332. 11 Unicorns from Seed, Quantitative Decision-Models for Selecting Investments, Thoughts on Male vs. Female Founders & Investors, and Lessons from Larry and Sergey in the Early Days of Google (Miriam Rivera)

Miriam Rivera

Miriam Rivera of Ulu Ventures joins Nick to discuss 11 Unicorns from Seed, Quantitative Decision-Models for Selecting Investments, Thoughts on Male vs. Female Founders & Investors, and Lessons from Larry and Sergey in the Early Days of Google. In this episode we cover:

  • Lessons from the Early Days of Google
  • Quantitative Decision Making in VC
  • Male vs. Female Founder Questions
  • And more! 

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Transcribed with AI:

Miriam Rivera joins us today from San Francisco. Miriam is Co Founder and Managing Director at Ulu Ventures. Ulu has invested in Figure, Palantir, SoFi, Span, Guild Education, and BetterUp amongst many others. By my count, she has invested in at least seven companies achieving unicorn status in the past two years, these wins have made Rivera number one on the Insider 25 list of top female seed investors and number 28 on their seed 100 list of the top seed investors. Prior to founding Ulu, she worked for a number of prominent tech companies, including five years as Vice President and Deputy General Counsel at Google, where she joined as the company’s second attorney. Miriam, welcome to the show.

Thank you so much for having me, Nick.

Yeah, it’s a true pleasure to have you. You’re a legend. And I’m really looking forward to the conversation here. You know, walk us through your background and sort of your initial path to tech.

Initial path to tech, I think started very early. I was in high school, unlike most kids that actually had required computer science. And that was way back in the late 70s and early 80s. So I had three years computer science in high school, which I think set the path for kind of realizing the economic potential of computerization. And I did my first business case in college on computerizing our job listing service for alumni at Stanford University, and really, ultimately ended up in tech after having worked in the not for profit sector, and just realizing I really wanted to be able to live and stay in the Bay Area. And I’d never be able to afford it at the salary I commanded at that time, but ended up really loving tech, and was co founder of a startup worked on the monetization side of technologies my entire career.

Amazing. So you joined Google in 2001, just over 20 years ago. Now. Can you talk to us a bit about where Google was at as a company when you joined?

It was a small company, we still fit in one building was 160 people. The engineers made the servers that, you know, carried our data in the hallway on real Baker’s racks. And it was pretty crazy shop, I remember, my first office was literally next door to Larry and Sergey. And outside, we had a guy that was just buying parts for all of the computer servers that carried the data. And interestingly enough, I think most people didn’t realize that Google was the third largest producer of servers in the world for its own business when we went public.

Amazing. So you left in 2006, it had to be a tough decision to leaves a company that was accelerating so fast.

I mean, it was amazing place to work. The five years that I was there, between 2001 and 2006, we went from closing an $85 million year to closing a $10 billion a year. And I grew a team from being a second person there to worldwide having a team of over 150, 160 people myself. So it was a tough decision. And I think a lot of the times, you know, I’ve had to make tough decisions as a woman and tech. I’ve left two companies related to issues of being a woman and tech, for example, at my startup, I was basically asked to leave because the investors didn’t want a husband and wife team. And also because I had a child that I was literally told by the Board of Directors, if it were my daughter or daughter in law, I’d prefer her to stay home. So those kinds of days aren’t over yet in tech for many.

Yikes. Miriam, did you have more interaction with Larry or Sergey? And can you share any lessons you learned from either of them about company building?

I learned a ton from both of them and had a lot of interactions with them over the years. So one thing I learned from them was really the importance of who you bring on in a startup. And when you do, they were involved in hiring decisions all the way until the point where I’ve left and maybe beyond that point, they were part of the hiring committee. So that was something that I think really marked their leadership in terms of the value of people in startups. The other things that I learned were to have incredible intestinal fortitude and making really make or break the company decisions. At one point when we were entering into our AOL deal, and this is now public, it’s been published in a different book, the company had the potential to become insolvent if we had to accelerate payments under that agreement. And, you know, I had to talk with the founders when I don’t know that that was really something that maybe he had contemplated that he could have built a company that had, you know, $100 million in revenue and could go insolvent the next year. So you have to be convinced a little bit. But that really was a make or break the company deal. It literally dropped the value of our leading competitor overture in the market by 34%. The next day, and it quickly led us to become, you know, valued at a billion dollars.

