Secrets of Innovative Angel Investors

Hey everybody, welcome to this Founder Institute webinar. My name is Jonathan Gruetchen, co-founder and CEO of the Founder Institute. We had over 900 people register for this event today, so it should be a pretty good crowd. And I know for a fact that we have a very good speaker. So if you are there, and I'm starting to see people are now starting to join in slowly but surely, but if you are in the audience, let us know where you're joining in from. This is a live event, all right? So the way that this is going to work is I will introduce our keynote speaker today in a moment. He's gonna go through, I think it's about a 25 to 30-minute presentation about what are some of the secrets that innovative angel investors are using these days to create a competitive advantage. And then after that, after that presentation is over, we're gonna spend the rest of the event, which will be about half an hour, just completely 100% focused on answering any questions that you have in the audience. So at any time, you don't have to wait until the presentation is over. At any time, throw your questions into the chat. We will be compiling all of them. And then when the presentation is over, we will just go through and basically have a sort of an open AMA type of conversation. And I'm seeing here Weston is joining from Berlin. Welcome, Weston. We have Ken Ken is from Montreal. Ken, you're pretty close to our keynote today, based in Toronto. We also have Panama, Pakistan, Mount Pleasant, Wisconsin. That sounds like a very nice place. Well, welcome everybody in the chat. And once again, at any time in the chat, answer any questions that you have. And when the presentation concludes, we will make this much more into an interactive event where we'll just go through the questions one by one and make it an open discussion. Okay, well, with that being said, I'd like to introduce our keynote speaker today, Kamal. So Kamal, let you introduce yourself in a second, but just so everybody— I've known Kamal now, it's got to be over a decade plus at this point. Kamal was one of the people that helped us launch the Founder Institute first in the country of Canada, and that's been one of our largest and most successful programs to date. And Kamal also, through his venture firm, Loyal VC has invested in more Founder Institute companies than any other VC around the world. So thank you for that, Kamal. And yeah, did I— anything to fill in there, Kamal?

I think it's probably useful for people to know that I spent about 15 years angel investing before I launched the fund. So the secrets I'm sharing today are secrets gained over 20 years of investing experience.

Awesome.

All right.

Well, Kemal, why don't you bring up your presentation and we'll get this started. So I'm looking at other people in the chat here too. Istanbul. Happy New Year, Betty. I see Manchester, UK raining. Michael, I feel like maybe that's not super unique there, but thanks for giving us that report. And with that, I'm going to hide my screen and mute my microphone and let Kemal take it away. Once again, any questions, throw them into the chat and we'll get to them after the presentation. All right, Kamal, the floor is yours.

