Paul Madera of Meritech Capital joins Nick to discuss Co-Founding Meritech, Betting Early on Facebook and Salesforce, Avoiding Shiny Objects, and Thinking Like a Public Market Investor. In this episode we cover:
- Challenges in Late-Stage Venture Capital
- Revenue Momentum and Investment Decisions
- Public vs. Private Markets and AI Investments
- Defense Tech and AI’s Role in Workflow Software
- AI’s Adoption Curve and Market Competition
- Investment Strategies and Future Outlook
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The host of The Full Ratchet is Nick Moran of New Stack Ventures, a venture capital firm committed to investing in founders outside of the Bay Area.
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0:18
Paul Madera joins us today from Palo Alto, California. He is the Co-Founder and a General Partner at Meritech Capital, a venture capital firm founded in 1999 that focuses exclusively on investing in late-stage technology companies. He’s backed some of the most iconic technology companies of the past two decades, including Facebook, Salesforce, Braze, Glaukos, and DealerSocket.
Prior to Meritech, Paul was a Managing Director and the Head of the Private Equity Group at Montgomery Securities and an investment banker with Morgan Stanley. He began his career in the U.S. Air Force as an F-4 and F-16 pilot after graduating from the United States Air Force Academy.
Paul has been named to the Forbes ‘Midas List’ multiple times, recognizing him as one of the world’s top tech investors. Paul, welcome to the show!
1:07
Pleasure to be here. Thanks for having me, Nick.
1:10
It’s a pleasure to have you. Just before the call, you told me this very nice story about your first interaction with Danaher and the rails brothers coming to visit you. Can you share that briefly before we jump in, be
1:21
happy to so. I was a recently departed Air Force officer going to business school at Stanford, and the rales brothers came in as the guest of our instructor, who was a guy, a legendary instructor there, named Jack McDonald. He knew the most interesting, iconic business leaders of the era. This must have been 89 and the rales brothers came in and told us about Dan or her, what they were doing, how they were doing it. And I, of course, had no money as a as a young Air Force officer, spending everything I had on tuition and but I listened closely, and when I made a little bit of money, my first $15,000 I put it into Danaher stock, and I still have that stock today. It has done fabulously well. So when I saw your background having been at Danaher, I thought, wow, that’s one of those special guys that really has done very well for my personal portfolio. Thank you,
2:19
Nick. Well, you know, in 11 years of hosting this podcast, I think you’re the third person that has mentioned, you know, their favorable experience with Danaher. There’s not too many of us in venture that have some connection to the company, so thanks for sharing that. And a big shout out to the rails brothers and and Larry Culp I saw a data point recently that Danaher has been the second best performing public stock behind Apple over the past three decades. So they’ve had, they’ve had quite a run. But this is about maritech and yourself Paul, so tell us a bit about your backstory and your path to becoming a VC. So
2:55
as you mentioned, I’ve got a little bit of a non traditional background. My dad had been a naval officer. We moved around Navy bases all my younger years. Dad was a sub captain, and so I grew up around the military, but I didn’t want to be in the Navy. I figured out I wanted to fly fighter jets, and so with a little bit of study, I figured out the most, the highest probability of getting into a fighter cockpit was going to the Air Force Academy, so I set my sights on that. I managed to apply, get admitted, Graduated, went to pilot training, and I got to fly fighter jets for 10 years, on active duty, actually, before I went to business school. And at the time, this was 1990 the very the popular career at the time was investment banking. So I went to Morgan Stanley in New York for several years before my wife told me she was she and the kids were moving out of New York. I was welcome to join them, but they were on their way. So I figured I probably ought to find a job in another place. So I did. I found another job in San Francisco, working for Montgomery securities, and for several years I did private placements for later stage venture backed companies, before I had the chance to start maritech with the sponsorship of Excel and and oak Investment Partners and red point and and we actually raised the first billion dollar venture fund back in 1999 the record from that fund not so great. You won’t see us bragging about that publicly too much. But since then, we we’ve continued to focus on later stage companies. We just started investing our eighth fund at this point, and it’s actually the first time we’re back over a billion dollars, and we continue to look for Series C and series D companies where we invest between 15 to $50
4:54
million for the first check in perfect. And
4:57
what was the motivation back then for. Excel in red point to kind of lock arms and support the first maritec fund. Well, back
5:06
then, you know, in the 90s, a large venture fund was $100 million and because companies could mature enough to go public and raise $25 million by the way, they they didn’t, there wasn’t a such thing as late stage venture, because there wasn’t really a need for it. However, the late 90s, there were a number of companies that needed another round, larger round of capital before they would be ready to go out. And as a result, Excel and oak and the like decided that they would try to have a partner Fund, which they invited me to help set up and and then, of course, that was, that was the beginning, really, of the late stage investing trend, which is today the largest part of the ventured capital continuum.
