E418: AI, Venture Capital & the Future of Investing

27:29What are the things we can focus our time on that are going to be the biggest needle movers for our business? But it turns out that there's probably a lot of other things you could also be doing that would also be adding value and kind of compounding in various different ways. And as you get better and better at using AI to help those things go faster, it affords you the ability to tackle a much broader set of challenges and work your way down that backlog. And that backlog effectively is an infinite backlog. I mean, maybe there's some end to it. And David Deutsch talks about this in the beginning of Infinity, that as you innovate, there's an infinite amount of innovation.

28:07Why? Because the innovations start to innovate on each other. Oftentimes the innovation is the result of multiple new innovations. People always see this retroactively. When the television was invented, I think like three people invented it within a year. Why? Because all these technologies were now available that made it all possible. So they see it retroactively. They don't think that there's something that hasn't been invented yet that if there's a couple of new innovations that could come about, now you could have a whole new technology. It's really interesting to consider the negative side of this, though, too, which is because suddenly everyone gets more productive and certainly feels more productive, and you start to open up that backlog.

28:47It'll be interesting to see what happens from a product experience and design perspective. because I think if companies aren't careful, they can also just do so many different things that they actually go past that optimal point perhaps. And then their products start to feel overly complex and overly convoluted. And they start to accrue all sorts of technical debt that they didn't probably need to. There's probably a limit in some sense for how many things people should do. And maybe some people kind of move past that optimal point. But I think the common feeling of being a startup founder is sort of feeling like you're drowning because there are so many different things that you ought to be doing.

29:24And I do think that AI is this incredibly empowering force to help people to kind of pull their heads above the water a little bit. And it's true for investors too. I mean, imagine just the thousands of companies that you wish you had time to go research and meet and it's easier to work with a much larger volume now. There's a great thought experiment that two different people, two very different people have brought up. Peter Thiel likes to ask this question, if you had to scale 10x in the next six months, what would you do if I forced you to scale 10 times? Alex Samosi talks about what is the one thing that you could accomplish that would make the next 10 things irrelevant.

30:00So for example, for us, sometimes I find myself stuck on a micro issue. Oh, I need a new sponsor for the podcast. And then I'm like, what am I thinking about? I could just do a new fund or new product and that'll pace for 1000 years of sponsors. So it's easy to get stuck in these problems that don't actually have to be solved if you solve other problems. Growing up, I thought managing money meant paying bills and balancing a checkbook. But as you know, that is only a small piece of the financial puzzle. Managing your money takes more than just checking your bank account every once in a while. And great financial decisions come from having a complete picture and proactive management of your income, expenses, and investments.

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31:39It brings together all of your accounts, investments, saving goals, and spending into one place, making it much easier to understand where your money is going and whether you're actually on track to achieve your financial goals. What I like most about Monarch is that doesn't just tell me what already happened. It helps me plan ahead. The AI system lets me ask questions about my finances in plain English, and the AI weekly recap highlights spending changes or upcoming expenses before they become surprises. It's like having a financial advisor in your pocket. Write your own money story with Monarch.

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32:46What I like most about Monarch is that it doesn't just tell me what already happened. It helps me plan ahead. The AI system lets me ask questions about my finances in plain English, and the AI weekly recap highlights spending changes or upcoming expenses before they become surprises. It's like having a financial advisor in your pocket. Write your own money story with Monarch. Use code invest at monarch.com to get your first year of Monarch core half off at just$50. That's 50 % off your first year at monarch.com with code invest. Framework a lot. I think it's true for investors too. I think, you know, there's this expression in startups where it's kind of like growth solves all problems, which I don't think is always true, but it certainly is true that it's a lot easier to let fires burn or fires seem smaller when you're growing a lot.

33:34And I think as an investor, it's also true that solving smaller problems might seem less important if you get to invest in an anthropic. That might make some of those other problems. As you were mentioning investing, I was thinking about SpaceX. I also was an investor in SpaceX. But when I look at a couple of different parties around it, Antonio Gracios, he invested in it 30 times. It was publicly made available. I think the number was he returned$127 billion. I think it was somewhere around that. And Lucas Nosek, who was a former Founders Fund partner, I remember meeting him at Founders Fund, he told me that he was starting a fund based on SpaceX, called Giga Fund.

