EP13: Greg Raiz - Data driven Founder Selection

Martin Tobias (00:01) Hi, this is the first bet. And every successful person gets asked about, you know, their successes, but very few people go back and ask people about the you know what was going through their mind before they placed the bet in when the information was l very small and they had to put their money on the line anyway. And that's what we talk about here at the first bet.

I'm Martin Tobias and I've made bets three ways as a CEO, as a VC, and as a poker player. And my guest today I've known for a long time. His name's Greg Reyes. And you know, one of the first bets he made, he walked out of Microsoft in 2003 with a laptop and conviction to start a company and ground away at it for quite some time, but it ended up as an 80-person company and he got a decent exit. After that.

he went on to run Techstars back east and now he's running his own fund, Founders Edge. And he has a really interesting survey that he's done for hundreds of founders, which maybe we'll talk a little more about that helps him sort of operationalize how to identify a good founder. And I'm really excited to talk to you today. Welcome, Greg.

Gregory Raiz (01:14) Yeah, thank you so much. Appreciate appreciate you having me on. It's it's been quite a ride and every day I'm learning and and diving into both the investment side and the operator side. So it's it's great to be on here.

Martin Tobias (01:26) Yeah. And I I saw also you you know, you've gotten real AI pilled and I appreciate it. I saw one of your webinars you talked about peop how to set up a chief of staff on Claude and the fact that you're still learning and upgrading your skills after all this time is I I think one of the key things about being good at making decisions is you know, catching on and and continuing to be curious about the new things that are going on. So before we started you talked about

you know, what your first angel investment was and maybe you could take us back to that first angel check and then we can move into some of the things you've learned over the time about how to make the the the capital allocation decisions when you didn't know anything. Maybe tell us about that early angel check, what you what your thought process was and what happened.

Gregory Raiz (02:12) Yeah, absolutely. I think when I was first getting started in angel investing, I was really still an operator. I was running my company and I had a little bit of, you know, I had we sold to a private equity company. So I had a little bit of cash, but I was still with the current company. I was doing the earnout. And so we had moved into a giant space and we wanted to have a number of startups in around our midst. And so we ran what I would

considered like a pseudo accelerator. It was like a non-equity accelerator. We brought in a bunch of companies. And the thing that was actually helpful was we got to see how those founders and startups operated. Like I think a lot of times, certainly in the angel investing side and certainly when I was doing tech stars, the amount of information is pretty limited. But when you see how teams are actually operating and what value they're actually driving, how they're

kind of interacting on a day-to-day basis, you get true insight on how teams execute. And this was an early stage team.

Martin Tobias (03:10) Fixed.

Gregory Raiz (03:11) they were interestingly enough, and this goes to some of our now thesis, but a little more experienced in terms of founders, like they were a little bit older. I think a lot

Martin Tobias (03:21) Uh-huh.

Gregory Raiz (03:21) of folks would have said like, hey, maybe you're not kind of the

Martin Tobias (03:24) Maybe.

Gregory Raiz (03:26) the quote unquote, you know, Harvard dropout or the the quintessential

Martin Tobias (03:29) Yeah.

Gregory Raiz (03:30) Zuckerberg or Peter Thiel.

Early stage founder, but they're a little more experienced, but they had a deep founder market fit, just incredible founder market fit around real estate and prop tech. And so their general observation was that they'd sold, I think, a close to a billion dollars in property and real estate by on the broker side. And they said there's huge inefficiencies in this, and we think that software could go solve these. And again, like I I wasn't necessarily a prop tech investor. I didn't have a lot of deep understanding of that space, but I could see A, how they were executing.

And how they were communicating

Martin Tobias (04:01) Uh-huh.

Gregory Raiz (04:02) and some of the things that they were doing early on. And ultimately they said, look, there's this huge inefficiency in PropTech where you have to go to a middleman, a player, who will essentially charge you know, a couple thousand dollars to sell you a mortgage. And the interest rate on that mortgage isn't really optimized. And they're like, we can do this way better with software.