Perfect. So this is a talk on the secrets of innovative angel investors. And as mentioned, I'm one of the founding partners of Loyal VC, a 4-year-old venture fund, and spent time with the Founder Institute before that. And I'm really grateful to the Founder Institute both for this opportunity but also for the partnership. As John mentioned, we've invested in over 130 Founder Institute companies from around the world, and we find the Founder Institute is a very important part of our sourcing. So happy to share a little bit of what we're doing there and just generally the way we think. But let me start off. I don't know how many of you are already angel investors or not, but for those of you who aren't, there's always a question of why should I be an angel? And look, we're very data-driven people. I love to pull up the data, and most of you probably are not surprised to hear that over 99% of the companies in the world are private and only 1% are public. But what most people don't know is if you look at the total sales in the economy, yeah, those public companies are very big, but they're still only 43% of the economy, whereas the private companies are 57% of the economy. So whenever you see a newspaper article which says the private sector was the engine of job creation, of course it is. It's over half the economy. So if you're investing only in public stocks, you're probably missing out. So you might want to think about how do you access the private markets as well. The other specific reason to access the private markets is to access tech returns. Now, if you look at companies like Microsoft or Amazon, from the day they listed until today, in 1986 and 1997 respectively, they increased their value by over 2,000 times. So it used to be 30 years ago that if you wanted to make money in tech, you could just wait for the tech companies to list on the public markets and invest in them then, and you'd make lots of money. Nowadays, even when you look at successes, Google was only a 40x since it listed in 2004. Facebook only a 7x in 2012, and Ubers hardly made you any money at all. All the money was made in the private sector first. So it was made by venture, private equity, angel investors. There was a sort of short-lived spike of SPACs to try to address this, which is no longer there. So look, it makes sense to be an angel to access the private markets and to access tech returns, which you can't do if you simply invest in public markets. Now, a lot of people know that 2022 has been a bad year in tech. And yes, it has been. And I want to tell you that's okay. Look, public software valuations are down 50%. The bottom— sorry about this. The bottom line about this, though, is that value— yes, revenue multiples are down. That's actually a really good thing. Because you make money in angel investing by buying low and selling high. And now is a really good time to buy low. The other thing about angel investing is it's all about home runs. It's about those few companies in your portfolio which are going to multiply by value by 10 times or more over a 5 to 7 year period or more. The thing is, whatever you invest in today is going to exit in 5 to 7 years, so you want it to be valued high then. And valued below now, that's wonderful. It's worth mentioning, by the way, that we've been here before. There's nothing new in this process. If you look over the last 20 years or so in the US, we have seen periods when valuations have gone up and down, when fundraising has gone up and down, et cetera. But it's just, look, there's all sorts of peaks and valleys. It's what this market is about. It's nothing new. We're seeing another one of them. Tell you a tiny bit about myself. I mentioned my angel investing experience. My partner, Mike, and I launched Loyal VC to basically try to create the fund we wished we had, wished were available to us. But if I want to talk a little bit about my own experience, I came into this like many angels do, which I was very confident when I started my angel investing. I've got an undergrad in engineering physics. I was top of my class in my INSEAD MBA, was a Bain company management consultant. So I thought I walked on water. And then I was an entrepreneur. And guess what? I made money as an entrepreneur. I increased the value of the company I was with by doing 10x in the valuation, 5x by revenue multiple. So I felt really comfortable that I knew what I was doing when I entered. And I knew what these stats were in the industry. In the industry, they always say, well, you're lucky if in 10 investments you have one home run and you're going to have 6 or 7 of your investments are going to fail. And I said, yeah, that applies to everyone else. But I'm different, I'm special, I know this, I can pick them, et cetera. And I learned humility very quickly by just jumping in and making investments. And out of my first 10 investments, 7 of them failed. Absolutely. 2 of them were very small victories, and 1 of them gave me 30 times my money back, but it gave me 30 times my money back 14 years later. So for a long time, I felt like a complete idiot with, yeah, I've got the 1 success, but Yeah, how much is it going to really make? My portfolio return is wonderful. I've got a 4.6x realized value. That one company has succeeded, was not one that I expected to succeed. So you'll learn a lot of humility in this game, and I'm not the only one. If you've never done it, it's worth looking at Bessemer Ventures anti-portfolio. You can just Google that. It's on their website. But they've also showed how they have learned a lot of humility. And this is just a list on their website. Of selected companies that they had the chance to invest in and said no to. Apple, Coinbase, Google, Tesla, Zoom. And the reasoning they did this for was really good. I mean, Facebook, they talked to them and they said, hey, have you never heard of Friendster? Move on. It's over. Or for PayPal, it was rookie team, regulatory nightmare. Forget it. So very good analysis. And yet they were completely wrong. And if you are going angel investing, it is worth learning some humility and looking at these stories of how they could pass on such amazing companies. If you look industry-wide, we've got really good data for venture investments, and it's pretty similar in angel investing in my experience, which is 65% of your deals are going to fail to give you back your invested capital. About 50% fail and give you zero back. If you then look at the next 31% of your deals, on average they give you about 3 times your money back. So if you add up those first 3 columns, 96% of your investments, you're going to end up with about your money back and nothing more. The last 4% of your deals give you something like 25 times your money back. So you will double your money and your portfolio will give you about a 2x. Now I mentioned that my portfolio will give me a 4.6x fully realized. That's great. I had one 30x winner. I had a 30x winner, there was a 1% probability of my having that, and I had 10 investments and was lucky enough to get one in there, which was fairly unlikely. So that is what the industry-wide numbers look like. And it's really valuable, I think, to always have this in your mind when you're investing. And one of the questions you start to ask yourself as you become more humble is you say to yourself, what kind of activity is angel investing? There's many people who look on early-stage investing very much like cooking from a recipe book. You have the recipe, you follow it, and you have predictable results. If you follow the brioche recipe, you do everything right, you know you're going to get a brioche that works out the other end, but as you start to say, "Hey, the things I thought would happen didn't happen the way I expected," then you start to ask yourself, "Is it more like playing poker?" An approach where you have unpredictable outcomes, and cooking is predictable and poker is unpredictable, For those of you who play this variant of poker, imagine that you've got two aces is what you're dealt with face down. It looks like the best hand, but you have no idea what cards are going to be drawn next. And you can end up having two or three aces, which loses to someone who has a straight or a flush, which only becomes revealed over time. So, you start off initially making your bets without really knowing what's going on, and as the cards are revealed, you know your odds better and better, and then you can start to predict and gamble and sort of, yeah, make your bets based on probabilities of different outcomes. If you start doing some more science, and this is all fairly recent science, this is from Abe Bachman of Angelus, a Kauffman Fellow, in December of 2019. A lot of people think that this business is all about minimizing false positives, finding reasons to say no. You look at a company, you can see there's a fatal flaw. Friendster is out there, it's got the market dominated. Guess what? Facebook. You've got a fatal flaw, you can't be your competitor, you're going to fail, I'm not going to invest in you, and you should give up right now. And that's a traditional VC view where you sort of look at everything, you find all the reasons to say no, and you pick 1 out of 100 deals. Um, if you look at the data, uh, as AngelList did, um, they actually, uh, challenge that, and they say that they have found that maybe this business is about minimizing false negatives. Uh, don't pass on the Facebook, put a lot of money in a few deals. And they said they found that seed stage investors, and specifically for early seed stage, I should put money into every credible deal. And yes, assessing whether or not a deal is credible is challenging. That's where you make your money because it's unpredictable. But still, you should really be thinking about putting money into every credible deal, not just 1 in 100. And