that is like good in a business case. I'm not sure that it like makes a lot of sense. Take the guardrails away.
Kendall: Does that make you more profitable? I'm not sure it even does.
Peter: I mean, Anthropic makes the argument that they have more guard and by having more guardrails that makes it more compelling for businesses.
Kendall: Yeah, then they can actually use it and they're not wringing their hands and they're not open to lawsuits.
David: Yeah, I personally don't want guardrails on mine, but. But enterprise is are terrified by the idea of everything that could go wrong. And they have to control it very carefully. And the extent that there's, you know, some protection in there that makes sense for enterprises and they're the ones that have all the money and spend all the money.
David: And I don't I don't I wouldn't bet on a Saudi Arabian horse. Now.
Peter: The other thing, too, that kind of surprised me is that, even though a lot of people talk about that from a consumer perspective, the number of like actual consumers that are using it is relatively small compared to the number that are, I mean, and actually paying for it. So a lot of people use it, right? But they use the free version.
Peter: But they there's not a lot of like individual consumers that are paying out of pocket for it on a regular basis compared to like business think.
David: It seems like coders get a lot of value from it. Yeah, but a lot of other people just use it as a modestly better search engine and businesses are going to use it everywhere all the time. Yep, in a really cool way. So I just saw a person on the hype train for like, Yeah, is it going to completely change everything in business?
David: Yes, it's going to change everything in the near term in your personal life. Not really.
Peter: Although you know, the counter that I have this friend and he was like, I don't know. You know, it's our big anniversary coming up and I got to like, do something nice. And he ended up like going to chat and being like, Here's like, here's my situation, here's my wife. Like, give me something like, good. And it like, gave him this big long love letter that he then, like, tweaked just a little.
Peter: Gave it to his life. His wife was like, this is.
Peter: The nicest, like most romantic thing you have ever done for me in my life.
Peter: Or she's going to put.
David: That into like, someday there will be something that checks.
Peter: If there are checks, she's going.
David: To put it in a checker one day and that marriage is done.
Kendall: Not all these and then claimed that it was trained on his letter.
Kendall: It'll be like it was trained on mine. It was the pinnacle.
Peter: Of I mean as long.
Peter: As he didn't lie, as long as he believed everything that was in the letter, then it's fine. Right? But. But I guess my point is, is like he's getting this additional value, right? As a consumer and something that's, you know, maybe a little less obvious. The other thing, though, I saw this chart recently and it was really interesting and they did the study and they they they had like two groups.
Peter: They had one group that had access to like a chat CBT and one group that didn't. And they looked at like productivity over time and they were able to demonstrate like the quality of output of the work was like a 1 to 2 standard deviations better on on average if they were using, you know, one of these, these, A.I. models like Chatbot to assist them in their work than those that didn't though is, was interesting because like intuitively we think like, yeah, that makes sense but they actually see it like in the data was interesting.
David: I really like using it to get me started something.
David: I use it to get started and then I try to go back to what I like is like my own tone. Yeah, I, I don't like the output, but I like having something handed to me that's half done.
Peter: Yeah, it's like a nice framework to get you started. Although, you know, it's like we did a podcast the other day and gone through in like, Hey, how to venture funds get evaluated and attached CBT and, and gave out this outline and I don't think maybe we maybe included like one out of seven sections. I think the it in that.
Jon: Episode there were a lot of internal like stats you were using outside of the music and the IRR that weren't included in the outline.
Peter: Yeah, I guess my point is that it's not always 100%. It'll get better over time.
David: But investing in choosing a venture capitalist is an art, and I'm offended by suggesting that that we be defined by our music or our TV's API.
Jon: Yet TV Guide was not included in in well in the output.
Peter: Yeah so we covered those kinds of things because they are the things that like this is get evaluated on right now and it was just an intro course enjoyable.
David: I'm just kidding actually I, I feel like the hard returns are the only thing that matters.
Kendall: So I was, I was telling David so we're LP's in quite a few funds and a surprising number of them when you go to like their investment meetings don't even talk about like the IRR or the net.
Peter: When, when they're pitching, when they're pitching their fund.
Kendall: No, these are like the annual update. So it's kind.
Kendall: A hard pitch, but yeah, when they're like saying here's the performance, a lot of them just ignore it. Ooh, I don't know if it's just us that that raises like a big red flag for or helps feel that way. I have no idea.
Peter: Well, I, I don't know. I've been to a bunch of LPA meeting or LP meetings and my feel is that the funds that are doing well have no problem. Yeah.
Peter: That they share the exact areas and the ones that are like, things are good.
Peter: So great, you know, try to try to hide it one way or another.
Jon: Yeah. You know, one of the things I've noticed is they're hung out with other VCs is how many VCs are investors in other funds? Why is that? Is that because it's the easiest way to get competitive intelligence or you just try to build the network?
David: Well, we're part of that for sure. I mean, we've invested I think we counted 13 venture funds that that is we're also a family office, as you might tell, from Scott Frazier and Kendall Frazier and David Frazier. So we've done our share of investing in VC funds, and some of them are really great. I think it was just we didn't have the deal flow at the time, so we had to park our money in venture where we liked.
David: But I think once you have enough deal flow, I don't I don't view co-investing as like the pinnacle of your best deals. I but the selection bias is really strong and actually I take an exception to that because Peter you've shared two of our best deals parallel and project. So thank you. But generally speaking, the deals that are really hot, super competitive, really compelling a venture fund will do, put all the money in themselves.