5:57
Amazing, amazing. So you’ve backed some category defining companies like Facebook, Salesforce, braze, where, in some cases, Facebook comes to mind. Price was scrutinized quite a bit on the way up in this new era with AI in the seemingly, seemingly limitless upside. You know, how do you think about price, and does price still matter? Oh,
6:21
it’s such a great question, particularly for now. And if there is one reason I really have learned the hard way over the years, it is that price absolutely matters. It matters a tremendous amount. Now you can pay up for great companies, but there are always hurdles and challenges that show up, impact the value, impact the timing to value. And so you can’t just go out and pay up for everything as as seems to be the case today when we when we paid up for Facebook and then Salesforce, you know, actually, interestingly, the price we paid for each of those was $500 million enterprise value, and it was quite high. It was quite high. However, having been at the banks earlier, myself and my partners could see that those companies had the characteristics and were close enough to going public and getting marked up to what public investors would pay. We were comfortable paying them. We do not have that feedback loop today, and it is. It is making valuing later stage investing so very difficult. How do
7:29
you think about the multiple that you can pay? Like, you know, what’s an acceptable range? How far forward do you go? Do you go forward? 12, forward 18, forward 24 like, talk us through that a little bit Well,
7:42
ironically, for so many years, investing in the venture world was at a discount to public multiples because there was illiquidity, obviously, and unpredictability. Today, companies of a certain size certainly are more predictable. So that that discount has gone away and what has come how, as time has gone on, now we’re investing at at premiums to public multiples. And so it is a it is a massive challenge. Now, ironically, prior to 2021 for 10 years, prior to 2021 which was the peak, the recent peak, we saw companies get valued more highly in the public markets every year, a little bit higher, the multiples would grow, and so even if you overpaid, you would be bailed out, because the markets would rise up and you would look smart for having overpaid. That has not been the case since 2021 we don’t have that feedback loop. If anything, we have this decreasing set of multiples that many of us who are investing seem to be wanting to ignore and expect that we’ll get back to those, those very high multiples from a few years ago. So it’s a really tough time now. That’s combined with another factor, which is there’s a tremendous amount of money in the marketplace. And unlike earlier cycles where a lot of that money was from public funds or from individuals, and it could leave the late stage venture sector and go elsewhere, these funds got raised and put into venture funds targeting later stage. So they’re there for a long time, and they’re not going anywhere else. So that exists today, and we find that is another factor that’s driving up pricing sort of beyond historic norms.
9:33
So so we’ve got some pricing challenges. We also have liquidity challenges. There’s a confluence of factors, companies want to stay public or sorry private longer for a variety of reasons, and there was some overpricing that occurred a couple of years ago, which some of those companies need to grow into price and can’t exit quite yet. The IPO window is, you know, has been shut for a while. It’s way down. So in your estimation. What do you think needs to happen, or Will anything happen to kind of relieve this liquidity crisis that we’ve been in, in the late stage markets? Well,
10:09
I think, I think a lot of things are happening now that that will help us. It’s going to take some time yet. I think LPs are investing less into funds by a significant amount. So the amount of money will certainly go go down over the next few years. That will be a favorable dynamic. The other one is, you know, AI is as early as it is, is proving and will be a tremendous boost in value that’s driven by functional contributions to the economy, and I so I believe we’re going to see a whole nother cycle that sort of started with the internet, and it’s been a wonderful sort of multiplier of investment opportunities for us, and AI will provide the same thing over the next few years. So with money coming down with a new investment thesis, as well as IPO markets opening up as they eventually will, things will improve. It’s just a little uncertain as to what the timeline is going to be. We talked
11:15
about pricing and we talked about multiples when it comes to late stage investing, revenue momentum seems to drive 90% of these decisions. Is that lazy underwriting? And how much should growth play as a factor in the decision?