34:12I thought that was the most absurd idea. And of course, the 137 Ventures, I think they owned roughly 1 % of SpaceX. So there are some investors that take this thought experiment literally and realize, well, SpaceX is a once-in-a-generation company. I should just keep on backing up the truck. There's obviously portfolio construction limitations to that, and it's not for the faint of heart, but it also applies to investing as well, not just productivity. It's impressive, some of these folks that backed up the truck for, in some cases, I don't know when Founders Fund made its first SpaceX investment, but it must have been well over 15 years ago, right?

34:48It's like a very, very long period of time. One thing we think about a lot at our company is how do investors handle everything that happens after that initial investment? Because people spend so much time and energy thinking about making a new investment, the rigor, the customer calls, the references, the research, the memo, the debate, the investment committee. But then for a lot of investors, after that investment occurs, the next investment in that company might be a quick conversation at the partner meeting. Oh, yeah, the company's doing great. They're raising their Series A. We own 15%. Let's do our pro brada.

35:24Everyone sound good? Okay, great. Let's do it. But in reality, some of those conversations, some of those decisions probably ought to have a lot more scrutiny applied to them, particularly when you look at the percentage of these funds that are used for reserves. It depends on the construction, but a lot of these funds will be 30%, 40%, 50 % reserves. So if you think about how does the firm generate alpha, good reserves planning and really prudent and oftentimes maybe more aggressive follow-on investment decisions can have a huge impact on fund performance, but probably get a lot less scrutiny than they deserve.

36:07And that's something that we're interested in kind of as a theme and an opportunity to help the industry. Speaking of Founders Fund, they're famous for concentrating on their winners and making so many fund returners on their winners. Hunter and Satya from Homebrew says that every single round for every investment, you need to be a net buyer and net seller. There's no hold. There's no pro rata. That's just lazy thinking. That's an interesting framework, net buyer, net seller. You have over 12 ,000 companies on your platform, some reporting, some not reporting, but you have this rich data set. You do research on this data set.

36:40what does surprise you the most about what you found? It's interesting. We find new things in the data every time we run these analyses, and we're also learning, and we've hired, recently brought on a new exec on our team named Ani Kotiyash, who is running portfolio analytics at Battery Ventures and was previously at Y Combinator, who's really helped us to kind of level up some of the analysis that we're doing around this. We see surprising things in the data every time, And some of them are very clear reflections of trends that are happening externally. And some of them are almost like counterintuitive.

37:15So I'll give you a couple of examples. So like when the ZERP crash happened, you know, late 2022, early 2023, we saw huge swings in revenue growth rates and profitability, as you might expect, right? Growth rates went down, profitability went up, companies tightened their belts. you know, ARR per FTE or revenue per FTE, probably a better way of thinking about it. You know, it was kind of climbing across all sorts of different segments, sectors, stages, et cetera. People got more efficient at generating revenue because funding dried up. Then over the last couple of years, you see this boom in very well-funded AI companies.

38:02And there's also this narrative that you might see on LinkedIn or something like that, which shows like, oh, we're like a three-person company and we have like 30 million in ARR. I'm sure you've seen these. Seat strapping. Yeah. And those companies do exist, of course. But interestingly, what we found in our data was that if you look at the AI companies versus the non-AI companies, for a long time, the non-AI companies were actually more efficient on a revenue per FTE basis than the AI companies, because we think access to capital was so much more readily available for the AI companies that they would go raise a big round and they go hire tons of people and SDRs and like tons of engineers.

38:41And that gap has closed. And we just published, I think, with Emergence last week, a short kind of add-on to a report that we did with them that showed that for the first time, revenue per FTE for the$100 million plus revenue companies had actually crossed. Now the AI companies were actually producing more on a per employee basis than the non-AI companies. So there's these interesting things that you see in the data, and you also start to see really large changes over time. The data from 2021 is not relevant, really, to what's going on in 2023. The growth rates of the top decile companies in 2023 are not relevant to what's happening in 2026.

39:24There are these major swings that occur that are driven by some of these underlying dynamics with interest rates and also new technology, of course. Tell me about the metrics behind top decile companies today in 2026. One slice that we find useful to take are AI companies versus non-AI companies. And it's a little bit difficult to distinguish between the two, to be honest with you. We do our best. Companies sort of self-identify on our platform, and they can adjust that and change that over time. And we do our best to verify that. But there's a pretty fine line between a software company that builds a bunch of really useful AI tooling into their product that their customers use and like using, and a company that is truly AI native from day one, kind of in the token flow.