Wow. So ultimately, you’ve had a storied career, you’ve had some big successes, you’ve had some challenges. What prompted you to make the leap to the investor side?

One of the things that I saw at Google was in the early stages, it was an incredibly diverse organization. In the 13 original vice presidents, there were three women, there were two immigrants. Sergey Brin was the son of immigrants. And then the first general counsel was African American, the son of a Tuskegee Airmen, the first CFO was Cuban American. So I saw it as a tremendous place of opportunity. And I remember one time, we were setting some financial policy for what had now become a Fortune 500 company, and I looked around the room, and the people in that room, we’re myself, an Afro Caribbean woman from English speaking Caribbean, I am Puerto Rican. And I consider myself Afro Latina. And then the Italian immigrant and a Japanese woman who was then the head finance person for the Tokyo Japan office. And I realized there’s not a white person in this room, really like a traditional white American man at the table. And I saw that that was partly just the diversity of the workforce and of the population that is working in tech. And then I would hear from engineers who were, let’s say, of Indian ancestry, that they were going back to India, because they couldn’t get funded in Silicon Valley, to do a startup. And now I think that’s really, really changed. There’s a real pro immigrant founder ethics in a lot of firms. And I think people from Google are highly valued that had, you know, been early engineers in the company. But at that time, about 14 years ago, things were very different.

Amazing. So you’ve been at seed investing quite a bit longer than most of us emerging managers out there. Tell us about sort of the thesis at ooo, today?

Well, the thesis of Ulu today is actually still very much what it was 14 years ago. And the kind of two founding principles of the firm are that we make decisions using data, and that we make all of our entrepreneurs go through the same process, and ask the same questions of all entrepreneurs, that is done to reduce bias in investment decision making. The other thing is that we will seek diverse teams, because we think that diverse teams are likely to outperform traditional teams. And that’s because we think they bring hopefully different professional backgrounds, different life experiences, and having been in different positions in society, they will also bring a voice for people that are either consumers or users of technology that may not be those for whom technology is traditionally produced.

And then Miriam, do you still have a seed focus? And are you leading? Are you co investing? Or is there a check size range?

Yep, so we are definitely seed. In fact, we kind of consider ourselves a pure play seed. And unlike a lot of firms, we don’t actually want to move up the food chain to be an A, B, or C firm. And that’s because of our mission to be able to demonstrate the value of good decision making process to reduce bias. And also because we want to really give diverse entrepreneurs a shot that is often hard for them to get in Silicon Valley, the cheque size is typically a million dollars, and we invest pretty broadly in enterprise FinTech, edtech, and a number of other verticals.

Can you give us an example of a data point, maybe a question you would ask of an entrepreneur and how that is converted into, you know, a data point in your system? I know much of what we do is kind of qualitative in nature. So I’m curious how you can structure that and systematize it.

So we actually do put a lot of qualitative information into a quantitative format. And I think that’s, you know, there’s places where our judgment is involved. And we’ll look at the judgment in terms of, you know, the risk of the team at every stage in the lifecycle of a company from early stage to Crossing the Chasm to eventually market leadership. Obviously, those are our impressions of this team relative to you know, some of the hunt have teams that we’ve looked at over the last 14 years. And we’ll put a number to it. And the reason for the numbers is to be able to later on, assess whether or not our indications of risk were right or wrong. And hopefully to update that. The other thing that we do is in terms of asking all the same kinds of questions, we start off our market mapping exercises, we call it with total addressable market analysis that’s led by the team. And the team is asked to parameterize pretty much every variable by a high, medium and low with a rationale for why it’s the high, medium and low. And so what we’re looking for is really an awareness, an ability to assess risk in terms of understanding their own market. And one of the things that we know from recent social science research is that often women are asked more risk oriented questions and men are asked more upside questions by venture capitalists. And that’s true both when the VC is a man and a woman, because bias affects all of us, it is not something that is because I’m a minority, I’m going to be not biased, or I’m a woman, I’m not going to be biased. So we have to actually control for that in our process.