11:32
It is really lazy underwriting. You’re absolutely right, and those of us who’ve been doing it for a while certainly have learned the hard way that it is not a great way to make most of your investment decisions. Ironically, in some ways, the early stage investors, the world you live in, Nick and and and others, don’t have a lot of things to look at. I mean, you’ve got you’ve got founder, background, ideas, team and so forth, and the sector, and that’s about it, and you’ve got to make the call based on a narrow set of criteria. We, in the late stage, have revenue momentum, but we have everything else as well. We’ve got we’ve got customers we can talk to. We have competitors we can talk to. We have management dynamics that are visible for us. And in fact, you know, I consider that those things equally important as revenue, momentum, this recent, this recent acquisition by Google of Wiz, I think, is a really interesting dynamic. I mean, there were people circling around that looking to invest just slightly below what Google took it out at and who can blame those founders for finding their exit? But that would not have been a great investment if you invested at $25 billion and it got acquired for 32 billion so anyway, there’s lots of things to look at, and it’s really important to go look at them in addition to just that revenue momentum. You
12:59
know, you brought up this, this Google acquisition of Wiz, and it remains to be seen if it will close. We hope so this time, because there was kind of a false start on that before. And we discussed a bit about how the IPO window has been shut, but it seems like M and A is back. And there was this quote that that came from the FTC and Matthew Ferguson that we’re not going to be deferential to the C suite. We will be the cop on the beat for big tech. So when we read that and hear that, it almost feels like a continuation of Lena Khan and her administration. Like, what’s your take and what do you think we should expect going forward? Oh
13:40
gosh, I wish I was better informed here. Lena Khan certainly made it very difficult for the startup community in ways I’m sure she didn’t intend. I’m sure she had all the great desires and focus on doing the right thing by most Americans, but she really didn’t, because the venture community depends on those M A acquisitions, that M A exit opportunity to both help the team realize great returns, recycle to another startup that’s going to provide value and do something innovative. And in addition, you know, they small companies typically can’t dominate an industry in a monopolistic way, so I hope that the new team is more cognizant of this and recognizes that there certainly are some combinations that shouldn’t be allowed, but the vast majority of smaller companies, startup companies, really are not going to impact The overall competitive landscape. Perfect.
14:40
So So Paul Public, SaaS, multiples have compressed while there’s still significant capital flowing into the late stage private deals. Are we living in two completely different realities, and which one do you trust more right now?
14:53
Boy, we are living in two different realities, and it’s a it’s a real issue for those of us in the late stage world. I. I trust the public markets and the acquisition metrics, primarily because they are the ultimate determinant of real liquidity, the real value of a company. I mean, when we look at markups to investment markups in our world, that is not liquidity, it is a small amount of capital relative to the overall value, and it’s being driven by a very narrow set of people and investment firms. And we should not fool ourselves into thinking that that is the the ultimate arbiter of returns and value. You know, the old DPI versus tvpi DPI is what really matters, and you don’t get that until a company goes public or gets acquired, and if anything, I mean, we’re we’re in our industry, as you know, Nick You and I have been around for a while. There’s a lot of younger investors who haven’t seen this full cycle. So they’re actually very smartly looking around, seeing what others are doing and how they’re paying for things, and they’re keying off that, as opposed to having the real feedback loop that we require, which is IPO and M and a base that data is just not coming back to us right now in this market, and we need it is
16:15
that something you encourage your late stage founders to do is spend time with analysts and folks in the public markets that can help them think about structurally, this is the way your business will be valued.
16:28
Yes, absolutely. I mean, it’s, you know, Facebook, you mentioned early on. It was really interesting to watch Facebook, pre IPO and post IPO. And the post IPO is a was a process that was really beneficial for them, and I think it is beneficial for almost every company, and by not having that, or having companies delay it when they can go out, is a real danger for them. For one thing, public markets value growth more so than other elements of the business model, but they still care a lot about a leverage of the business model, trends and the longer term market opportunity. When you’re in a private company and you can do some rounds and get some liquidity for the team, a little bit, you don’t have to, you don’t have to go through the very arduous preparation for public markets. You don’t have to file an s1 you don’t have to look very carefully at how you run your business and how it’s going to improve on a quarterly basis. And you don’t get very careful on how you spend your money, because the private markets don’t hold you to the standards those metrics the same way the public markets do. And for Facebook, who saw that, you know, different focus and feedback loop pop up, they really did change what they did very quickly and very positively for both the business growth and for leverage in their in their in their business itself and those companies that actually delay it now that could go public but choose not to, they’re there. They’re a little bit lazy, but they’re also not going to benefit from getting that feedback, which will help them get better. How
18:15