David: They'll say, This is the best thing we've ever seen. I love it more than anything. There's no room to share. And then there's a tier down where they're like, Hey, you know, we don't really want that much. No other venture funds really want it, and therefore we will syndicate.
Peter: Or they'll do stuff that's outside their stage, right? They're like, like we're a series shop and you know, they're raising a series D and you can invest in that. But at that point, you know, valuations are high and you know, they'll run SPV. Then other things that make those happen. So but that's particularly helpful if you're a seed fund.
David: I don't view investing in other venture funds or their co-investment. I don't view that as like the end perfect situation because the co-investing is is good, but not arguably not as good as just sourcing your own deals.
Peter: I think like us, I'm an LP and a handful of funds and for me it's partly because it's they're my, they're my friends, you know, and I like them and I like their performance. Then, you know, I want to be supportive and and I have friends that are LPs in my fund that are at other venture funds. And so there is I wouldn't say it's like a quid pro quo per say, but like there is a little bit of like, yeah, like I'm an investor in your find your investor in my fund, like we're friends, let's go like makes fun stuff happen together.
Peter: It's I think there's also a little bit of like hey this is an opportunity for me to diversify a little bit because like, for example, I'm in, I'm an LP and a super, super, super early. Like Pre-spring Seed Fund. And that's not what we do as a fund, but I think it's an interesting place to be. So I'm, you know, small LP and they're fun because, you know, I like the diversification and I like looking at the stuff that they're looking at, you know, and, and so I think there's a little bit of that.
Peter: I know there are a lot of funds like Sequoia does a bunch. I know where they'll make investments in like early pre-seed funds and they're just hunting for deal flow from that perspective. Or they're like, we want to rate, we want to do the series A, and so we want like insight into as many companies as possible. So they'll they'll be an LP and a bunch of these pre-seed funds and then those funds go out and write, you know, 100 checks.
Peter: And so with, you know, an LP commits, they can have access to like 1000 companies, their metrics and track them and so forth. So I think there's like value there depending on what your strategy is. but yeah, I mean that's, that's my perspective on kind of why I've written paychecks.
Jon: How has it changed your, your thesis as an investor and then how would that and would that correlate or change your, your thesis as a founder if you're a founder?
Kendall: I would say it hasn't, but I could say better than I have. I think what the Frasers really look for is something that can have a long term competitive advantage. And sometimes, like a company like Physics shoes or Project Solar will come to us and our first inclination is like, No, never in a million years we invest in something like that.
Kendall: It's not software, but we dig deeper and we see like, okay, we really like the moats that they can build and the competitive advantages and different aspects of it, and we'll do them anyway. And so I think for I it's the same where we just hold it to that same standard and that's why we would invest if it can own the data or the users.
Kendall: And if it can't, like we just wouldn't give it credit for A.I., so we maybe would still invest just because they're using A.I. and maybe they're over claim they're overselling The A.I. part isn't like we're not going to not fund it, but they don't get the A.I. credit because that part is going to be commoditized. So I would argue that it hasn't changed our fundamentally, but.
David: I think that having just the existence and the efficiencies of A.I. is a good thing for investors because there's always kind of this pull, push and pull between, Hey, here are these legacy solutions that already work, that have already figured something out, and meeting a need. And then here's these younger companies that are trying to disrupt and they're trying to change the way things are done.
David: There's always this push and pull, and I feel like A.I. is causing the gap between the two to be wider than ever. You look at some dinosaur, some Yardi or RealPage, if you're in real estate or, you know, or anything.
Kendall: That's on prem software.
David: Software. Right now, there are companies that are like, Hey, they work and they're, you know, they, they check every feature set box that we have and so they stick with them. Even though you're like, Why aren't you doing this new cool company? They do really cool. But anyway, now the gap between the two is wider than ever. And so it's making, I think, all disruptive companies and young companies are going to be able to eat the dinosaurs lunch a little bit better.
David: Going to make them a little bit more stinky.
Peter: Yeah, I mean, basically, right. Like if you're on prem, you're going to have a real hard time implementing true AI tech into your text textbook and providing those that value, whereas a new up and comer that's more cloud based right out of the gate can theoretically offer all of those same features, plus a whole bunch more. That's even, you know, it's even more difficult from for those incumbents to be able to catch up.
Peter: So yeah, I think I think that's a great point for me. Like it really hasn't changed our strategy whole lot other than what I talked about is like when we're looking at opportunities in AI is the infrastructure stuff, it's the data set stuff. And so if you're starting a new company and you want to be in the air space, I would be thinking about like, well, where can I play in those too?
Peter: Because if you're going to be just an AI wrapper, you're effectively building on someone else's platform, which you don't control. And that's just always a super tenuous place to be. And then I also think you're lacking the things that are like truly competitive and and create, you know, real barriers which as customers and, and to a certain extent data as well that your incumbents have.
Peter: And if your incumbents have like a reasonable tech stack, they're going to be able to implement AI very effectively.
Jon: So what areas of infrastructure are you looking at?
Peter: Be anything from like we've all you know, we've looked at like some of the large alarms, we've looked at companies that are more on the, the, the actual like dpu cloud processing space. We've looked at companies that are providing like security, in that tech stack, different like optimization tools, like picks and shovels really. so those are a few different types of examples of stuff that we are looking at or have looked at.
