5 Ingredients for the Perfect Investment | Jeff Horing Interview

[00:00] I'm a big fan of the value prop. I want to hear the entrepreneur explain how they're generating real value for the customer. In fact, I I think when I look at what makes for the perfect investment, I have kind of thought about the the five ingredients to me all at zero. Perfect investment. So, [Music] I thought it would be fun to begin with a kind of weird but interesting question
[00:30] per our past conversations, which is if you could go back in time and think about the original SoftBank vision fund, which was hundred billion, huge fund. Of course, everyone was talking about it. Who knows what'll end up happening with it. The story is still not fully written, but if you could go back in time and you were fully personally in charge of deploying that hundred billion dollar fund, how would you have approached that problem? It's a lot of money to put out the door in a couple of years. How would you have done it? Personally, >> I I first of all, it was an eye openener
[01:00] to me when it happened and uh you know, we had sort of a small strategy that I always envisioned could be a big strategy, but maybe to kind of go backwards and say what are the best call it private equity venture deals of all time. Yeah. >> And this is a cheat answer. It's not the real answer, but I would say in my own view probably the most cleanest, best example of of return is probably VMware. Technically EMC was the private equity buyer. They spent about $650 million and
[01:32] sold it for 60 billion. So that's a $60 billion gain plus or minus. Uh you could argue Instagram billion to probably a trillion. You could say YouTube is probably a billion to a trillion. So interesting if you look at some of the M&A that strategic companies have made with some synergy that probably delivered a portion of that gain. But I would argue a lot of that was going to happen. Independent PayPal another good example. Uh almost no real eBay I think effect that really drove that. And I
[02:04] thought to myself, we had done a bunch of what we call venture buyouts and some were growth buyouts in and these could have been hundred million dollar investments of taking control of smaller software companies where we made five, six, sometimes more times our money. >> And I just always had in my head I would love to be competing with Microsoft. or Palo Alto or uh eBay for a deal because then the entrepreneur was like, "Wow, I could have my cake and eat it too, right? I could sell to Jeff for a billion dollars my next Instagram and
[02:35] still retain massive ownership, maybe even get reloaded on the options. I'm not 100% sensitive on those sometimes and that kind of a deal." And we've done that and we've had some bigger deals where we bought companies for about a billion dollars and uh there were small smaller growth standards. So there were not like what you would consider to be classic buyouts where you have cash flows and debt and all sorts of other things underpinning it. It was really just the markets and the growth and the entrepreneurs that you're betting on. And I thought if I had $100 billion rather that's what I would do. I would be like wow wouldn't that be interesting
[03:05] because I think you could really differentiate yourself tremendously from the pack. And interestingly Masa did one deal like that called ARM and it I think he's made four times his money on a really big check maybe more. I haven't tracked the stock lately. So uh you know pushing it to late stage growth I thought was a much harder strategy both for companies to consume that capital valuations that you needed to pay to get into those deals to justify that capital though obviously he made that return in Alibaba he made that return in uh I guess Yahoo was probably more my example
[03:36] Yahoo Japan of where he bought control of something and and turned it into a massive win. So anyway, that was kind of a dream I've always had. And people often ask, how does one scale >> our industry? And certainly if you look at those types of outcomes, you'd be like, well, I guess there's a chance you could do it. Could we compete >> Yeah. >> for those deals? I don't know. But uh it certainly on paper pencils out. >> Obviously, Insight has raised some of the largest funds in our industry, 10 plus billion, 20 billion. What size would you set a fund 100 billion or some other number if you wanted to do today
[04:08] in 2025 the thing you just described like how big would it have to get so that you were actually competitive with the >> today's tougher it's tougher I mean when I first this was probably 2016 >> uh when the vision fund came around and you know the concept of liquidity billion dollar exits as a massive victory for the venture I mean to get benchmark or sequoia to sell something for a billion dollars probably doesn't get their heart rate up today. So, the likelihood that they would do those deals again today knowing what the world looks like and what the upside could be
[04:38] for these types of assets is pretty small. >> So, I think it's just a little bit harder because the scale has changed. But, you know, we still and we look for these sub a billion is really the sweet spot that we could consider. But to find hyperrowth shareholders willing to exit is still tricky. Uh, and most of the deals getting done under that are getting bought for really strategic reasons where the financials can't even be imagined >> and modeled out, right? Palo Alto pays $500 million for 30 guys in Israel, that's a different
[05:08] >> game that we can't really compete with. >> And so, if you were to size a fund today, put it a little bit differently for the best possible riskadjusted return where like fund size dictates the strategy, where do you think you would size it? >> I think we're pretty close. >> What's your marginal one? >> We're about 12 billion. Okay. >> And you know, so we're deploying three plus billion a year in invested capital across a range of strategies. But I would say we definitely don't feel capital constrained to the opportunity
[05:38] set. I think if we were to, and I don't think this is part of our strategy, lean in on some of these big late stage growth rounds, you could envision a bigger fund. And certainly others have raised money specific to target that type of deal flow. That's not really the thing that that's more of a maybe a better version of that vision fund where you're buying into open AI or anthropic in big volume at latest stage prices, but it's it's not really what we we don't lose sleep over >> Yeah. >> that not being our core strategy. >> What do you make of this? I think you you were investor in the big data bricks
[06:08] round in anthropic more recently. What do you make of the latest stage private markets today? It's gotten it's gotten so interesting and crazy relative to when you started Insight. You've had a bunch of folks on this podcast I've heard who've talked about the changing private public market dynamics and you know there's I mean that data bricks is still a private company at this scale is sort of unheard of. Uh you could argue OpenAI is still a young company relatively speaking to the timing of its revenues, but um for reasons that maybe
[06:39] represent just the shifting of capital, uh companies are staying private longer and doing basically IPO plus plus rounds in the private markets. And you know, look, we look at these like we look at anything else through a lens of, you know, what's the forecast, what's the likely exit value, and what's the return on that capital. Once in a very rare while you see something at size that prices in a way that you feel like you can make riskadjusted venture-like returns. >> Maybe a a fun thing before we get into insights strategy specifically is to
[07:09] talk about your day and your life as an investor. What's interesting and unusual about you, there's basically nothing available about you on the internet. You don't give interviews like this. You seem to just be a heads down investor. um you you could have long ago retired and and yet I it my sense from talking to some people on your team and and talking to you is that you're working about as hard as you've ever done it. What is like a given week look like for you >> today and it wasn't always the funnest day. Uh I would say starts with some internal meetings of just you know
[07:39] investment committee looking at >> people's new deals uh partners meeting to spend time together and kind of sync. So this is, you know, first day back kind of day, uh, in this case, but that would be a typical Monday. >> And then I'd say a big portion of my day is going to be dedicated to prospects. >> And I make a point, as do most of my senior partners, to be spending as much time as possible hearing the stories, whether it's in person or by Zoom, uh, of new companies. Then there'll be a fair amount of portfolio calls. So I
[08:09] probably had three calls so far today on uh portfolio companies hopefully more strategic in nature than just you know what's your latest quarter and then some internal meetings on we had we'll talk about it later on you know how we're scaling the firm and do using AI to do diligence and all sorts of fun things like that. >> So it's sort of a a big blend of where I think I can contribute. What I try to do and no one's perfect at this is spend as little time as possible on things I'm not good at >> of which there's a pretty long list. So, you know, I think those are areas where
[08:39] I think I can have a meaningful impact >> and uh and also enjoy it. So, it's a lot of fun for me to do that. >> What would you say uh is the the skill on the prospect side evaluating a founder, a business, whatever that you've most improved at over the entirety of of insights existence. So, you today versus you in 9596. >> I'll say team broadly because some of us are much better at this than I am. I think our analysis of what numbers matter has changed a lot. >> Uh I remember six years ago at an LP
[09:09] meeting telling LPs we think we're at like 11th grade math on software. The industry is probably at seventh grade math on software. I think we're getting closer to college today. Uh it's still amazing what we continue to learn about metrics that really are the best predictors for future outcomes, which is really the >> the dream, especially in growth investing. you have enough almost enough data to start to kind of predict and we've also gotten better I think at uh kind of understanding sort of qualitative TAM issues and then
[09:41] it's a never- ending journey on management right like every year you learn something new in both the good and bad ways >> so uh you know people are always complicated but you definitely get better at it as you get more experienced >> can you teach us some of that college level math and understanding software businesses >> well I remember five years ago one of my companies was going public and the rage on Wall Street was net retention. I'm just picking a random one. I was already at my 11th grade math. So, I'm like, this is one of the least informative numbers I could think of. And yet, that
[10:11] was the only number that Wall Street asks. I said, the only number that really, well, two numbers really matter. GDR, which is gross retention, which is really how sticky is your customer base? How resilient is that? And more importantly, >> how much of that bucket do you have to fill every year? And you know there are very few companies with lowish software low would be 80s low80s gross retention that are in the top 20 market cap businesses. You could probably count on three fingers companies with that statistic. And the problem is that you
[10:41] get big and let's say you're losing 20% of your business every year on a billion dollars of revenue. That's $200 million of business that you have to go find just to fill >> the bucket. And then you of course want to grow 30 40 50% on top of that. So those become daunting numbers that usually reflect itself in your average cost of acquisition, right? So that would be a take your net new bookings divided by the spend that you had to get to that. Um and those numbers really kind of tend to to move together because you just have to keep filling more of
[11:11] the bucket with sales reps uh just to stay even. So I think that was an example of one. I think uh another time years ago I think we were starting up our public hedge fund but I thought a lot about calling ourselves the second derivative because so much more was learned and I think a couple guys had this right at Facebook like the early or late you know kind of the billion-dollar kind of guys that came in there but the change in new business is way more important than you know the change of the change right I'm growing 100%