they said that, look, over a 10-year investment window, indexing, funding everything, actually beats 90 to 95% of investors picking deals. So the takeaway as an angel investor is maybe think about putting smaller amounts of money into more deals because that's what the numbers say you should be doing. Um, the reason why this indexing outperforms is because you're less likely to miss out on the unpredictable rare mega winners, the Facebooks of this world. You make a lot of your money from that last 4%, and the fewer deals you have, the less probability you have of having these few outside winners, outsized winners, in your portfolio. Even if you can't fund everything, and we've done some math here just to sort of say, look, what's the impact of diversified portfolios? We've got a Monte Carlo simulation we built based on the data you see here. You just run it through a Monte Carlo simulation and you can predict the sort of probability distribution of outcomes. And we've built a model which actually very closely matches the results from venture capital with a 10 VC deal portfolio. So you run this, take 10 deals, you get something that looks like this. What happens when you increase it within the model to 150 investments? Well, a couple of interesting things happen. First of all, there's a much lower distribution. In your standard VC fund or in your standalone angel investing, you've got a very good chance of actually losing money absolutely in your deals. If you diversify enough, say a portfolio of 150 investments, you will not lose money. Similarly, your returns will be capped. You'll probably make something in a sort of 8% to 18% range of returns. So it's a good range of returns, but that's sort of the range you should expect to get, which is, by the way, is very good compared to public markets. But the other thing I want to point out here is your median return goes way up. So a median return of something like 6% turns into a median return something like 12%. And the reason it does is the more investments you make, the more probable it is that you have home runs in there. And those home runs, statistically, you're just going to get more home runs with a broader portfolio. And that's what gives you the more predictable returns. And if you do too few angel investments, one of two things will happen. You'll either have a home run in your first 10 angel investments like I did, and you'll think you're a genius because you made a whole bunch of money, or you won't have have a home run in those first 10 angel investments. And you'll think, oh, there's a problem with the asset class. I shouldn't be an angel. People just lose money in angel. And you'll have all sorts of experiences, which we can talk to. But that's something to be aware of, is that the math really says more investments, absolutely better for you. Now, if you're going to diversify, you want to diversify just like any mainstream investor would do, which is great. You can say, I'm going to diversify into 100 investments. But if they're all blockchain investments in Silicon Valley, you are very exposed to an industry and a geography. So you should really think about diversifying by geography and by sector if you're really trying to protect your capital. And I know it's very counterintuitive because people always say, well, you need to be an expert in an industry, only invest in areas where you're experts. That may be if you think about this as a predictable business, but if it's more unpredictable, it's more random, it's more like poker than it is like cooking. Then you maybe want to think about that diversification even when you don't have the expertise, as long as you have enough expertise and are connected with enough people to triage deals. Um, the other way you want to think about diversifying is diversifying by time. These are the average return from VC funds, and it'll be very similar from angels, which is it varies dramatically over time. You can see that the returns from the median fund were negative in the sort of 2000-2002 period, and around the 2009-2010 2010 period, the median fund was returning 15% to 27%. So you didn't have to be that expert. You just had to be investing at the right time in the cycle. If you were trying to time the cycle, now's probably a good time to be investing in the cycle. But just more generally, if you don't want to try to predict cycles, diversify over time. Make investments predictably every year for the next 5 to 10 years. Deploy capital every year. Whatever state the market's in. That is the best way. And that's something we practice. We're an open-ended fund. We invest every year no matter whether the markets are up or the markets are down. Another thing I want to mention very quickly is diversifying by gender. And I want to present this— I mean, you can absolutely look at this as a justice point of thing, but I want to present it to you as an investment opportunity point of view. For those of you who don't know, less than 3% of VC dollars go to companies which have a woman CEO, so there is no argument one can make that women are underfunded relative to their proportion of the population. So there's a couple of other interesting stats out there. There's a stat which says that— BCG had a study which said the revenue per dollar of funding in a woman-led versus a male-led company was 250% more. So you can make the argument that actually we're ridiculous, that women are far better investors, are far better investments, and you should invest more in women. And there's another theory out there which says, okay, well, this is the justice thing can be fixed by having more women become VCs. Well, guess what? 16% of VC decision makers are women and growing, and that's been up from sub-10% in the past decade. But it's 16% and growing, and yet the percentage of VC dollars go to women-founded companies has been flat. So will women fund women? No, it hasn't been proved out. Are women better? I mean, my experience isn't that women are any better or worse, but women are underfunded. And if you look at the reason why, and I think a lot of this comes in, there was actually a really, some really good study where they actually took actors to present and pitch a company to an audience of men and women who would then be grading whether or not they wanted to invest in the company. They took an identical script and they basically showed you pictures of the person presenting and you could hear their voice as they read it out. And basically good-looking men had dramatically higher scores than very average-looking men, who also outperformed women of both average and outstanding looks. So it was a real— and you can see there's a marked difference between the company being scored out of 10, a 5.21 versus a 4.14 on an identical script and identical slides and changing only the presenter. So we know that if you listen to a pitch, you're going to be scoring people based on their looks and gender. And by the way, the results were the same whether it was a woman or a man. So women are biased towards men just like men are biased towards men when they listen. People are generally biased to fund good-looking men, so you want to think, be aware that this bias exists, and think very hard, as I said, about how to profit from it, because not everyone is going to be funding top women. If you become very data-driven, it eliminates this pitch bias, so you've got people like Social Capital, Clearco, and ourselves, Loyal, who are typically funding 30 to 40% more women CEOs, So in tech entrepreneurship, there are fewer women, but there's fewer women, i.e., you look at top MBA programs, 30-40% women. You need to look at engineering programs. Again, there's sort of 30-35% women. So you should expect to see the ratio of funding be about that. And if you're looking to make money, you want to be taking bias out of the equation, looking how can I invest in the people who will make me the most money? And that's really what it's about. Now, if you look at the principles we run by, I've talked a lot about diversification here, and diversification is one of four things we do, which is sort of a little bit unusual. So yeah, we're trying to deliver excess returns with reduced volatility. I'll show you a little bit about the staged process we do for the excess returns, but diversification is a big part of the reduced volatility in the portfolio that we're trying to create. And we do this through the enablers we have for our processes. We've got these global networks we work with. We have a global partnership with Founder Institute, also with INSEAD, and we've built our own network of over 1,000 people to support our portfolio companies. And we've got an open-ended structure. So let me talk a little bit about this staged investing, which is the other secret we use. And you talk to a lot of angel investors, and they often will do this. If you ever talk to an experienced angel, they'll say, When you write a check into a company, you should reserve the same amount again for follow-on investments. You should reserve at least half your capital to make follow-on investments into companies. Never put it all in the first check. We take this to an extreme where we put 3% of the capital into the first check and we save the bulk of it, 97%, to deploy afterwards. And what we do is we start every company off with a $10,000 check. We do 6 of those a month. We've made 286 of them so far. And then every month we pick the top 2% of those pilots and we offer them $200,000. We've done 84 of those so far. We do 2.5 a month. And then every month we pick the top 2% of those, around 1 a month. And we've now done 13 of those follow-on investments. So what this is doing is it's doing two things. We are massively diversified here, yes, but we're really trying to say we can't predict who's going to fail. But if you give— and it's