And nobody's really doing this. And so I kind of called BS on them. I was like, yeah, this sounds like a good idea, but like, how do I really know? And they said, well, we'll save you tens of thousands on your mortgage. And I was like, okay, well, that's a bet. Let's let's go. And so they

Martin Tobias (04:39) Yeah.

Gregory Raiz (04:40) they actually said they had a little Google form. I mean, the software was very thin, but

Martin Tobias (04:43) Sparkle is very thick.

Gregory Raiz (04:44) they literally set up a MVP, which was a Google form, filled in a little bit of information, and then they were like, we can plug it into our back end and get you an answer right away. And I had my real estate.

mortgage broker. And so like, I'm gonna call Donna. And so Donna

Martin Tobias (04:58) Mm-hmm.

Gregory Raiz (04:58) got me a rate and they got me a rate. They saved me like 30K on my re

Martin Tobias (05:02) Wow.

Gregory Raiz (05:03) refinance. And I literally like, okay, that's your angel check. And so I invested in them. And they recently had an exit close to 300 million dollars. So it's a great great, great early entry. But you know, definitely a couple learnings from that and certainly things that I've carried away is that the a lot of the research and a lot of the data that we've leaned into is

more experienced founders tend to outperform the and founder market fit in particular. So like really knowing your domain space and go to market within a vertical huge advantage in terms of execution.

Martin Tobias (05:37) Right. So that's something you had in the back of your mind when you made that check. And the other framework that you said, which I think you replicated a lot at Techstars, was one way to close the information gap is to watch these teams execute over a little bit of time before you write the check. And in your case, it was, you know, don't tell me, show me and they showed you a thirty thousand dollar thing and you're like, Okay.

And I think that's another way to reduce your information asymmetry is to watch people and and and and actually experience the value yourself or w with one of your customers. What are so let's go b back like that was an angel investment and and how did you did did you learn anything else when you went to tech stars?

w was it a similar process or what are some of the things you learned seeing, you know, a hundred hundreds of companies

going through tech SARS?

Gregory Raiz (06:36) Yeah. Yeah.

One one of the things kind of as I started angel investing is like you know, I'm an engineer by training and education. I went to school for computer science. I worked at Microsoft, it was my first job. And so I had kind of this analytical, you know, how how do how should I think about this? And I was also like I I knew I had no idea what I was doing. Like when I entered and started angel investing, I was like, I know I I don't know what I'm doing. And so I joined I think seven angel groups just to see.

How are people operating? And I think my goal high level was surround myself with people who I felt were smarter than me or had more experience or depth or or whatever. I gotta say, like I lost a bunch of money angel investing. Like it was not really fruitful. And I think part of it is that that the folks who tend to angel invest, and again th there are different classes, but especially a lot of the angel groups tend to not take it particularly seriously.

And so they're not digging into the data, they're not doing the research. They're

Martin Tobias (07:34) Yeah.

Gregory Raiz (07:36) kind of there's a lot of like, I like this idea, I like this founder.

Martin Tobias (07:38) I'd like to make that like send that right.

Gregory Raiz (07:39) And one of the things I was looking for was like, how do we get really, really good at this? You know, fundamentally my belief is that the world

Martin Tobias (07:43) But how do we get the roads? You know, otherwise we invite ease.

Gregory Raiz (07:47) needs a lot of change and that entrepreneurs and founders are the best people to create that change. And so for me to kind of have the best impact, I have to get really, really good at investing. And so I was looking for data and research. And so

Again, my initial stab was like, let me surround myself with a bunch of other investors. Maybe they have the research and data from our first hand. And I really didn't get significant signal. Again, I learned some of the methodology, some of the language around, you know, safes and convertible notes and kind of some of those things. But I went to Techstars looking for deeper data. You know, Techstars obviously one of the leading accelerators. They've seen hundreds of thousands of companies and

I was looking for that institutional knowledge around, okay, when you operate at scale, what are the things that are significantly beneficial to founders or to founder success or investment success? Every managing director across Techstars

Martin Tobias (08:39) He missed your record.

