Invest Like the Best with Patrick O'Shaughnessy - Jeff Horing - Building Insight Partners - [Invest Like the Best, EP.440]

Episode Date: September 16, 2025

My guest today is Jeff Horing. Jeff cofounded Insight Partners and has been the Managing Director since 1995. This is one of Jeff’s first public conversations about building one of the world’s most successful technology investment firms with over $100 billion in AUM. Jeff reveals the mechanics behind Insight's legendary sourcing machine—60-80 people systematically calling companies worldwide. He explains their contrarian "one fund" strategy that deploys $12 billion across everything from $10M growth deals to billion-dollar buyouts, and why he thinks this creates unmatched competitive advantages. We discuss remarkable talent diaspora, AI representing a "TAM accelerator," and Insight’s five-ingredient framework for perfect investments. Please enjoy this great conversation with Jeff Horing.  For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠.⁠⁠⁠⁠⁠⁠⁠⁠ ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ramp⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ramp’s mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ramp.com/invest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to sign up for free and get a $250 welcome bonus. – This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ AlphaSense⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. AlphaSense has completely transformed the research process with cutting-edge AI technology and a vast collection of top-tier, reliable business content. Invest Like the Best listeners can get a free trial now at⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Alpha-Sense.com/Invest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and experience firsthand how AlphaSense and Tegus help you make smarter decisions faster. – This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ridgeline⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ridgeline has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Head to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ridgelineapps.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to learn more about the platform. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Show Notes: (00:00:00) Welcome to Invest Like the Best (00:08:35) Insight Partners' Investment Strategies (00:13:06) Evaluating Software Businesses (00:22:51) The One Fund Strategy (00:29:32) The Evolution of Insight's Sourcing Strategy (00:35:09) Operationalizing the Sourcing Process (00:44:43) Adapting to Market Changes and Strategies (00:49:45) Navigating Market Corrections and Investment Strategies (00:51:40) Challenges and Opportunities in Venture Buyouts (00:54:12) Talent Development and Retention at Insight (00:56:03) The Importance of Sourcing and Pattern Recognition (01:02:08) Scaling and Operationalizing Investment Strategies (01:20:24) Impact of AI on Investment and Software Markets (01:27:40) Reflections on Winning and Selling Strategies (01:30:34) The Kindest Thing Anyone Has Ever Done For Jeff

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To see what happens when you eliminate the busy work, check out ramp.com slash invest. Hello and welcome, everyone. I'm Patrick O'Shaughnessy, and this is Invest Like the Best. This show is an open-ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money. If you enjoy these conversations and want to go deeper, check out Colossus Review, our quarterly publication with in-depth profiles of the people shaping business and investing.

You can find Colossus Review along with all of our podcasts at joincolossus.com. Patrick O'Shaughnessy is the CEO of positive sum. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of positive sum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of positive sum may maintain positions in the securities discussed in this podcast. To learn more, visit PSUM.v. My guest today is Jeff Hoaring. Jeff co-founded and leads inside partners and has been the managing directors since 1995. This is one of Jeff's first public conversations about building one of the

world's most successful technology investment firms with over $100 billion of assets under management. Jeff reveals the mechanics behind Insights' legendary sourcing machine. It's 60 to 80 people systematically calling companies worldwide. He explains their contrarian one-fund strategy that deploys $12 billion across everything from $10 million growth deals to billion-dollar buyouts and why he thinks this creates unmatched competitive advantages. We discussed their remarkable talent diaspora, AI representing a TAM accelerator, and Insights Five Ingredients Framework for Perfect Investments. Please enjoy this great conversation with Jeff Horring. I thought it would be fun to begin with a weird but interesting question for our past conversations, which is if you could go back

in time and think about the original SoftBank Vision Fund, which was $100 billion, huge fund. Of course, everyone was talking about it. Who knows what will end up happening with that 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 $100 billion 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? First of all, it was an eye-opening me when it happened. And we had a small strategy that I always envisioned could be a big strategy, but maybe to go backwards and say, what are the best private equity venture deals of all time? This is a cheat answer. It's not the real answer. But

In my own view, probably the most cleanest, best example of return is probably VMware. Technically, EMC was the private equity buyer. They's about $650 million and sold it for $60 billion. So that's a $60 billion gain plus or minus. You could argue Instagram billion to probably a trillion. YouTube is probably a billion to a trillion. 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, almost no real eBay effect that drove that. We had done a bunch of what we call venture buyouts, and some were growth buyouts, and these could have been $100 million investments of taking control of smaller software companies where we made five, six, sometimes more times our money. I just always had in my head, I would love to be competing with Microsoft or Palo Alto or eBay for a deal because then the entrepreneur is like, wow, I could have my cake and eat it too. I could sell to Jeff for a billion dollars my next Instagram and 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 there were smaller growth standards. So they were not what you would consider to be classic buyouts where have cash flows and debt and all sorts of other things. Underpinning it, it was really the markets and the growth and the entrepreneurs that you're betting on. And I thought if I had $100 billion, that's what I would do, because I think you could really differentiate yourself tremendously from the pack. Interestingly, Masa did one deal like that called Arm, and I think he's made four times

his money on a really big check, maybe more. I haven't tracked the stock lately. 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, take. get into those deals to justify that capital. Though obviously he made that return in Alibaba, he made that return in, I guess Yahoo was probably more of my example, Yahoo Japan, where he bought control something and turned it into a massive win. So that was a dream I've always had. 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 for those deals? I don't know. But 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 in 2025, the thing you just described? How big would it have to get so that you were actually competitive? Today's tougher. This was probably 2016 when the Vision Fund came around. The concept of liquidity, billion dollar exits as a massive victory for the venture. 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 can be for these types of assets is pretty small. It's just a little bit harder because the scale has changed, but we look for these sub a billion is really the sweet spot that we could consider. But to find hypergrowth shareholders willing to exit is still tricky. 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 $1,000 for 30 guys in Israel, that's a different game that we can't really compete with. So if you were to size a fund today for the best possible risk-adjusted 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. We're deploying $3 plus billion a year in invested capital across a range of strategies, but we definitely don't feel capital constrained. to the opportunity 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.

Certainly others have raised money specific to target that type of deal flow, but that's not really the thing, that that's more of a better version of that vision fund, where you're buying into open AI or anthropic and big volume at late stage prices. We don't lose sleep over that not being our core strategy. What do you make of this? You were investor in the big Databricks round and Anthropic more recently. What do you make of the late stage private markets today? 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 Databricks is still a private company at this scale is sort of unheard of. You could argue Open AI is still a young company, relatively speaking to the timing of its revenues. but for reasons that maybe represent just the shifting of capital, companies are staying private longer and doing basically IPO plus plus rounds in the private markets. We look at these like we look at anything else through a lens of 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 risk-adjusted venture-like returns. Maybe a fun thing before we get into insights strategy specifically is to 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. You could have long ago retired. My sense from talking to some people on your team and talking to you is that you're working about as hard as you've ever done it. What does a given week look like for you?