David: We saw one that I thought was really cool that was making machine learning more accessible though maybe they're not that that long term perfect protected, but they were basically saying hey to get to a good machine learning model data has to be in this kind of a state, have to spend this much time to get there and we've got these kind of pre-baked not quite as efficient models, ways to structure your unstructured data, but at least let you ask build kind of some shaky machine learning models and you know, they're not perfect.
David: And if you spend a long time refining your data, you get a better answer. But it's kind of like a, hey, get a quick and dirty answer and then spend the time to build something really robust. I thought that was pretty cool. But but as I think about it, I wonder if, you know, eventually that's not open. AI's first mission is to make, you know, models more accessible or value more accessible.
Jon: So if each of you were to start an infrastructure business, what would it be?
David: Banana stands and always money in the banana stand.
Peter: I mean, honestly, I probably wouldn't because that's not where my expertise lies.
Jon: But if you had to like of trends, you're saying like, let's get the secrets from the VCs without violating India's.
Peter: I mean, I'd probably take a look at like all of the different softwares that sit on and around like AWB and other cloud providers and think, all right, what are the things that are going to be needed that are similar to this for AI companies, right, Whether it's all the way down from like, hey, what's the next like digital ocean of AI to what are like different cybersecurity tools that need to exist.
Peter: What are the analytics packages, right? And I mean there's going to be a point where like, like you have companies like cloud ability that help companies that are on us better manage their spend and understand that there are going to be companies like that that are going to be needed on the AI side as well. So I don't know.
Peter: I'd be looking at them stuff in and around that.
Jon: As with an ABC rep this morning was talking about that idea, they'll just have these mysterious 50,000 $100,000 bills now that all these CEOs are like, do I? And they're not going to know what the actual impact is from that, that investment in infrastructure for. Mike Dawe.
David: I think my advice regarding infrastructure would be to select a niche that's small enough to win that you can dominate the I if you just said, hey, make another, you know, add on AWB or something. I worry about that. We invested in a company called Opinion that was doing something not very special reputation I give you give five star reviews and leave and surveys, but they did it in the multifamily real estate space where they came.
David: They said, Hey, you know, if you want really great reputation, you could just go to podium and that'd be fine. But we opinion are going to make it exactly for what a property manager needs and it's going to do exactly what a property manager wants when they want it. So you get a you get a maintenance fix, then you get a review request or you're going to leave in three months.
David: Then you get a survey saying, are you going to stay? You're going to leave. So they were doing something that wasn't going to win in the broader ocean, but they picked a small enough niche where they said, Hey, we're just going to make exactly what people want here. And I felt like they won because of that. They're doing great.
David: So I would just try and narrow down small enough where someone hasn't quite cared about it quite yet.
Jon: Okay, what about the data side? So the infrastructure side we've talked about what about the data side? What part of that are spaces where it makes it a compelling like company to run or the investment to?
Peter: Well, I mean, I think like I mean, this is not entirely fair, but I think like File Vine's a good example of a company that has unique data, right, that they can leverage. So, you know, I don't know necessarily Li where all the unique data sets might reside or where the potential there is, but entrepreneurs that have insight into like, Hey, here's an area where I can tap into a very valuable data set based on the experience that I've collected over my career, like, and I'm going to leverage that now with AI to come up with really interesting insights.
Peter: Like that's, I think, an interesting opportunity. And frankly, there's so many of those potential data sets that are out there for people to either create or to leverage to do interesting things with.
Kendall: Maybe target on prem. The industry that's dominated by on prem software file Vine, is there kind of a market for law firms? He told me that 80% of the companies of larger law firms still use on prem case management software. So if you look for an industry with likes tired sleep, like there can be big competitors, they just need to be like the tired, sleepy on prem ones rather than like hot, well-funded San francisco startup giants.
Kendall: I also ben peterson with the bamboo bamboo h.r. Told me that when he was thinking about starting bamboo h.r. He looked at the industry and he's like, you know, there are a lot of h.r. Asses. And there's some really big, sophisticated, hated, scary ones, but he's like but they're just like such bad companies. They're boring dinosaurs. And so they were able to come in as like, a lean startup and displace them.
Kendall: There is still a lot of work, but that's who they were competing with. When we evaluate companies, we draw this big difference, like what's the competitive landscape like? And if it's some big boring company, then yeah, that's okay that those that they are competing with them. But if it's like well-funded San Francisco start up and it's really slick and good, then it's like maybe I don't want to compete with them.
Kendall: They have a huge part.
David: In my advice. If you're saying, Hey, where should I go for to build a data advantage in my next business, I think you should just pick whatever is adjacent to what you've where you've already been working and what your experience is. You've been at Divvy and you like factoring in credit cards and do something related to that. Or if you were at Qualtrics, then do a Qualtrics related Qualtrics just wouldn't solve this problem.
David: And, and I will. So I, in my mind, even more important than saying like, this is a better place would be just, hey, what are you good at? And what do you kind of know really Well.
Peter: Yeah, yeah, 100% agree.
Jon: Where does I go beyond limbs?
Kendall: Yes, I think it goes more broad. I think the labs are already really good at what they do, and the core is basically there. I don't think a year from now you're going to see that dipped for the core LMB like an order of magnitude better, but I think it's going to go wide. So and you know, that's it's already going multimodal so you're getting images and audio files that it can process and that's good.
Kendall: And I think people are hard at work giving it power to actually do stuff for you. And it's going to go just really broad and wide. I think people are still scrambling to take advantage of the core that's already there. And I think we're going to see that. And I wonder if we're going to see more like stuff that's like limbs, but not for words.