[11:42] year-over-year my net new bookings that second derivative is really powerful where you see a lot of companies with almost zero change in the new business that they add each year off a small number that could still look like a really big growth rate, >> sometimes as much as 100% or 75%. >> But you can copyright that number if it's flat. And that happens a lot for example in vertical software >> where you quickly saturate the number of decisions made in a given year and all of a sudden you model out five years with a flat new bookings number and your
[12:13] exit growth rate is going to be a lot different than what Google was able to do which was compounded 100% for 15 years. One of the things I think is so interesting about Insight is the ability to just price different numbers that it's not just I think that you're buying 95 plus% gross retention and accelerating top lines or something like that. You'll buy companies that don't have those metrics. >> Changing on that a little bit. I meaning like we keep learning that you sometimes get fooled into the trap of value and it
[12:43] is not a great way to make money in my estimation and people do it and people are really good at it. I'm not going to say it's not doable, but buying cheap in technology is is certainly there's not a long list of really rich people who've done that, right? As compared to the people who've just bought the dream where there's a very long list of people who've made lots of money on the dream. >> So, I think making sure those metrics especially at scale looks like we will not do a low gross retention business today unless we really are confident we could change it. Um we think that metric
[13:13] is really the fundamental driver of all exit values >> uh and ultimately large companies. We'll obviously make exceptions if we think we can fix things or we think maybe there's a good story as to why it was maybe you know not enough sales capacity this that but you know if you ask at least half my partners would tell you they prefer not to compromise on any of those metrics like their view is if you look back in time nine out of 10 times those metrics have been the driving metrics for our success. If I think about gross retention as like one avenue of math to
[13:43] go down and that's algebra 1 like what's algebra 2 like what if you kept pressing on gross retention as an example of how you then keep digging into the business how does it work zoom out the simplest math is LTV divided by CAC right that's all you're trying to understand is I invest in money and put assume R&D gets somewhat normalized to levels that are kind of uh industry standard so that's really what you're trying to tease out GDR is a great predictor on LTV right the less I lose of a customer the longer it lasts the present value of that cash flow stream is higher. CAC is the other
[14:15] big variable on that. And then what you're trying to figure out is the market pull for that. Like how quickly am I accelerating that number? Can I add if I added 10 million of new business this year, can I add 20 million next year and 40 million the year after? And the smaller the company gets, the harder it is to tease out >> whether you're just rapidly walking into a finite market and you saturate that decision- making in that market or is it deep enough that you could imagine growing for multiple years. So take
[14:45] Whiz, which is obviously one of our favorite stories in life and great team and they've been able to double or more their net new bookings each year for six years. And just when you do that math, if you start at 10 and start doubling that for five years, that's a really big number of new business added each year, which keeps your growth rate at close to if you literally doubled it every year, you would have a 100% growth rate, you know, add infin item. >> What qualitative questions do you like to ask on the back end of the quantitative investigations? Like when
[15:16] so let's say you've got a company that has great gross retention, how do you then continue to separate? So you have to do qualitative especially as you get earlier because a lot of these numbers are still forming and it it's hard to be false precision I think could get you in trouble. I'm a big fan of the value problem. I think when I think about investing I want to hear the entrepreneur explain how they're generating real value for the customer. uh I then kind of look at in fact I I think when I look at what makes for the
[15:47] perfect investment I have kind of thought about the the five ingredients to me all that's here >> perfect investment so value prop is critical and that usually could and should translate to selling price right and then I kind of distill that and say well imagine you're going after the hospital market we looked at a chantic AI company in that market and if Epic sells $10 million a year on average in the hospital market and you're selling half a million dollars a year in the market. They're 20 times your size on average selling price. Pretty hard to imagine that you're going to be as big
[16:17] as Epic, right? Like you could sort of frame it and say, "Best case I'm probably 120th." Epic is a dominant player. You know, rare that anyone gets more market share than they do in a given sector. Best case is I'm probably 120th the size of Epic. So that's kind of a good framing of TAM in my mind as opposed to the how many customers are there? Can I multiply by this? and like the sort of top down approach I think is is riddled with errors in and thought whereas if you kind of look at what's my selling price how does it compare so you kind of want to see that average selling
[16:47] price and then compare it to companies that are targeting the same number of customer universe and that gives you at least a ballpark of what could be uh you obviously want to look at the landscape of competitors and say well what market share am I realistically going to have I think the hidden data point for me especially for early companies I've pushing on and this is where AI is sort of a pretty neat idea is what's the time to value right so when you think of a customer making a decision on installing SAP versus using open AI right one is I
[17:19] literally point my cursor to a web page and I'm getting value immediately and the other could be a three-year very expensive journey to change my organization to get it up and live and and productive and SAP has massive value to that customer base But it's a very long time to implement and that's going to just inherently slow down realistically how fast you can grow both your own ability to succeed with those customers but also just the decision-m around those complex decisions. And I think that's that's kind of framing a
[17:49] little bit of that. And then I think obviously phenomenal CEOs are always the dream. Uh some of that I I listen to the podcast I'm like wow people are really a lot smarter than I am because I sometimes write that story after the fact. Uh I certainly have plenty of phenomenal CEOs that were rejected by a lot of other firms. Uh so it's not always obvious, but I think you certainly when you get that ingredient right, whether you're able to see it or whether you just, you know, got it and then a phenomenal tech team that goes with it right because I
[18:20] think this is a world in the last 10 years where product really drives outcomes. And you've had folks on your show that talk about, you know, happiness and product satisfaction, things of that nature. putting those five things. >> Can you list them once more just so I make sure I have them? >> I'm gonna go look at my little cheat note because I I wrote them down for you. It's big ROI, big ASP, time to value, CEO and tech. Yeah. >> And management team that goes behind that tech. That's my five. I think whiz might be the end of >> checked all five. >> Yeah, maybe Monday had a bunch of that
[18:50] too, but like it's it's rare like to get the time to value and the ASP is really rare. Does it stand to reason that you think like for an SAP type company where uh the benefit of that long install process is very sticky typ you know typically on on the other side of it that the right time to invest in those kinds of companies after they've gotten their install base like that's the better riskadjusted entry point. >> I think for those companies I'm a I don't know why I have this number in my head but 15 customers that are referenceable is sort of a magic number for inflecting on growth. So the challenge with those companies is as
[19:21] much they're very hard to sell those products. It's a lot of missionary selling early on. And so you can't really scale your sales organization until you have a certain number of referenceable customers >> that you could lean on. And you know if every sales guy is pointing to the same reference site, that customer gets a little annoyed after a while. >> So you're kind of constrained by that. But around 15, not only do you know the product is really pretty solid, but you also have an ability to start to think about supply constraints to scaling, not
[19:52] demand constraints to scaling. >> Maybe you can um walk through the one fund strategy that you've chosen to pursue at Insight, which is really interesting. And I'm especially interested in how in a fund that's $12 billion, it's worth your time to look at say like a $10 million investment or something like this. So that tension is fascinating to me and the one fund strategy is fascinating to me. I know you have strong beliefs about it. So maybe describe why it is this way and and the trade-offs. I'll give you a couple angles on it, but first I was
[20:22] lucky enough to get my first job and it was a lot of luck and somebody who believed in me that hired me um at Warberg Pinkis which you know founded in 1968 maybe the world was a different world anyway but sort of developed a one fund strategy there is included stage and industry right so they were kind of stage agnostic industry agnostic some of that was mapping to LP demand for the biggest of LPs back then the pension plans there's Two things I think that if you taught finance in classic portfolio
[20:53] theory, you would be sort of scratching your head and thinking, gee, why isn't everybody doing this? So, one is risk management. So, one of the really interesting things about the vision fund was their ability to write a $200 million check that was inconsequential to the return of the fund. >> So, it did give you the obviously you could abuse that and take risk that maybe aren't sensible risks, but it was sort of fascinating that you could most of us really sweat out those big checks, right? And we're really pretty riskaverse. We want to make sure the downside is absolutely locked in. Probably the 2x case is really visible.
[21:25] There's very few firms out there. Vision fund was probably the one exception that could look at that and say, I could think of that divide by a hundred as a $2 million check in a billion dollar fund where we all could easily say, "Oh, of course I'm not going to get too worked up over a $2 million check. I'll take a flyer." So, there's a little bit of just risk management. And you could do it with check size. So, you could look at stages slightly differently. um you could look at different types of bet sort of differently. And the second advantage a single fund has in my view is I think all my peers would sort of
[21:57] admit that the best bet on the table is the double down bet, right? In blackjack, we all know that, right? You've got an 11 against a five, you double down. Like it's the best bet in the not only do they give you the good odds, but you know, you have way more information than you had before you got the hand out. >> And you know, we're not all perfect. Sometimes we fall in love with our babies, but if you went back in time and looked at our double down checks, they were our best checks. And if you kind of looked at that, we've taken5 to10 million positions. We took a $5 million
[22:28] position to a billion dollar position. >> We never would have seen the billion dollar position without getting the relationship with management with a $5 million position. We've routinely in some of our biggest exits from Monday and CENO a bunch have started with under $25 million bets that have come up to $200 million over time and we just see secondary opportunities. We see followon opportunities. So if you kind of zoom out you're like isn't that the most rational way to do it? Like why would you do anything else? And I know there's
[22:58] some phenomenal firms I've heard on other podcasts that I have a ton of respect for and they intentionally want to give that bet away. Uh and then obviously the more common approach now is I'll have a separate pool of capital for that bet. But that has its own constraints, right? Because sometimes the kind of charter of that fund, the pitch to the LPs is a little more nuanced and you find yourself in tweener bets. And I'm sure you could talk to a bunch of early investors that have growth funds that aren't always at their best deals and you're like, well, how'd that happen?