Gregory Raiz (08:41) kind of had their own way of doing this. And I was really looking

Martin Tobias (08:43) Right.

Gregory Raiz (08:44) for quantified data. I'm actually an LP and maybe two or three you know, former Techstars managing director.

Funds and again, they're all super smart, but they have very differentiated approaches. And so early on, I actually wanted to study the data. And so I had a hypothesis. and the hypothesis was that there should exist questions that if you

Martin Tobias (09:05) It's just a question.

Gregory Raiz (09:07) ask a founder, those questions are more predictive of higher success. And so the

The reason I thought this hypothesis could be true is

Martin Tobias (09:15) Headbox of headboxes of the computer.

Gregory Raiz (09:17) because there's empirical data that serial founders tend to outperform. And so because

Martin Tobias (09:22) Yeah.

Gregory Raiz (09:22) serial founders outperform, I'm like that there must be something either that they know, something in their network or something in their ability to execute that de-risk their investment. and again, I wasn't quite sure what that was. And so we came up with a whole series of kind of hypothetical questions that could be predictive,

like.

You know, have you ever played a competitive sport? Do you play a musical instrument?

Martin Tobias (09:45) Mm-hmm.

Gregory Raiz (09:46) Are you creative? You know, how long have you known your co-founder? How much market experience do you have? How much domain? Where did this idea come from? Did you patent it? Did you incorporate? Is this your first company or your seventh company? And the idea was to collect this data. We we surveyed and collected data from a little over 3,000 entrepreneurs. About 10% were high exit entrepreneurs, folks who had had seven, eight, nine figure exit.

To try to understand what these things

Martin Tobias (10:10) Mm-hmm.

Gregory Raiz (10:12) appear to be a little more predictive. And over the last I've been running this research just internally within Founders Edge for about three years. We just did another batch of this over the summer. And again, going deep using, you know, modern AI tools and things like that to read hundreds of research papers and studies across tens of thousands of entrepreneurs to try to distill what are the things that that are more predictive of higher success.

Martin Tobias (10:38) Mm-hmm. And that's the this founder's edge profile. So it seems like

Gregory Raiz (10:43) Hey.

Martin Tobias (10:44) you start you started saying I met an interesting guy, he delivers some value, and I went to Techstars to try to find a little more structure, didn't find enough structure, so you started to build it a l a little bit more yourself.

Gregory Raiz (10:57) Yeah.

Yeah. I think even more so for myself. Like when I exited my company, I started to kind of look inward and I was like, okay, I'm an immigrant founder. You know, I worked at Microsoft, which is, you know, large tech company. My co-founder was someone who I met through college. you know, are those things my father was an entrepreneur, like some of these are kind of entrepreneurial tropes. And I started to wonder, like, how much of that is actually significant data and how much of that is coincidence. And

From an investor side, are these important signals to go look at or not important signals? Like some funds in particular, you know, they have a thesis around immigrant founders. And so I'm like, well, yeah,

Martin Tobias (11:36) Sure. Eh's.

Gregory Raiz (11:38) yeah, there's a number of them. And I'm like, okay, well, how much of that is their quantifiable data? And can I validate that data myself? because I I think there's a lot of myths in investing. And so I'm trying to figure out like what is actual signal, what is noise.

And how do we use that signal to become better investors?

Martin Tobias (11:58) Yeah. that's certainly one way to to bridge the low information thing is to just get better much, much better at pattern matching. matching it's not pattern matching?

Gregory Raiz (12:07) Well it's not pattern matching. I I think that that's actually the the

the yeah, that's the challenge is that pattern matching humans are really bad at pattern matching, right? And so I

Martin Tobias (12:16) Yes, they are.