Kendall: Maybe you'll see it related to images or other types of machine learning. I don't know.
David: I was talking with the founder of Twin Thread who does the machine learning and maybe it's just because he's kind of old, but he was telling me he was kind of a hater. He was like, you know, a lot of these models the labs are built on, they're algorithms that are created in the eighties or earlier in the sixties.
David: And it's just the fact that there's enough processing power now that people are these models that are finding success and they're being more successful than anyone expected. So I guess in my mind, I don't think anyone has a you know, here's our language models and now here is the next evolutionary step. I don't think it exists yet, even in its infancy.
David: I don't think anyone but the Kendall's point, our labs are going to be so successful, they're going to be everywhere, going to be a thousand times more usable and ubiquitous, though I love that and I don't want to understate that, but I don't think I don't think there is a a next step or when there is, it'll be something surprising that no one knows.
Jon: Now, twin threads out of Virginia right.
David: There in Bozeman, actually by.
David: But all they're machine learning. People are professors at the University of Virginia. So.
Jon: Okay. How did you come across this deal?
David: Next, Frontier Capital shout out to them. They operate in there in Montana and they invest in like Colorado, Montana, Idaho, Utah. They're just really great, really smart. So they shared it with us. They've been in very early. They knew the founder of Twin Thread for a lot of years. So they're great people and stuff.
Peter: And what do you guys think? Do you think AI is going to replace jobs?
David: I think if you're saying they're more if they're adding efficiency into a business at the moment, you say that you're also saying you don't need as many people doing the exact same jobs. I think that's that seems that seems like just like a tautology to me. Like you say this. You're saying that as well. But I think the other half of the question is, are there so many jobs out there?
David: Are there things that people can still do? Like is there there going to be a net fewer jobs in the world? I don't really think so. I if people could say that about cars and horses and anything that's gone out of fashion and there have been new jobs, though.
Jon: Entertainment, lots of entertainment jobs now that weren't there before.
David: Yeah, I think there will be huge disruption. There will be jobs that one person does that five people did before. There's definitely that. But in terms of can new people, will new jobs exist?
Peter: Yeah, I mean, I think the thing that's kind of interesting is that the jobs that are least likely to get displaced are the more manual labor jobs that have been under threat from technology and robots. And the jobs that are the probably the most threatened are a lot of white collar type jobs. You know, I was talking to some.
Peter: To somebody earlier today and he was like, yeah, I was going to you know, I went and worked at a big accounting firm and even the big four, you know, accounting firm was like, hey, with all this technology coming down the pipeline, it's going to totally like change what accounting is. And he was like, Crap, If you guys are saying that I'm not going to have a job, I need to transfer industries ASAP.
Peter: Right? So, you know, I think I think you'll see more of that where like there's don't need as many accountants or lawyers or, you know, a bunch of these jobs, which I actually view as a great thing because I joke at University Growth Fund that I try to convince a lot of accountants and lawyers not to do accounting or lawyering things and because it's kind of a waste of their life and potential, I feel like in a lot of cases that they could take that same intellect and use it to create more create, you know, to do things that are more creative.
Peter: And I think that's where like there can be some really interesting new job opportunity, these new careers, new businesses that exist, because we were able to kind of unlock some of that human potential that currently gets locked up in law firms and accounting firms and in other places like that.
Kendall: I think that's right. And I think you're particularly at risk if you're like entry level white collar worker, like paralegals are probably at more risk than a full fledged lawyer. And I think the lower level accountants are probably more risk because I think the AI is going to say we just need fewer paralegals because they write. AI is doing that and I don't know in ten years where it'll be, but I think in the short term it's kind of those entry level white collar workers who are really at risk.
Peter: Or anybody that doesn't have any sort of like real, true differentiated expertise. Yeah.
David: Right. John, can I hold your phone? So it seems like I'm reading from this.
David: John, what do you think about Universal Basic Income or or A.I. tax? Like, do we need to.
Jon: That's not on there. But it was.
David: Well, tell us your thoughts on righting the wrongs of of air disruption.
Jon: when I look at the economy right now, I see a massive amount of, of investment of our time and whatnot being spent on entertainment. And I look at that in relation to universal basic income in two aspects. One, have we just run out of opportunities to do productive things And so will I just push that much more where we can entertain ourselves, you know, 8 hours a day and do 2 hours of work?
Jon: Or is it the flip side of a of this entertainment is just a drag and it's keeping us from going to the next stage of like civilization, like a Dyson sphere joke on that joke about the Dyson sphere.
David: But but does that mean, like, spending more time outside and feeling the grass or what? What's that? If if entertainment is the drug, what is the.
Jon: Art of it's the drug or the symptom? The symptom that we are becoming so advanced we don't have to work 12 hours a day like we used to, or it's, you know, a combination I should put this back on, you know.
David: But what should people be doing with their time if they they just like, hey, you get one hour TV, What is what is the thing they do?
Jon: I think people should be focusing a lot more in education. I think education's more important than ever before, and it's going to take more and more discipline to do that when there's more and more distractions around. And when you see all these there.
David: When I like to skip getting educated, I don't think like it answers the question. It answers the questions for. And you don't have to learn the math.
Kendall: Like, what's the point that I can do? If I need to know a history, I'll just ask at that moment, just in time history retrieval. I'll get it from there. I.