[23:28] >> Right? Now, sometimes they find a way to do it and it's great, but a lot of times they they actually because the bit the deals get bit up a little earlier than they expect doesn't really fit what you would consider to be a typical pitch to a growth fund, but it's clearly not an early stage bet anymore. And it's check size is too big for an early stage bet. What do I do with it? And we don't have to think about any of those conflicts. And we certainly don't have to think about conflicts between the two funds, which is really, you know, it could be managed, but it's not zero. like am I bailing the company out? Am I really
[23:59] supporting it? Like >> how that all looks optically could get funny over time. >> What are the biggest downsides of doing it this way? Like what what annoyances does it introduce that maybe you wouldn't have to deal with had you >> I think the biggest is you lose a little bit of discipline from third party pricing. It goes both ways. So sometimes we pra deals and we think we get great deals. I'd say more often than not that's the belief that we have is we make it easy for the founder. The pitch to the founder is you're done. If you want us, you got us for life. If you want to go out to find another partner, that's okay, too. Like, we've got our
[24:29] position. We're not going to be upset with that. But we're also here to support you the entire journey. Up till 2017 18, that was really common. >> You know, the world got really competitive starting in 18 and and a lot of those follow-on checks. We even if we wanted, we couldn't get them at the values that we thought were exciting or the founders just wanted to get third party pricing >> for their own reasons and we're going to support that. But, you know, the downside is you could kind of believe your own PS. You can get a little sloppy with a small like the $2 million kick save checks. I got to keep this. I want
[24:59] to bridge to a sale. I want to do this that. I could argue that goes both ways. Plenty of those have actually worked out where we have bridged to a sale. We have recaped the company and and and gotten some of our original money back. But you could certainly see how you could be chasing good money after bad if you're not careful. >> And what about from the LP's perspective? Like does the one fund strategy, is that a feature to them? Is it a bug? Does it depend on the LP? >> We don't fit into a bucket. My whole life I've never fit into a clean bucket. And that's the probably the most glaring one. How do you man? How do you think about that? I'm like, well, you know,
[25:30] doesn't feel like that at all when you're on the inside. It just feels like a a pretty welloiled process. But I think from the outside, we look like an N of one. Uh, you know, you go back in time to firms that scaled over the years. They almost always scaled on check size. And one of the reasons Insight exists today is literally because some of the best firms in the world at the time we started it were moving up market and putting in sort of rules of we do $50 million checks, we do $100 million checks for the reason you outline because those are the checks that will probably move the needle. Uh
[26:02] though obviously Sequoia and Benchmark and others will tell you otherwise. Like they've written plenty of $5 million checks that have been breathtaking in outcome. But, you know, I can sort of see the logic as you get bigger that that's a temptation to kind of put that sort of constraint in place. And, you know, our DNA just didn't want that anyway. So, some of this was not fully thought out in the way I've described it, but it it in fact holds really well to time. Uh, and some of it was just our DNA was so driven off of sourcing. And
[26:34] the history of Insight was sort of based on some experiences where I found some small deals that didn't fit with a bigger firm and I was like, I don't want to be that guy again. I don't want capital to dictate my strategy. Um, and it turns out it doesn't have to. Like you could get a little bit invested in and find your way to backing up the truck for bigger ownership. Uh, and then as the world changed, it's increasingly hard to come in late. So now I would argue that there's some really good firms that have been around for as long as we have that were the pre-minent
[27:05] latestage funds that like us look at some of these later rounds are like that's a pretty tough spreadsheet. There are other ways to deploy that capital that seem better riskreward adjusted. Um, now again there's some that are great, but most I'd say the spreadsheets start to look like, you know, two to 3x. You could do much lower risk buyouts or venture buyouts or other types of deals with the same return curve with a lot more upside and an ability to control your destiny
[27:35] in a better way. So, uh, I think it's sort of become a bit of a necessity too to get on the balance sheet uh, by getting in a little bit earlier. >> You mentioned sourcing in the early days of insight. so much path dependency to all these stories. If you ask people that study this industry to say something about insight, I think the first thing they'll say is something about your sourcing strategy. And so now would be a great time to just like hear how it what it is and how it evolved. And maybe that'll be a good jumping off point into investing firms that have strategies or not um as businesses. But
[28:06] but let's start with sourcing. When I wrote the original business plan, which is not tremendously different than today, uh, which is a longer story, but I was leaving Warberg, I actually I love software, wanted to just do software and was really interested in doing smaller deals than that firm was set up to do at the time. And uh, nobody would hire me. So I tried to get a job at at least three of the leading then software was tiny. It was IBM and Microsoft just to put a setting in the world. SAP was sort of this mainframe guy coming along.
[28:37] Oracle was probably the coolest cat in town in terms of like open systems, whatever you want to call it back then, client server compute, but it was a really really small market. Like you can count on one hand, I think the top 50 software companies, like number 50 was like 10 million. Like it was tiny. >> Um, but I loved it. I thought it was a a big growth bucket. I thought specialization uh had a real edge. uh we were disadvantaged by being in New York. I mean, I guess I could have moved, but I
[29:08] had family and other reasons why I like New York a lot. And so trying to compete on the West Coast terms made no sense to me. Um and so one picking an area of specialization where the model was still pretty new to people and it was pretty different than the hardware companies before it that were really the more typical uh venture investing. uh and the DNA of a sales guy of software back then and Oracle's DNA that was a really different DNA than what most folks were used to. So we thought specialization was absolutely critical to understanding
[29:39] an industry really well and we picked software. In hindsight it was probably the best bet I've ever made, but like it wasn't cuz I saw the vision to where it is today by any stretch. So that was kind of this the start of it all. And in like the mid 90s, like early 90s I should say, I was still at Warberg. went to a conference and Kevin Landry who was at the time the founder and managing partner at TA Associates was presenting to a large crowd and he was walking through his playbook and I was like the classic Vince Lombardi story like here it is I don't really care
[30:11] good luck good luck was his comment like no one and I'm like 26 years old I'm like all right like that's pretty cool he's ripping out I help wanted ads from the New York Times or whatever magazine that you're reading and he's calling these companies up and it turned out back And it was a really opaque market. Very few companies were, you know, other than those in Silicon Valley were out there raising capital in any professional way. Uh, and entrepreneurs were really receptive to just being called up and saying, "Hey, I think you've got something cool. >> Would you be interested in uh talking to
[30:43] me?" And I started at Warberg. I sourced a bunch of deals that way, which was pretty unusual for what was largely a shake the tree partner kind of model. um and realize I could find deals all day long like this and especially software lent itself to being outside Silicon Valley especially applications right because if you're building banking software do you want to be in Silicon Valley or New York City if you're building pharma applications you want to be in New Jersey or do you want to be in uh Silicon Valley and I can go down the list right of industries that you know really made sense to be much closer to
[31:13] your customers >> which themselves had clusters around the US and even in Europe this was like a nice add to the fact and And most software companies back then started as consulting projects that got bootstrapped to some degree to a product. >> So you could actually find these things well after their incubation phase and startup phase which again was very counter to the uh West Coast model. Um and so I hear Landry speak. I start doing what he's doing and I'm like this is working. I could do this. And we start Insight. I had a partner with of
[31:45] mine that was sort of a consultant to Warberg. We started up. We just start sourcing deals and almost like on the phone call calling everybody and you know we found a bunch of deals before we had a fund and then we kind of put together scrapped together $16 million blind pool of capital from some high net worth folks and and that was what begot insight. But in that thesis was focus sourcing and then the focus was going to give you both an ability to source better because you knew where to look, you knew what magazines to read, you knew what trade shows to go to. All that
[32:16] kind of lent itself to the same. But it also gave you a chance to think about how do I add more value to the companies I invest in. And we were actually the lead investor in almost everything we did. These were kind of bootstrap businesses that didn't have partners. And I wanted to be helpful to the founders. And most of the founders were technical by background and didn't really have that Oracle sales DNA that was really the cutting edge of what B2B software was back then. and we started to build some network of people who knew how to do that and ultimately brought some of those folks in-house and one of
[32:46] my first hires as a partner was somebody who was president of one of my companies who was one of the best sales guys I'd ever met. Um and so that was kind of the thesis, right? So focus sourcing value ad by being the best at what we could be. Um and obviously the world's changed a lot since then, but those core ingredients are still 100% insight. So if you think about the the sourcing platform inside of insight and chunk it up into chapters back into the mid 90s through to today, how what are the major
[33:16] chapters like how is it? >> Chapter one is me and my partner then >> calling people. Uh chapter two is I I hired three associates uh one out of Summit uh Mike Triplet which was a big decision and Mike brought me concrete I've been there done it at the best of the best my partner Jeff Lieberman and and one other partner and so they started doing it too and you know Mike was you know for him it was second nature because he'd been doing it his whole career which wasn't very long at the time he was probably 25 but uh long
[33:46] enough and that kind of elevated us and we were kind of basically investors doing it ourselves. And then we made a decision in 1999. We hired a young man out of Dartmouth, which is where Mike went to school. Uh, and he became our first official analyst. We decided to go right after the undergrad kids because we realized it's a really hard job and if you've actually been working at Goldman Sachs or Mackenzie, you kind of get spoiled >> and you don't want to go back to picking up a phone and calling somebody up without any context. So, it's it's a lot
[34:17] of work. It's it's it's a lot of effort. And that became the first I guess two chapters really. We then just started to operationalize what that young man was doing and we started having classes and then we started going down to the best schools to recruit and then we started to have training programs and we started to really institutionalize that entire process and that's really the last 20 years. It hasn't other than technology >> I'd say that the hiring and profiling of of what we do hasn't changed tremendously. the class sizes generally speaking have gotten bigger as the
[34:48] market's grown, but you know, we're just trying to cover everything. So, whatever that takes in terms of human resources. Um, you know, I'd say the next chapter for us, it's been probably the last 5 years, is just can technology really make an impact on who you focus on. And there's a lot of firms like ours, I think, that are trying to do that. I think the human in the loop still matters. Uh, that's our belief. Uh, you know, entrepreneurs aren't just going to react to the first email they get from you. So, the fact that you think XYZ company's super hot doesn't mean they're
[35:19] going to return your phone call. Uh, I'll have analysts give you stories of, you know, 25 phone calls, couple FedExes, and then landing on somebody's, you know, street corner, uh, begging to take a meeting, right? like it's hard sometimes to get the attention of somebody who's successful, >> especially in today's world where there's probably 30 more 50 more firms reaching out to that individual, right? So, we're we've shifted from a world where capital was a little bit more in power. It wasn't perfect in even the 90s. It was already shifting, but today
[35:50] clearly the entrepreneurs got lots of choice >> and we're very sensitized to that choice and really want to make sure that we meet that. So if I came in today and saw the current setup um could you describe it in as much detail as possible? So like how many people are there? What like what is how are they given their assignment? Are they just given free reign? Do they have a coverage universe? Like what like just give me the detail of the actual platform today. >> First my my management style which is not very good but can be very effective for the right people is to throw you in the water and just say swim.
[36:20] >> And I think we have a much better training program right now. So thankfully I have some of the folks that have come through the sourcing program that are still with me have been you know much better at managing than I am and and have been able to kind of institutionalize some of the lessons to get people up the curve quickly. But you know within a few months you've learned what you can learn from the system. You're learning from your peers but at the end of the day no one tells you go call XYZ industry up. You have to kind of sort this out yourself. You hear you listen. Maybe your partner that you work with is giving you some advice on industries
[36:50] that they're intrigued by. Uh but it's a lot of trial by error and and learning and different folks pick it up in different ways. Different folks are better suited for that than other jobs. But uh it's it's pretty much a a you know self-starter highly personalized initiative to get going. We have probably in aggregate 60 plus people >> depending on you count 60 to 80 people that are still heavily engaged. you know the process has gotten a little bit more sophisticated because you know founders
[37:20] also want to meet with more senior folks and you know we have you know mid-level folks that could help direct manage and coach so we have a lot more support for these folks to be really good and they're getting daily kind of coaching from the folks who've been there and done it >> I would say that I think almost all the partners at insight but one or two at the sort of high investment committee level started off in that program right so we've kind of mostly homegrown which we could have a whole another uh angalon because I I think this it's an important
[37:50] story to hear about where the the insight diaspora has has wound up. We have largely cultivated our own teams over the years. Uh what we have done is you know we also have a very big practice of uh McKenzie like brains that are there to help the portfolio. So they come in also fairly young, maybe two years at McKenzie and then join insight and that's another career path for people to kind of get to know investing but to know it through the operational side. It's a fantastic talent pool too.