40:15Those two things may also converge more and more over time. But regardless, there's a very large difference between the AI companies and non-AI companies when it comes to growth at the top decile. If you look at median growth rates across different revenue bands, AI companies are typically growing faster than their counterparts. I don't have exact data points for you, unfortunately, like during this podcast, I wish I did. But if you look at the top decile, that's where you see like a huge swing. The fastest growing AI companies are growing faster than any companies ever in human existence. That's why there's such a focus on them.

40:52So it's interesting. You end up learning a lot more from the top decile, I think, in certain cases than you would just looking at media. And that's one reason why having a huge data set is very useful. How would you explain that intuition? Why are the top decile AI companies just growing so much faster than everybody else? That's a really good question. From first principles, it would be that either the level of product market fit is so much stronger and or the ability to distribute effectively is so much stronger and probably some combination of the two, of course, because product market fit can help to drive distribution.

41:28And then distribution also is driven by fundraising too. So companies with incredible access to capital, the best teams, the most backable teams that are able to raise capital very aggressively, very early with amazing products, those companies have significant advantages in terms of distribution. And if they can translate those advantages into just a radically superior product experience, it can lead to pretty unprecedented growth. The other thing I'd say is that people talk a lot about gross margins. I think that one thing that's kind of interesting about the AI era is that investors' attitudes toward gross margins have changed a little bit.

42:16meaning people still care about gross margins, but I think a lot of people are taking a pretty forward-looking view on gross margins. Not necessarily what are gross margins today, but hey, this is a venture bet. If this company is successful in doing what they say they're going to do, what does the long-term gross margin structure of this company look like? And hey, this company might need to raise a billion dollars in capital to get there, but if the end result is a company that's worth tens of billions of dollars, they're going to be able to go and do that. And so we saw this host of companies with relatively mediocre gross margins and in certain cases maybe perhaps negative gross margins if the full accounting was done, be able to go raise enough capital to go and really scale incredibly rapidly to get to that place where suddenly the gross margins end up looking pretty good.

43:00They didn't get stuck in that valley of death. the market was forward-thinking enough and efficient enough that it allowed those companies to kind of hop over that valley and get to the place where they start generating significant amounts of gross profit. It's pretty interesting that it played out that way. And I think that the net result is now a lot of companies that have kind of crossed that chasm and are now very powerful. It makes absolute sense if you think about it from the power law lens, which is all the returns come from the biggest high flyers. And if a company is growing really fast, even if it has lower margins, you're really taking one bet, which is that they could improve their margins.

43:40And if they can, then it could be a 10, 50, 100 ,000 X return. Totally. Power law versus in private equity. You can't have 50, 70 % of your companies go out of business and it would be nonsensical to make that bet. That's totally right. And then I think the interesting middle case between private equity and venture capital are going to be things like AI native services companies, right? That sort of can have venture-like growth, but maybe map a little bit more to the type of business model that one would have seen kind of on the private equity side. And I'm really excited about that category. And we, in some sense, consider ourselves, we provide a lot of heavily AI-assisted services.

44:23And we also, of course, sell software. So we're kind of straddling the lines between those two business models. There's this thesis that, As software becomes easier to produce, the next layer is where the value is going to come. The services, the etch cases, helping customers deal with their problems that are not directly solved by the product. What do you think about that? In many cases, that's absolutely true. This kind of gets back a little bit to the question around network effects and single player versus multiplayer. There's some question, I think, around responsibility. Who's responsible for something?

44:59AI can't be punished for making a mistake. There's sort of a level of responsibility that a human being can take that a model can never take. And so you want to engage with third parties sometimes to take on very important tasks where somebody needs to. I think it has to do to some extent with like just liability. There's a benefit to others taking responsibilities and liabilities off of your plate, especially if they're not your core competency. And there's a benefit for human beings being held accountable for the quality of that work. It's almost another form of cognitive load. There's only so much responsibility you could take on.