Jon: I look at it right now from a coding perspective as it's really good at guessing like, what's the next one, two or three logical steps. But I feel like it has a much harder, you know, it's a much harder process to say, hey, what's, what's the degree or two order of magnitude better? And that's brief. Like there's going to this huge breakaway.
Jon: So you're gonna look at like I think a lot of junior white collar jobs. We don't perhaps need as many and maybe we'll end up spending more time in school getting educated. But I think becoming a critical thinkers more than ever before. One of my favorite stickers I have on my computer at home was when it's talked about the last two years of the market.
Jon: It was it says this is like the year of technical debt. And the idea was that when the interest rate for money was close to zero, people spent a lot of money just building code fast, building crappy code, and not really thinking things through because it was free. But I also I see that same sticker being applicable even more so today, where people, they don't have to really think things or really analyze it.
Jon: And like I look at as beauty and these other tools is doing really good jobs, but it will miss very important things. And there's been times where I've made decisions and I've like sent messages to other people based on analysis. And then I went back and I'm like, it made a completely wrong analysis. So I think I think, you know, we we shift we can accomplish more, but critical thinking is more important.
Jon: Being self disciplined is more important. Learning structure and rules is more important today than it was yesterday.
Kendall: I know. I just thought of something. I want I to disrupt the four year like college education that you have. I, I don't know. It's like, are people going to want to sit in school and spend four years of their lives learning like rote facts and learning like skills that are, like, almost outdated by the time they get out of school and like it'd be.
Kendall: Or would it be better for society if people just skip it, get into their education, you know, start working on something that's valuable, and then kind of what?
Jon: Right. What are your.
David: Or you could go to the four year school, but your four years are like, Hey, you spent a year this time and then you got a real job and you did this real thing, and then you furthered your education again. I agree. I don't think it has to be a big lump. Yeah, like a big upfront boom. Here's just these years that you're educated and then you're uneducated ever again.
Peter: I will say, though, that one of the things I worry about with I from an education perspective is like, if you think about true innovation, usually people talk about it as the intersection of two separate disciplines and and the problem with, you know, is that if you never learn, you never become like an expert in a given space because you're always just going to you have this crutch called AI that just serves up stuff.
Peter: You never actually end up becoming an expert enough in, you know, enough disciplines to be able to identify new, innovative, creative problem. So that I mean, I think, you know, the flip side of saying, Hey, AI is going to solve a lot of this tedious work that we do is going to open up opportunities for us to do more higher level thinking.
Peter: It also backfire in that regard, too, in that like if it becomes too much of a crutch that we don't, we don't learn, we don't gain experiences and so forth like could be a problem for us. It is I'm not a huge fan of for your education. I think I think for the most part you don't use 90% of what you learn in school.
Peter: And it's it's a tremendous burden financially for a lot of people. and I think they're much more effective ways to achieve the same or similar or superior results, such as programs like University Growth Fund, frankly. Right where it's like, come join our fund and let's look at some deals together and we're going to teach you finance and we're gonna teach you analyzing markets.
Peter: We're going to teach you analyzing competitors and assessing management teams in real time, looking at real deals versus like reading through a case study where you don't have enough context or depth to really get.
Kendall: Like that sounds awesome. Now, where was that 20 years ago when John and I were in school?
David: Well, the cool thing about a program like University Growth Fund is the answers aren't always like you're black and white either, right? I guess a textbook kind of says, this is a better example because it's so obviously this way or that way.
David: And so that's that's a cool program.
Peter: But the real world is not like that, right? You know, they're varying shades of gray and sometimes it's hard to tell which shade is brighter, the darker from the other. And sometimes there's a lot of just like variability in life and investments and all kinds of stuff where you're like, I never thought that company would succeed. And that ends up being wildly successful.
Peter: And the company you thought, like checked every single box ends failing for some reason in this debate. So I do wonder, though, back to your basic universal question.
Peter: We didn't actually just go through an experiment of that over the last couple of years.
Peter: Yeah. So you think about like all the.
Peter: Money that was spent in COVID, right? That went out to people to basically help them meet their needs over a certain time period. Right. And one of the big results of that was inflation, obviously. But the other was this huge employment gap. And how hard it is for so many companies, particularly like restaurants, you know, manual labor type jobs to find people to work there.
Peter: And like how frustrated I don't know if you guys have felt this, but like you go to a restaurant and it's like there's nobody there to, like, serve you. Right? And it kind of makes sense because it's like, why? Why would I do that when you know, they're not paying me enough? Right? And so, my business partner is just telling me the other day that you can go and you can work at Panda Express and make like 22 an hour, right?
Peter: I mean, if you're working 40 hours a week, that translates into, like $44,000 annually for serving up some lanterns. I mean, you know, it's.
David: But it is hard work. I, I, I admire people who work hard hard 40 hour work week now.
Kendall: So David and I have a friend who's 16 year old daughter was basically running the whole front end of this sushi restaurant and he found out she was like serving alcohol and managing the whole thing. And he came in and he's like, Nope, he's 16. He's like, put the kibosh on that. But it was just funny. He's like, They're in such high demand that my 16 year old daughter was just running the front in the restaurant completely like, Well, she's a smart girl.
Kendall: That's really impressive. But also it's like. But it went too far. Yeah.
Peter: Well, no, I agree. I think, I think they it is a hard job and it know requires a lot of time and effort. But that wasn't a problem that existed before all of this.