about a year for a company to move to one stage to the next. If you watch a company developed over a year and you do a lot of diligence on them, you'll start to see who's performing well and who's performing poorly. And you just don't give any more money to the poor performers. You're going to be writing that off. And the very best performers, you give more money to. And in theory, this should give you better returns. And this is very similar to what top poker players will do. Top poker players aren't going to sort of bet everything on the double aces when they see it. They're going to watch the cards get turned over time, and they're going to see what those cards are, readjust the odds in their brain, and they place most of their bets as the cards get exposed and they can play the odds. Because the outcomes are predictable, but they come revealed over time. So staged investing matches exactly how poker players invest. Um, we use very fixed rules, um, and I'm going to flag these things up. I can tell you about our compensating strategy, but I want you to really focus in for the cognitive biases here, um, because human beings have a whole bunch of brain pattern things we fall into which really hurt you when you're trying to invest. So we do fixed amounts at every stage. We do only the top 2% go on to try to mitigate against this. So some of the biases you have are sunk cost. You want to save your investment. We do large steps up because you're not investing $1 million to save a $200,000 investment. It's nonsense. You've got the endowment effect where you love your deals. So we force ourselves to only pick the top 2% every month. And if you know you've got a restricted choice, well then, even though you love a deal, you can rationally see that something else is better and you don't want to say no to the best deal. People get very overconfident. They think a deal is sure to win. That's why we do fixed sizes at every stage. That's what reduces the volatility, the portfolio allocation. Good entrepreneurs will get a bandwagon effect. You have to invest now. The train is leaving. Which we resist by this top 2% only and at least 3 months diligence per stage. And then of course you've got all the biases we have about who we think can and will and should perform. And we just watch the companies over time and you see how do they perform, not who do you think will succeed, but who is actually succeeding. Good theories. What about the data? I'll just show you one little piece here of our own data. And there's a little warning thing up front, which is because we're showing you our personal inside data. This is what our returns look like right now from our 286 pilots. You can see this sort of been tracking the market a little bit, and we've got a 9% annualized return, which, as mentioned, is sort of what you get from a sort of average VC portfolio. If you look at our follow-on investments, they've been returning well over 25%, and you can see we're making the money in these follow-on investments we believe because we follow such strict rules and we're very aware of our biases. The last thing which people forget about is there's a question here of, will the entrepreneur let you invest? It's not just about you picking the entrepreneur, it's about the entrepreneur picking you. And a lot of people say it's much more about access than it is about sort of good picking. You need them to choose you. And there was a really interesting, another good piece of work by the Kauffman Foundation where they asked a whole bunch of VCs, what do you think matters to the entrepreneur? And they said, look, entrepreneurs value relationship, they value the brand of the VC, they all want to go with Sequoia or Andreessen, they value deal terms. And they asked the founders the same thing. And the founders said, yeah, we care about the relationship, that's number one. And we care about deal terms. That's number 2. Factor number 3 that we care about is speed of investment. And if you're part of an angel group, you know one of the challenges angel groups have is that they can be very slow. And you often will miss out on good deals because you're just too slow and the founders want you to move quickly. By the way, the brand of the VC, couldn't care about it at all. It's factor number 8. Factor number 4 was other founder references. But this is really what people think about. So if you're doing your own investing, think very hard, yes, about being nice, building up a relationship with the founders, but also think about how you run your process to do enough diligence, but yet be able to act very quickly. You know, these strategies which we're talking about, the staged investing to drive your returns, protecting your capital, broad diversification. This is something— these are known strategies you've seen in the past decade. These are emerging in top Silicon Valley firms. Sequoia has been famous for years for their scout funds to give them inside access to follow-on opportunities. You've got people like 500 Startups who are famous for— you need 500 investments to be properly diversified. And there are a few funds, Loyal is one of them, which is simply combining these into a fund. You can do the same strategy with your own money. The one thing to remember when you do it with your own money, if you're new to this, remember you're locking your money away for a very long time. You have to have a long-term view with your angel investing. There is a long time to exit. It's 7 years for half of M&A, 8.5 years for half of IPOs. And, you know, my 30x M&A took 14 years for me to be able to exit from that investment. So there is a long time period and you need to be very patient. It often shocks a lot of people. They start investing, the angel invests for a few years, and then they deploy all their money and they run out of money and they stop investing because they didn't realize just how long it is to get back. In fact, it's still a long time to fail. It'll take you 3 years till half your companies fail, 6 years for 90% of the failures to show up. So failures can take a long time, but this is a really long-time industry. That's one of the reasons why when we set up our fund, we said, what could we do that we'd be better for an angel than being— I mean, better for investors than just doing their own angel investing? And that's why we set up an open-ended fund to address this issue of, in our fund, you can trade out. We set a price every quarter, and you can buy or sell that quarter. Sequoia also did the same thing. More and more VCs are starting to see the advantage of the long-term view. Most VC funds have a fixed 8, 10-year timeline, it really changes their interactions with the entrepreneurs. And Sequoia recently announced that they're moving open-ended. They price twice a year, allow you to buy and sell. We've been pricing 4 times a year for a few years longer than them. But there's been about 200 open-ended funds out there in the past decade or so. It's something which is slowly starting to happen. The big challenge if you want to be open-ended is pricing. I can talk to this, but you have to be brutally honest with your pricing. And if you look at our pricing, we price things rapidly, adjust to market conditions. You have to be really willing to mark down just very honestly, very rapidly, because if you're letting people buy into your fund at the new price, you don't want the price to be inflated. It's bad for all the existing investors, typically including you as one of the GPs in the fund, who's one of the first investors. So yeah, there was a quick overview. I started off talking about why you want to be an angel. I think many of you may know that, but for those who don't, look, you want to access the private economy, especially early-stage tech. There is some— there are two different approaches to investing, and it really says, is angel investing a recipe where you learn the rules, you follow the rules, you get predictable results. Many people invest as though that's the way this industry is. A number of innovative people are thinking very differently and thinking this is more like poker, that you might have an amazing hand to start with or a horrible hand to start with, but over time it's revealed that it's the opposite of what you thought it was. And we believe things like the Bessemer Ventures anti-portfolio are good evidence that you fundamentally cannot predict the future. And look, if you could predict the future, VCs who are really smart, experienced people, uh, the industry as a whole, the people who get funded, 65% of their deals fail and only 4% are home runs. If home runs were really predictable, don't you think the experts would have done it? So we really think that the solution to this is diversification. It's a numbers game. Diversify a lot because it's not predictable, because home runs aren't predictable. And when you're diversifying, remember also to think about diversifying by gender, ditching the pitch, and really be aware that pitches are a sort of biased way of screening people. You want the best investments. Look at the numbers much more than the pitch. Diversification will give you good, stable, steady returns, average returns. If you want to have excess returns, We think you can create them by following a staged process where you watch deals develop over time. You then build an advantage. You've got the relationships, so people give you the follow-on money. So you want to think very much about this staged investing. We do it with very fixed rules because of cognitive biases. This staged investing also gives you access if you understand that VC is an access game. And yeah, and then we do an open-ended fund and just be aware if you're investing your own money, have patience. This is a long-term game. Let's stop there and throw things over to you, John, for questions.