Very interesting. We’re in congrats, by the way on making Insider’s seed 25 list. You’ve said we a bunch of times, it’s clearly the focus is not about you, it’s about your team, how does your team get exposure to every deal? And how can they assess every deal, you know, through these parameters in the system, you know, when often, maybe it’s just a single person that meets with an entrepreneur over zoom.

We kind of do things a little differently. So yes, any one of us can meet with an entrepreneur and have a first meeting. And then in our pipeline discussion, we’re going to decide what goes on to a second meeting as a team. And then the team often and depending on the company, there’ll be potentially different people in the room. But there’s often multiple people in the room and that second meeting on zoom, and one of the things that we’re trying to get is a read on that company from the different interdisciplinary perspectives on our own team, in terms of people who are stronger, and finance stronger, and marketing stronger, and regulatory, you know, there’s a bunch of different factors that might be relevant to a particular company. So we want to have those viewpoints in the room. The process, then if the second meeting goes, well, would be to do some of the background diligence. And then we would move on to the market mapping, which is used to be an impersonal exercise. Now it’s completely done on Zoom. And we will also typically have multiple members of the team involved in that process, and actually in the process. So for example, one person may be facilitating that discussion to structure the total addressable market in a way that makes sense for that particular business. Another person may be checking data sources, as we’re needing them and or kind of validating some of the things that an entrepreneur is saying about their market, another person may be modeling. And you know, frankly, a lot of the times, I’m considered a somewhat the empath on the team. You know how they had that in like Star Trek, they would have an empath, who was part of the team, because when you’re dealing with different cultures, you might need to have a different facility with that. And so I’m often observing, how’s the team dynamic working, you know, are different people participating? Are people having fun together? Or they’re being respectful towards each other when they have differences of opinion? And so those kinds of observations are going into our market map.

Does your your firm assign attribution to specific deals?

We do not assign attribution to any deals. And I think we believe that, but for the others on the team, we would probably not be making the quality of decisions that we are that has led to us having 11 unicorns and three public companies today.

Interesting. You know, I noticed your husband and partner Clint Korver came in higher than you on this ranking on this list. He was in at 26. How do you explain that when your firm doesn’t assign attribution?

I don’t know what the algorithms are, that were used to make these placements. And frankly, I didn’t even know that this was happening. Like we got it yesterday when it went public. And it was kind of a lot of internal discussion about, well, how do we really feel that and we’re really thankful for the recognition of our firm and the work that we’ve done both because we want to bring attention to diverse entrepreneurs and how they are just kicking ass. And to because it’s actually more difficult, I think for women and minority led firms to raise capital So if it helps us be able to raise more capital so that we can give those diverse teams a shot, we’ll take the publicity any day, and we’re thankful for it. But I think it’s hard for us to know why one of us would have ranked higher than the other. Because even though we might each think the other is the better investor, we know that but for the gifts that each of us bring, this firm wouldn’t be able to achieve what it has.

Right? I mean, it must be very nice to me to make the list here and to be recognized for all the efforts and the successes of the firm. Also a bit curious why, you know, in light of the fact you don’t assign attribution, why one investor would be above another, but that’s not really for me to even discuss, because I don’t I don’t know how they do their their algorithms and how they do their assessment.

Black box.

Yes, right. So moving on here, Miriam, let’s talk a bit about founders and sort of the way you think about diversity. Why include diversity, a diversity mandate as part of your thesis at Ulu?

It’s not a diversity mandate, meaning we have teams of all kinds of stripes, you know, there’ll be all white male teams. So there is not a mandate around it. But we believe as an investment thesis that diverse teams will outperform. There’s a number of data and studies that would demonstrate that diverse teams have a tendency to outperform. So we’ve, you know, we’ve reviewed the data. And for example, the Kauffman fellows Research Center indicated that having a woman on the team tended to increase returns by 30%. And having, for example, founders of color also had a similar impact on returns. But they also found that when you add diverse members to the C suite, even later than the founding stage, you actually increase diversity by 60%. So we’re driven by data like that, in both the public markets, which it pre existed any real studies in the venture capital back company sector, but we hypothesize that the same thing was true 14 years ago. And now data is coming in from both Harvard Business School, Kauffman fellows Research Center to indicate that that’s also true in private companies.