Kendall: I also kind of wonder, didn't a lot of that like stemming money find its way to like just like some of the biggest tech companies like Apple and Amazon and was that is that a wrong perception like those people just the money flowed like they spent it but it all just flowed into some of the people.
Peter: They spent it somewhere.
Kendall: Right? Yeah, they spend it. I'll spend it at the same place. I don't know. They're all kind of just flowed to these mega tech companies that I don't know. I don't know how you address that. Or maybe you don't with the universal basic.
Peter: Yeah, I don't know. I just think it's an interesting thing to think about.
David: Universal basic income for me, but not for the that's my thought.
Peter: And so I want to know.
Jon: What are some of your your biggest misses as investors.
Peter: Though like investments we made that failed or weren't in investments that we should have made? I mean, like the whole.
Jon: The whole reason I got into the venture space initially was, is I was a student at Brigham Young University. I recognized or perceived the value of being if you could find the next like Google early on I ometer was the example I gave, but no one knows what armature is anymore unless you're like part of the old school.
Jon: But like, how do I find those opportunities that I think of the opportunities I missed? Like I saw Lucid Hour when it was just Ben and I introduced him to his first business co-founder instead of like, you know, taking that opportunity for myself, I was with the Utah Angels with ben petersen, and I saw him start bamboo h.r.
Jon: And i'm like, this is this is crazy. And there's been like a handful of others that I've seen or been connected to.
David: I actually feel like you you shouldn't live your life looking at what could have been, and you just say, look, you know, i'm going to try and make money the best way i can, and if this company makes sense to me, then invest in it. But I worry that if you if you look at it from the perspective of, boy, if I missed this one and it it could have become $1,000,000,000 that you're going to get stuck into the the FOMO route and you're then you're going to do even worse.
David: So even even though we've missed some big ones, we missed.
Kendall: We missed bamboo, but we were a little light on cash. Ben Petersen Pitch before David Nyerere pitched our dad for money right at the very start, he's like, I was light on cash. I didn't do it because I should have made room to do it. But so we do have a fair share of misses. But yeah, David lectures us all the time at the Frazier Group.
Kendall: Like not over learning from specific examples because it can become like a logical fallacy almost to just over train yourself based on like, well, this was a huge hit and we missed that. And I invested in this and something unexpected happened and it did worse than it should have. Like, you need to learn from those. But most a lot of investors over learn from just a couple of those data points and you have to have the conviction to say, no, I'm we we invest in things that are like defensible and have a moat and long term competitive advantages.
Kendall: We're not going to fall into the FOMO trap because if it violates our core convictions, then we just have to say no and have confidence that if.
David: There's a there's a company in Utah that drew up to $1,000,000,000 valuation, they're now lower than that, although not officially. And I was convinced that the founder was a scammer, a literal actual fraudster, and I told as much to a VC, They're like, Would you introduce me to the founder? And I said, I will. But also I want to tell you that I'm convinced they are like legitimately actually real life fraudulent.
David: And I connected them anyway. And then they invested and then they made a ton of money. I'm kind of hoping, though, that the company goes to zero so that I can be right. I if you think to yourself, who is the biggest, like the craziest founder, then you're probably thinking of the one I I'm.
Peter: So I don't know. I don't.
Kendall: Know. I can think of like ten that that that the.
David: No but the number one and number one we're not we're not talking Josh James is here we're talking top dog.
David: I'm just I'm just.
David: Guess the point is you you, you're you're wrong all the time. And I just think you got to be wrong is as long as you're right, sometimes do. Then your job.
Peter: I was at this part and I think I've mentioned this before in other products, but I was at this meeting with a partner at at Lightspeed and he made the comment. He's like, Venture is like the only career where you're wrong 70% of the time and you are held as an absolute God.
Peter: Right? Because you were right.
Peter: The other 30. And so, you know, I definitely respect what David was saying is that like, don't get too caught up on your failures and this because so many of those are like anecdotal data points. Right? And when I think about like when I failed, it's because I didn't like we have a relative, you know, strike down box, whatever.
Peter: And like when I go outside of that, that is where I'm like, that was dumb. Yeah, right. Like, like, like we did this like party round and like, we usually co-invest alongside another institution or investor that's like a core tenant of ours. And like, we went outside of that in this round and it has not gone particularly well.
Peter: And the thing that's frustrating is we're one of the larger investors and so they spend, they, they hit us up a ton and I'm like, I'm not a fund that is designed to like save your company, right? This is not our design. It's like it's not a good or bad thing. It's just not our design, right? So and then there are other there are other deals where I'm like, we should have done that deal because I checked all the boxes for us, right?
Peter: And we missed it because either we were too slow or because we misunderstood some key piece of the business. You know, the one I talk a lot about is not that we actually looked at at Uber, but at the time. But I remember when Uber was out raising and thinking to myself, like, really like people are so excited about taxis.
Peter: Like this is a highly regulated, highly fragmented $11 billion market, like which 11 billion is decent. But like, that's it. Like, you know, I was like, it's not that attractive of an opportunity. And what I missed there was it wasn't the taxi market. They grew the overall market and it really was the transportation market, which is a trillion plus dollar market.
Peter: Right. So like, those are the times where I think about like, hey, what can I learn from that where it's like, hey, there's a shift in perception that I should have that I didn't have. And maybe like when I'm looking at businesses, can I maybe challenge my perceptions a little bit to be a little more expansive so that I don't miss out on huge opportunities like that?