Awesome. That was great, Kamal. Thank you. Thank you for that. And we do have a lot of questions coming in the chat. Please do keep those questions coming in. So I just, I want to get started. I have a couple of questions. Questions quickly, and then I have been taking some notes here. Miguel, Jan, and Rafael, and a few others have some questions that I have queued up, but for anybody else, please do throw them into the chat. So I know, Kamal, you know, the ditch to pitch, right?

Yeah.

I know the ditch to pitch, and I know the why there, right? It's a very quick way to eliminate a lot of those biases that you pointed out. But I, and I know part of the answer to this question, but I'd like you to share it with everybody here, right? With your approach of ditching the pitch, you know, I think that the logical question for a lot of angels would be then, okay, well then how are you looking at these companies and how are you actually getting the information that you need?

Yeah, we rely a lot on references. So one of the things we do when we work with the Founder Institute is you have directors of a Founder Institute program who spent 14 weeks with 20 different entrepreneurs, and they've got 14 weeks of weekly assignments and weekly work they've done. So there's a lot of information from people who know the entrepreneur, and you can think of Founder Institute as a sort of advanced interview process. I still remember one of the founders who's actually in our portfolio right now, uh, a relatively new Russian immigrant to Canada who did the program with me, who said I want to build software which every multi-location in business in the world can use because managing multiple locations is hard. And we listened to her and we just laughed. I mean, every person, every time she did a pitch, people listened to the pitch and they said, this is ridiculous. Well, I want to fast forward to today where— well, first of all, say what happened then. One of the nice things the Founder Institute does is it gives special assignments. So she was doing very poorly and we said, okay, well, look, no one's ever going to buy this. Special assignment, go out and find a multi-location business which wants to do a pilot with you. You've got 72 hours to do it. And she came back and she said, yeah. And she had expressions of interest from multiple different places with stores. And we said, well, we must be missing something. But guess what? She's building something that works. And we thought SAP must do this. And she's saying, no, no, no, there's a market. And fast forward to today, I mean, she's working with multiple multi-location retailers across the US with a business which is still under the radar, but which is an essential part of their operations. So she performed. The pitch sounded crazy. She was not credible as a new immigrant. I think she was 26 at the time. Not a bit of tech experience. She actually went through 3 CTOs. I mean, there's every reason to look at this business and say no. And yet watching it over time. We also do references with other people. We often find that reference checks with people who have been able to compare you to multiple other businesses is a much more fair way to do it. The other funds I mentioned on there, their strategy is just look at the numbers. Ask people to share with you their revenues over the past 10 months, their monthly revenues, their customer, sort of the user behavior, the user characteristics. So that's the other thing you can do. If you don't have this person who can give you the reference, look at the numbers.

Got it. And that really does tie into Jan's question here too, was like, okay, Jan was asking also, you know, you're removing a lot of these biases, so what does the due diligence look like? And in particular, you know, is there anything— Rafael also had a question related to this— or is there anything with regards to teams and kind of looking at the dynamics with teams that you're using in your due diligence process.