Very good. And how do founders and investors in the audience here, you know, accelerate the process of a more diverse and inclusive tech ecosystem.

But I’ll be 100% honest, we looked at the data between 2005 and 2015, on investments in underrepresented minority founders. And what we learned was that two thirds of the investments made in the United States during that period, were made by firms that had people of color on their partnership, and decision making group. So one is hire diverse people, to be part of your firm, bring in their diverse networks, and hopefully give them real decision making and real economics that align their interests with your firm. One thing I’ve learned recently is that a lot of the funds that are diversity oriented funds that have been raised by bigger firms, actually do not have partners that have economics in those firms, even though they are often the face of the firm with respect to investments in those funds. So I think that’s really something that we need to change as an industry. And I think it’s particularly important when you think about the wealth creation industry, which is assets under management 98% Of all the funds, including from pensions, that include like teachers pensions was predominantly women’s money and public employees, for example, that are often very diverse workforces 98% of the capital that is in their pensions has been invested in white male led firms only.

Well, disappointing. Miriam, I want to talk more about, you know, your quantitative methodology for selecting founders. You know, more specifically, what commonalities Have you found in winning businesses and winning founding teams?

Well, in terms of the methodology, one of the things that’s a little different about it is that it is not a blackbox kind of analytic approach. So one of the things that we do is we’re in this collaborative work environments, kind of whiteboarding environment, we use Lucid Chart, which I’ll plug because Karl Sun, who was an attorney at Google and worked for me at that time, was one of the founders of that company. And the technology is used to kind of facilitate a collaborative picture development of the market for a particular company. And so we’re trying to find out what are the drivers of risk and return? The things that we’re doing are trying to get the best data into that model because obviously garbage in garbage out And so the founders may have access to good data, we may have access to different or better data or better data that we think maybe higher quality. So we’re going to use both. But we’re going to be able to show the founder, where we disagreed on which data was used and why we disagreed with it, we’re also going to share that model, like we literally give them the model, we may get an input model where they can change some of the inputs and see what the sensitivity and analysis is that drove us to make our investment decision as we did. So one of the things that we have found this helpful about that is, we’re making a principal valuation of the company, the founders are involved in the process, they can disagree with us. And often they can change the model to show us where we might have gone wrong. In terms of our analytics, sometimes they’re bringing in like, Oh, you didn’t give me enough credit for my adjacent markets, I’ve really got three proof points here with these companies. And, you know, you’re also welcome to talk to those companies. And so we actually have some real tangible ways in which we’re helping that founder to be able to talk about the value creation model in their business, not just with us, but with other investors and with customers.

And what would you say are the key factors that are driving return? And or the risk side of the model?

That really varies a lot by companies, right? Because sometimes in certain companies, it will be things like, Well, how much can you sell on a per person basis, for example? Or how many competitors will there be in the market? So there’s different drivers for each company, but we’re trying to develop a framework, that’s a general framework, but each application is particular to a company. And for many founders, it’s like a brain dump of everything that they’ve been worried about and thinking about in their business, and has no place to put and now they’ve got a diagram of the value creation in their business. And they’ve got a model, and it’s one that they can tweak.

Miriam, any commonalities in the businesses that have not worked out? So well, across the portfolio?