[38:20] So we now have I think one of the core differentiators of insight which again is a very hard message to get across is we have the best youngest talent by far in the world as reflected probably in the fact that I think we just counted for this interview I think we have 16 or 18 funds >> that were started by insight alum I've got 30 plus partners at other firms today that were insight alums I'm going to come back to the people the alumni effect that you described it's a lot of funds to have started out of a single place um so that's really cool coaching
[38:50] tree like in football or something. >> That's exactly the email. I use the Bill Parcel. >> Yeah, Bill Parcell's coaching tree. Those 60 people today, how do they relate to one another? Do they feel like they're and and what's the incentive structure like? Am I am I incented to compete directly with them? And if there's if there's a good deal, do I have my own lane? Like how >> you've got lanes and we've got technology to claim. I mean, it's probably a lot like if you were in a good software company and you looked at the PDRs and that software company and sort of looked at the sales folks and you thought, "All right, who gets what
[39:20] territory and how we're not going to give people territory in the same way, but we're going to give people a chance to claim a deal." >> Yeah. >> And then it sits on their pipe and it has a certain rules around how long it could stay in that pipe until it's acted on, >> up for grabs again. >> Then it's up for grabs again. So, it's sort of a you got the ocean, you could call whatever you want, but you know, once it's on somebody's pipe, it's their deal. You know, I'd say we try really hard to encourage collegiality. So, if somebody's looking at a deal that's not getting followed on on somebody's pipe, please pass it and we'll work together on it. And we tend to overcompensate for
[39:51] cooperation. So, the general goal is not to at least have comp be a reason not to be cooperative. >> Uh, obviously people like their own track records and they get a little it's hard to take type A people and make them, you know, full, you know, full players on that, but I think we do a pretty good job of that. But you know in general you're going to step on toes. I think other firms are more delineated by buckets. >> You go after infrastructure, you go after AI, you go after and I think what we found was just a lot of misses that
[40:21] way. It's it could be just a partner's prediliction to doing a certain type of deal. And so this other kind of deal, it's just as good, but it's technically one partner's bucket doesn't get acted on. And so, you know, we try to create a little bit more openness to what those lanes look like. But, you know, we also know and the partners at the senior level know, you know, if somebody finds a cyber deal, there's a few of us that do a lot of cyber. Like, please share it with one of us. What's the point of getting educated and we're all comped the same. So, we're not exactly trying to, you know, this is one for all, all
[40:52] for one to make the firm successful. And, you know, we try to direct the deals to where they're both going to get won and focused on. Is the person incented to just get a deal to a certain stage or get a deal that gets done like and how are is it just like a salesperson like they're sort of paid the equivalent of a commission or something like that on >> I mean they get paid very good salaries bonus on that. So I think and the at this age the money is not the driver for these guys. I mean, the the the golden carrot is so big, whether it's at our firm or somewhere else, of being a
[41:22] successful investor. By and large, the real motivation is they want to be successful and win and deal >> and have a good deal, right? You don't want to be pushing a partner to do a bad deal and >> have to put that on your resume for the rest of your life. I don't think anyone's really just because you got a couple thousand dollars of But we do get deal bonus for the 23 year olds that are making the calls. At what stage does it get handed from them to some other part of the business, some other person, some other diligence process? Presumably, they're not the ones doing the underwriting. >> First of all, we have now about eight teams which are basically IC members
[41:53] who've been with me in most cases 20 plus years. >> Seven six of us together for at least 25 years, you know, a few 10 years. Um, and that's kind of the pods that we would basically say these are the senior people within that. There might be some other investor MDs, some principles and VPs. And so it kind of bubbles up. It starts with maybe a VP or senior associate working with that analyst that source the deal and then recognizing all the key signals to what might be an exciting company. It's not as tricky as
[42:23] you might think and maybe the early stuff is but most of what we do is pretty clear when something looks interesting >> and then it just keeps bubbling up and then eventually uh it'll elevate to the IC member on that team and say time to meet the company and let's get you on a plane. And sometimes we can't get into the company without that meeting. So we know all the external data points point to hot. We we we see that we're like okay that founder does not have an interest in taking a call uh from somebody more junior. Those junior
[42:53] people have a lot of influence at my firm. So they they run my schedule for sure. For sure. But that's a hard to crack and you know the partners will get jumped on planes and you know I've been this year to Estonia, Sweden, five other places. >> You've been there? Yeah. >> Oh yeah. No, I mean like >> I think you told me your your your calendar is dictated by 24 year olds. >> Totally. They set it up and today every meeting was, you know, set up by the analysts, which is fun. I I like it. It's easy also, by the way, because it's really hard to get all these meetings that Yeah. >> Well, but the part Yeah. The partners that work at other firms, the nice thing
[43:23] they have is it their calendar gets filled up by doing deals, so they can't do more deals. Sort of a nice regulator to deal flow. sometimes could catch us a little bit because it's so much of what we've done. We've we've kind of systematized uh that it's it's relatively easy for us to get the meetings, but it also means that like they can go on forever if I don't like I can't say I'm too busy. Like these guys are out there hustling. I want to make sure that they get the attention they deserve. They're working so hard. >> What makes a great sorcerer? Like if you
[43:53] think across the probably hundreds at this point of sorcerers you've had over the last several decades, what distinguishes the very best of them from like the merely good? >> It's got a lot of classic sales skills, which is hunger, winning, probably lack of self-awareness. Meaning like you'll make a phone call to anybody and not care. >> Yeah. >> Ability to handle rejection well. But combined with a lot of content, right? So the really good ones are going to get really deep and those conversations I have with the founders are shocking. I had remember one meeting distinctly in
[44:24] like mid 2000s and the company was in New York. So I just popped over to meet the CEO and we ended up investing in this company. First question out of the CEO's mouth is you know where's the analyst like her name? And I was like oh you just got me sorry like she's still in the office. Like I didn't really realize you like so they get really connected. I mean the letters you will see us get from founders on the relationship that the analysts have built the trust that they built with these founders and and the work hard
[44:54] work they do to generate real value for those founders before we invest >> is remarkable. >> If you think about the that skill that salesmanship and the ability to do sourcing well if if I were to pull people like you've talked to so many founders some would say bad things about insight what would they say? Would they say it's annoying how much they call me or they're trying to pull information out of me that I don't want to give? >> Two things. One could be we definitely, >> you know, they get turned off by that model. Like I think it's unjust, but it
[45:24] is what it is. Like some people have a view they only want to talk to the top. These are good kids that are really working hard and and they're going to get you to the top. And then obviously rejection is really tough too. So we probably get by talking to so many people we're obviously >> rejected a lot. >> Yeah. We're and we tried to be really thoughtful about it and usually what we're trying to do intentionally is not reject but postpone because life changes people's business get better and sometimes things are just not right for us then and the last thing you want to do is is is is damage a relationship
[45:54] with a founder. >> In addition to the the sourcing which we talked about in the one fund concept another distinguishing feature of insight is how you've made sequential I think typically small to begin bets in new deal types. Um, and if you look today, like a huge chunk of your assets are what I would call like private equity style deals, not venture rounds, not growth rounds, um, you know, traditional sometimes, you know, big private equity rounds. How did something like that start? What have you learned about bet sizing for uh, new types of
[46:25] deals? Because this is really important. >> Go back in time 90s like software wasn't big enough to think about buyouts, even unlevered buyouts, like it just didn't exist as an industry. There was also a pretty strong belief broadly in venture capital that without a founder, like giving cash to a founder was like a four-letter word. Like you never do that. That was like the rule number one. >> And I bet if you talk to some of the best of the best and ask them what they were like in the '90s, secondary sales
[46:55] to founders were just not acceptable. I think TA Summit kind of were breaking that model a little bit in the '90s. And I think when we dug into software, we pretty quickly realized if you built a good software company, assume that the risk there was that the founder got demotivated, right? That was the reason you didn't want to give him cash. Oh, now he can afford a house. He's not going to work so hard. And we just sort of felt like if we break it, we can own it and we can manage it. Like we just got a lot more confidence as we did more of these that if for whatever reason it didn't work out with the founder, they decided to
[47:26] retire, whatever it was, we're okay running this. Like we could find a new CEO. We obviously that's a big part of all venture capital jobs is is is you know keeping management where you want and not everything works out with the original team. Um and so we just the more confidence we got and then you we saw I guess two deals that the owners were not typical shareholders. One was a former founder that had hired a full
[47:56] team was out and we bought the company from him or we bought his shares. We're like well we don't have to demotivate him. and we don't even want them involved in the business. And then the other was owned by a large insurance company >> um which is now called Veraphor, the software company that we bought. So it was the first that was the first buyout I'm aware of in well not sure there was probably you know a few others that were not done by private equity firms but um it was certainly one of the earliest buyouts in private equity in 2099. Um and we just started to see the other side of software as it got bigger that
[48:27] when they start generating cash flow which till mid200s very few got to that scale where you actually saw the profits and the cash flow coming in and that particular buyout was interesting. We were high-fiving with two times leverage from a crazy hedge fund that believed in us and that was kind of like considered a highly levered software asset. Today Vertor probably has nine times leverage. Um so very different world but that was kind of the beginning of of software buyouts and we made a series of bets through the mid 2000s. Um and then we
[49:00] also started looking at uh just taking control of really high growth companies. We had a company that was in Australia and the founders were ready to go surfing and we had a CEO in our pocket that was ready to take over and we're like we'll take that risk. It's, you know, it's a $5 million business, but we think we can transition to the new management team and we had the, you know, tech team sticking around. And the more confidence we got that we could own control of something and not risk the kind of entrepreneurial DNA that went into it, um, or it was past that sort of point where that was critical, uh, the
[49:32] more we started looking at those types of deals. And, you know, it's been a fantastic sector for us. I mean, we've made a ton of money, especially in the what I'd call, we call them venture bias, but the unlevered 30 40% growers. They're tweeners, right? They're not growing fast enough for a minority investor to get super excited except at a very big discount. And they're not big enough TAMs for strategics to go jumping up and down saying, "I need to own this asset." So, what happens to it? >> And my suspicion is there tens of thousands of those now,
[50:02] >> right? Like, they're good companies. They should belong somewhere. Um there's a lot more folks like us now willing to take those bets. So it's it's not quite the same market it was a decade ago. But you know for us again it was just I said this to my LPs I think this last annual meeting. Stage is not a strategy to me. Like you could argue seed investing is a very different skill set generally. But I'd say it's not like we're incompetent to look at something quite that early. We're not nearly as good as a lot of the guys out
[50:32] there and we don't have quite the same deal flow and buyouts requires a certain you know transactional skill set that but pretty straightforward to hire for. It's not like it hasn't been done before. There's you know not only in software but in tons of other industries there's plenty of skills to do it. Then everything else is just a spreadsheet >> sits in between and you're just trying to as accurately as possible put that spreadsheet together >> risk adjust it and then put a price against it and say what's it going to be worth. And there's a very big range of