So we have two types of due diligence. There's a due diligence to get a $10,000 check from us, and there's a due diligence to get a $200,000 check from us. 3% of our money goes in the $10,000 checks. 97% goes in the $200,000 checks or later. How much diligence should you do for a $10,000 investment? Not very much. We call up John, we say, hey, let's introduce this to the person who runs a program in Mongolia. Let's talk to the director of Mongolia. Hey, director of Mongolia, who's the outstanding people in your cohorts in the past 6 months? Let's write them a check.

So it's really at that point, it's a reference then, right?

At that point, it's a reference.

Basically reference check. Yeah.

Well, it's a reference check, but there's a whole bunch of stuff goes in. I mean, you know that Founder Institute does a personality screening on people when they come in. We will look at their test results from earlier. So there's a bunch of things we will look at. If you look at the screening at the $200,000 level, we have monthly calls with companies. It takes a median of 10 monthly calls. These are diligence calls will be held with multiple people on the investment committee, always a call with member of the investment committee so they can hear themselves. We've got multiple advisors. If there's tech we don't understand and we need tech expertise, we'll get the tech expertise. We'll talk. So we get all these points of view developing month in, month out, month in, month out. It is probably the most intensive diligence process you can imagine if you think about it as diligence. But the way the founders think about it is every month they jump on a call with us and we say, what's your biggest challenge? How can we help? So you can think, and then we say, okay, and it's our job to impress you to get you help. So then we're sitting there every month and we spend 10 months So for them, they're having these calls in return, they're getting help and introductions to top people from around the world who can advise them.

And I think, you know, Jan was also asking like in terms of, you know, what does your data room look like? And I think the moral of the story here is that, you know, there's this traditional view of doing investments where it's like, okay, set up a data room, they share all this stuff, you look at it, you do your due diligence and you make a decision, yes or no. Right. And really what you're saying is, yes, like obviously you want data to be shared and all that kind of stuff, but it's almost more important to see the evolution of that data over time and the progress than just that initial, you know, data dump of the data room itself, especially at these earliest stages.

Yeah. And it's also, look, um, I've been an entrepreneur for 20 years. Entrepreneurs all sit down and complain that VCs are really dumb. There's like, VCs are dumb, they don't get it.

And the fifth on that one.

And the funny thing is, it's absolutely true, but VCs are very smart people. So they're very smart people who are making very dumb decisions because they're having to make very quick assessments and all their biases and filters come into place and they think, oh, Friendster already does this, Facebook's an idiot idea, which is a very good first assessment. Whereas when you have a call with a company every month over multiple months, then you can sit there and say, this makes no sense. Friendster is doing it. But then you start looking at their data and you say, okay, well, show me your user behavior. Oh my God, you've got people who are jumping on here 5 times a day and looking at what's going on. There's something unusual. And that's what we found this with this company, Intellikate, I was talking about earlier. When she rolled out her first trial with a big box retailer in the in the US, she had 60% of store employees were signing on to her system every day in a trial period. And if you've ever tried to train store employees to do something, you know they weren't doing it because they were told to. They were doing it because they got value from it, right? But you get time to see the story and you hear the first thing, it sounds ridiculous. But if you're talking to them every month, then you can get into these things. and then you know what data to look at. Whereas if you send me a data room dump, I can't understand it all. It's just going to be— my eyes glass over and I'm on to the next thing, right?

And I think it lends itself to— I'm just— but your, your point is that really the trick here is to minimize the false negatives, not the false positives, right? Uh, at these earliest stages. And I think most people that start their angel investing journey are looking at that completely in, in the other light. They're looking at it backwards and trying to just pick the greatest winners and really relying so much on— It's a little bit of Dunning-Kruger, where it's just at that point, nobody really knows much of anything.

Yeah.

And that's— Elaine was asking a question here too, and this sort of— You were just alluding a little bit to FOMO, right? Elaine's question was, how do you avoid investing in a black swan like FTX? Well, I think probably that slide you had of biases, you might have been able to check a lot of those on that, right? And I think honestly, Elaine, that the quick— my quick answer there would be that nobody did any proper diligence on that.

But this is it. If you have a monthly call every month with the SAM trying to understand what's going on in the business, at some point you're going to say, oh, tell me more about this relationship with this other fund. What's going on there? I'd like to understand that side of the business. And the second you start to diligence that— and you won't diligence that in the first phone call, but by the fourth or fifth phone call, you've run out of other things to look at, and you're sort of going to go, okay, I want to understand this part of it now.

For sure. Um, and, and just to dive a little bit into the, the bias parts as well, and there's a lot of people in here who who are kind of clapping about trying to invest in more women, invest more underrepresented founders. And I think it's always, and you and I, we share this belief is like, yes, you should do it because it's the right thing to do. But your larger point here is like, it's that, but it's also the best thing for your returns to do also because they're basically, they're under, they're just, yeah, they're You're just, you're playing the math. There are assets that are just not getting nearly enough attention. And, you know, there's also a lot of studies out there that showing that these assets, not only are they not getting attention, but they're actually outperforming.

Yeah. But, but I mean, that's to be expected if you've got two populations and you're picking only the very best women and then you're picking the best and only good men. Then the very best women will always outperform the average of the best and very good men. It's just so long as you believe that human talent is equally distributed. And if you believe that human talent is equally distributed, you know you have a problem if you look at your portfolio and your portfolio does not reflect the mass of humanity sitting around you wherever you are. Then you know that by definition you do not have the best of all people if you believe that talent is equally distributed among all of humanity. And I fundamentally believe that. And every piece of data I've seen says that on average entrepreneurial success, and you know from the test from entrepreneurship, there are many different ways to succeed as an entrepreneur. There is no one formula. You can take many different strategies to succeed. But just look at your outcomes, and if your outcomes don't match the population around you, you have problems in how you're investing. You are not finding the best deals. And then ask yourself, how do I get the best deals? And the best deals will reflect the population around me for sure.