45:41Yeah, it's a form of cognitive load. It helps you go to bed at night in the future if there's sort of an issue, there's somebody on the other end. even if it's not like a legal issue, there's somebody who is responsible for making things right. Whereas if you insource every activity, if you're your own law firm and you're your own software developer, and there's just so many things you could take on your own plate. If those things aren't your core competency, there's distraction related challenges. And then there's also this challenge that comes up, which is like, if something goes wrong, I have to be the one to go and fix it versus somebody else is very incentivized to go and fix it.

46:19So yeah, there may be cognitive load is a good way of thinking about it. Pet peeve with my wife. Sometimes I'll ask her to find a place for us to go grab dinner and she'll come back to me with three choices. And I just want her to make a decision. I just want it to completely be just decided by somebody else. There's only so many problems I could deal with. That analogy is great. And the other analogy that I like is like, when you talk to people, I remember having this experience who like bought their first apartment or their first house about what it's like. One of the first things people always say is when something breaks, now I have to go and figure it out.

46:54You know, it's like if there's a problem with the toilet or there's a problem with the sink, I can't just call the super and someone comes and fix it. Like I got to be the one to go and find the right subcontractor and go do it. So look, in certain cases, people are going to internalize more things. If people are more productive with AI, it gives people the opportunity to go and internalize more things. However, the opportunity cost is that instead of internalizing those things, you could instead go and take on more areas in your core competency. If you're a venture capital firm, you could take on a wider scope, or you could take on a broader strategy, or you could go talk to more entrepreneurs or spend more time helping your portfolio companies.

47:35So I think every company will evaluate to some extent on a case-by-case basis where it makes sense for them to use AI to internalize more activities outside of their core competency and where it makes sense for them to continue to rely on others to be responsible for that work, probably in a more AI-assisted fashion, and go deeper into their core competency. It's kind of an interesting, broader economic question, I think. How do you see AI changing the relationship between you and your customers? That's a really interesting question. One thing I will say is that nothing beats getting on a plane or Ubering over or whatever to go see a customer in person.

48:15And the trust that's built in person, I think, is something that is impossible to replicate and may never be possible to replicate through technology. Particularly per our previous conversation, the idea of externalizing responsibility for certain core areas or sharing responsibility for certain core areas. I do think that in-person conversations are incredibly important. So that hasn't changed. Although interestingly, one thing that we've been doing, and I know that other software companies do too, is actually sitting down with customers in person to work on AI-related projects together. Because oftentimes there can be a gap in understanding sometimes where the customer isn't as familiar with using different AI tools.

49:01For example, a lot of our customers use our MCP to go and build a bunch of really cool automations, but some firms have never used an MCP before. So there might be a knowledge gap. There's also a knowledge gap on the other side, which is that sometimes our customers are using our product in ways that we didn't necessarily design. And we're learning from them. That's often a good sign. It's a great sign, yeah. I mean, I think it's so exciting. Like, we'll get these reports back. Like, oh, this customer's, you know, found this really creative mechanism for doing X, Y, and Z. And we're like, oh, that's so cool.

49:31So I think that the in-person stuff for us is critically important. And I think where it helps us in terms of the customer relationship, we've gotten a little bit better and we're still working on this, processing a lot more qualitative and quantitative information alongside our customers to show them all the different ways that they're using and getting value from our product or maybe gaps in our product. And so the idea of like a partnership review, right? Okay, let's sit down. Let's talk about how things are going. that's one area where it does feel like there's an opportunity to have a much much richer conversation than there was in the past because going all of these different gong calls and dashboards and data it was doable but there's there's a lot of work and you can kind of automate more of that now and make that make that easier um we work with a lot of our customers in slack also.

50:29And, you know, I think that there's going to be some cool ways for over time for more, let's call it like external agents to become kind of part of that workflow. My simple response to your question would be like the direct conversations and whether it's on Zoom, but especially, you know, at least occasionally in person, that is as valuable or more valuable than ever. And for products like ours, where it's a considered purchase, where there's at least a important shared level of responsibility around the outcomes, I think that that will continue to be really, really important for companies like ours.

51:05If you go back six years ago, and you could give yourself one timeless piece of advice, what would that be? There's certain things that you learn building a company that are difficult to fully internalize until you go through them yourself. like words of wisdom about company building that you could read in a book you could understand theoretically um but it's only until you've actually gone through it and or made mistakes that you um fully internalize one example that comes to mind for me um the idea of hiring people for a startup that really care about that startup and really care about the mission of that startup and are aligned with the values of that startup.