Gregory Raiz (12:17) I I didn't want to pattern match because pattern matching leads to bias. And so what I really wanted to do is I wanted to say like quantifiably, what does the data say about this founder? Now, pattern matching is what I do after that. And so again, like we have hundreds of founders who may come in via the website. Like I

don't want to bias them based on pattern matching. I want to know quantifiably, you know, again, I'll get warm introduction to founders, you know, that that's a little bit different. But if I'm looking at founders who apply cold, how can I use data to de bias my own investing to make sure I'm investing in truly the highest aptitude founders?

Martin Tobias (12:52) So so you give all of the founders that come into you this survey and what are the if you if you're if I don't know if you shared it publicly, but through this research of three thousand founders, what are the top sort of two or three things that you have through data found to be correlated to success? You already mentioned one, a little bit more of a mature founder.

Gregory Raiz (13:11) Yeah, it it

experience and founders, founder market fit are actually vr surprisingly incredibly important. relationship and co-founding team is really, really important. And so you know, th those are three aspects. I think high level, you know, all the all the typical things that, you know, investors talk about, you know, grit and determination, those are also important, but they're harder to quantifiably

measure.

Martin Tobias (13:34) Yes.

Gregory Raiz (13:34) And we

kind of use our early screen to be like, okay, is this a first-time entrepreneur or third-time entrepreneur? Being a third-time entrepreneur with no wins under your belt is less important than being a third-time entrepreneur with several wins under your belt. you know, entrepreneurship is a game and really the data shows that the more wins you have under your belt, the more likely your next win is going to be a bigger win. And so

Martin Tobias (13:58) Mm-hmm.

Gregory Raiz (13:59) domain experience is super important as well. So

If you're a third time founder building in the same vertical that you have prior experience with, that's actually super predictive of additional wins. But if you're a third time founder building in a completely different domain, you're actually

Martin Tobias (14:13) Yeah.

Gregory Raiz (14:14) same as same as average. You're not necessarily gonna outperform.

Martin Tobias (14:18) Yeah, yeah. I've I I I've seen that. But the three things you just mentioned are also things that you don't hear as much in public because in in public you you know, people are like, Stanford GSB, MIT, X Microsoft, and you didn't find I've talked to other people who've done research on it and they've found no correlation between where

Gregory Raiz (14:40) Yeah, we

Martin Tobias (14:40) you went to school or where you worked and your future startup success.

Gregory Raiz (14:44) Well

yeah, what we found is that school is predictive of funding, not of success. And so if you have a high

Martin Tobias (14:49) Yes.

Gregory Raiz (14:50) degree of from a a prestigious university, you are more likely to be funded because that is a bias in the investing kind of ecosystem, but it doesn't actually predict higher returns or success. And so execution is, you know, and so again, there's different ways to to do execution, but like one of the questions that we ask is, and

Again, we validate some of this, but like we'll we'll ask, how do you track your metrics? You know, it's a simple question. Like, I don't track your metrics, I have a spreadsheet to track my metrics, I have a third-party tool to track my metrics, or I've developed my own tool to track my metrics. And again, like the the teams that are more sophisticated in terms of how they think about success, you know, they're executing, right? They're not talking about it. They're they're out in the arena building it.

Martin Tobias (15:37) They're probably gonna be the ones that built their own tool to do it or have an and Yeah, yeah.

Gregory Raiz (15:39) Yeah. Yeah. And so th those are simple things, right? We'll we'll ask

people a simple question, how do you execute? You know, what show me something that that you built that is impressive. And again, when founders can do that very easily, like it's not it's not difficult for an exceptional founder to say, look, I built this thing, it's on GitHub, or I built this thing, this is the website, or I built this thing, this is the company sold or exited. But we see a lot of founders who we ask the show me something that you built, and they have they have a hard time showing something that they built.

And again, that that's an element of execution. We see incredible pitch decks with poor execution. Like a lot of our focus is actually that pitch decks are kind of BS. they're a little bit of startup theater. Like, I'd rather invest in a founder who can really execute and build great product, but he needs help in building a pitch deck. In fact, we have a great story of that. We had a founder who submitted via our website.