It starts with some internal meetings, investment committee, people's new, deals, partners meeting to spend time together in Sanchez's first day back kind of day in this case, but that would be a typical Monday. 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 of new companies. Then there'll be a fair amount of portfolio calls. So I probably had three calls so far today on portfolio companies, is hopefully more strategic in nature than just what's your latest quarter. And then some internal meetings on how we're scaling the firm and using AI to do diligence and all sorts of fun things like that.

So it's a blend of where I think I can contribute what I try to do. No one's perfect to spend as little time as possible on things I'm not good at, of which there's a pretty long list. So those were areas where I think I can have a meaningful impact and also enjoy it. So it's a lot fun for me to do that. What would you say is the skill on the prospect side evaluating a founder a business, whatever, that you've most improved at over the entirety of Insights existence. So you today versus you in 95, 96. I'll say team broadly because some of us are much better at this than I am, but our analysis of what numbers matter has changed a lot.

I remember six years ago at an LP meeting telling LPs we think we're at 11th grade math on software. The industry is probably at seventh grade math on software. I think we're getting closer to college. It's still amazing what we continue to learn about metrics that really are the best predictors for future outcomes, which is really the dream, especially in growth investing. You have almost enough data to start to predict. And we've also gotten better, I think, at understanding qualitative TAM issues and the never-ending journey on management. Every year you learn something new in both the good and bad ways.

People are always complicated, but you definitely get better at it as you get. more experienced at it. Can you teach us some of that college level math on understanding software businesses? Five years ago, one of my companies was going public, and the rage on Wall Street was net retention. I was 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 was the only number that Wall Street asked, I said the only number that really,

well, two numbers really matter, GDR, which is gross retention, which is how sticky is your customer base, how resilient is that? And more importantly, how much of that buckets you have to fill every year? There are very few companies with low-ish software low-would-be 80s, low-80s 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 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 fine just to fill the bucket. And then you, of course, want to grow 30, 40, 50%, percent on top. of that. So those become daunting numbers that usually reflect itself in your average cost of acquisition. Take your net new bookings divided by the spend that you had to get to that. And those numbers tend to move together because you just have to keep filling more of the bucket with sales reps just to stay even. So I think that was an example of one. Another time years ago, I thought a lot about calling ourselves the second derivative because so much more has learned. A couple guys had this right at Facebook, the billion dollar kind of guys that came in,

there, but the change in new business is way more important. The change of the change, I'm growing 100% 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, on vertical software. We quickly saturate the number of decisions made in a given year and all of a sudden model out five years with a flat new bookings number and your exit growth rate's 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 price different numbers that it's not just that you're buying 95 plus percent gross retention and accelerating top lines or something like that. You'll buy companies that don't have those metrics. We keep learning that you sometimes get fooled into the trap of value, and it 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 not a long list of really rich people who've done that as compared to the people who've just bought the dream. There's a very long list of people who've made lots of money on the dream. We will not do a low gross retention business today unless we really are confident we could change it.

We think that metric is really the fundamental driver of all exit values 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 not enough sales capacity, this, that at least half my partners would tell you that they prefer not to compromise on any of those metrics. Their view is, if you look back in time, nine out of ten times those metrics have been the driving metrics for our success. If I think about gross retention as one avenue of math to go down and that's algebra one, what's algebra two?

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. Simplest math is LTV divided by GAC. That's all you're trying to understand is I invest in money. Assume R&D gets somewhat normalized to levels that are industry standard. That's really what you're trying to tease out. GDR is a great predictor on LTV. 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 big variable on that. What you're trying to figure out is the market hole for that. How quickly am I accelerating that number?

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 can imagine growing for multiple? years, WIS, which is obviously one of our favorite stories and great team and blah, blah, blah, they've been able to double or more their net new bookings each year for six years. 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. If you literally doubled it every year, you would have 100% growth rate at infinitum. What qualitative questions do you like to ask on the back end of the quantitative investigations? 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 false precision, I think, could get in trouble. I'm a big fan of the value problem.

When I think about investing, I want to hear the entrepreneur explain how they're generating real value for the customer. When I look at what makes for the perfect investment, I have thought about the five ingredients to me of the perfect investments. So value prop is critical, and that usually could and should translate to selling price. And then I distill that and say, well, imagine you're going after the hospital market. We looked at the Gentic 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, so 20 times your size on average selling price, pretty hard to imagine that you're going to be as big as Epic.

You can frame it and say, best case, I'm probably 120th. This epic is a dominant player, 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 the sort of top-down approach is riddled with errors in thought, whereas if you look at what's my selling price, how does it compare? So you want to see that average selling price and then compare it to companies that are targeting the same number of customer universe. And that gives you at least the ballpark, you obviously want to look at the landscape of competitors and say, well, what market share

am I realistically going to have? The hidden data point for me, especially for early companies I've been pushing on, and this is where AI is a pretty neat idea is what's the time to value? So when you think of a customer making a decision installing SAP versus using open AI, one is I 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 productive. SAP has massive value to that customer base, but it's a very long time to implement, and that's going to inherently slow down realistically how fast you can grow, both your own ability to succeed with those customers, but also just the decision-making

around those complex decisions. Obviously, phenomenal CEOs are always the dream. I listen to the podcast. I'm like, well, people are really a lot smarter than I am, because I sometimes write that story after the fact. I certainly have plenty of phenomenal CEOs that were rejected by a lot of other firms. So it's not always obvious. And then a phenomenal tech team that goes with it. 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 happiness and product satisfaction, things of that nature. Those five things. Key list them once more just so I make sure I have them. It's big ROI, big ASP, time to value CEO in tech,

and management team that goes behind that tech. That's my five. I think Wiz might be the end of one. That checked all five. Maybe Monday had a bunch of that too. But to get the time to value and the ASP is really rare. Does it stand a reason that you think for an SAP type company where the benefit of that long install process is very sticky, typically on the other side of it, that the right time to invest in those companies after they've gotten their install base, that's the better risk-adjusted entry point. I think for those companies, 15 customers that are referenceable is sort of a magic number for inflecting on growth. So the challenge with those companies is they're very hard to sell those products. It's a lot of missionary selling early on. So you can't really scale your sales organization

until you have a certain number of referenceable customers that you could lean on. And if every sales guy is pointing to the same reference site, that customer gets a little annoyed after a while. So you're constrained by that. 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 demand constraints to scaling. Maybe you can walk through the one fund strategy that you've chosen to pursue at Insight, which is really interesting. I'm especially interested in how in a fund that's $12 billion, it's worth your time to look at a $10 million investment or something like this. That tension is fascinating to me, and the one fund strategy is fascinating to me. I know you've strong beliefs about it.

describe why it is this way and tradeoffs. I was lucky enough to get my first job, and it was a lot of luck in somebody who believed in me that hired me at Warburg-Pinkus, which founded in 1968, maybe the world was a different world, but developed a one-fund strategy. There is included stage and industry. So they were stage-agnostic, industry agnostic. Some of that was mapping to LP demand for the biggest of LPs back then, the pension plans. But there's two things, I think, that if you taught Finnsic.

in classic portfolio theory, you would be scratching your head and thinking, gee, why isn't everybody doing this? One is risk management. 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. Obviously, you could abuse that and take risk that maybe aren't sensible risks, but it was fascinating. Most of us really sweat out those big checks. We're really pretty risk-averse. We want to make sure the downside is absolutely locked in. Probably the 2x case is really visible. 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 100 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 risk management and you can do it with check size. So you could look at stages slightly differently. And the second advantage, as single fund has in my view, is all my peers would sort of admit that the best bet on the table is the double down bet. In Blackjack, we all know that.