51:49I think I had this idea in the early days of standard metrics, sometimes that the goal was to hire really smart people and then you could figure out how to mold them into your values. You know, as long as they were like a reasonably good values fit, you can kind of mold them into your values. And as long as they kind of cared about the mission, you can get them really excited about your mission. I think for some people that's true. but for a lot of people building a startup is really hard and you need people to be incredibly well aligned on the way in which forces you to be much tougher and much more stringent about how you hire not just on the hey this person did great on the you know coding interviews or has great references or crush their quota at their last company or whatever the evaluation process is for their function, but more figuring out, like, why do they want to be here?

52:42So if I could go back in time and give myself advice before starting Standard Metrics, I think the biggest piece of advice that I would give myself is hire slow and screen relentlessly for mission and values alignment and be more comfortable saying no to really talented, smart people because they're not a good mission and values match. Is that because startups, as you mentioned, are hard and when times get tough, they're going to leave to another firm or mentally check out? Yeah, that's part of it. I think that part of it is, you know, what's the reason why this person gets up for the fifth time after they've gotten, you know, bad news or punched in the face or their colleague has left or the customer issue happened or they lost the deal or whatever it might be.

53:28And then the other part of it is that I think that especially in a small company, you know, we're 68 people now, so we're not tiny, but we're not a big company by any stretch of the imagination. Every person has such a deep impact on the culture of the company. And it only takes one or two people who are not aligned with the values of a company or the certain way of doing things for, you know, distractions to emerge. and we're talking a little bit before about like the backlog and the core competencies and you know what's where should you focus your time i think that when you look around and everyone is on the same page for why we're here and why what we're doing matters and how we do business and how we work together it makes it so much easier to like reduce that mental load and just focus on the work you're working on the mission not in essentially babysitting and aligning people to that mission?

54:23One of our company. So one of our four core values is work in the open. The idea is that we lean into transparency at our company. There are certain things that we don't work in the open on. For example, we don't do like performance reviews in front of the whole company or whatever. Some companies do, like I think Bridgewater or something like that probably does. But the default at our company is if you have a meeting, write it down. It goes in Notion. Everyone can see it. If you're creating a doc, write it down. It goes in Notion. Everyone can see it. Slack defaults open channels. If you're telling someone you're running late, it's fine.

54:54If you're talking about something that's really sensitive, totally fine. But in general, make things discoverable to other people. And it turns out that that's now extraordinarily valuable because of AI tools. Suddenly we have this exhaust that, especially via MCPs, think like Slack, Notion, Salesforce, all these tools. You can start to get really, really valuable insights for what's going on across the whole company. but even before MCPs was really useful. There are certain people that were hired over the years that did not buy into that. And I kind of thought to myself, like, I'm going to work on that.

55:28I'm going to figure out how to get them aligned with that. And that's a risky endeavor. And it turns out that if you're kind of misaligned with one of those core values, it can create so many downstream challenges. And then other people say, oh, well, you know, David's not you know taking all their meeting notes and notion like I don't need to either and it's our kind of like spreading on the team that's probably one of the biggest things that I've learned is knowing that people can change and having a growth mindset I think is important but relentlessly screening for values alignment and mission alignment on the way in is kind of a critical critical tool and that's something that I I continue to interview every single person that we we hire and I plan to do that as long as I possibly can for mostly for that reason.

56:15My second master's is in psychology and gives me a unique lens into to these problems and one of the new ideas in psychology is this concept of internal family systems. If you want to look at there's a kid depressed or a kid has anxiety oftentimes it's not actually you can't just look at it in a vacuum you have to look at it within the family system and oftentimes it's these family systems that have these dynamics that actually cause this anxiety or these problems in the kids. And same goes with organizations. You can't just take the person outside of the organization to try to psychoanalyze them or understand what's going on.

56:50Oftentimes, it's this effect of the organization having. And sometimes you take one part out and the problem goes away. Sometimes you put one person in, the problem comes back. So it's much more interconnected, the way organizations work, than most people realize. I think it's a really good point. And it actually there's actually a couple of interesting downstream implications of that. Like one of them is, you know, how do you assess somebody well if they haven't actually worked inside of your company? Everything that you're doing during the interview process is kind of a simulation, right? It's like we're going to meet the head of sales.