Yes. You know, it’s interesting, like, I would say that, you know, founders have got to be optimists, right. And actually, I think venture capitalists got to be optimist too. Because if we look at some of the data, for example, from Cambridge associates, it indicates that the average VC, like out of four to six thousand investments that are made per year at our stage two and a half percent of them will generate nearly all the profit in the industry. So we have to believe we’re going to be the ones to find those two and a half percent companies. And but my sense is that the things that often lead to failure mode, obviously, Team issues lead to the failure modes, but a lack of ability to take in data realistically and act from that data. Sometimes, you know, I call it wishful thinking. There’s a difference between wishful thinking and optimism that I think is super critical in terms of entrepreneurs success. And so you know, when they see things taking longer do they take the hard actions that need to be taken, like, you know, reducing salaries in enough time or, you know, reducing expenses, cutting people that are not in the direction where the company is moving if they need to pivot? A lot of the times, if you’re engaged in too much wishful thinking, you just won’t give yourself enough time to actually achieve success.

Interesting. Miriam, you’ve been investing at seed now for over a decade, aside from increasing valuations and lots of capital flooding the market now, you know, what are some of the biggest changes you’ve observed sort of at at the startup level, over the years?

I mean, when we first started, probably a seed round was $500,000, of capital, which is one of the reasons we picked it because we started the family office, and we had a portion of our capital that we had made in the Google exit that we were applying to our angel investing, you know, we ultimately invested like $3.6 million in what is kind of characterized as fund one. So smaller seal size, also the incredible geographic spread of companies. And that was true even before the pandemic, but I think it’s become absolutely true now, where a lot of the development teams of our diverse teams happened to be in other countries, many of the times they have relationships because they went to engineering school in India or Mexico or Columbia or wherever. And that is one of the advantages that they have in terms of having a lower cost of debt. element of technology. So that’s been very interesting. And I would say that the explosion of FinTech in our portfolio over time has been really amazing. And as a person who’s kind of lived through, you know, the computerization, like, you know, I literally worked on the first personal computers and an intern program that I participated in, you know, 83, let’s say, and then the first software for the personal computer, so I got to be a part of that whole revolution. And then when I worked on the Infoseek IPO, which was a search engine company that predated Google, there were 30 million users on the entire internet. So I’ve seen this the cycles of technology. And one of the great things that companies like Facebook and Google have achieved was that they were the first organizations to a billion participants in the history of mankind in the sort of timeframes in which they were raising the companies. So one of the coolest things about my career has been observing this change in technology. And when you know, Google and Facebook got to be the first organizations that reached a billion people apart from television in the world, I saw the huge impact that that could have. And one of the areas where I think that’s really playing out now with 5 billion users on the internet is in financial services, which is obviously also one of the most outdated technology industries, you know, they’re still having people that are programming and COBOL, at some of the major banks. So I think this is really ripe for disruption. And I think one of the reasons the Federal Reserve Bank and other government institutions are really trying to understand blockchain and crypto and potentially facilitate the use of technology in certain markets like financial services.

And are you all at Ulu investing actively in web 3 and crypto and blockchain?

Yes, we have a number of investments in fun two that use blockchain technology. One is in the real estate area. And, and some of this is really about democratizing access to capital in a lot of different ways. So petoro, is a company that is bringing the ability to have investors that are much smaller, invest in infrastructure type projects, like, you know, let’s say, a railroad, a dam, electrical generation, for example, very expensive kinds of projects, that are really the reserve of a very few types of investors in the world. And they hope to make it much more accessible to a mainstream financial services organizations or real blocks, which is a blockchain that helps real estate funds be able to raise capital as well as to be able to have interests that are much smaller and much more tradable than what we’re used to in typical assets under management funds, and figure and provenance are their own phenomenon as well. And obviously, that has really changed some of the ways in which people are doing mortgages, and he locks as well as custody and a number of other types of financial transactions that exist in the real world and trying to bring them onto the blockchain and make them cheaper and more transparent, could help the whole economic system ultimately, to be able to make better decisions.

Miriam, what are your thoughts specifically, with regards to venture capital on interest becoming more liquid and secondaries markets sort of evolving?

Well, we’re invested in a number of companies that we think will help facilitate that change. And again, part of our mission is actually addressing the wealth gap through increased access to capital, because the world capital markets have literally been so skewed, that it’s hard to even imagine that, you know, so much of the United States wealth is in the hands of such a non representative group of Americans. So from our point of view, we really welcome the opportunities that Fintech is creating. And I think we’re still obviously very concerned that this be done in ways that are legitimate, you know, and then don’t undermine existing ways of doing business and aren’t really just about facilitating illegal acts. So we have to be really careful walking that line between innovation and regulation.