You've got an 11 against the five. You double town. Not only do they give you the good odds, but you have way more information than you had before you got the hand held. 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, there were our best checks. We took a $5 million 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.

in some of our biggest exits from Monday in Cino, a bunch have started with under $25 million bets that have come up to $200 million over time. We just see secondary opportunities. We see follow-on opportunities. If you zoom out, you're like, isn't that the most rational way to do it? Why would you do anything else? And I know there's 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.

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 because sometimes the charter of that fund, the pitch to the LPs is a little more nuanced than 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? Now, sometimes they find a way to do it and it's great. But a lot of times, because the deals get bit up a little earlier than they expect, it 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. Check size is too big for an early stage bet. What do I do with it? We don't have to

think about any of those conflicts. We certainly not have to think about conflicts between the two funds, which can be managed, but it's not zero. Am I bailing the company out? Am I really supporting it? How that all looks optically could get funny over time. What are the biggest downsides of doing it this way? What annoyances does it introduce? The biggest is you lose a little bit of discipline from third party pricing. It goes both ways. So sometimes we preempt 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. We've got our position. We're not going to be upset with that, but we're also here to support you the entire journey. Up until 2017-18, that was really common. The world got really competitive starting in 18, and a lot of those follow-on checks, we couldn't get them at the values that we felt were exciting, or the founders just wanted to get third-party pricing for their own. reasons and we're going to support that. The downside is you could believe your own BS. You can get a

little sloppy with the $2 million kick save checks. I want a 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 bridge to a sale. We have recap the company 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? The one fun 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 probably the most glaring one. How do you think about that? I'm like, well, it doesn't feel like that at all when you're on the inside. It just feels like a well-oiled process. But from the outside, we look like an end of one. You go back in time to firms that scaled over the years. They almost always scaled on check size. 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 rules of. 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. Though obviously, Sequoia and Benchmark, others will tell you they've written plenty of $5 million checks that have been breathtaking and outcome. But I can see the logic as you get bigger that that's a temptation to kind of put that constraint in place.

Our DNA just didn't want that anyway. So some of this was not fully thought out in the way it described it, but in fact holds really well to time. and some of it was just our DNA was so driven off of sourcing. And the history of insight was 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. I don't want capital to dictate my strategy.

It turns out it doesn't have to. You could get a little bit invested and find your way to backing up the truck for bigger ownership. 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 preeminent late stage funds that like us, look at some of these later

rounds. We're like, that's a pretty tough spreadsheet. There are other ways to deploy that capital that seem better risk-reward adjusted. There's some that are great, but most I'd say the spreadsheets start to look like two to three-x. 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 ability to control your destiny in a better way. It's become a bit of a necessity, too, to get on the balance sheet 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.

Now would be a great time to just hear 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 as businesses. So let's start with sourcing. When I wrote the original business plan, which is not tremendously different than today. I was leaving Warburg. 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.

Nobody would hire me. 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. Oracle was probably the coolest cat in town in terms of open systems, client server compute. But it was a really, really small market.

You can count on one hand. I think the top 50 software companies number 50 was like 10 million. It was tiny. But I loved it. I thought it was a big growth bucket. I thought specialization had a real edge. We were disadvantaged by being in New York. I guess I could have moved, but I had family and other reasons where I liked New York a lot.

Trying to compete on the West Coast terms made no sense to me. 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 more typical venture investing and the DNA of a sales guy of software back then an 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 an industry really well. And we picked software. In hindsight, it was probably the best bet I've ever made. It wasn't because I saw the vision to where it is today by any stretch. So that was the start of it all. In like the early 90s, I was still at Warburg.

I went to a conference and Kevin Landry, who was at the time the founder and, managing partner with T.A. Associates was presenting to a large crowd, and he was walking through his playbook. And I was like the classic Vince Lombardi story. Here it is. I don't really care. Do it with the way. Good luck was his comment. And I'm 26 years old. I'm like, all right, that's pretty cool. He's ripping out Elp Wanted ads from the New York Times magazine that you're reading. And he's calling these companies up. And it turned out back then, it was a really opaque market. very few companies were out there raising capital in any professional way. Entrepreneurs were really receptive to just being called up and saying,

hey, I think you've got something cool. Would you be interested in talking to me? And I started at Warburg. I sourced a bunch of deals that way, which was pretty unusual for what was largely a shape-to-tree partner model, and realize I could find deals all day long like this. And especially software lent itself to being outside Silicon Valley, especially applications.

If you're building banking software, or 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 Silicon Valley? And I can go down a list of industries that really made sense to be much closer to your customers, which themselves had clusters around the U.S. and even in Europe. Most software companies back then started as consulting projects that got bootstrap to some degree to a product. So you can actually find these things well after their incubation phase and startup phase, which again was very counter to the West Coast model.

I hear Landry speak, I start doing what he's doing. This is working. I could do this. And we started insight, had a partner, was a consultant to Warburg. We started up. We just start sourcing deals, called calling everybody. We found a bunch of deals before we had a fund, and then we scrapped together with $16 million blind pool of capital from some high net worth folks.

And 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 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 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. 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 my first hires as a partner was somebody who was president of one of my companies who's one of the best sales guys I'd ever met. That was the thesis. Focus, sourcing, value add by being the best at what we could be. And obviously the world's changed a lot since then, but those core ingredients are still 100% insight. So if you think about the sourcing platform inside of insight and chunk it up into chapters back into the mid-90s through to today, what are the major chapters? How is it a lot? Chapter one is me and my partner then. Chapter two is I hired three associates, one out of Summit, Mike Triplett, which was a big decision and brought me concrete. I've been there, done it at the best of the best.

My partner, Jeff Lieberman and one other partner. And so they started doing it too. And Mike was, for him, it was second nature because he'd been doing it his whole career, which wasn't very long at the time. It was probably 25. That kind of elevated us. And we were 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, 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 McKinsey, 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. It's a lot of effort, and that became the first two chapters, really. We then started to operationalize what that young man was doing, And we started having classes and then we started going down to best schools to recruit.