[51:02] strategy that sits in that middle. And that was sort of a view that we had that why constrain ourselves. You know, up until 2017, late stage preIPO growth was a really cool market, right? Multiples were expanding, companies were growing really fast, typically longer and faster than you expected. You could actually make four or five times your money on those preipo rounds, even more if you did the consumer internet stuff. And then it started getting really competitive, right? hedge funds came in, sovereign wealths came in and as I mentioned earlier, some of those rounds
[51:32] are now getting, you know, modeled at two to 3x with like a gentleman's a lot of things have to go right. We could model them all. Why can't we just put risk against that model and just try and find the markets that are the most attractive? The market recently corrected in 21. There wasn't a lot of things that you wanted to touch in growth because it was a lot of the companies that raised a ton of money, they didn't need it, but the ones that needed it, you didn't necessarily want to invest in. But then this whole middle got neglected again, right? And so we're like, let's go lean back in on the middle where you've got these 30% growers that look really nice, cash flows are good, and you know, their
[52:04] salmon farms and roller coaster ride software and things that nobody's really >> putting a lot of mind to and and and we did a bunch of those deals back in in 23 24. Uh, and you know, now AI is probably re-energizing some of the growth stuff, but you know, I I like the idea of of being able to move around the markets based on where we think the most value is. >> And they change a lot based on capital flows. >> If you look at like the last fund or two and you had to break that 12 billion or
[52:34] so down into deal types between like traditional earlier stage buyout, venture buyout, however you want to chunk it up, like what does it look like? I think early stage is like 10% call it growth is probably 30% growth buyout which is like this what we call venture buyout is probably another 30 40% and then lbos are probably 20%. Mhm. >> And that, you know, moves like the buyout market looked great when interest
[53:06] rates were zero and multiples were expanding and you went from 15 times cash flow to 20 times cash flow and that was a pretty interesting time to be leaning in. It's a little trickier today, but more entrance prices are pretty good, rates are higher, multiples aren't quite as clear, growth rates are coming down a lot for big cap software. That's not a fixed number, and we don't want it to be a fixed number. I mean, it's it's a guideline. We're never going to get super early as a big number. I just think we feel like one those get to be much bigger checks. They could start at 10% and grow to 20%. If we if we get
[53:38] back to an environment where we could be the lead investor in the next round, you know, M&A is a huge part of the strategy. So, if you look at levers for winning in a venture bot, you get sort of 30% baked in growth, maybe some operational improvements, and then inorganic growth rates that can consolidate and give you tail outcomes. If you think about what you want returns wise for these funds, how do you even triangulate it given all these different deal types? >> Look, I think the buyouts were willing to take, you know, five points lower
[54:08] than everything else. Everything else is blended pretty close to the same. You know, 30% is kind of a gross number that you'd say we'd target. We probably miss a little bit more on the early stuff than the venture bio. Our hit rates are just super high. Mhm. >> Uh just because you've it's a lower risk profile. So it's sort of a market that's been a little bit better and very few competitors. So it's it's played and it plays perfectly to our sourcing engine,
[54:38] right? Because how do you find these companies that are selling salmon software to the salmon industry? Like that's not an easy >> source, right? That's sort of >> people jumping on planes and calling up companies in Norway. >> Yeah. >> Um so and and again, it's not mainstream. They're not showing up at conferences. They're not showing up on venture capital lists of hot companies to back or things of that nature. >> If I look at some of the deals, you mentioned Whiz, talked about data bricks, you mentioned Monday, uh, Enthropic came out in the news recently that you were an investor in this big round. That sounds more like
[55:08] traditional, you know, uh, kind of venture growth style investment. >> Well, I mean, whiz, we backed when it had zero revenue. So, >> it's a big price, but, you know, we loved everything we saw, including team. Uh Monday it was an interesting company but not the most obvious funded company. It was you know probably five million in size when we backed it and Cena is another public one I'm involved with. It was sort of four or five million in size when we got there. So some of them just grow and have TAMs to support those exits. But you know it's tempting to always go for the shiny objects and we
[55:39] fight a lot internally about you know how do you become part of the generational companies. I'm curious to hear the anthropic story specifically just since it's so extremely recent and such an exciting company like and that's more more along the lines of >> that's a little bit more driven from our public strategy just to be clear so it's not in the core fund that's a good example of one where had I heard the story >> two years ago I would have had a much more positive view earlier >> you know and this is a classic case where you know Darius is phenomenal CEO
[56:09] has a very very thoughtful articulate >> view of his business and the second you hear you're like okay there is a mode or there might be a mode and obviously the numbers in the last four months there are incredible right so it it inlected with coding and and and the like but when you sort of think about how he's invested around that that's not accidental that was intentional and probably defensible like you know there's a risk it's not but you know I think it's it's a pretty interesting bet to make >> what do you make of those 16 or 18 funds
[56:40] that have emerged from insight and One way to think about it is, wow, that's incredible. A lot of talent that's been able to be independently successful. Another way is like, why couldn't why didn't you try to keep them there or something? >> We often do. And one of the biggest ones that came out, I bent over backwards to see if we could find a role. But in the end, you know, his entrepreneurial drive overwhelmed what we could possibly do without breaking the system. So sometimes we just can't break our model. And if you're that good and can raise that kind of money on your own, I can't replicate that economics for you. Yeah.
[57:12] >> Like it's just not doable. Um, and so 1 plus 1 equals three in that case. And we couldn't have raised the billion dollars that he was able to raise just on his track record. So it's just inevitable, but I think it's it's healthy for us. And I'd say 80% of them, we still have a really really good relationship with these firms. We talk to him all the time. We do deals together. Um, so it's, you know, McKenzie, I think, has set a great precedent out there of what could be done if you kind of embrace that network and don't take it as a negative, but take it as a positive. And then
[57:42] obviously having partners at other firms I think is just great for us to see deals and I'm now a decade or more from being really close to the analyst classes that came out. But you know they go to their weddings. there like it's incredible. The the pictures I get of the camaraderie of the classes never goes away because you're in that pit working 10-hour days or plus and and in a pretty tough environment and it's you know we try to make it fun too but you know they really connect with each other and it's it's become real I mean some of the best friends I think in the world
[58:12] have probably come out of that. And why do you think you've been able to graduate so many people? Like what is it about the training they get at insight? That's that's certainly that number is certainly higher than >> this is the Bill Parcell's question, right? Like and I actually think this is my favorite question for sea level executives. It's the same question. Who who are your be best protegs and where are they now? >> Right? And I feel good that I can answer that in a pretty good way. Right? And certainly when you hear this CEOs out there that could start rout I have one good friend of mine who's retired now
[58:42] but he's got 12 CEOs of some of the biggest best companies ever some of that was timing right it was days of Oracle and Oracle DNA was just awesome but some of it was him so he obviously built a great hiring system spotted talent really well and then cultivated that talent really well and then had a system of thinking and approaching in this case software but in our case investing that's really valuable but I Ultimately, the training you get at 23 at Insight is like no other job in the industry
[59:12] because all you're seeing is at bats. >> You were seeing more pitches than any other firm out there. And you're 23 years old and you're just your brain is a sponge. It's just looking at all those pitches and you start seeing your own patterns and inevitably you're going to become a pretty good investor. It's again it's not the same as the productdriven strategies that other venture funds have but you know you just see this you hear and see and hear and see and and we are a big pattern recognition business right I think
[59:43] investing is pattern recognition and everyone can draw their own you know graphs out of those patterns but you know that's fundamentally the core thesis like you could be the smartest guy in the world but if you don't see the patterns or if you don't see the deals guess what your track record is not going to be that good. >> Like so I think that culture and then the culture of just how important sourcing is to being a successful investor. Uh you know we just drill into people at a very young age and I think
[60:13] that just sticks with them in their later life and I think it probably makes them look good to the peers that they have that didn't have that culture. If we're building like a like a Madden player that has points and different attributes for something and you were to give uh yourself scoring on C pick and win and and and maybe support as well, but especially interested in C, pick and win. It sounds like C sourcing you'd give yourself like >> that's a firm. >> Yeah, a crazy high score. Um, you know, differentiating. >> We see every pitch. Picking in the middle is awesome or picking on the edge
[60:44] is is okay. >> Say more about what that means. when you see something that's really kind of got a little bit of an edge to it on the source where the numbers are pretty tight and the valuation kind of is is not west coast crazy. >> Yeah. >> Right. We're really good and we're really good at winning too. Right. So if you kind of really think about what I do for a living, it's >> I got to find and this is what I told my LPs day one. You got to find deals. >> See everything. >> You got to win deals. You got to pick them and you got to make them work. That's it. That's my job. And I'd say on the picking, we're really good in that middle zone. and especially some of my
[61:14] partners better than me even had it that really can kind of parse the numbers look at the trends and figure out how to get that spreadsheet as accurate as possible at the edges it just inherently gets harder I think we have some disadvantages on early relative to California because we're not getting all that little like >> more subtle stuff >> the whisper is so strong here you got to lean in so there's that whisper deal flow and trends that we won't see then on the buyout side there's just there there's some equally great investors And it just it's you know it's a game of you
[61:46] know combination of discipline uh focus and and operational execution and there's some great firms out there. So I think we're really really good in our sweet spot. I think we're we still could use our sourcing to our advantage on the early stuff but we have to use the sourcing to get us that edge. I think if you just you know lined us up against the best of the best and the valley like those guys are awesome. Like I'm not saying we're going to be, you know, able to connect the dots that they connect because they're just using different dots to make what I'd call intangibles
[62:16] work. >> Sounds like the winning is is quite successful in your sweet spot as well. How do you how do you do that? Like what what is what are the keys to successfully closing a deal in that sweet spot? >> First and foremost, it's showing up hard. getting on planes, you know, invited or uninvited, showing up to people's doors and and asking them to have a conversation. So, we started with just like, gee, we know software really well. We can introduce you to five friends who could help you out, run your sales force, run your marketing organization to 130 people from super
[62:49] smart Mackenzie folks that could do any analytical thinking that you might need to the best of the best sales process folks to marketing process to HR process. We bought a pretty expensive uh large interest in Riviera Partners which is the largest tech recruiting firm for sea level or sort of CTO and CPO talent um which is you know they're really an interesting asset especially in the AI age where talent is everything right so we put a lot of emphasis on talent we've got 15 people that do nothing but lies
[63:21] with Fortune 500 companies which is probably the biggest you know if you think if you're a CEO first and foremost give me revenue if you're a small company, right? That's number one ask. Number two ask will be give me people. So, we've really surrounded those two functions with resources that we think could be competitive. And we've helped jumpst start companies where we've gotten the first 10 million of revenue, right? It's a big impact in the journey of some of these companies in terms of getting them started. And so, we really push really hard to to bring that
[63:51] program to as be as big as it can be. Uh, and constantly innovating on that. And so this is and we'll get to sort of the other chapters of insight, but I think it's it's it's all about winning. And so it's a combination of personal connections, really showing up and caring about the entrepreneurs problems, and then helping the entrepreneurs, right? They have choice. We know they have choice. They're the winners. We're just here for the ride. We've talked before you and I about strategy of investing firms and how even though all