That’s right. That’s right. Move fast and break things but break things ethically. All right, Miriam, this question is called three data points. I’m going to give you a high pathetical situation with a startup. And you can ask three questions for three specific data points. Let’s say your approach to invest in a seed stage startup, the company is based in San Francisco. Let’s say the sector is FinTech as we’ve been talking about FinTech, they have 250k of ARR. They’re growing 20% monthly. Again, the catch is you can only ask three questions for three data points in order to make your decision. What three questions do you ask?

So the first question I would ask is, why are you doing this? What got you into this business? I want to understand the founder motivation. The second question I would ask is, who is your customer? You know, I think the last question depends on the area. A lot of the times in FinTech, there’s a regulatory question. Even in edtech, there’s kind of a regulatory question. Some of the companies that we invested in have no awareness of things like student privacy and edtech, or regulations related to know your customer in FinTech. And so those are indicators that we’re going to be in a different relationship with that organization than one that is highly sophisticated, and is already thinking about like, Oh, we’re gonna hire a former adviser who was an SEC commissioner to guide us through this process on regulatory like, okay, good.

You know, one more question on the model. Was this something that you and Clint develop when you began and started the firm? Or is it kind of been an evolution of thought and sort of codifying all these instincts and qualitative factors, you know, over time, can you give us a little more color on that and how it’s come together.

So Mike is a PhD in decision and risk analysis from Stanford, I met him in a business school class where we were paired in a negotiation, and I happen to end up being the best negotiator in the class. And so we ended up becoming friends. And I ended up taking decision analysis in the School of Engineering and thinking, as time went by that this is like the best way I could imagine to make decisions. So we quickly implemented it as just our way of living, if you will. And everything that’s kind of an economic decision, or a career decision has kind of been running through some sort of decision analysis. And we literally indoctrinate our children. When they’re about to make a decision about what school they go into, you know, we make let them make the decision when they apply to like private school or college, they get to make the decision, but we help them with the process. So it’s been under development for a long time, Clint had used it with many Fortune 2000 companies over the years, but he had developed a special framework around it. This was developed at Stanford, Professor Ron Howard, who is a very dear friend of the firm, is one of the great practitioners, he helped create a strategic decisions group, which is one of the leading proponents of this in the consulting world. But Clint helped create a Turbo version of it. And it’s because of that Turbo version, that we’re able to actually do this with entrepreneurs. And so it’s gotten more and more simplified over time, so that it can literally be done in three hours. And we think we get a huge amount of value from it. And we think the entrepreneurs also indicate that it’s a value to them in our diligence process.

And how do you assign the weighting of different factors when, you know, often business types can be highly variable and markets may be nascent?

It’s really a Fundamentals Analysis. So we’re looking at like, oh, well, you know, if you have a business model, and how much can you charge? What do you think the range is at the high, medium and low for that amount? How many people are there in your target customers that will be users of it? How will you market this in terms of is it a, you know, more consumer oriented product? Is it an enterprise product? Are there other modules or adjacent markets that you can pursue afterwards, but everything has got like a high, medium and low associated with it. So we don’t really assign weights and ranks to things. What ends up happening is that we literally run all of those permutations in a model. And we end up doing sensitivity analysis to see which of those factors is actually the most influential in terms of return. And then we look at that sensitivity analysis as a map for how we conduct our diligence, the ones that are going to be the biggest drivers of return on risk. We’re going to spend more time on in our diligence process.

Miriam, if we can feature anyone here on the show, who do you think we should interview and what topic would you like to hear them speak about?