And then we started to have training programs and we started to really institutionalize that entire process. And that's the last 20 years. Other than technology, the hiring and profiling of what we do hasn't changed tremendously to class sizes. Generally speaking, they've gotten bigger as the market's grown. But we're just trying to cover everything. So whatever that takes in terms of human resources, the next chapter for us, it's been

probably the last five years is just technology really make an impact on who you focus on. 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. That's our belief. 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 going to return your phone call. I'll have analysts give you stories of 25 phone calls, a couple FedEx's, and then landing on somebody's street corner begging to take a meet.

meeting. It's hard sometimes to get the attention of somebody who's successful, especially in today's world where there's probably 50 more firms reaching out to that individual. 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, 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, could you describe it in as much detail as possible? How many people are there, How are they given their assignment? Are they just given free reign?

Do they have a coverage universe? Give me the detail of the actual platform today. My measurement style, which is not very good, but it can be very effective for the right people, is to throw you in the water and just say swim. 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 able to institutionalize some of the lessons to get people up the curve quickly. But 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. 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 that they're intrigued by. But it's a lot of trial by error and learning, and different folks pick it up in different ways. Different folks are better suited for that than other jobs, but it's pretty much a self-starter,

highly personalized initiative to get going. We've probably in aggregate 60 plus people, depending on you count 60 to 80 people that are still heavily engaged. The process has gotten a little bit more sophisticated because founders also want to meet with more senior folks. We have 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 coaching from the folks who've been there and done it.

Almost all the partners at Insight, but one or two at the investment committee level started off in that program. We have largely cultivated our own teams over the years. We also have a very big practice of McKinsey-like brains that are there to help the portfolio. So they come in also fairly young, maybe two years of McKinsey and then join Insight. And that's another career path for people to get to know investing, but to know it through the operational side. But it's a fantastic talent pool. One of the core differentiators of insight is we have the best youngest talent by far in the world.

would absolutely put us against anybody on talent. And 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. It sort of reflects the fact that we are building a good model for people to learn how to invest. It may not be the only model, but it's certainly a good model. And people around the industry obviously respect it. I'm going to keep dwelling on it because I'm so interested by it. That's a lot of funds to have started out of a single place. So that's really cool. coaching tree like in football or something? I use the Bill Parcell.

Yeah, the Bill Parcell's coaching tree. Those 60 people today, how do they relate to one and other? And what's the incentive structure? Am I incentive to compete directly with them? And if there's a good deal, do I have my own lane? You've got lanes and we've got technology to claim the, I mean, it's probably a lot like if you were in a good software company and you looked at the BDRs and that software company and looked at the sales folks and you thought, all right, who gets what territory?

And 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, and then it sits on their pipe, and it has certain rules around how long it could stay in that pipe until it's acted on. Up for grabs again. It's up for grabs again. You get the ocean. You could call whatever you want. Once it's on somebody's pipe, it's their deal, and 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 cooperation. Obviously, people like their own track records. It's hard to take type A people and make them full players on that.

But I think we do a pretty good job of that. 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. And I think what we found was a lot of misses that way. It could be just a partner's predilection to doing a certain type of deal. And so this other kind of deal, it's just as good, but it's technically in one partner's bucket doesn't get acted on. We try to create a little bit more openness to what those liens look like.

But the partners at the senior level know, if somebody finds a cyber deal, there's a few of us that do a lot of cyber. Please share it with one of us. What's the point of getting educated? And we're all comp the same. This is one for all, all for one to make the firm successful. And we try to direct the deals to where they're both going to get one and focused on. Is the person incented to just get a deal to a certain stage or get a deal that get done? Is it just like a salesperson? They're sort of paid the equivalent of a commission or something like that. They get paid very good salaries and bonus on that. At this age, the money is not the driver. The gold and carrot is so big, whether it's at our farm or somewhere else,

of being a successful investor, everyone has a slightly different take on this, but by and large, the real motivation is they want to be successful and win and have a good deal. 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, just because you got a couple thousand dollars of 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 I see members who've been with me, most cases, 20 plus years, six of us together for at least 25 years, a few 10 years. And that's kind of the pods that we would say. These are the senior people. Within that, there might be some other investor MDs, some principals and VPs. And so it bubbles up, starts with maybe a VP or senior associate working with that analyst that sorts the deal and then recognizing all the key signals to what might be an exciting company.

It's not tricky as 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 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 see that. We're like, okay, that founder does not have an interest in taking a call from somebody more junior. Those junior people have a lot of influence at my firm, so they run my schedule for sure.

But that's a heart to crack, and the partners will get jumped on planes, and I've been this year to Estonia, Sweden. I think you told me your calendar is dictated by 24-year-olds. Totally. They set it up. Today, every meeting was set up by the analyst, which is fun. The partners that work in other firms, the nice thing they have is that their calendar gets filled up by doing deals so they can't do more deals. It's sort of a nice regulator to deal flow. This sometimes could catch us a little bit because it's so much of what we've done and we've systematized that it's relatively easy for us to get my time set up, which is great, but it also means that they can go on forever. I can't say I'm too busy. 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 source of 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. You'll make a phone call to anybody and not care, ability to handle rejection well, but combined with a lot of content. The really good ones are going to get really deep. And those conversations they have with the founders are shocking. I remember one meeting distinctly in mid-2000s and the company was in New York. So I just popped over to meet the CEO.

And the first question out of the CEO's mouth is, where's the analyst? Oh, you just got me. Sorry. She's still in the office. So they get really connected. The letters you will see us get from founders on the relationship that the analysts have built, the trust that they've built with these founders, and the work they do to generate real value for those founders before we invest is remarkable.

If you think about salesmanship and the ability to do sourcing well, if I were to pull people, 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? One could be, we definitely get turned off by that model. I think it's unjust, but it is what it is. Some people have a view they only want to talk to the top. These are good kids that are really working hard and they're going to get you to the top.

Obviously, rejection is really tough too. By talking to so many people, we're obviously rejected a lot. 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. The last thing you want to do is damage a relationship with the founder. In addition to the sourcing which we talked about in the one fund concept, another distinguishing feature of insight is how you've made sequential, typically small to begin bets in new deal types.

If you look today, a huge chunk of your assets are what I would call like private equity style deals, not venture rounds, not growth rounds, traditional sometimes. big private equity rounds. How did something like that start? What have you learned about bet sizing for new types of deals? Because this is really important. Go back in time, 90s, software wasn't big enough to think about buyouts, even unlevered buyouts.

It just didn't exist as an industry. And there was also a pretty strong belief broadly in venture capital that giving cash to a founder was a four-letter word. You never do that. That was 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 to founders were just not acceptable. TA Summit were breaking that model a little bit in the 90s.

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. That was the reason you didn't want to give him cash. Now he could afford a house. He's not going to work so hard. And we just felt like if we break it, we can own it and we can manage it. We just got a lot more confidence as we did more. these that if for whatever reason it didn't work out with the founder, they decided to retire,

whatever it was, we're okay running this. We could find a new CEO. Obviously, that's a big part of all venture capital jobs is keeping management where you want and not everything works out with the original team. We saw two deals that the owners were not typical shareholders. One was a former founder that had hired a full team and we bought the company from him. We bought his shares. We're like, well, we don't have to demotivate him. We don't even want him involved in the business. And then the other was owned by a large insurance company, which is now called Vortifor.