And we're looking at the pitch deck and it's awful. Like it we can't make

Martin Tobias (16:36) Mm-hmm.

Gregory Raiz (16:36) heads or tails of it. It's really confusing, but like the founder index score is really, really high. Like the our AI model is essentially saying there's something really interesting about this founder, but we're looking at the pitch deck, we can't make heads or tails of it. Like deep on page nine of his pitch deck, it says he's the third time founder, building his third company in the same domain.

Martin Tobias (16:57) Mm-hmm. And you're like, why isn't that on f slide one?

Gregory Raiz (16:58) He'd bootstrapped us well, he had in

he had bootstrapped his first two companies. He'd never done a pitch tech before. And I'm like, Okay,

Martin Tobias (17:05) I see.

Gregory Raiz (17:05) that's an easy thing to f like we can show you how to build a pitch deck. It's really hard to show you how to build and scale a company.

Martin Tobias (17:14) So as someone who's made a lot of investments and you you have a lot of data, you've just mentioned a few of the things that are highly correlated, you think to success, which is how you one of the ways you make a decision to to to write the check. what are some of the things that are the cases against, or what are some of the things over the years that you've learned are either not correlated or negatively correlated to returns that would turn you to a no?

Gregory Raiz (17:41) I mean it it's it's all the the ante of that. And so it's it's lack of technical skill or technical ability. And this is definitely some of the early mistakes I made in angel investing, where I had a really charismatic, strong CEO, but the really strong CEO wasn't paired with the strong technical talent to go build that product. I can probably name seven or eight companies that you know just went

belly up because they couldn't recruit the technical talent to build. And so build execution is definitely something that I've learned a pa

Martin Tobias (18:14) Build execution.

Gregory Raiz (18:15) painful and expensive lesson. and so yeah, build execution, team cohesion is another one. And so one of the things that's pretty predictive of of startup success is the trust factor between a founder and a co-founder and kind of how well do they work together. I think

you know, I I D C had some study on the top reasons that startups go out of business. About I I wanna say about twenty to thirty percent of businesses go out of business because of founder co-founder disputes or conflicts. Yeah. Yeah, it's pretty high. And so,

Martin Tobias (18:44) I've heard numbers even higher than that, but yeah, it's it's a a top number. It's very high.

Gregory Raiz (18:49) you know, the how the founder and co-founder know each other, how they've worked through adversity. One of the questions that we asked early on, we we don't ask this anymore, but variations of this question is you know, has your co founder let you down?

And you would think that, you know, having a co-founder let you down would be a negative thing. It's actually a fairly positive thing to the predictability of the success that when a co-founder relationship has been strained, when you've actually tested that relationship and you've been resilient past that, that really is a sign of a stronger founder-co-founder relationship. If like everything is hunky-dory and we met at co-founder matching and we built a prototype over a weekend and like please fund us.

Like that relationship really hasn't stood the test of time or kind of the stress of

Martin Tobias (19:35) Exactly.

Gregory Raiz (19:36) s of startups. And so making sure that that that kind of the the the depth and complexity of of truly being co founders with one another when things get hard.

Martin Tobias (19:46) So so so here's a question. do you back solo founders or do you require co founders?

Gregory Raiz (19:52) We have back solo founders. we the the data is seems to point in the direction of co-founders being strongly predictive. in fact there's some some research that it's a almost a linear correlation with more co founders being better. teams of

Martin Tobias (20:08) Yeah.

Gregory Raiz (20:08) three or four or five are even even better provided that the team is strong. Like when you have larger co founding teams, effectively you're getting significantly more sweat equity.

for you know again typ typically you're not paying early co-founding teams a lot. And so this is your ability to convince four or five other really smart people to work with you on a particular business that that's likely to be a strong business because all of those smart folks have to agree to invest their time and limited life

Martin Tobias (20:42) Mm-hmm.