I think you should invite Clint Korver to come in and speak to a real particular reason why then also working with him on a paper on portfolio construction, but I think it’s a A really multifaceted look at portfolio construction and how founders of firms should think about it and what aspects of it may be different. I think one of the things is that so many people have this sense that portfolio construction should be just about the same for everybody, like, oh, you know, we should have this concentrated basket of stocks, and then we should watch the basket. You know, and that’s really not true. We think when you look at the underlying risk in, for example, in our stage of investing, I think he’s going to look at that. And we’re also looking at what are the cultural implications of having a large portfolio construction, and of having the belief that really nobody can pick winners. So we’re trying to do is improve our decision making. And we think that increases collaboration and teamwork in our firm. And that that is one of the things that helps us help our companies.

Amazing. I mean, that would be a very good topic to cover on the show. And it’s very timely, do I get a lot of questions from emerging managers on that very topic? And I’m no expert on it myself. Miriam, do you have any tools or hacks that are a secret weapon?

As much as we talk about methodology, I mentioned that I’m kind of an empath. And I think in our firm, my ability to kind of connect with people is one of the secret weapons that we have as a firm. And I also think that just honing my intuition in so many different ways over many years, one way was not a very fortunate way, I grew up in a very physically abusive family. And one of the things I had to learn as a kid was, what’s the mood in this room right now, I need to be able to kind of know whether it’s the sort of place where I need to like tiptoe and move away from or can I enter safely. So I learned there, over many years of doing deals, I’ve learned so much about the people in the room, their motivations, giving people the benefit of the doubt, even under challenging and difficult negotiations. And then in hiring, for example, to hire my team of 150-160 people, I read 5000 resumes, I interviewed 500 people. So that is really helpful in terms of I think, supporting our founders in hiring decisions from key people, if I get a chance to meet them, I think that’s a very important thing. Because I think at the early stages, people and relationships really matter in building value in companies.

So sorry to hear about, you know, the the challenges in childhood, but it sounds like you’ve used it to your advantage. Are there one or two key questions that you ask in a hiring process of a potential candidate that cut through the noise and kind of help you get a quick read on whether they’re a potential fit?

You know, I really love to hear people’s personal journey to entrepreneurship and to this particular company, and part of what you know, I know different people call it something like we call it insight at, at Lu. Some people call it a secret, like, I think Andreessen says, We want people who have a secret, and it’s a knowledge that they’ve developed from lived experience. And so we’re looking for insight into a particular problem or a particular market that’s based on lived or worked experience. But often, it’s kind of the journey that led somebody to be an entrepreneur is also a really important part of whether or not they’re going to have the grit and stick to itiveness to remain focused on a particular problem for a long enough period of time, and be willing to make both the sacrifices and difficult decisions that lead to ultimate success. So from my point of view, as you know, maybe the impasse in the team, that is often a very important part of the diligence. One thing that I learned from another PhD Samick Raha, who was a senior associate with us for a time at Ulu. He did his research with people talking about themselves with sensors on their fingers. And I think it was the heart rate monitor. And when people are telling stories, and you know, one, they might have to be a skilled storyteller, but people get into alignment in terms of their heart rate and their brainwaves in storytelling. So when we talk about storytelling, and I know people say this adventure all the time, you are actually having a biological impact on the listener. And so being able to hear those stories, find the incongruence in the stories, be able to assess, you know, what resonates what doesn’t resonate is actually a skill that helps you understand the author anticipate the story and to make your decision about the people, which is really the first failure mode of startups where 60% of companies fail because people and teams don’t work well together.

Amazing. And finally, Miriam, what’s the best way for listeners to connect with you and follow along with Ulu?

I posted a lot on LinkedIn. So you know, that’s a good place to see what we’re posting about in our companies and their great accomplishments. And in terms of connecting with us on our website, if you’re looking to have your deal, or your company looked at by Ulu, we do have a process where we try to do the intake in such a way that we’re actually able to collect information about the diversity of our teams and be able to report from kind of onramp to final decision, are we really moving that pipeline forward in a way that is reflective of what comes into our pipeline? So please help us with that process by using that button on our website. And then of course, my email is Miriam at uluventures.com.

She is Miriam Rivera. She is a legend in seed. And I know so many people that are going to be really excited to listen to this interview. Miriam, thank you so much for spending the time today. I really enjoyed the discussion.

Thank you, Nick. It’s been a real pleasure.

Transcribed by https://otter.ai