That was the first buyout I'm aware of. There was probably a few others that were not done by private equity firms, but it was certainly one of the earliest buyouts in private equity in 2009. We just started to see the other side of software as it got bigger when they start generating cash flow, which until mid-2000s, 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-time's leverage from a crazy hedge fund that believed in us.

That was considered a highly leveraged software asset. Today, Verte4Pri has nine times leverage, very different world. But that was the beginning of software buyouts, and we made a series of bets through the mid-2000s. And then we also started looking at 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. we'll take that risk. It's $5 million business, but we think we can transition to the new management team and we had the tech team sticking around. And the more confidence we got that we could

own control of something and not risk the entrepreneurial DNA that went into it, or it was past that point where that was critical, the more we started looking at those types of deals, it's been a fantastic sector for us. We've made a ton of money, especially in the venture by us, but the unlevered 30, 40 percent growers or tweeners. 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 are tens of thousands of those now.

They're good companies. They shouldn't belong somewhere. There's a lot more folks like us now willing to take those bets, so it's not quite the same market it was a decade ago. I said this to my LPs. Stage is not a strategy to me. You could argue seed investing is a very different skill set generally. 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 there, and we don't have quite the same deal flow. And buyouts require as a certain transactional skill set, pretty straightforward to hire for it's not like it hasn't been done before. Not only in software, but in tons of other industries, there's plenty of skills to do it. And then everything else is just a spreadsheet. It 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? There's a very big range of strategy that sits in that middle. And that was a view that we had. Why constrain ourselves up until 2017, late stage pre-IPO growth was a really cool market. 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 pre-IP rounds, even more if you did the consumer internet stuff. And then it started getting really competitive. Hedge funds came in, sovereign wealths came in. And as I mentioned earlier, some of those rounds are now getting modeled at two to three X. A lot of things have to go right. So we said, well, we see it all. We could model them all.

Why can't we just put risk against that model and 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. A lot of the companies that raised a ton of monies that 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. We were like, oh, let's go lean back in on the middle where you've got these 30% bank growers that look really nice. Cash flows are good and their salmon farms and roller coaster

ride software and things that nobody's really putting a lot of mind to. And we did a bunch of those deals back in 23, 24. Now AI is probably re-energizing some of the growth stuff. But I like the idea of being able to move around the markets based on where we think the most value is. 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 so down into deal types between traditional earlier stage, venture buyout. What does it look like? Early stage is like 10%. Growth is probably 30% growth buyout, which is like this,

what we call venture buyout. It's probably another 30, 40% of LBOs are probably 20%. The buyout market looked great when interest 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. Multibles 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. It's a guideline. We're never going to get super early. It's a big number. We feel like one, those get to be much bigger checks that could start at 10% and grow to 20% if we get back to an environment where we could be the lead investor in the next round. And then a lot of the venture buyouts, M&A is a huge part of the strategy.

So if you look at levers for winning in a venture buyout, you get 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? How do you articulate it to your own piece? I think the buyouts were willing to take five points lower than everything else. Everything else is blended pretty close to the same.

30% is kind of a gross number that we target. We probably miss a little bit more on the early stuff than the venture buyout. Our rate is just super high. It's a lower risk profile, so it's a market that's been a little bit better and very few competitors. And it plays perfectly to our sourcing engine. Because how do you find these companies that are selling salmon software to the salmon industry? That's not an easy source. That's people jumping on planes and calling up companies in Norway. It's not mainstream. They're not showing up the 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 WIS, we talked about data breaks.

You mentioned Monday Anthropic came out in the news recently that you were an investor in this big round. That sounds more like very traditional venture growth style investing. Well, I mean, Wiz, we backed when it had zero revenue. We loved everything we saw, including team. Monday was an interesting company, but not the most obvious funded company. It was right, $5 million in size when we backed it. And Cien was another public one I'm involved with. It was four or five million in size when we got there.

So some of them just grow and have dams to support those exits. But it's tempting to always go for the shiny objects and we fight a lot internally about 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, such an exciting company. 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. This is a classic case. Darry's phenomenal CEO has a very, very thoughtful, articulate view of his business. And the second you hear, you're like, okay, there is a moat or there might be a moat. And obviously, the numbers in the last four months there are incredible. It inflected with coding. And when you sort of think about how he's invested around that, that's not accidental. That was intentional and probably defensible. It's a pretty interesting bet to make. What do you make of those 16 or 18 funds that have emerged from insight? One way of thinking about it is, wow, this incredible, a lot of talent that's been able to be independently successful.

Another way is, why didn't you try to keep them there? What are the size of this coin? 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, is 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. It's just not doable. One plus one 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. It's just inevitable. But I think it's healthy for us. And 80% of them, we still have a really good relationship with these firms. We talk to them all the time. We do deals together. McKinsey has set a great precedent out there of what could be done if you embrace that network and don't take it as a negative, but take it as a positive. Obviously, having partners at other firms, I think is great for us to sea deals and there's still a lot of camaraderie of the classes never goes away because you're in that pit working 10-hour days in a pretty tough environment. We try to make it fun too, but they really

connect with each other and some of the best friends I think in the world have probably come out of that. And why do you think you've been able to graduate so many people? This is the Bill Parcell's question. This is my favorite question for sea level executives. It's the same question. Who are your best protegees and were they now? I have one good friend of mine who's retired now, 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 DNA was just awesome, but some of it was him. So we 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 think ultimately, the training you get at 23 at Insight is like no other job in the industry because all you're seeing is at-bats. You're seeing more pitches than any other firm out there. You're 23 years old. Your brain is a sponge. It's just looking at all those pitches and you start seeing your own patterns. Inevitably, you're going to become a pretty good investor. It's not the same as the product-driven strategies that other venture funds have. And we are a big pattern recognition business. Investing is pattern recognition. Everyone can draw their own graphs out of those patterns, but that's fundamentally the core thesis. 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, your track record's not going to be

that good. The culture of just how important sourcing is to being a successful investor, we just drill into people at a very young age that sticks with them in their later life, and I think it makes them look good to the peers that they have that didn't have that culture. If we're building like a Madden player that has points and different attributes, and you were to give yourself scoring on C, pick, and win, and maybe support as well, but are especially interested in C pick and win. It sounds like C sourcing, you'd give yourself a crazy high score. We see every pitch.

Picking in the middle is awesome. Our picking on the edges is okay. When you see something that's got a little bit of an edge to it on the source where the numbers are pretty tight and the valuation is not West Coast. crazy, we're really good and we're really good at winning too. So if you really think about what I do for a living, it's you got to win deals, you got to pick them and you got to make them work. That's it. On the picking, we're really good in that middle zone, especially some of my partners that can parse the numbers, look at the trends and figure out how to get that spreadsheet as accurate as

possible. At the edges, it inherently gets harder. We have some disadvantages on early relative to California. 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. And on the buyout side, there's some equally great investors. It's a game of combination of discipline, focus, and operational execution. And there's some great firms out there.