Gregory Raiz (20:42) resources to building that company. I think Alibaba had sixteen

Martin Tobias (20:45) Yeah.

Gregory Raiz (20:46) co-founders or something crazy like that.

Martin Tobias (20:48) I I didn't know that. So for the for the solo founders, if there is a data that shows that multifounders is better, what gets you to a yes on a solo founder? Is it looking in his past, his ability to recruit people you know, in the past, or what gets you to a yes on a solo

founder?

Gregory Raiz (21:05) Yeah, I mean the the we we've done one deal with the solo founder and this happened to be a founder who had eight prior companies, two of them which were quite successful. And so again, not super typical, but definitely like, okay, this this is super interesting in terms of founder experience and founder depth.

Martin Tobias (21:22) 'cause he since he'd done other companies, he's proven that he 'cause that's for me with a solo founder, the issue is always why are you a solo founder? If you've not been able to convince anybody else who's smart to come along this journey with you, you know, it's gonna be hard to to scale this and I'm gonna have a I mean, it's got to scale and and and if you're not a proven sort of talent magnet, sometimes you meet early enough where they just haven't pressed the gas on the talent magnet, but they've proven they've been a talent magnet before.

Which gets me to a yes on a a solo founder. But I'd prefer

Gregory Raiz (21:53) Yeah, I think

Martin Tobias (21:54) this to see that talent ability, you know, before we write the check, frankly.

Gregory Raiz (21:59) Yeah, I I I

tend to agree. I do I do think there's been a little bit, I'll call it like fashion of like, hey, can you can I be the first solo founder to build a billion dollar company? And again, some founders who have that depth may be able to convince themselves and others that they're the person to do it. But all things being equal, having co-founders is in data shows is super, super helpful to building large companies.

Martin Tobias (22:23) I'm yeah.

I'm not a big fan of this whole idea of solo founders. even though there was that one medical online medical subscription company that got to like a couple hundred million dollars of revenue with two employees. I I don't think that's necessarily the the the future. you could be a solo f you know the question is like would you fund Elon Musk in whatever he did next? He's a solo founder. Yes, I would because he's

Gregory Raiz (22:47) Yeah. Yeah.

Martin Tobias (22:48) proven that

Gregory Raiz (22:49) Yeah.

Martin Tobias (22:50) he can attract the smartest people you know because he's that kind of leader. as long as the person's a a leader, it doesn't matter if they're you know you know enough of a leader. but the idea that he could run any of his companies by himself is stupid.

Gregory Raiz (23:02) Yeah. Yeah.

Yeah. Yeah. And and again, like it's different skills. you know, ha having built a company, like you can't be everything to everybody. And so like, yes, you can lean in more to adjunct tools or skills or services to help some of that. but I do think surrounding yourself with brilliant people will help you execute even faster.

Martin Tobias (23:22) So this is a question I ask everyone. And obviously, you know, you have been somebody that obviously has a lot of confidence in yourself when you left Microsoft to start your own company, when you started writing angel checks, you know, when you started your own fund, when it was a hard time to to raise funding. Where do you think that confidence, your personal confidence came from? You're an engineer. Was it, you know, data collection? Was it the opportunity? Where did the confidence come to take?

bigger risks like a career risk. Leaving Microsoft was

Gregory Raiz (23:53) Yeah.

Martin Tobias (23:53) the safe place for the hard place. You know, you had to have some fundamental confidence. Where did that come from for you?

Gregory Raiz (24:02) Yeah, it's interesting. I I actually think that some of it you know, the optics of what what is confidence versus what is imposter syndrome. Cause I talk to a lot of CEOs, a lot of

Martin Tobias (24:11) Mm-hmm.