Peter: But but honestly, it's hard, right? Like so many funds have missed out on so many amazing deals. And as a VC, like I can always give you, I don't care what company is serve up any company to me and I can give you ten reasons why it's a terrible investment. So that's not the hard part. The hard part is like knowing, but then also being able to see the potential and like marrying the two in such a way that you get into at least some of the winners some of the time and that you're not wrong.
Peter: More than 70% just kind of rambling there. But no, I like it.
David: I like that one of.
Jon: Peter's comments is to be a good we see there's like ten deals every year to be on the Sequoia level. The win. How would how does the Frazier group look at like that type of a theory because like if you look at like I mean Peter's going after different type of logos. I think you guys go after he goes after, you know, he's in Spotify, Lyft and these other like larger consumer brands.
Jon: And I think that's a very different persona than what you guys go after, Correct or incorrect, We.
Peter: Also do growth stage. So, you know, there's also that, you know, I'm not smart enough like, like the Frazier group to go after Pre-seed and seed.
David: We do I would say yes we look for ten great. But what we think differently is the ten deals don't aren't ten New Deal. They are often we've already been invested in for five years and we say we really need to get more money into this company, which means we need to call everyone who's left. Every employee who's left the company, ask if they'll sell us their stock or it means we need to like we file Vine.
David: We've been asking, asking and asking, Hey, can we put more money and can we put more money in? And then one time one of the executives needed to buy a house on a day move and they're like, okay. And so just stuff, stuff like that where I would say, you don't have to necessarily pick and brand new great companies, but pum pum your current opportunities as much as you can as well, and then you'll still get your ten.
Jon: I mean, are you guys looking for companies to IPO specifically?
David: Want to make money.
Jon: Yeah. So like, how is that different? Because I think a lot of the standard VC persona is can this company go public? Can this be $1,000,000,000 company. And like when you talk with like I've got a friend at A16z the like when I was fundraising a couple of years ago for a project, you know, you talk with some some in some companies they're like well if you're not at a billion we're not interested some of these and I talked to A16z and they're like a billion too small.
Jon: We're not having interested. And I assume that you guys have a very different.
David: Model that's the size of their check. They're writing to.
Peter: You because of the.
Kendall: Seed. Look for companies that can monopolize what they're doing. And so that means they're going to, over the long term, be able to get a higher margin on the business. They do. So it's similar to that, but we don't have a number like a billion. It could be a smaller market, like an opinion where it has a little smaller niche, but they can just dominate it.
Kendall: We get in and we get in it a good valuation and you know, hopefully that will be a really good IRR for us. I'm sure it will.
David: We were in GitHub, but they were acquired.
Peter: I didn't know you were in sub. Yep. That's cool.
David: Yeah, we were in GitHub, but they got acquired by me. By someone who. By someone who thought they were more valuable under their umbrella. And so we don't, we don't particularly care whether they're acquired or have an IPO. But like Kendall said, they need to have a monopoly potential or a competitive advantage, and those ones tend to grow big.
David: So, you know, it's like, hey, we're going to buy 20 each back, only Jiffy Lubes and operate them really, really well. And our customers are really going to love us then, you know, we don't we don't like.
Peter: Because it can't get big. Yeah, I mean.
Peter: What I've said in the past right is, is that there are only a handful of deals in any given year that matter that are going to generate like the vast and that's just the power of venture capital because you've got you know, it's just super risky. Most companies are going to fail and then you'll have a few that generate such massive returns that like the company after them, you know, is is a fraction of its as much return.
Peter: Right. And so if you're you know your Sequoia you and your and you're like one of these big firms like they have be in those deals in order to win. But I think there are a lot of other models where you don't necessarily have to do that. And I think that's actually one where the Fraser Group has done really interesting things there in some of like the big successful companies in Utah for sure.
Peter: But they're also really good at identifying some of these smaller niche businesses that don't need to be worth $10 billion and can still generate a very compelling return for their investors.
Kendall: What we like to think is like by Logo, I don't know, half of your companies might ill or maybe 70%, but by dollar allocation, like 90%, 95% of our money doesn't go into. Yeah, we write like the pre-seed in the seed it's like yeah half half of those or whatever aren't going to be big winners and that's okay.
Kendall: And maybe we wouldn't normally like go out and fund companies that are at like a stage C or D or B. Yeah. For the initial check. But it's different if you're, if you have a board seat and then they outgrow you and it turns into a board observer, But you're still watching then. We do feel qualified to continue to pile money in.
Kendall: Plus you getting money in like in between rounds at those later stages and you're valuing it based on the previous round at that in that case, when you're buying a secondary purchase. So we kind of make up for it later. Yeah, but that's different most, you know, venture funds that are like the seed or the pre-seed deploy like 80% of their money into just brand new logos.
Kendall: First tiny little reserved. Yeah. And I just don't know how they can make money doing that. Maybe they don't.
Jon: Maybe. This is my last question and I don't what other questions you guys have. Does the Frazier group still follow what I call the Frazier Curve? Yeah, we're going to we're going to coin this guy that's going to be a new term of an.
Jon: And the example of one of the most iconic venture investing like presentations I saw was from your dad, probably like one of the second to last. You to Angel meeting. And he talked about when you look at founders like Josh James. So you start all mature. You see a founder who can grow and get a business like a million, 2 million, 5 million, 10 million in revenue.