So I think we do a very good job on that. We're really, really good in our sweets, but 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. If you just lined us up against the best of the best and the value, those guys are awesome. I'm not saying we're going to be able to,

connect the dots that they connect because they're just using different dots to me, what I'd call Intangibles work. Sounds like the winning is quite successful in your sweet spot as well. How do you do that? What are the keys to successfully closing a deal in that sweet spot? First and foremost, showing up, hard, getting on planes, invited or uninvited, showing up to people's doors and asking them to have a conversation. We started with, 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 smart McKinsey folks that could do any analytical thinking that you might need to invest to the best sales process folks, to marketing process, to HR process. We bought a pretty expensive large interest in Riviera Partners, which is the largest tech recruiting firm for CTO and CPO talent, which is really an interesting asset, especially in the AI age where talent is everything. We've put a lot of emphasis on talent. We've got 15 people that do nothing but liaise with Fortune 500 companies. If you're a CEO, first and foremost, give me revenue. If you're a small

company, 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 jumpstart companies where we've gotten the first 10 million of revenue. It's a big impact in the journey of some of these companies in terms of getting them started. We really push hard to bring that program to be as big as it can be and constantly innovating on that. It's all about winning. And so it's a combination of personal connections showing up and caring about the entrepreneurs problems. 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 the strategy of investing firms and how even though

all these firms are investing in companies that they hope have a great vision and strategy and roadmap and all this kind of thing that investing firms tend to have that to a lesser extent, either no strategy or not big institutionalized strategy. I would say the majority struck me is our strategies were really good investors, which is true probably for some of these guys. Like they probably are really good investors. And they kind of tweak that into what might sound like a strategy, especially to some LPs. But I think if you really press what I just said, there's only four things we do.

We find deals, we win deals, we select deals, and we make them work. and then you put that layer on, how do you do that better than everybody else? Put selection aside because that's the hardest to institutionalize. How many firms really can articulate? And there's lots of ways to do it. Mark Andreessen was on here. He has an absolutely great strategy different than us, and we could never do what he does. But he's thinking about it every day, and he's using his marketing engine.

I think he was recently quoted this basically, I'm a marketing firm with an investment arm. I wanted to be a software company with an investment arm. And that was kind of my pitch 10 years ago to LPs. That's how I thought of myself. People could think of us as we know so much about software. They could outsource a lot of that know-how. And then we have an investment arm to monetize that. There's lots of ways to skin the cat.

We've just taken one approach. Some firms obviously could do it just by sheer presence of being first, and they've made great investments over decades. Other firms might pick different industries. Some firms have done it in the buyout space, where they've just used capital combined with expertise to just be able to lean in faster and harder. There's lots of ways to create moat, but 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. Putting rigor around that and operationalizing it, we hired one of my good friends years ago as a chief operating officer of insight. He subsequently started his own firm, but he, He was a mechanical engineer at McKinsey who spent time at Putnam and Lehman. He woke up every day and it was like, how do I make that pencil, do it something without a human touching it? That's how his brain worked. And mine works in a very similar way from a more strategic side. But it's sort of systematizing what tasks we do that we could have others do better. And then how do I create moat to the extent that it's possible?

Because like capital is not a huge mode. 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. Warburg-Pinkas 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 buyout world.

Capital is tougher, though. So you just need to think about those four disciplines and say, well, how am I going to be way better? Some guys do it by appearing on podcasts and getting their thought out and their vision and excite the founding community of how smart they are about an industry. that's a perfectly legit way to get deals. Others have cultivated networks in different ways, and winning could be, I'm just going to get on the plane and do it, an individual partner that works my tail off, and it's not very

leverageable, but it's certainly a good strategy. How do you institutionalize systematize that and operationalize it is not easy? We found also scale was a real opportunity, and I heard Mark Henderson talk about this, too. Every industry but ours was considered to be better. as they got bigger. For some reason, this type of investing, tech investing was like, no, we want you to be a cottage industry. We're smartest partners do all the work. I remember very distinctly sitting down with one of my partners in 2015. I'm like, why do LPs have this allergic reaction to the word scale? Because, again, everywhere else, it seems good. I looked at those four

buckets of what we do. I'm like, clearly sourcing is better with scale. I could see everything. You might have to debate how you pick, but great that you get every pitch. You could certainly see how winning can get better with scale. I've got more resources I could support every round that you need. It could be your one-stop shop. And then obviously on the operational side, that's the biggest impact scale I 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 a bit of a hard one for us 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 bigger deals, smaller deals. Like maybe they're priced differently. Maybe the competitive landscape's different. There's a lot of reasons why just writing a bigger check often won't yield better returns. So scaling by check size was not necessarily a clear direction in my view of how to do scale. Some might scale with geography.

We tried that. Oh, was that painful? We're 90% in New York City by headcount and probably 100% by investment commitments. Certainly I see is all in New York. It's really hard to export judgment. We had a European team that raised a European fund and it was the worst of all timing. It was 2000. 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 over the five, ten years before that at insight. But geographic scaling is a really common strategy for a lot of folks, but I could see why LPs would be nervous about that. And then lastly, people scale by doing something that they weren't doing before. I'm a great software investor. Now I'm going to do health care. 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 Blackstone, others have done that really successfully. But you could argue it's not easy. Maybe Blackstone did a great job of it, but two other firms didn't get those top quartile 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 it bought something in a different asset class and struggled to make it work. We kind of said, well, we don't need to do any of those things. Software's just growing.

We're barely scratching the surface on what we do already. Why can't we just do more of good deals in the category we love and know? 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. There's nothing unique about it other than it just happens to have more zeros in its business model. Open AI, even more true. If you just turn 12 billion into 12 million, you're like, wow, this is a fast-growing company. Why wouldn't I jump at writing a $10 million check? So some of this was 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, 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? Why should we just stick to some smaller strategy or artificially constrain what we do? If understandable, you want to keep a bar high, and we've definitely over the years sometimes fucked that up and been caught up in the moment, if you will. We looked at scale in that lens and we're like, this is win, win, win. 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 perfectly to start. We hired young kid becomes less young, becomes principal and ultimately junior partner. They were on their own and we kind of had a little bit of partners or 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 tennis match. Everybody goes out, plays tennis, compare scores, and we won the match or we won the tournament. We were trying to

be more like a soccer team, but we played tennis for a little while, and we realized that young partner as a deal comes to me, and it's like mom and dad, I'm a little busy. You're only hearing one third of what's coming 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 deal that's in trouble. And we're like, this isn't working. We need to think about 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 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. 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. We don't do that many deals a year, except for 2021, but it wasn't an insurmountable number. It wasn't like I needed to spend 20 hours on another partner's deal, but three hours, I can get a lot of instincts. My instincts may be more on alcohol, I'll call the intangible excitement around the deal. Other partners are really good at the financial side. We keep tweaking that a little bit, but that was fundamentally a breakthrough in how we can try and scale judgment without break. the model and saying, let's just have pods of very experienced partners managing and working

with other partners, both operating partners and young hungry deal partners 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. One thing you hear a lot is even in firms where there's your level of systematic setup and rigor, that it's really important that the leading investors be able to just throw everything out

and sometimes make a deal or do a deal based mostly on the intangibles out of the spreadsheet. Can you talk about your experience with that and how you think about that type of deal? We can mobilize 15 people from my McKinsey brains to my sales ops team or marketing ops team to dive in and really try and uncover as much as we can in that very short time window that we have. once in a while, 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. I'll do a little bit of those on the smaller side where I feel like a unique team with unique technology and there's not a lot of numbers to support it.