Gregory Raiz (24:12) folks who are more successful, they don't necessarily have that bar for themselves that they perceive that level of success for themselves. They just they're just executing. And I'd say, you know, like objectively, I could certainly look at myself and be like, yeah, I've had a lot of career success, a lot of wins. But you're always as an entrepreneur in a

I like to introduce myself. I'm a recovering entrepreneur, right? Like I'm always thinking what what what's

Martin Tobias (24:35) Recovering, yeah. Me too.

Gregory Raiz (24:37) what what what's next. And I think that that element of what's next and how do I challenge myself is kind of how I find, you know, again, I wouldn't necessarily even dub it as confidence, but like I find that like, well, I need to continue to push myself because that's the only way to get better. And so it's that kind of strive for, you know, what what's next? How do I how do I get to the next wrong?

of either thought or process or data or execution or team or whatever it is.

Martin Tobias (25:05) It also sounds like you are an intensely curious person. For me, it wasn't so much confidence when I left Microsoft to start my own company. It was that I was curious about something else and I wasn't fucking doing it at Microsoft. I got interested

Gregory Raiz (25:18) Ha ha.

Martin Tobias (25:18) in this full category of things that I could have stayed at Microsoft, but it would have been it it didn't feed my curiosity, you know? and and and yeah.

Gregory Raiz (25:25) Yeah, a hundred percent. Like I I

yeah, I I'm deeply, deeply curious about a lot of this stuff. And for me it's genuinely fun. Like I am playing with AI tools, I'm installing things, I'm coding my own models, I'm playing with circuit boards, and it's not because I have to or that's my investing job. It's just like I genuinely find curiosity in how do you take these things apart, putting back together and what makes them tick and work, and then thinking through

What is the next stage in evolution of software? And so that kind of thought process of like, well, what's what's next? And how do these software blocks like for me? It's kind of I'm a kid again playing with Legos only instead of Lego bricks, it's like LLMs and AI models and you know, circuit boards and ESP32s

Martin Tobias (26:07) I guess I can have other ends that you have nothing on the last screen.

Gregory Raiz (26:13) and all sorts of other stuff. And like what what can you build and how can you change the world with these new pieces, these new bricks?

Martin Tobias (26:19) Yeah, yeah. I think for me that's a real im important thing to that that that keeps me willing to take low prob make low probability bets is if I'm incredibly curious and if the thing the person's building is something that I really want to be in in you know in in the world. so how would you as we wrap up here, if there were sort of one or two

pieces of advice, lenses or rules or frameworks that you would give to people who are facing their own low information capital allocation decisions? what would those be?

Gregory Raiz (26:54) Yeah, I'd say look look for signals and data. Try to question your own assumption

Martin Tobias (26:57) Signals in data.

Gregory Raiz (26:59) Like there's a bunch of things I thought were true. And then I was like, do I think this is true because other investors have told me this is true? Or do I think this is true? Because I've actually done a little bit of digging to verify if this is true. And then kind of like be intellectually curious with the things that you're doing. Like for me, this is certainly, you know.

Martin Tobias (27:17) Be curious.

Gregory Raiz (27:18) I I I do this, yes, I'm an investor. Yes, it's a financial, you know, I'm a fiduciary, I have LPs, I want to be successful, but I'm like genuinely incredibly curious about how to shape and shift the world and how to help entrepreneurs build incredible companies. And because of that, I think it creates deeper connections with founders and they're willing to refer other founders to me. And that again, fli you know, virtuous flywheel of deal flow and execution.

Martin Tobias (27:47) Absolutely. Well I I appreciate those and thank you for your time. People can find you where LinkedIn, Twitter, your website,

Founders Edge.

Gregory Raiz (27:58) yeah, you can find me on Founders Edge. I'm posting on TikTok and Instagram, a little bit on X,

Martin Tobias (28:03) TikTok.

Gregory Raiz (28:03) but not not as much these days. But you can find me online, LinkedIn and and whatnot and hope to hear from you.

Martin Tobias (28:09) Okay. All right. Thanks for your time, Greg.

Gregory Raiz (28:12) Awesome. Thanks, Martin.