long do you expect we’ll be in this period of sort of opaque pricing discovery, where it’s it’s so hard to even figure out how to price a lot of these AI startups, because the business models haven’t quite evolved to where they need to be. And a variety of other factors that you mentioned, you know, is this, is this a temporary issue, or are we going to be in this for an extended period? It’s
18:39
it? Well, it is temporary. But how temporary I could I just don’t know, you raised the AI companies. How do you value them? I think that’s a really good question right now, as you know, we’re pouring tremendous amounts of money into these companies. It’s seeming very high valuations. I mean, we all know that open AI just raised at 600 billion. I think was the price tag, you know, to get a 3x return on that money, they’ve got to be valued as one of the top five most valuable companies in the world and and so, you know, one can say, what’s the chances of that? You know, it could happen. But is it more probable than not? I don’t know. The problem with AI is that it has such promise, much like the internet did back in 1999 I think we’re going to go through a really interesting shakeout on AI that’s going to perhaps be similar to what we saw in 99 it won’t take nearly as long, but if you remember the dynamic in the big tech bubble bursting, it was that this internet thing came up, and lots of smart people said, that’s going to be fantastic for our businesses, our personal lives, online shopping, connectivity and the like, and all of these kinds. Companies came to the market with this wonderful vision, and they sold private investors and then public investors on this vision, before the business was really there. And it turned out the early versions of the internet couldn’t handle the traffic. The second piece was the software wasn’t really ready to deliver the value promise. And the third piece was customers weren’t ready to change the way they’d been doing things, even if it made perfect sense. So that first wave of companies essentially failed, most of them, and it wasn’t until 10 years later that the next wave of companies really could deliver the promise of that, of that first wave. And now, of course, our lives have changed. We do things so much differently. We rely on these companies. The tech world has grown dramatically. I think we may be in for something similar in the AI world. Now, it won’t take 10 years. It’ll be much more compressed, but these first companies coming out are offering sort of different elements of the AI value stack delivery process, and we don’t know yet which are going to be the most valuable or the least valuable. We do know there aren’t very many barriers to introducing a layer of software that promises certain functionality and can deliver it, but it’s all based on on on Compute provided by someone else, and a large language model provided by someone else, and that top layer of software is certainly going to commoditize. It’s really easy to do, and lots of people are doing it. So where exactly the value shakes out how valuable these companies will be will be a very interesting couple of years, I think, for all of us to see.
21:52
And when you cite some of the model companies, like open AI, a $600 billion valuation, I mean, these companies have grown to a size and scale where they’re not public, but they’re kind of quasi public, private, like it’s, is this like almost a new asset class, you know, beyond the C or the D round. I mean, how should we think about that?
22:13
It really is. It really is. And it’s a different class, because you can get some liquidity, some limited liquidity for founders, for team members, and that has become almost an annual thing for many of these large companies. You know, SpaceX is doing it. Stripe has been doing it, Klarna has been doing it. And they’re just reflective of lots of companies doing it. And so they sort of relieve the pressure to go public, and they provide a little bit of liquidity, not to investors, but to the team members. So there isn’t, you know, investors are not necessarily aligned with company leadership in that, in that way. I think that it actually it, it’s something that I’m not sure I have a great solution for, because we all tend to want to let company leadership do what’s best in their view for the company. And if they can keep putting it off, I suspect they will do so more than they should, and that’s not a great place for investors to be. So
23:20
Paul enterprise SaaS was kind of this big bowl category for the past decade, but defense Tech has re emerged as a hot sector. Actually, one of our leading companies is in the aerospace and defense industry. What’s changed that’s kind of brought defense tech back in vogue and attracted to VCs. Once again, it is
23:41
quite interesting to see. You know, as a guy who spent some time in the Air Force, grew up around the military, I love defense tech. I actually stay very close to many defense organizations. And I hate to, I hate to be the bearer of bad news, but I think there’s some real danger there too. And I say that because I know very well how the Defense Department buys, how it utilizes, how companies can grow within that environment. And ironically, I think they are a very fickle customer, because the actual decision makers change continually over in the Department of Defense, it’s very hard to talk to the end customer as an investor, because they don’t really want to talk to you, and they don’t think they should have to talk to you. And then, you know, the last thing is that there’s been a relatively short list of liquidity experiences by defense tech companies so far, you know, there’s been one IPO, that’s Palantir, so I love it, and I and I think that the dynamics are changing by the way. We know that from the top down, there’s tremendous pressure on the bureaucracy to change the way they’re doing things, and there’s real urgency from the bottom up. Up to get access to new and different technology, and so it will happen. I think the bigger question is just, what’s the timing? How? How long will this take to to play out? And, you know, change it into more like a commercial investment opportunity than we’ve than we have seen so far. So I’m very hopeful. I just don’t know if it happens later this year, next year, the following year.