Jon: And for whatever reason there's a debt and they start losing money and then they go through this kind of like tranche and then they start going back up again. And your dad talked about this being an example of them having to learn how to like retool, learning how to shift, how to pivot.
Kendall: And he it's just the company finding product market fit and it takes a long time. So even if the people are the same, it just takes.
Jon: The dust or follow that model or is that he's it's like he's like, I don't care if I hate the idea if I if I see this this rise where they can get to significant traction and then they kind of stall and have to pivot and shift around and they lose profitability once they start coming up. He was like, I don't care.
Jon: That's what I'm going in. That's what I'm investing in. That's what I'm grabbing secondaries. Is that still true today?
David: I think that's something we want to do. If you're looking at a company and I guess it's separating yourself from emotional baggage or all the baggage in the past of like, hey, they raised this money and this went wrong. And you're it's very tempting to avoid those situations because if you then put money in and get it wrong, you're kind of doubly exposed because you you should have quote unquote, known better and so I think it's an admirable thing to just say, look, you know, now is now and then was then and, you know, figure out what went wrong maybe and see if that's that's better.
David: But kind of rambling answer of, yes, you shouldn't you shouldn't hold someone's history against them.
David: More than holding like if they do wrong things or if you know they're they're no different than Yeah.
Peter: If they haven't figured it out, if.
David: They haven't changed then don't throw good money after bad. But I think that's important to just that's.
Jon: Like the phrase your legacy probably gained a lot of it's market valuations were more compressed no one would believe in the founder at that point but it's like here's a team who could demonstrated they could they could execute they recognized they learned to pivot and then they start seeing an uptake again.
Kendall: Yeah, but part of the reason those are good is because other investors act irrationally. And so if you're up their shares, they're selling at rock bottom price when they shouldn't. But I would say in a perfect world, no, because ideally you invest in it and it's just up and up and up. Those are just real rare. We have some of those and we love those.
Kendall: Those are like the best, but it's like most of our investments don't follow that track. And so, like, they'll find it. It was always good from day one and that's great, but there's not a lot of companies.
Jon: Like, yeah, like I like he obviously he didn't others but that was if you saw that trend it was almost like yeah yeah green flag.
Kendall: I would say it's more like David's saying it's it's not we don't look for that and say, well that's a big winner because it's because it had a downgrade because it had a down round isn't like necessarily a plus. We just don't hold it against them. We come in with fresh eyes and we have done well. The latest example, there's probably consensus where we put in like two or 300 K in 2014.
Kendall: They had kind of some ups and downs like that. And then in 2022, now we've put in another like five or 6 million and we got it. Prices that were pretty darn close to that 2014 price because just all the other investors were tired of it and they're like, Yeah, we've heard that story before. It's been on the roller coaster, but it was more based on looking forward and seeing the traction and having that board seat for so long than it was the actual roller coaster.
Kendall: It was just looking forward and not back and then capitalizing on other investor. You just want to get out of it.
Peter: Yeah, well we are co-investors with you guys on that one.
David: You were we actually we approached you to buy your shares and that.
David: Three or four times and you're.
Peter: Like, no, Darren's a rock star.
Peter: What are you talking about? Yeah. So he's going to figure it out. Or did figure it out?
David: We we tried. We tried. I think that's where.
Jon: Darren at consensus. Darren O'Hagan.
David: Darren Got it. Yeah, he still is.
Kendall: He's still the CEO and.
David: Impressive. Great company. You guys stuck through it.
Peter: But I mean to your point, right? Like, they pivoted their business model. They didn't have true product market fit. At least run we invested.
Kendall: No. And then the enterprise from SMB to enterprise.
Peter: So yeah and then they figured it out. They got product market fit. Their metrics are incredible. And at that point, though, like to your point, a lot of people are like, I've been in this for a long time, this deal's got hair on it because like, you know, the valuations are all over the place. They're always, you know, running low on funds.
Peter: They just want out, you know, a lot of people wrote it off.
Peter: Sold, but a lot of people sold.
Kendall: Yeah, you'll get into trouble if you're just bargain hunting. I don't believe in, like, looking for the bargain.
Jon: I've never seen. Your data are the Fraser cult. The Fraser dynasty is to the fore. You have to, as a part.
Kendall: Of this has to legitimately be a company. We want more money into. And then you're like, okay, what are the dynamics of the cap table, the board, the other investors? And you kind of it's.
David: The Warren Buffett put money into a great company at a good price, not a.
Kendall: Yeah. And so it's different for every company, but first and foremost, it has to legitimately be a good company. And then you your get your wheels turning on how you can get more of it.
Jon: for sure. For sure. So let's call it the Fraser Dynasty instead of the Fraser Group deal.
Peter: David Dynasty and we did that.
Kendall: Fraser Brothers.
David: We got to cut Scott out of this.
Jon: That made me sad. I love Scott. Did you like? My thought I took of him.
Kendall: A week ago was fantastic.
Jon: I Should get that printed on a shirt.
David: Thanks for having us. This was really fun for us. Hope. I hope people enjoy it too, But thanks a lot, Don and Peter.
Peter: Yeah, thanks for being on the on the.
David: Part of hanging out with you guys.
Jon: All right. And so this is the first time we've been kind of like messing with this type of flow. Leave comments below on YouTube, on Instagram, on on Twitter.
Peter: Guess what you think? Should you want more of this? You want less of this. You mean how could you not want more users?
David: Smash that like unsubscribe.
Peter: That's right. Smash it.
Jon: All right. Thanks, guys. See?