And Emotional Ideas Inc. here, uh, is, is also mentioned as well, you know, in terms of Black founders, you know, they're receiving less than 1% of funding. And I think it's the same, it's the same exact argument. Argument, right? Where it's just even more extreme than the women founder argument, is that it is— it's an under— from an angel investor perspective, right? So even if you remove all of the— remove all of the, uh, you know, morality and all that kind of stuff, even if you are just purely looking at dollars and cents, it's an underutilized asset to invest in.

Exactly. And you make more money, but it's supply and demand. You buy low, you sell high. And guess what? When everyone's chasing after the same deal for that white male Stanford engineer who worked at Facebook, you're going to pay a higher price to get into that, and you will probably get a lower return than someone who was not white male Stanford engineer who worked at Facebook. You'll pay less, and you'll pay less, and their success will be about the same, and you'll make a lot more money. Right.

So when is asking— and I think this is an interesting question— so user behavior data, right? So if you're working with the company over time, looking at the growth of that data over time. Makes a lot of sense for market-ready SaaS, you know, some consumer stuff. But, you know, she's curious on how you would evaluate that with regards to deep tech, you know, some products that would just take a lot more time for you to actually start collecting, you know, user data, so to speak.

So deep tech is a good example. We have a company, we have a company in our portfolio, Looks Good AI, who takes hand-drawn PowerPoint slides for major consulting firms, and the consultants draw out a hand-drawn thing, and they turn it into a PowerPoint-ready slide, a PowerPoint slide. And you listen to that, and it's obvious if you— I used to work at Bain. It's pretty obvious that Bain would love to buy this if it existed. And that's the sort of thing that sounds like magic. It sounds like, oh my God, yeah, I'd love that if only it could be built. And you find that with a lot of deep tech. We've got another deep tech company, Purifier, out of the UK, which takes carbon dioxide out of the air, carbon capture. So it's pretty obvious that there is a market for this and a growing market over time if they can do it. What you do in that case is you, A, there's no— you have to start to get deep on the tech. You have to understand where the tech is, what the economics of the tech are, what the next stages of development they're moving towards, what do they need to prove, where the risk is. And you want to watch because in this case, lots of people judge the team by the experience. Don't judge the team by the experience. Judge the team by their ability to perform over time. So you just watch them develop this tech over time and see, can they take it? The next thing is you have to learn yourself customer. If they're building this, they'll have some sort of pilot trial, early indication from industry of people who will come back and say yes. I mean, we have another company who's doing recycling of rubber, and she's signed contracts now with two large tire manufacturers. And if you're doing recycling of rubber, you know who you would sell that to. So if one of those big buyers of tire rubber says yes, I want to work with you, then you know they're doing something right and that technology is starting to pay off, et cetera. So you look at that sort of thing. You look at the tech itself. And the third thing, advantage we have, and you should always do this yourself, is we have a bunch of tech experts. And I remember this myself. There was an angel investment done by a friend of mine. He's a VC partner who does angel investments on the side. And it was— I used to be an engineer for IMAX, and he was investing in a display technology. And he said, Kamal, can you come in and do due diligence for me on the display technology itself? Because you are an expert in display technology. He's the smartest person I know in it. Can you tell me if there's anything to their tech? So get someone who knows that tech, who comes in, and that looks good company I mentioned who's turning sketches into PowerPoint slides. We have a guy who was down Silicon Valley, was a Google AI scientist. who said, gee, that sounds impossible. And we said, just have a call with them. And he had a call with them. He said, oh my God, this is really amazing. I actually like their approach. I thought it was impossible superficially, but the way they're doing it makes a lot of sense. And they are now moving forward, and they're already adopted by a major consulting company who's using it with like 150 of their employees right now, even in an early stage with a lot more still to develop.

Okay, yeah, thanks. That makes a lot of sense. And it's, it's a lot of what we tell our founders as well, right? It's like, look, if you have If you need to show, quote unquote, traction to an investor in a type of business where that traction is not going to happen anytime soon in the traditional sense, then it's getting the validation from the people that know what the hell they're talking about, right? Whether it's getting somebody on your team that has experience that would show that, okay, they're not going to get involved in something that's not feasible or pilots or things like that. I mean, it makes total sense. So a couple of people have been asking kind of around the economics on being an angel, right, on the earliest stages. So let me get into some of those. So Miguel was asking at a high level, any kind of deal structures or tips that you have to kind of protect yourself from dilution in future rounds that you're doing. Now, I'll say to some extent, it's unavoidable, right? I mean, that's just literally the math. But, uh, so if you're trying to protect yourself from all dilution, then you're in the wrong game. But, uh, but yeah, any, any tips or tricks you want to share there on that?