25:25
Interesting. Yeah, you brought up Palantir. It makes me think, like defense companies that have built their entire new platform, a completely new business, we’ve seen a lot of success there and and those that want to spec into an existing platform, maybe like, you know, used to fly the F 16 or something like that, like you can get specked in for many, many years, but much less control over your fate on those types of endeavors. So let’s go back to AI. We talked a bit about AI. You mentioned kind of the software layer, you know, sitting below compute and the model layer. Do you think that vertical AI and application layer AI is kind of the new version of SaaS, and does it replace SAS as a category, or do the two coexist alongside each other?
26:13
I actually think they’ll coexist, and I think they’re going to coexist in a really phenomenally positive way for all of us. If I can give you an example, I think that a lot of the workflow and we’ve invested in many workflow companies over the years, and one that I’m particularly excited about is company called filevine, based down in Utah. They do legal workflow for medium to small legal law firms, and I think they’re a wonderful example of what’s likely to happen here over the next couple years with AI, which is the customer set, gets very familiar with their workflow software, whether it’s Salesforce or file vine or or a service now and so forth. And what those companies can do and are doing are layering in AI on top of that workflow that the customer is already used to, working with, interfacing with, is trained for, knows how to utilize and collaborate with the rest of the firm around and so I think that’s where we’re going to see most of the early AI impact, which is combined with SAS as you say it. I mean, there’s lots of other AI standalone offerings out there, but I think they’re mostly experimental at this point. I think I think boards and senior leadership of companies are saying, let’s go out and try it all. And so companies are doing that, but it’s not really sticking quite yet into the workflow, which is still owned by those classic companies that we know as SaaS companies.
27:50
Interesting. So I imagine that as you’re working with portfolio companies and sitting on boards, you’re collaborating with those founders on Best Use of AI, whether it be internal operations or in the customer facing product, and how best to deliver the solution in a more elegant way.
28:08
Absolutely, absolutely. Every board is talking about it. Every board is looking for ways that we can do things faster, smarter, more accurately. I actually think a lot of the agentic offerings will be another delivery channel for AI, whether it’s the chat that we’re all using, or it’s the or it’s the call centers those are adopting AI very quickly. You know, they have a very limited, I should say, bounded, set of of reactions and advice and processes to go through. It’s easy to to program those things in a way that that they can show real value very quickly. But the reality is that, you know, there’s just a few categories where it’s going to be really obvious and add value immediately, I think.
28:56
And Paul, how do you account for the risk side? Right? We love talking about the upside of AI, but do you believe in this AI risk curve? And there was a nice article written by probably butchering the pronunciation here, but Yaman ball or Jamin ball, and he outlined how AI startups grow fast and fade fast. Is that a useful lens for late stage investors?
29:20
It really is, and it’s a real danger, I think, for late stage investing, you were talking earlier about revenue momentum. Well, many, you know, actually, many of those early internet companies actually had really great early momentum. I remember a company called shoe Dazzle. You remember that I do? Yeah, shoe Dazzle. What was shoe dash? Shoe dazzle was this online offering for young women who liked fashionable shoes, and you could join shoe dazzle for a monthly fee, and they would send you a new pair of shoes. You could decide if you wanted to buy it or just sort. Abuse it, send it back, and it grew spectacularly for the first eight months, and then it fully penetrated its market, and it stopped growing at 45 million of annual revenue. And so it went from being incredibly valuable with an unlimited future to very capped value. And I think we’re going to see something like that around AI, and that is that AI is so easy to adopt in some ways, unlike the the SAS companies who sell you a workflow software, which you have to install on your on your servers at your company, you’ve got to customize it in certain ways. Then you have to train the employees to use it. Then you have to beat them over the head so they all get on it and they all use it the right way. AI is very easy to layer in it interfaces. It’s smart. It’ll configure itself. It’ll start offering value very quickly. And so it’s really easy to put in, but it’s equally easy just to take out. And SaaS software is not the same way. I mean that there’s friction around pulling out that software that everyone has used and trained on, and not as much on on AI. So we do see a lot of these AI offerings have a great deal of churn here early on as companies experiment and find it easy to say, No, I’m going to go try another one. Maybe I’ll come back. Maybe I won’t.