But that's going to be an allocated part of the portfolio that's going to be very small. That's more risk managed again by 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. 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 really have to die because they had so much money put into them. Maybe they're starting. One of the weird things is that market prices haven't really caught up to the reality of the underlying businesses. And I'm curious for your perspective on what things are generally worth in terms of like a simple multiple. Everyone kind of thinks in 10 times multiple or something for a software business. But I think these things are often worth way, way less. By the way, you could see this with the secondary market.

It's a little hidden secret. Go look at how some things trade in the secondary market. If when you're at 70 cents on the dollar, your marks aren't on us. 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?

If you were to pay three times for something, what GDR and growth rate does that imply? That might be low single digit growth and 80% GDR. So if you go into the public markets and look at those companies, they're disasters. Few are even public today. It was a category that early SaaS, a lot of those went public and ultimately the markets caught up to the unit economics. PE guys are looking for long-term, this is cash flow. We have a company which now Vista owns that has a mid-80s GDR,

but its CAQ is three months, which is a very low number in the world of CAQ. So you can make a 30% margin business if it's an infinitely sized market with a relatively low CAQ. There's an exception to everything I'm about to say. But if you're in a more normalized enterprise world, you're going to have 12-month CAQ, which means it's one year up front 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 and a half times to one time dollar invested. Plus I've got R&D. Plus I've got support, GNA. You're not going to make a lot of money. So those companies tend to be in the 10%, maybe, maybe squeak out 20% margin versus 100% GDR company will have 50, 60% margins. If you just thought of multiples of cash flow translating to multiples of revenue,

that's going to give you a big delta. 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 seven and a half times revenue. I think the markets more or less eventually will look into that financial model. And some companies, 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 still get yourself to ultimately you're trying to get the cash flow margins.

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 existential risk, somebody could come in in your model and disrupt it. So those are just the framework that I think most public investors in late stage buyout guys are thinking. How resilient is that cash flow? Are you running a core banking system for a bunch of banks? That's not getting ripped out in a recession. You don't really care about a recession. What's the growth rate of that cash flow? And then what's a reasonable multiple based on that, and some of that will be interest rate sensitive. 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 long-key multiples. You just can't model those out in your exits. They're rare earth kind of numbers. One of the things that I'm curious about the temptation around, given how the markets evolved, is the andrels of the world, non-software technology companies, some of which have gotten quite big, quite quickly. And consumer too for us. 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 understanding and mandate. It also really favored the West Coast. 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. It was a great outcome. Managed to get

Twitter over the line before Muscat all took over, but we've just gotten comfortable that our misses are so high in those categories over the years that we're like, whatever. We can't be everybody to everything and we can't do it all. 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 sticking to what we know well in enterprise software and flavors of that, it's both massive and opportunity and the returns can 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, you describe the method that you used to run those personally? Different investors on your team will do it differently, but I'm especially curious about your method. I've developed, I'd call a similar line of start, which is I love origin stories. What was in your mind? Why did you choose to solve this problem? What were you doing before that made you think about this problem? And then I love to get to the value problem. I just love hearing how you're making somebody's life different and better and why customers are going to be excited about buying your solution. I'm probably the least focused. on drilling in on the numbers.

I mean, I like to hear the top line numbers, but entrepreneurs probably aren't always the most forthright about what they give you. Like they give you, because they're a little more happy years on those usually, which is where diligence can corroborate or not. But those are the stories I want to hear is what makes you tick

and what's this passion that you have about what problem and why? Those really range a lot in response. Like, you're enough people pitch and you're like, that one really resonates. Elevator pitch, I got it. Some, you need to, double click, double click, double click.

You know, I was on the call today with one, and I was like, I think I hear you, but I'm not quite getting that moat. I'm not quite getting that long-term direction of where you're going to be. It doesn't mean it wasn't there, but it's a 45-minute call. You're not going to nail it exactly. Sometimes the numbers tell you way more than the story. 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 the newbies. on the team at the senior level. To what do you attribute that? What is your management style with those people? How do you relate to them? What would they say about you? I am pretty forgiving on mistakes. Some of my partners would say too forgiving,

but I try to see inputs. I have a thing that we instituted insight changed a little bit from the vision, but I call it the X factor. Type A employees, they always want to know where their careers are going and always ask me these tough questions. How do you give somebody valuable career advice

in what we do? because the outputs are so long coming, and there's so much luck. Let's not kid ourselves. There's a lot of luck in what we do. And I start with, well, if I took you out, what would have happened? Would the deal have stolen source?

Would we have won the deal? Would we have decided to do the deal? How much of those decisions did you play in that process? X is the removal of you. Are you adding X to that equation? It's not easy to review somebody that has great inputs, but the outputs are long incoming. And one of my best partners had a really slow start. 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. People learn, people get better to marathon. Obviously, at some point, the marathon ends, but that's generally how I try to approach it. My style is similar to what we do with the analysts is really to give people an environment, where they could be creative. Take risk. 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 and 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 doesn't work out. I think I'm definitely in the ladder camp. My goal is, I call it the tush push.

You're at the one-yard line, you've got one little thing nagging you about the deal. It's okay. You've thought about it well. The risk reward is good. It may not work out. It's not your career in the line if it doesn't. If you look at generational firms, risk appetite is probably the biggest challenge. 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 this is a great business. If you don't get fired, you're going to be pretty successful. The impetus to really stick your neck out on the spectrum is really low. People, especially in bigger organizations, I hope they make mistakes. My biggest frustration with one of my partners who left was the things he didn't do. Why don't we do that deal? We always had five reasons not to do it.

He was very conservative and to the point where we missed a bunch of really good things. You need the balance. I've got a lot of partners. who are holding people back from the cliff, it's a good yin-yang of some folks that are going to make you feel really scared to stick your neck out, but then hopefully, especially my senior partner is knowing I've got their back always. I'm 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 on outright

as a disruptive force, how you use it yourself to make insight work better. Investment opportunities to create it like an anthropic. There's a lot going on with this nuclear bomb that's gone off in a good way. How do you process it? I remember like a bunch of years ago, even before the chat, GPT aha moment, and I'm not the technology wizard in the firm by any stretch, but 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.

There's a lot of jobs where that's pretty much what you do. I started talking about it at some of the LP meetings, and then we were doing the vision stuff, which was not in any way exploding like the language has exploded. Not sure why. I never got the buzz. I don't know, but vision just for whatever reason was good, but not compelling. And you could look at MRI companies. And 10 years later, they're 80 million.