[64:22] these firms are investing in companies that they hope have a great vision and strategy and and roadmap and all this kind of thing that investing firms tend to have that to a less lesser extent uh either no strategy or or not >> listening to your podcast I would say the majority struck me as our strategies were really good investors. I think if you really press what I just said that there's only four things we do, right? We find deals, we win deals, we select deals, and we make them work. And then you sort of put that layer on how do you
[64:52] do that better than everybody else. Um, put selection aside because that's the hardest to kind of institutionalize. You know, how many firms really can articulate and there's lots of ways to do it. You know, Mark Andre was on here like he has an absolutely great strategy, totally different than us, and we could never do what he does. Um, but he's thinking about it every day and he's using his sort of marketing engine. I think he was recently quoted as basically I'm a marketing firm with an investment arm. I was like, uh, you know, I I wanted to be a software company with an investment arm. That was
[65:23] kind of my pitch >> 10 years ago to LP is like that's how I thought of myself as >> people could think of us as we know so much about software. They could outsource a lot of that knowhow and then we have an investment arm to monetize that. But there's lots of ways to skin the cat. like we've just taken one approach. I think some firms obviously could do it just by sheer presence of being first like and they've made great investments over decades. Uh other firms might pick different industries. Some
[65:53] firms have done it in the biode space where they've just kind of used capital combined with expertise to just be able to kind of lean in faster and harder. So you know there's lots of ways to create moat but you know not many of us wake you know most of us back our way into this life. I started when I was very young but I think a lot come to this after they've had other careers and other things >> and this is sort of a nice fun thing to do and absolutely is and uh you know putting sort of rigor around that and
[66:23] operationalizing it and then sort of looking you know we hired one of my good friends years ago as a chief operating officer of Insight. He subsequently started his own firm but you know he was a mechanical engineer at McKenzie who you know spent time at Putinham and Lehman like he woke up every day and it was like how do I make that pencil you know whatever do it something without a human touching it right like that's how his brain worked and mine works in a very similar way from a more strategic side but you know it's sort of systematizing what tasks we do that we
[66:54] could have others do better and then how do I create moat to the extent that it's possible because look capital is not a huge mode. Uh it was with the vision fund that was like awesome strategy. I just outraised everybody in a way that I could do deals that no one else could do. You know, Warberg Pink has had that for a while too. When I first joined, they were significantly larger than almost anyone else out there. But that's increasingly difficult. I think Toma Bravo could do that today with their scale in the bio world. Capital's tougher though. So, you just need to think about those four disciplines and
[67:25] say, "Well, how am I going to be way better?" Some guys do it by, you know, appearing on podcasts and and really getting their their thought out and their vision and and kind of excite the founding community of how smart they are about an industry. That's a perfectly legit way to get deals. >> Uh others, you know, have cultivated networks in different ways and and winning could be I'm just going to get on the plane and do it. An individual partner that, you know, works my tail off and it's not very leverable, but it's certainly a good strategy. So I think you know how do you
[67:55] institutionalize systematize that and operationalize it is not easy. We found also scale was a real opportunity and I I heard Mark Andre talk about this too like every industry but ours was considered to be better as they got bigger. Like for some reason this type of investing, tech investing was like, "No, we want you to be a cottage industry where the smartest partners just do all the work." And I remember very distinctly sitting
[68:25] down with one of my partners in 2015 and I'm like, why do LPs have this allergic reaction to the word scale? Because again, everywhere else it seems good. And I looked at those four buckets of what we do. I'm like, well, clearly sourcing is better with scale. like could see everything. Like >> yeah, >> might have to debate how you pick, but like great that you get every pitch. Um you could certainly see how winning can get better with scale. I've got more resources. I could support every round
[68:55] that you need. I could be your one-stop shop. And then obviously on the operational side, that's the biggest impact scale could have because now I could really hire the best and the brightest on my team that could support your business in whatever way you need. And then selecting was kind of like the one, okay, how does that scale? And that was kind of a bit of a hard one for us to to wrestle around a decade ago. Most firms that scaled scaled in a few dimensions that were understandably scary for an investor. One was, I'll do
[69:27] bigger deals. How do we know the bigger deals are like the smaller deals? Like maybe they're priced differently. Maybe the competitive landscape's different. maybe the economics like there's a lot of reasons why just writing a bigger check may not yield in fact often won't yield better returns. Um so scaling by check size was not necessarily a clear direction in my view of how to do bigger to do scale. Some might scale with geography. We tried that. Oh was that painful like brutally painful. We're you
[69:57] know we're 90% in New York City by headcount and probably 100% by investment. you know, commitments. Certainly IC is all in New York, right? It's really hard to export judgment. >> Yeah. >> And so, you know, we had a European team that raised a European fund and I, you know, it was the worst of all timing. It was 2000 and like, okay, that was bad. But, you know, I was ready to pull my hair out. It was so hard to create consistent thinking and judgment that you could say, okay, that judgment reflects the same judgment that we built
[70:28] over the 5 10 years before that at Insight. But geographic scaling is a really common strategy for a lot of folks. But I think I could see why LPs would be nervous about that. >> Um, and then lastly, people scale by doing something that they weren't doing before. Right? Okay. Like I'm a great software investor. Now I'm going to do healthcare. Now I'm going to do financial services or now I'm going to do credit or something maybe that's outside my core competency. And you know, look, Blackstone, others have done that really successfully. Um, but you
[71:00] could argue it's not easy. Maybe Blackstone did a great job of it, but two other firms, you know, didn't get those top cortile funds in the areas that they didn't have a lot of experience in trying to scale. And certainly, there's plenty of examples where firms, you know, bought something in a different asset class and struggle to to make it work. And so, we kind of said, well, we don't need to do any of those things. Like, software's just growing. We're barely scratching the surface. Why can't we just do more of good deals in the category we love and
[71:31] know? >> And if we put aside all those other ideas and said, "We're not going to just chase bigger deals because they're bigger. We'll do a bigger deal because the world's gotten bigger." That's fine. Data Bricks, if you just divide everything by 10, looks like a great classic growth deal. Like there's nothing unique about it other than it just happens to have more zeros >> in its business model. Open AI even more true, right? I mean, if you just turn 12 billion into 12 million, you're like, "Wow, this is a fast growing company." Like, why wouldn't I jump at writing a
[72:01] $10 million check? So, some of this was just just looking at a world that's just gotten tremendously bigger to when we first started where that would be a good reason to write a bigger check. But if we sort of just said, "We're going to keep the same underwriting criteria in the same market and just grow with the market. The market's getting bigger, which means there's more good deals out there. we're really good at winning them and finding them. Why shouldn't we consider them? Like why why should we just stick to some smaller strategy or just sort of artificially
[72:31] constrain what we do if again understandable you want to keep a bar high and we've definitely over the years sometimes been caught up in the moment if you will. So I think we looked at scale in that lens and we're like this is win-winwin and we were in the right position to do it because we were organizationally already aligned on sourcing. We were already aligned on management. So we had to really think through the investing side and the selection side and that was the part that we definitely didn't do
[73:02] perfectly to start where you start to have you know we hire young kid becomes less young becomes principal and ultimately junior partner and they were on their own and we kind of had a little bit of like partners are underwriting deals we bring it to the investment committee and we debate the deals which is pretty typical I'd say of a lot of firms that have grown is they have senior partners young partners but usually they're kind of all doing their own I call the tennis match, right? Everybody goes out, plays tennis, compare scores, and yeah, we won the match or we won the we won the whatever
[73:33] the tournament. So, we were trying to be more like a soccer team, but we played tennis for a little while, and we realized that, you know, young partner has a deal, comes to me, and it's like, "Mom and dad, I'm a little busy. Jeff's not really paying. He's only hearing oneird of what's coming in out of my mouth." I pitch him the deal, he nods his head, we do the deal. Deal blows up. Jeff doesn't want to spend time on it because I didn't really take ownership of it. And all of a sudden, Young Partner is now stuck with a a deal that's in trouble. And we're like, "This
[74:03] isn't working right. We need to think about legitimately how you get the most experience on the judgment as well as the other parts of the operation that were more obvious." And so we kind of said, "Well, look, there's some of us who've been here at the time, it was six of us for 20 years. We've all built track records. We've all been through multiple cycles. Why don't we just we have enough time in the day to meet every company that a team of people that would work with us including young partners sources like we don't do that many deals a year like except for 2021
[74:35] but um like it wasn't an insurmountable number. It wasn't like I needed to spend 20 hours on another partner's deal. I but three hours I can get a lot of >> instincts >> judged and you know my instincts may be more on I'll call it the t intangible sort of excitement around the deal other partners are really good at the financial side and you know we keep tweaking that a little bit but that was fundamentally a breakthrough in how we can try and scale judgment without breaking the model and saying let's just
[75:06] have pods of very experienced partners managing and working with other partners both operating partners and young, hungry deal partners uh and combine that DNA into a more cohesive team approach and then make sure that an investment committee member owns every single deal >> and if somebody leaves it's on me. If somebody screws up, it's on me and there's no hiding it. Like >> that's what that's what we did. M one thing you hear a lot is even in firms where there's your level of sort of
[75:36] systematic setup and rigor that it's really important that leading the leading investors be able to just throw everything out and sometimes make a deal or do a deal based mostly on the intangibles based most not in the spreadsheet but but out of the spreadsheet. Can you talk about your experience with that sort of thing and how you think about that type of deal? we can mobilize 15 people from my Mackenzie brains to my sales ops team or marketing ops team or you name it to
[76:06] dive in and really try and uncover as much as we can in that very short time window that we have. I probably am the only one who does what I call concept deals >> at a big price. >> Even I'm not doing that right now. Like I don't feel compelled to do that at the moment. So I'll do a little bit of those on the smaller side. >> Uh where I feel like it's a unique team with unique technology and there's not a lot of numbers to support it, but that's going to be a allocated part of the portfolio that's going to be very small. >> So that's more riskmanaged again by
[76:37] check size and we have that benefit. So when we start seeing something that maybe our spidey senses are tingling and we're like this could be something special, maybe we could use check size to manage it more intelligently. But it's really not a big part of the portfolio. It's not what our DNA is about. I mean, we started with growth. Not saying we're only in growth, but we try to put some metrics around most of what we do. >> One of the spillover effects of 2021 is all these companies that got funded with tremendous amounts of capital that don't
[77:08] really have to die because they had so much money put into them. >> I think they're starting. >> Maybe they're starting. One of the weird things is that there's not market prices haven't really like caught up to the reality of the underlying businesses. And I'm curious to just get for your perspective on what things are generally worth in terms of like a simple multiple or something like everyone kind of thinks in 10, you know, 10 times multiple or something for a software business, but I think you think these things are often worth way way less. >> Yeah. And by the way, you could see this with the secondary market. It's a little hidden secret, but you know, go look at
[77:38] how some things trade in the secondary market. You're like, okay, your marks aren't exactly right. >> If when you're at 70 cents on the dollar, your marks aren't on us. So I think look, we look at GDR growth rate. Those are the two things we're going to look at in valuations. And that could be a really disappointing three or four times revenues for a lot of companies that were backed in that time frame where they're not growing fast and they have low GDR. What would those numbers be like? What would an example of like three times revenue, GDR, and growth rate be?