31:26
Is, is most of that churn due to other offerings that are promising something better, or is it the original promise of the AI was so exciting that it was adopted, but maybe the the true delivery, you know, didn’t kind of measure up to the promise? Yeah,
31:42
that that’s a great question. I actually think it’s more the latter. I think, I think that top down, demand that we get on AI and study AI is generating a great deal of interest, and people going out and spending to try it out, and they’re finding it’s not quite what they expected, or it doesn’t work quite the way that it should for them. So they’re they’re happy to just, just get off it, rethink it
32:06
interesting. So Paul software spend continues to rise, yet company growth is slowing. The top quartile of SaaS companies are growing at slower rates today than the bottom quartile of companies in 2016 and the median has never been lower in the past 10 years. So are we hitting the limits of SAS scalability, or is this a temporary effect caused by, I don’t know, IPO gridlock and aging private companies, et cetera? Well,
32:34
I’m glad you asked this, because for once, I can be a little more positive. I actually think we’re still early in the software slash AI revolution. And by that, I mean I look at Salesforce, which I know intimately. And you know, when Salesforce came out, it was the solution for everything that the Salesforce needed to touch. It was the full package. It had everything. And what we have seen over the years is that there’s been plenty of new entrants that have come in and offered one new slice of that sales force, offering in a better, more complete way. You know, vertical offerings, for example, high spot up in Seattle that generates tracking of of sales pitches and material. There’s outreach, which is another sales tool for sales forces to go out and very organized chase down their their clients. There are. There’s BDR management tools that have all popped up. So all of these came out of the original sales force footprint. Yet Salesforce is still doing great and still growing and still and this, this, this slicing up of these various sectors is is still in the early ages. I believe, you know, we’ve seen it happen in the marketing slice. We’re seeing it we’re seeing it happen in the IT slice. I mean, all of these sectors that we know and think of as separate categories are all seeing a plethora of new offerings, all that have to offer new value for people to buy them and use them. And they’re doing it. And I think this actually continues for many years to come. Yet, how
34:11
has sales? Salesforce maintained its advantage? Right? You know, classically, these companies grow and they get so large, and they start to become everything to everyone, and then they become nothing to anyone. And that’s the opportunity for startups, right is to niche down and like, serve like one customer set or one wedge. How is Salesforce maintain this dominance? You know, with CRM
34:37
such a good question, because it is a wonderful lesson for all of us to look at and and what they did is they continually have thought about, how can I offer more value to my customers, and where will the Where will the startups come after me? So they did things like start the force.com platform, the force.com platform that effectively allowed other. Were offerings that were related to Salesforce. To plug in. They had to pay Salesforce for it, and they do Viva being the biggest and most impressive example out of that. But it also offered all these, all these younger companies without much of a market presence, a way to take advantage of Salesforce and Salesforce could partner with them. Salesforce also offered, has continued to acquire and expand the breadth of their offerings so that they were in more sectors and offering more value. They’ve done it very, very well. And companies should watch them study that. And as you get to a certain size, go do it. I mean, Oracle was doing that before them. Love it. And
35:42
in a maybe a loosely connected way, maybe Mark Zuckerberg is doing that with his recent announcements on the llama side. And, you know, speaking of Danny off and Zuckerberg and grimagian, I mean, you’ve worked with some of the greats. Like, what do these folks have in common? Wow.
35:59
You know, for one thing, they’re not conventional. There’s they’re really great. Entrepreneurs are just a little different from you and me and most of us. They have this, this, this determined view of their product and their world that they stick to long beyond when they should. And maybe, and maybe Mark Zuckerberg didn’t go through this as much as Benioff, but, you know, Benioff could not get conventional venture funding when he started out for many years, because there was this thing called Siebel systems out there that was so much broader and more capable than Salesforce was to start with. And as a result, nobody wanted to give many money and fund it, but he, but he did what great entrepreneurs do, persisted, chase down his friends, raise money through unusual ways, and, and, and, you know, they’re just, I don’t want to use the the word weird, but they are a little different from most of us, and They and I have learned to accept that and embrace that actually look for it in in interesting companies that we’re evaluating. So
37:08
before we move on from Ai, you know, I think we all expect it’s going to change the world at this point, it also seems to be priced as such, but we’ve seen how long enterprise adoption can take, right? You’ve talked a lot about software and how software will sustain for a variety of reasons, but we’re still seeing less than, I think, 50% total cloud software adoption in the enterprise, according to the last reports from a battery and index that I read. So will AI’s adoption curve be more rapid than what we’ve seen with cloud software? It
37:40
will. It certainly will. It’s easier to adopt. It doesn’t require nearly as much investment, time, energy, a tech resource, and so forth. And it’s actually going to get easier in the near term. I mean, it’s that’s the beauty of AI. I do think though. I mean, just to give you an example, I mentioned earlier how all of those companies in 99 that got started up, most of them did not do well. You remember who they were. They were web, Van pets.com, us, web, our house was the hardware offering, SGS and the like and all those things, of course, are, are, are remarkable companies in their vision early on, and today, someone else is fulfilling that vision. And I think that, I think the AI companies might have more of a chance to to realize the vision than some of these early internet companies, because it’ll happen faster, but nonetheless, I do think that. I do think we’ll go through a period of turbulence and uncertainty as to which ones are really going to survive and do very well. Paul,
38:51
I’m curious, you know, how do you parse vision from maybe execution and nimbleness? And you know, everything post investment? Because you have some companies you mentioned, ask chiefs, right if, if Ameritech makes a bet on achieves, you know, you’re blocked out of the Googles of the world. Or if you make a bet on a MySpace or a Friendster, you don’t have a shot at Facebook. And so, you know, how do you parse these things? You know, there’s a lot of entrepreneurs pitching us at new stack with incredible visions, but you know, the follow through might not be as at the level of some of their some of their competitors. So how do you think about that?