It's like the biggest one, maybe. What happened to that? I can't explain it. But for some reason, the language took off. We looked at other waves, and it was pretty easy for us to kind of sit on the sidelines. lines. Others on your show are big fans of blockchain, maybe now it's crypto because the blockchains. No one could articulate the use case. And it was back when I debated this with people, it's 12 years in, come on. There's a whole religion around it. And maybe someday every

bank will be on it, whatever. But it's definitely way longer than anyone forecasts to be valuable. And I certainly had a funny story. Someone told me, all the technology guys that love blockchain, think the technology is kind of meh. But the finance aspects of it are really cool. And all the finance guys are like, the finance aspects of this aren't so great, but the tech looks really cool. I'm like, huh, nobody was like, this is the best database I've ever seen in my life who understood database technology. And finance guys are like, this isn't really how the world and finance is going to work. So we've looked at other waves of technology and been a lot more sanguine about the potential and even the self-driving car. That was a big hotspot a decade ago.

That was more vision. This one is different. And I don't know if it was the problems it could solve immediately. certainly the consumer side of this is mind-blowing what you can do as a consumer and watching my own family in the last three months convert from Google search to Gemini or to chat GPT. And it was a game changer in so many ways. And we kind of were playing around the edges of it in some ways. And then 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. I mean, we probably

have 25 agentic AI bets that we think could be really profound in the commercial markets. We've been noodling on all sorts 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 Claude to write my next SAP, we're not losing any sleep over that, quite the opposite. Why not? Because that's not what software ever was. It was never a technology barrier. It was always a business knowledge barrier. Maybe you could literally have AI look at SAP and plagiarize it and try and build something equivalent. 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. The cost of developing software is 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. We've gone through generations of productivity tools and software development. This is more profound for sure. For those who are old enough, the 4GL was a pretty profound tool too. Back in the day, you just had a database with a screen. Applications weren't all that complicated, and the 4GL was meant to basically make it really easy to build the screens. It was impactful, but it didn't radicalize every SAP and all these other companies

didn't get displaced because of it. But it's taking away a lot of probably budget. I think you'll probably be seeing a lot of companies feeling the pain of, that's not the cool kid on the block to buy a CRM software today. That's just not my priority. I want to automate something else. So that matters. That's growth rates. 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 doing image recognition, things like that. What's your point of existence now? By and large, I don't worry about the usefulness of 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. really focused on is it's a massive TAM accelerator. My core software is not as sexy, but now I can

go after a whole set of problems that my customers have that I before could never automate. I'm on the board of a couple CRM-like vertical applications where we're just capturing data. 95% of the person's day is generating and getting the data. If I could automate a big portion of the 95% of the time that you're getting data into the system, that's hugely valuable. We've got already half a dozen or more companies really re-accelerating off of new products that they've launched in very short timeframes that are creating massive TAM expansion for their businesses. And I have no doubt the bigger public companies are working aggressively at the same thing. Like Microsoft.

Microsoft looks at that. Could I build a new PowerPoint with it? Probably. I don't know, maybe. But can I make PowerPoint the existing product way better with a co-pilot? Probably can. I think that's way more interesting or Adobe. How much better is Adobe?

that has a 3% market share of humans to Photoshop and now could expand it to 20% because user interface and learning curve has gone down by an order of magnitude. 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 out-engineer them with a new product. It'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.

I think we're still quite a ways away from even getting to the point where the speed to which you could build software is so dramatically better. You said before that 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, and yet your activity in the firms is quite intense. And this is kind of an interesting dichotomy. and I'm curious where the drive to win came from. I don't care about beating other people so much as just satisfaction my own success and winning.

So it's a different kind of drive than I think other people get. I have friends who I play golf with. I can't play without betting. They can't have fun. They can't try hard if they don't have something on the line. That's how competitive they are, but they're competitive against me.

They want to beat me. That's what drives them. I'm like, I just want to get my own score as low as possible. If you shoot at 65, I'm high-fiving you, I'll buy you a beer. I'll be the happiest guy to give you 20 bucks. I don't really care at all if I have a good round. 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. That's what gets us a little endorphins for the day. These conversations always go the same direction where 98% of the conversation is about buying and almost none of it's about selling. What have you learned about selling, selling well, when to sell? I've had a good year on that one.

We've sold a lot this year. But the easy things are the ones that come naturally. IPO, strategic knocks on your door, they pull you in, you sell. The harder one is we have to push it to make it happen. I think at 1.99, we had a 4x on our 99 fund in the public markets that we couldn't sell. They were locked up. And by the time we could get off the lockup, it was down to a one-X. These are quick windows.

They come and go and you kind of learn. Some of this was also, we put COVID as a piece of it, which was a combination of the demand shift and change. You know, some ideas that look great. 2021 virtual conferences looked like a great idea. It felt like that could really have legs even post-COVID. The answer is they had no legs after COVID or very little legs. And then some of it was just us. Decision-making, probably not what we thought it was.

over Zoom. And we had like everybody else a year of 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 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. We'll absorb what we think are great deals. But the bar has never been higher since summer of 22. We've been pretty focused on making sure that we make as much money as possible for LPs, I'll call it a little bit more boring. I had at one time firm building ambitions that I still have a little bit of where we could add assets making us the world's best software company. What would make me a great partner

for my portfolio, we still have some of that ambition, but it's going to take a different flavor. Is there anything essential about insight that you feel like we've missed? There's definitely a lot of positives on our culture that don't get seen by entrepreneurs. it's a combination of we don't have to be the loudest voice at the table ever. 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. 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 by and large, the idea is to really support each other in a meaningful way. We talked about winning, which is a big part of us. We also just never want to give up. We really, really want to be there to the end. We're lead investors. We're not passive investors. Somebody's going to be on top of these companies until the end. It's important for us, 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 trying to fix it. It's really satisfying on the few times that you can actually turn it around and just feels like it's the right thing to do. Well, it's really cool to get the inside view on this. It's a firm you hear a lot about because it's so big. You've made so many great investments over the years. It's very hard to figure it out from the outside. So thank you for the two hours. It's 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? Mentoring has always been an area where some of it might be broadly self-interested, but most of that is selfless. And I've had two examples, but my first job at Warburg, the person I work for there, pulled me out of a very, a hat in terms of resume, saw something in me that no one else did. I think I'd tried getting a job at 100 firms, and he was the only one who was willing to hire me. I learned a lot in that experience

as well. But then I think when I started Insight, we sort of randomly bumped into an interview by name Steve Friedman, who was the just then retired CEO of Goldman Sachs. I think it was a mutual connection from one of the high net worth guys at Goldman that knew one of my partners. Steve, for reasons I still don't know, one of the nicest guys I've ever met took me under and gave me amazing counsel in the first decade. Ultimately introduced me to his co-CEOOOO, 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. Nice to air issues, challenges, and focus. So that, to me, was certainly one of the best things that happened to my career. Incredible. Jeff, thank you so much for your time. Awesome. If you enjoyed this episode, visit join colossus.com where you'll find every episode of this podcast complete with hand-edited

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