57:27You're going to, you know, present this thing. You're going to have this interview with John. It's all trying to get at predicting how well this person is going to perform within your company and what kind of team member you're going to be. Some companies have taken the approach of these effectively firing up these working relationships before someone becomes a full-time member of the team. How do you do that? There's one way that we do that. We don't do that with most employees. We have done a lot of internships that have converted into full-time roles, especially for folks that are coming out of undergrad or, in certain cases, out of business school.

58:07That's been really powerful for us. Because if someone spends a summer at your company and is just an unbelievable team member and you've gotten to know them really well and you've seen them under pressure and you've seen them perform and you've seen how they align with your values and how deeply they're kind of embodying the mission of your company, you have a really good sense for what they're going to be like as a full-time employee. So I think the hit rate there for us, you know, knock on wood, has been very, very high. And then the other thing that I think is interesting is like people oftentimes in the earliest days form a very cohesive startup kind of culture by hiring people that they've worked with and that they already know.

58:49That's your risks. Which has pros and cons. it's not perfect, but if somebody's worked with someone on the team professionally, and that person is a great member of our team, and they strongly vouch for them, and they bring them into a recruiting process, that doesn't mean that we don't go through our full process and try to evaluate them very strictly. But I think there's a much higher probability that that person is going to work very well within our company, because that person who's referring them has a strong incentive for them to work out. If they don't work out, it's kind of a painful experience for everyone.

59:26So there's this additional layer of filtering from the team that oftentimes extends into that area. There's a couple of ways we sort of get at it. Have you seen any interesting examples of companies that do these? I don't even remember what people are calling it now, but these kind of like work practice or kind of consulting engagements before they start working together and that kind of stuff. I've seen on a customer basis the fully deployed engineers Palantir would send over the engineer on Friday to work on your problem before everyone else, their competitors pitched on Monday. So they would literally give you a work sample.

59:56We use internships as well. It's a big problem. And a lot of the top CEOs that run organizations with 10 ,000, 50 ,000 people, they've oftentimes, many of them have told me that they know whether someone's going to work out the second week. And then the question is, how do you compact that? I think internships are a great thing. And whenever possible, doing projects, which I think with any form of information, the goal is not to reduce 100 % of the errors, but can you, is there an 80-20? Is there a one-week project that you could give, or a case study that you could give, a one-day case study that maybe takes your failure rate from 50 % to 20 %?

1:00:38That's a massive difference just right there. So I think it's an unsolved problem. Yeah. The other thing that we've tried to think about a little bit is, how do we make sure that we do everything within our power to make sure that people leave their onboarding process aligned, excited, and well-ramped? One of the challenges that we face, which is also a strength in other ways, is that we are a remote-first company. We have an office in San Francisco. We have an office here in New York, but we also have team members all over the world. One change that we made over the last year, which I'm actually really excited about, is that whenever a new person joins our company, we fly them either to San Francisco or New York for the better part of a week for onboarding with their manager.

1:01:21That act helps to really reinforce and strengthen some of those more kind of qualitative aspects that we discussed before. But yeah, it does feel like an unsolved problem. There's so many people that I would love to say, hey, come work at a company for a month. We'll pay you handsomely for that time. If it's a great fit, amazing. If it's not, no hard feelings. I think the challenge that we face there is just that people are so busy. People have so much going on. Oftentimes, it's an existing job or it's hard to do that. But I know other companies, I'm trying to remember which ones, but there's a few other companies that I've seen that have leaned in hard there and sometimes only hired people after they've done at least maybe like a week plus of work with them.

1:02:06And, yeah, maybe we should give that a go. The last thing that I forgot to mention before is developing more managers from within. It is very hard to know what someone is going to be like as a manager at your company. And if someone's been an IC on your team for a year, two years, three years, four years, and you've seen them every day, you probably have a lot better sense for what they're going to be like as a people manager. Right now, for example, we have four engineering managers at our company, and all four of them started out as ICs on our team, which I believe is the way that Ramp has approached it.

1:02:36I believe they may have a rule around that, where it's like, Like, eng managers all need to start out as ICs first. And that, I think, helps to reinforce some of these kind of values and cultural norms. John, this is an absolute masterclass. Thanks so much for jumping on. Thanks for having me. Thanks.