Yeah, there is a term to protect yourself from dilution. It's called anti-dilution clauses. They're horrible for you. They're horrible for the company. They're horrible for you. You should not try to do them because they will get taken out very quickly by later rounds. But what you should be more worried about is preferences. And the later round preferences are really going to disadvantage you. So just be very aware of that. Whatever preferences you may get when you— in fact, I did this. One of my first angel investments was in a knitting software company back when this wasn't all easy stuff to get online. And I put money into this business and had all sorts of protections I wrote in for myself. Around limiting what they could do. And they had a next investor came to them and was going to put $1 million in to expand the business. And they said, I'll put $1 million in to expand and grow this business on condition that I can buy you out for your investment plus interest. I said, no way, forget it. But then I'm sitting down with the founder and the founder's sitting here going, look, this company's going to fail otherwise. I have to take these terms. Or we're just going to sort of bankrupt the company. Come on, do you want to bankrupt the company or do you want to get your money back plus interest? But it was a real— when you start down this path of imposing preferences on an entrepreneur and you think, I thought, wow, I'm putting all these preferences on, I'm so protected. Paradoxically, I was not protected because the stronger my preferences were, the next investor wanted to either get rid of me or have even stronger investor preferences for themselves. And then you talk about being on the bottom of the capital stack. So I actually paradoxically think the way you protect yourself is by building a good relationship with the founder and by minimizing the preferences you take to start with, because that sets a precedent. And talk to the founder to set a precedent that preferences will be minimized for all future investors as well, and keep keep that relationship going to encourage them. And then what you can often do is if they insist on giving preferences to later people, ask, well, if you give preferences to later people, I want equal preferences to whatever happens. As a relationship thing, you can't contractually force it. You can try, but you can't contractually force it. But because you've built up that sort of goodwill, you can often get them to do it, because the founder themself is the one who decides which money to take and which money not.

Yeah, exactly. And every— I think what's lost in a lot of people is that in these deals and subsequent funding rounds, like everything is negotiable. Okay. Like literally. So a lot of people have an attitude of, oh, it's like, okay, well, this is the contract that it's sort of a set it and forget it thing. But they don't realize that, okay, in every single step of the funding journey, right, terms are put on the table. So if you're not maintaining that relationship and if you're not, you know, that's That's even stronger in a lot of cases than the written word, right? Is maintaining that relationship over time. So, some questions here also, and I know that you kind of have a unique approach to this valuation. Okay. And I know you could probably do a whole half an hour on how you guys do valuation. But Sabina was asking here, you know, how do you do the valuation? Do you have a formula? And it's very relevant question, Sabina, by the way, for Kamal and for anybody who wants to do this kind of volume strategy, right? Because it's just, if you're going to spend a day trying to value each company and you're trying to invest in a lot of companies, and that's not going to make a hell of a lot of sense. So yeah, just any high-level thoughts on how you typically look at that equation?

You know, the first thing is actually a really simple thing, which is a price is what the price of something is, what people are willing to pay for and what people— how do you know what people are willing to pay for is what they actually did pay? So the first thing you want to look at is if you just had a funding transaction, what's the company worth? It's worth exactly what the investors paid for because that is what the values were. Now, people sometimes get tripped up because if you have different rights, then the value is not what the new people got because they got better rights. It's you have to try to discount for what your own rights. But that's the first thing you look at. The second thing, it's common sense. If I invest in a company at a $5 million valuation a year ago, and that company has now— one company has 10x'd its revenue and the other company, the revenue has increased by 10%. It's pretty obvious that one company is worth more than the other. There's a little bit of an art to saying which one is worth how much more, but it doesn't take rocket science to say your expectation was probably that in the year they would've 2x'd or 3x'd their revenue. So the one which 10x'd should be a higher valuation because it outperformed your expectations. And the one that stayed basically flat should be marked down because it underperformed your expectations. So actually, the valuation, it's all common sense rules. You just have to be willing to put those into practice, and not everyone is willing to do that.

Makes sense. And Anne has an interesting question here, especially in light of all the buzz around generative AI. ChatGPT, but Anne is asking, you know, if the numbers are telling us to diversify and that the gut feel is, you know, not working, do you see AI or algorithms, you know, really taking over and then just becoming a much larger part of this game as we move forward?

Well, so it depends where and how the algorithms are applied. Most people take the very short-sighted view that the algorithms can be applied on the intake that I'll take 100 companies, I'll run their numbers through my algorithm, and that that's going to decide who's going to succeed in the future. And my contention is you'll take 100 companies, you'll run them through the algorithm. Yeah, you make some good investments, but 4% of those will be home runs and 65% of those will fail, more or less, with perhaps if the AI is slightly better or slightly different. But you'll only have 4% home runs on that, maybe 5% or 6%. That's all because It's not what happens at the one point in time that matters. You have to see how the companies— how does the company react? How does the company react to COVID? We had a company started by one of the biggest, one of the top RNA virologists in the US that we funded in 2019. RNA virology was not a hot topic in 2019. In March of 2020, it became very hot. So you can't predict those things. Or vice versa, travel companies that we have— travel company funded in 2019, which we did a down round and made very good money out of because their other VCs refused to touch the deal in 2020, at the end of 2020 when they ran out of money. Right.

Yeah, that makes a whole lot of sense. And even if you ask like ChatGPT right now, it avoids anything Even if it can sense that even the littlest ting of you asking it for a prediction, it immediately says, you know, I am an AI and I cannot predict. Like, it's, it's, um, it's interesting on how they're, they're handling that internally right now. Um, okay, well, uh, we're, we're out of time here. Uh, thank you so much, Kamal, for joining. Kamal, I don't know if you want to put in the chat here, uh, an email, uh, because there were There's a bunch of questions here in the chat that I did skip over because they're probably a little too specific about the innards of the fund and things like that. So it's just, it's kamal@loyal.vc.

Yeah, it's kamal@loyal.vc. And look, if you are an investor and you want to ask many more details about our investing, we have loyal.vc/askusanything. Um, and that's an information session we do regularly for potential new investors. And you can just ask us I mean, we're totally transparent about our strategy, so you can learn a lot for yourself even if you're not investing in us.