[78:09] >> Meaning >> like if you're to pay three times for something, what GDR and growth rate does that imply? That might be low singledigit growth and 80% GDR. >> So if you go into the public markets and look at those companies like they're disasters, >> right? And they're not few are even public today, right? And it was a category that early SAS a lot of those went public and ultimately the markets caught up to the unit economics. But the public markets by and large and private markets at scale. So the PE guys are
[78:39] looking for okay I'm gonna long term this is cash flow and so to us GDR is largely and look you could have a really we have a company which now Vista owns that you know has a mid 80s GDR but it's CAC is 3 months which is a very low number in the world of CAC so you can make a 30% margin business if it's an infinitely sized market with a relatively low CAC um so there's an exception to everything I'm about to say but if you're in a more normal normalized enterprise world, you're
[79:10] going to have 12-month CAC, which means it's one year upfront to get that customer on board. And if they only last for four years, you can kind of do the math and say, well, that's present value worth maybe two two and a half times to one time dollar invested plus I've got R&D, plus I've got support GNA, you're not gonna make a lot of money. So those companies tend to be in the 10% maybe maybe squeak out 20% margin versus a 100% GDR company will have 50 60% margins. So that if you just thought of
[79:41] multiples of cash flow translating to multiples of revenue that's going to give you a big delta, right? So if I'm willing to pay 15 times cash flow for a given growth rate, a 20% margin business is three times revenues. A 50% margin business is, you know, 7 and a half times revenues. I think the markets more or less eventually will look into that kind of financial model and they'll kind of figure out and look some companies could take they're just super efficient in other ways. So you could still have some of those metrics that I just described being a little bit off but
[80:12] still get yourself to ultimately you're trying to get to cash flow margins, right? That's all that matters is multiples of cash flow and then predictability of that cash flow in a recession. How good do you feel in whatever times in you know whatever existential risk somebody could come in your model and disrupt it. So those are just I think the framework that I think most public investors and and certainly latestage buyout guys are thinking right is how resilient is that cash flow? Are you running a core banking system for, you know, a bunch of banks? Like that's
[80:42] not getting ripped out in a recession. Like you don't really care about a recession. Um what's the growth rate of that cash flow? And then, you know, what's a reasonable multiple based on that? And some of that will be interest rate sensitive. Uh and then obviously you have a different world once you start to get to 100% growth rates of which there are very few public company data points but that's when you start to see wonky multiples like you just can't model those out in your exits because they're just so on they're rare earth >> kind of numbers. One of the things that
[81:12] I'm curious about the temptation around just given how the market's evolved is uh the Andres of the world, the sort of like nonsoftware technology companies that some of which have gotten quite big quite quickly and consumer too for us >> and consumer >> right I mean if you look at the biggest exits of the last generation they were internet and mobile apps >> and we did not really lean in on that because it was sort of outside our kind of understanding and mandate. It also really favored the West Coast. Almost
[81:43] all those were West Coast. >> Yeah. >> Designed. You know, we looked at Uber at a really attractive round. We fought like hell as a partnership over it and we finally passed. Obviously, huge mistake, right? Like it was a great outcome. Managed to get Twitter over the line, which you know, at the time was we got out even before Musket all took over. But um I think we've just gotten comfortable that our our misses are so high in those categories over the years that we're like whatever. There's we can't be
[82:14] everybody to everything and we can't do it all. It it's obviously hard because you sometimes have to benchmark yourself against folks who do have exposure to the markets that might be the better markets. But, you know, just sticking to what we know well in in enterprise software and sort of flavors of that, it's both massive in opportunity and the returns could still be incredibly consistent. >> When you think about the god knows how many first meetings that you've done with founders across the last 30 years or so, how would you describe the method
[82:44] that you use to run those personally? And I'm sure obviously different investors on your team will do it differently, but I'm especially curious about your method. How do you like to run a first meeting? What kinds of What are you after? like what's the >> I mean I have a I've developed I'd call a similar line of start which is I love origin stories. What was in your mind? Why' you choose to solve this problem? What were you doing before that made you think about this problem? Uh and then I love to get to the value problem. Like I just love hearing how you're making
[83:15] somebody's life different and better and why customers are going to be excited about buying your solution. And I actually, it's probably my why I need partners is, you know, I'm I'm probably the least focused on drilling in on the numbers. I mean, I like to hear the topline numbers, but entrepreneurs probably aren't always the most uh forthright about what they give you. Like they give you a little more happy ears on on those usually, but which is where diligence can kind of corroborate or not. But those are kind of the stories I want to hear is like what makes you tick and what's this passion
[83:47] that you have about what problem and why? And you know those those really range a lot in response. Like you hear enough people pitch and you're like that one really resonates. You know elevator pitch. I got it. And you know some you need to double click double click double click. You know I was on the call today with one that I was like I think I hear you but this was a little bit in a different language. So it was a little harder for me to process to begin with. But I'm not quite getting that mode. I'm not quite getting that long-term
[84:18] direction of where you're going to be. Um, doesn't mean it wasn't there, but this is a 45minute call. Like, you're not going to nail it exactly. And sometimes the numbers tell you way more than the story, right? Like, you need to always take a look when you see numbers that are exceptional. When you have the group of partners that you have at the top that you said have been with you 25 years, sometimes 10 years is like the newbies on the team at the senior level to what do you attribute that like? What is your management style with those people? How do you relate to them? What would they say about you?
[84:49] >> I'm pretty forgiving on mistakes. >> Uh I would think some of my partners would say too forgiving, but I I try to see inputs. I have a thing that we institute at Insight. It's changed a little bit from the vision, but I call it the X factor. like because everyone always want you know type A employees they always want to know where their careers are going and you know always ask me these tough questions like how do you give somebody really valuable career advice in what we do because the outputs are so long in coming
[85:19] >> and uh and there's so much luck let's not kid ourselves like there's a lot of luck in what we do and I sort of start with like well if I took you out what would have happened >> with the deal still open sourced, would we have won the deal? You know, would we have decided to do the deal? Like how much of that those decisions did you play in in that process? And
[85:49] X is sort of like the removal of you. Are you adding X to that equation? One of my best partners had a really slow start. You know, he just made a lot of mistakes, but I saw his inputs were great. I thought the way he was thinking about things was great and he was like a sponge to get better and now he's probably the best investor in the firm, right? Like so it it it people learn, people get better. It's a marathon. Obviously at some point, you know, the marathon ends, but you know, I think that's generally how I try to approach
[86:19] it. And I think my style is is similar to what we do with the analysts is is really to give people an environment where they could be creative, take risk. I think probably the thing that I still do the best for the firm at large is there's two different approaches I think to a senior partner at a firm. One is the one that's constantly holding you back from falling off a cliff, scaring you to take a risk. The other one's shoving you over the cliff >> and giving you the confidence it's okay. I'm with you. I've got your back if it
[86:50] doesn't work out. >> And I think I'm definitely in the latter camp, right? My goal is I call it the tush push, right? Like I'm there at the one line. you're at the one yard line, you've got one little thing nagging you about the deal. And I'm like, it's okay. You've thought about it well. The riskreward is good. It may not work out. It's not your career in the line if it doesn't. >> And I think a lot of young folks get really worried about if you look at generational firms, risk appetite is
[87:20] probably the biggest challenge >> that it goes down. >> Yeah. Yeah. And some once in a while they get a wacky successful investor who just re-energizes the firm's risk tolerance and it goes back up again. But more often than not it gets consumed by look this is a great business. If you don't get fired you're going to be pretty successful. So you know the impetus to really stick your neck out on the spectrum is really low. And I think people especially in these kind of
[87:53] bigger organizations really, you know, I hope they make mistakes. You know, my biggest frustration with one of my partners who left was the things he didn't do. Why didn't we do that deal? Like that was a really and you know, he always had five reasons not to do it. But you know, in the end, he was very conservative and to the point where we missed a bunch of really good things. So, you need the balance. I I've got a lot of partners who are holding people back from the cliff. So, it's it's a good yin-yang of of of some folks that
[88:25] are going to make you feel really scared to stick your neck out, but then hopefully, especially my senior partners, knowing I've got their back always, like I am never going to get upset with somebody if they took a calculated risk that didn't go well. I'm curious how you think about something seismic like AI both in terms of how it will affect the companies that you already own stakes in or own outright as a disruptive force how you use it yourself to make insight work better um investment opportunities that it creates like an anthropic I mean there's a lot going on with this with this with this
[88:55] nuclear bomb that's gone off in a good way how do you how do you process it >> yeah I remember like a bunch of years ago even before the chat GBT aha moment and I'm not like the technology ology wizard in the firm by any stretch. But I I we were already doing vision deals and I could see language was next. I was like, imagine if you can automate vision and language in the workforce. I'm like, there's a lot of jobs where that's pretty much what you do. >> And so, you know, I started talking about it at some of the LP meetings and
[89:26] then we were doing the vision stuff which was not in any way exploding like the language has exploded. Not sure why, like never got the buzz. I don't know. But vision just for whatever reason was good but not compelling. And you could look at, you know, MRI companies and they're like 10 years later they're 80 million doing it's like the biggest one maybe. Like what happened to that? I I can't explain it. >> But for some reason the language took off. We looked at other waves and we were it was pretty easy for us to kind
[89:56] of sit on the sidelines. Others on your show are big fans of blockchain. Maybe now it's crypto because the blockchain's like no one could articulate the use case and it was back when I debated this with people. I was like, "It's 12 years in. Come on." Like, >> "Yeah, should be something. >> Something should be, you know, and there's a whole religion around it and maybe someday every bank will be on it and whatever." But it's definitely way longer than anyone forecast to be valuable. And I certainly had a used to there was like a funny story someone told me, but it was basically like all