39:30
Well, ironically, that that’s a really good question. And unlike those of you in the early stage who who don’t have a lot to go on, we do have, we do have some track record to go on, and so we can actually evaluate the differences between several different by the way, as you know, what happens now, soon as one company makes it or carves out something that looks interesting, it gets five instant competitors. There’s enough money out there to to five. Run them all. And our job, of course, is to try and pick the one, and I mean the one, the top one, as opposed to number two or number three, which don’t typically don’t get nearly as much of a market share or ultimate return as that leading entity. We have to pick and see which will be that leading one. So we spend a tremendous amount of time talking to the customers, and specifically, if we could get them to the decision maker of the customer who went through a process of evaluating and figuring and selecting and and then, of course, we want to look at the company itself and see if the team is really equipped to go to the next level. By the way, one of the one of the things we will look closely at, because it’s so relevant to our stage, is, can the CEO make that hard decision to upgrade members of his management team who need it? You know, a lot of these CEOs recruited their friends, the people they knew. They’re really beholden to their team, and it’s very tough to decide your head of marketing may not be the right guy to get you to 50 million or 100 million run rate as it was to get to 10. And so that’s that’s an element of evaluation that we’ll go through amongst many is, is
41:18
that something that you look for observed behavior, maybe at pre previous series, or is it more Q and A with the the leader, like, you know, what are your plans for your C suite here?
41:28
Yeah, it’s both Q and A as well as seeing what they’ve done. I mean, a lot of these entrepreneurs are smart enough to know what the right answer is, but they may not emotionally, it might still be difficult.
41:41
Yeah, yeah. So who do you think wins the AI race, the incumbents, the startups or or everyone?
41:48
I actually think it’ll be everyone. I actually think there’ll be lots of AI offerings that get that get attached to existing workflow software, and so there’ll be a lot of upside for a lot of people because, because there really is synergistic value when you combine those things, I do think that there will still be a lot of failures in the AI world, just as there have been in the software world, because either the product doesn’t work perfectly, someone else comes along. I actually think AI starting up an AI company is so easy relative to the earlier generation and to the previous generation that we’re going to have a lot of competition. That’s going to be great for us as consumers, as business leaders, because we’re going to have a lot of choices, and it’s going to be easy to swap out what what works best. And we’re going to do
42:42
that, Paul, do you think there’s reason for sort of the the existential threat, fear, or, you know, is that overblown at this point? Because it seems like on the consumer side, when I speak to, you know, lay people that maybe don’t work in tech, seems like there’s a lot of negativity around AI. People are not seeing the way that it can advance their life, make things easier, become like their personal assistant rewrite their emails. I mean, there’s just all these incredible advantages that we in tech see because we have to use it as part of our jobs. But a lot of people are kind of really latched onto this fear that, you know, it’s going to become a weapon of mass destruction in some way, and it’s going to take over our jobs. You know, what advice or what, what words would you share for the audience on that? It’s,
43:33
it’s really an interesting one. We’re all having those conversations with our family members, I suspect, and and, and Schwarzenegger didn’t help us by telling us such a great story about how Skynet was going to destroy the world. And I think that’s what we all in the back of our minds are terribly afraid of, and we should be, however, as you know, I mean, right now, it is so hard to get AI to actually answer the question of, can you change your flight reservation from San Francisco to Chicago to be at a certain time and to arrive at and get a rental car at the same time that’s around the corner? But we’re a long ways from having a sentient a standalone, thoughtful AI system that can make decisions that are harmful to us on its own. So I just think it’s, it’s not a realistic fear anytime in the near term. Perfect.