[90:26] the technology guys that love that know the blockchain think the technology is kind of meh, but the finance aspects of it are really cool. And all the finance guys are like, you know, the finance aspects of this aren't so great, but the tech looks really cool. I'm like, huh? Nobody in who's got really the the right DNA on both. Like, nobody was like, this is the best database I've ever seen in my life, >> you know, who understood database technology. And finance guys are like, this isn't really how the world in finance is going to work. You know, we've got reasons. Anyway, so we've kind of like looked at other waves of
[90:57] technology and been a lot more sanguin about the potential and whether it was even the self-driving car like we that was a big hot spot a decade ago that was more vision and this one is different. I mean both and I don't know if it was the problems it could solve immediately. This certainly the consumer side of this is just I blow I mean it's mind-blowing what you could do as a consumer and I mean just watching my own family in the last 3 months convert from Google search to
[91:27] Gemini or chat GPT and just like just religious right so it's it was a gamecher in so many ways and really we kind of were playing around the edges of it in some ways and then really about a year ago we started to see the application of it where we really played the most in the commercial landscape and now you're seeing phenomenal we probably have 25 agentic AI bets that we think could be really profound in in the commercial markets and so you know we've
[91:58] been noodling on all sorts of sort of impacts it's going to have but you know it's clearly a phenomenal growth engine it's also sucking a lot of the air out of the traditional software market so I think the bare case on software hey I could just use claw to my next SAP. We're not losing any sleep over that. Quite the opposite. >> Why? Why not? >> Because that's not what software ever was. It was never a technology barrier. >> It was always a business knowledge barrier. And yeah, maybe you could
[92:28] literally have AI look at SAP and plagiarize it and try and build something equivalent. But I I'm just not worried about that market changing. The cost of developing first of all, we haven't seen any of it in our companies. Like the cost of developing software, it's inching down, but it's not collapsing overnight. And I can't explain exactly why, but the idea that a complex application is going to get built just because we have a better productivity tool. You know, we've gone through generations of productivity tools in software development. This is more profound for sure, but you know,
[92:59] for those who are old enough on this call, like the 4GL was a pretty profound tool, too, because back in the day, you just had a database with a screen, >> right? applications weren't all that complicated and the 4GL was meant to basically make it really easy to build the screens and it was impactful but it didn't radicalize every SAP and all these other companies didn't get displaced because of it. I think it's but it's taking away a lot of probably budget. So I think you'll probably be
[93:29] seeing a lot of companies just feeling the pain of like that's not the cool kid on the block to buy a CRM software today. like that's just not my priority. I want to automate something else. So that matters like that's growth rates. I I I'm not there's obviously a few companies that are probably more squarely challenged by what it can do because they're probably working around documents and you know doing image recognition things like that that you oh so what's your what's your point of existence now? But I think by and large I don't worry about the usefulness of
[94:00] software so much as the budget being moved away from software to AI. And then on the flip side, which is what we're really focused on, is it's a massive TAM accelerator. >> So, okay, my core software is not as sexy, but now I could go after a whole set of problems that my customers have >> that I before could never automate. So, you know, I'm on the board of, you know, a couple I won't even pick on the public ones, but like, you know, CRM like vertical applications where we're just
[94:32] capturing data, but 95% of the the person's day is generating and getting the data. Well, if I could automate a big portion of the 95% of the time that you're, you know, getting data into the system, that's hugely valuable. And so to me, we've got already maybe a half a dozen or more companies really reacelerating off of new products that they've launched in very short time frames uh that are creating massive TAM expansion for their businesses. And I have no
[95:02] doubt the bigger public companies are working aggressively at the same thing like Microsoft, right? Like it's it's an opportunity. Microsoft looks at that. Could I build a new PowerPoint with it? Probably. I don't know, maybe. Can I make PowerPoint the existing product way better with a co-pilot? Yeah, you probably can. And I think that's way more interesting or Adobe like how much better is Adobe that has a 3% market share of humans to Photoshop and now could expand it to 20% because the user interface and learning curve
[95:33] has gone down by an order of magnitude. >> So my suspicion is this is largely TAM expanding for the established companies. they will build products as well. I don't think it's a great use of time in most of the legacy apps to be trying to outgineer them with a new product. It's just there's just more to that market than just the actual body of code that runs your core banking. There's just a lot more going on and I think we're still quite a ways away from even getting to the point where the the the
[96:04] speed to which you could build software is so dramatically better. You said before that uh you really just like to win and that's maybe like a major driver of all your activity. You have this interesting combination of you seem pretty low-key like you're not uh just like you just seem kind of low-key and yet the activity your activity and the firms is quite intense and it's kind of an interesting dichotomy and I'm curious where the drive to win came from. I don't care about other beating other people >> so much as just satisfaction in my own
[96:35] success in winning. So it's a different kind of drive than I think other people get, which is I I have friends who I play golf with. Like I can't play without betting. Like they can't have fun. They can't try hard if they don't have something on the line, right? That's how competitive they are. But they're competitive against me. >> They want to beat me. Like that's what drives them. I'm like I just want to get my own >> score as low as possible. if you shoot a 65, I'm high-fiving you, I'll buy you a beer. I'll I'll be the happiest guy to give you 20 bucks. Like, I don't really care at all if I have a good round. So,
[97:05] I think that's just and I think the culture of the firm has maybe modeled after that. I attracted people like that, but I would say the majority of us are much more focused on our own success than it is that somebody else isn't >> at the other end of that successful. And that's kind of what just gets us a little endorphins for for the day. >> These conversations always go the same direction where 98% of the conversation is about buying and almost none of it's
[97:37] about selling. What have you learned about selling? Selling well, when to sell. >> Had a good year on that one. So, we've sold a lot this year. But I think the easy things are the ones that come naturally. IPO, strategic knocks on your door, people pull you in, you sell. You know, the harder one is when you have to push it to make it happen. I think at one point 999, we had a 4x on our 99 fund in the public markets that we couldn't sell. We were locked up and by the time we could get off the lockup, it was down to a 1x. So, you know, these
[98:09] things, these are quick windows. They come and go and you kind of learn and look some of this was also we we put co as a piece of it which was a combination of the demand shift and change you know some ideas that look great 2021 you know virtual conferences looked like a great idea and it felt like that could really have legs even postco no the answer is they had no legs after co and then some of it was just us like decision-m probably not what we thought it was over zoom and you know we had like everybody
[98:40] else a year of, you know, remote work. Really, really bad. Never going to do that again. >> If you think about the next decade of Insight, how do you think it'll change? >> We're feeling like much more of a rinse and repeat model. I don't think we have crazy ambitions to expand the business beyond what we're really good at. And just I think this is a just kind of we'll we'll absorb what we think are great deals, but the bar has never been
[99:10] higher. Since 20 summer of 22, we've just really been pretty focused on uh on really making sure that you know we make as much money as possible for LPS. >> So I think it's going to be I'll call it a little bit more boring. like you know I I had at one time firm building ambitions that I still have a little bit of but you know where we could add assets that were again making us the world's best software company right like what would make me a great partner for my portfolio we still have some of that
[99:40] ambition but it's it's going to take a different flavor >> is there anything essential about insight that you feel like we've messed with >> I think culture is and others have probably talked about it but there's definitely I think a lot of positives on our culture that don't get seen by entrepreneurs. I think it's a combination of we don't have to be the loudest voice at the table ever. Um, we want to be the most helpful voice at the table and we don't need credit for that help. So, we want to stand behind the founders who really do a lot of good work. I think
[100:11] internally that reflects itself in as much as you can do in this industry, a really collaborative teamwork approach and we've got a big firm and there's no doubt you'll always have people stepping on toes but I think by and large the idea is to really support each other in a meaningful way. Um obviously we talked about the part of winning which is a big part of us um but we also just never want to give up. So, I I know some folks have been on your podcast about, you know, sort of sticking it out till the
[100:43] bitter end. And maybe to a fault we do that, too. But we really really want to be there to the end. Like, we're leaders. We're not passive investors. Somebody's going to be on top of these companies until the end. And it's important for us to kind of even though that's not where you make money, those are the worst hours of ROI that you can possibly get is taking a deal that's gone sideways and and try and fix it. But a it's really satisfying on the few times that you can actually turn it around and b just feels like it's it's
[101:14] it's a the right thing to do. >> Well, it's really cool to get the inside view on this. I I it's a firm you hear a lot about because it's so big. you've made so many great investments over the years, but you don't it's very hard to figure it out from the outside and so thank you for the two hours. It's such a such a fun time to explore it. When I finish these, I always ask the same traditional closing question. What is the kindest thing that anyone's ever done for you? >> I sort of think that first you need to be someone to be kind to you. It's out of the goodness of their heart, not out of their own self-interest. And I'm
[101:46] somewhat fortunate not to have that many situations where I've needed that help. But I I guess as others have said in this mentoring is is one area where I feel like that's always been you know an area where people didn't you know some of it might be broadly self-interested but most of that is selfless and I've had you know two examples but my first job at Warberg uh the person I work for there pulled me out of a hat in terms of resume saw something in me that no one else did. I
[102:16] think I tried getting a job at a 100 firms and he was the only one who was willing to hire me. Um, and I learned a lot in that experience as well. But then I think when I started Insight, we sort of randomly bumped into uh an indent by the name of Steve Freeman who was the just then retired CEO of Goldman Sachs. And I think it was a mutual connection from one of the high net worth guys at Goldman that knew one of my partners. And Steve, for reasons I still don't know, one of the nicest guys I've ever
[102:46] met, took me under and gave me amazing counsel in the first decade, ultimately introduced me to his co-CEO, Bob Rubin, who also became part of that mentoring and just was such a nice access for me who had no one else to talk to other than, you know, it's like nice to air issues, challenges >> and and focus. So, you know, that to me was certainly one of the best things that happened to my career. >> Incredible. Jeeoff, thank you so much
[103:16] for your time. >> Awesome. [Music]