44:28
Paul, if we could feature anyone here on the show, who do you think we should interview and what topic would you like to hear them speak about? Oh, well,
44:36
first you ought to get Jim ball. I think he writes a wonderful column. He’s a thoughtful guy. He’s out here in Silicon Valley. You should get my partner, Alex Clayton. Alex puts together a an s1 analysis of sort of leaning tech companies that go out. It’s read by 1000s across the industry. He’s he’s really quite a celebrity in that, in that sense. And. And I know you like founders outside of Silicon Valley, so I would recommend you get one of my latest investments, the CEO of company called E Jim. E Jim is led by a guy named Philip Roche. Philip is is a German. He’s in Munich. He’s probably going to be moving to the US, but Philip is a really interesting company leader and visionary who’s developed a company that is immensely successful already, both selling a high end set of gym equipment as well as a wellness pass, a gym pass, product that he sells to the HR departments of companies, and it’s doing phenomenally well. Brilliant, perfect.
45:44
Paul, what book article or video would you recommend to listeners?
45:48
I will give you two books. One is called command and control, and the other one’s called Skunk Works. May have heard of these, but command and control is kind of the history of nuclear weapons, and this guy who used to sit nuclear alert myself. I was fascinated by this, but I had no idea what the history was from Alamogordo, New Mexico, when the first explosion occurred in 45 all the way to today, and how we have guarded those weapons, and how we’ve had so many near accidents with nuclear weapons, that we’ve been immensely lucky, that very few have really been tremendously damaging anyway. It’s wonderful story about that. The second one Skunk Works, is the story of the Skunk Works, which is the original Skunk Works. It was at Lockheed Martin, led by a guy named Clarence Kelly Johnson. Clarence Kelly Johnson designed the P 38 when he was 23 years old, that had great success in World War Two. He went on to lead a small, very capable group of engineers, machinists and manufacturers that both designed and built many of the iconic airplanes we know today, the u2 the SR 71 the f1 17 stealth fighter, and so forth. And he did it in a way that startups would approach businesses just small, capable teams that that produced wonderful product.
47:22
Love it. Love it. Coincidentally, I’m in Santa Fe at the moment. We’re going to the Trinity site tomorrow. So Whoa,
47:28
is this now? Is it one day a year that is open up?
47:33
Not to my knowledge. I think you can go and visit. And the locals here have have told me that you can go and visit and walk through all the buildings and oh,
47:42
years ago, I used to fly over that site when I was in training out of Holloman Air Force Base, and they were only opening it up one day a year, no kidding, and people would go out and try and find those pieces of trinitite glass that that were laying around on the ground. I don’t know if it’s there anymore, but Well,
48:01
yeah, hopefully the radioactive activity isn’t too high, because I’m gonna have my seven year old. But Paul, do you have any habits, tactics or behaviors that are a force multiplier? I
48:11
do, and my partners like to laugh me about this, but I’m going to show you. This is the very old world style checklist that I use to track. You know, both things I need to do, near term, longer term projects, portfolio companies and so forth. And I update it every day. I start my day with with that process. I carry it around with me. I check things off, I add notes to it, and I find it’s a wonderful way to keep track of what I’m doing and be efficient, still on a physical copy too. Yeah, absolutely, I print it out. Yeah, so much for the advanced tech guy here. Well,
48:50
part of the problem I find with the laptop or the phone is there’s all these notifications and distractions and so, like, sometimes it’s nice just to have a physical sheet with the priorities. It is yes. And then finally, here, Paul, what’s the best way for listeners to connect with you and follow along with meritech?
49:06
Yeah. I mean, it’s to the meritech website, meritech capital.com and they can find me and my partners there and see what we’re up to. Well,
49:15
Paul, thank you so much for taking the time to do this. This is a bucket list item for me, and it’s just such a pleasure and such a privilege to have you on so thank you.
49:23
Thank you, Nick, thank you. Have fun. Tomorrow, I will
49:31
all right, that’ll wrap up today’s interview. If you enjoyed the episode or a previous one, let the guests know about it. Share your thoughts on social or shoot them an email, let them know what particularly resonated with you. I can’t tell you how much I appreciate that some of the smartest folks in venture are willing to take the time and share their insights with us. If you feel the same, a compliment goes a long way. Okay, that’s a wrap for today, until next time, remember to over prepare. Choose carefully and invest confidently. Thanks so much for listening.
