The Exchanges

Q I'd love to start this day with a little on you and how you made your foray into the world of early stage investing. So what was your entry point, Rich?

A So I was actually quite an accidental venture capitalist. I was a operating exec. I ran the products group of a company called OpenWave Systems, which was a pioneer in a wireless internet and mobile technologies. And I really thought I was going to stay going on the operating executive side of the world, looking for sort of the right COO or president job as, as the next gig. And I'd known the Excel team for many years, mainly because we had worked in similar telecom and internet spaces in the past. And so when I came to see them to look for ideas of companies to go work at, they were looking for someone who had a background in mobile technology. And that's how I ended up wandering into venture capital.

AI assessment note: “that's how I ended up wandering into venture capital”

Q I'd love to start this day with a little on you and how you made your foray into the world of early stage investing. So what was your entry point, Rich?

A So I was actually quite an accidental venture capitalist. I was a operating exec. I ran the products group of a company called OpenWave Systems, which was a pioneer in a wireless internet and mobile technologies. And I really thought I was going to stay going on the operating executive side of the world, looking for sort of the right COO or president job as, as the next gig. And I'd known the Excel team for many years, mainly because we had worked in similar telecom and internet spaces in the past. And so when I came to see them to look for ideas of companies to go work at, they were looking for someone who had a background in mobile technology. And that's how I ended up wandering into venture capital.

AI assessment note: “And that's how I ended up wandering into venture capital.”

Q and B from my analysis. So talk to me, being too late to not be price sensitive, like the first checks, and too early to be overly price sensitive, how would you respond to, say, Peter Fenton on the show, who said never turn down a company based on valuation, it's a mental trap. How do you think about price sensitivity and your feelings towards it when making those deals?

A Well, I would say I mostly agree, but not completely. I mean, I think certainly at the early stage, you're purely, you're betting on team. I see that the company called Mopub, there were a couple of engineers and product managers that came out of a previous investment, AdMob, and so they were, you know, entrepreneurs that completely understood the category they were working in, had a authentic understanding of the problem still to be solved. That was one where you were purely betting on team, and it really wasn't a debate about your valuation at all. That is also true of companies being pricing Insensitive and not worrying about that too much. It's also true of companies that you believe have some unbounded or uncapped upside, and we'd like to say that all companies do, but the reality is not all of them have that truly uncapped, unbounded upside. So, a company like Atlassian, I think we were not on the low end of how we put in our term sheet in terms of the valuation that we ascribed to Atlassian at the time. That said, I think there are other companies that the category or the nature of the competitive set, you have to have some amount of Price discipline in order to achieve true good returns. And I think those are in categories that you, there's just simply not a completely unbounded upside is where you have to be somewhat price conscious. That is largely true of almost ever…

AI assessment note: “I would say I mostly agree, but not completely.”

Q You mentioned the two different elements of the fund structures there. I'd love to discuss the two different elements of decision making with regards to initial investment to follow on. How do you think about reserve allocation with Excel, and what's the thought process around allocating reserves effectively? How does that look?

A Right. It's not obvious to me we necessarily do it all right, but I'm happy to describe what we do, what we do do. You know, of course, things are often very cycle dependent and company dependent, but I would say when you do an early stage investment, On average, we at least reserve an equal amount of capital. So if you put in an eight million dollar series A, one might reserve eight, 10, eleven million dollars, you know, for follow-on rounds to support the company as it grows. I would say that ratio decreases the later stage one is involved as you spend those reserves. Obviously, if you were to do a series B or a series C as the initial investment, you know, I would say that ratio declines somewhat as the company moves further along. Historically, 10 years ago, when I first came to Excel, I would say, historically, we would do the standard pro rata or slightly below pro rata as our standard way of following on to any of our early stage investments. I think that mentality has changed in a smart way, meaning we can actually see the companies that have the chance to scale to these multi-billion dollar opportunities, and it is just illogical that we wouldn't use those investment opportunities to then do pro rata or, in some cases, super pro rata behind these growing investments. Qualtrics that we've spoken about a couple of times here is a good example of that, where we invested p…

AI assessment note: “when you do an early stage investment, On average, we at least reserve an equal amount”

Q And then let's finish today on your most recent publicly announced investment, and why did you say yes?

A The most recent publicly announced investment is a company called Instabug, which is based out of Cairo, Egypt. And a couple of entrepreneurs that came out of the YC system, but, you know, almost their entire team is based there in Cairo. You know, I think in terms of why I said, yes, I think they're a, they're a team that had proven, even at this very early days, value prop and market fit. And it very much fits many of the things that we talked about today in terms of the globalization of VC and the chance to build a scale company, even from a different geographic headquarters. They sit at the intersection of Product development and mobile, so they sort of fit the intersection of my sort of Atlassian sort of world plus my mobile background, and I was just super impressed by the founders, Omar Motaz, and so we're very honored to be investors with them.

AI assessment note: “The most recent publicly announced investment is a company called Instabug”

Q What have you changed your mind about in the last few years, and why do you think you changed your mind on that?

A Well, I think when we first started out, it was when I first started out, there was very much a belief that, I very much had the belief, it was unclear what the value was of having a large syndicate or a very strong syndicate of fellow board members that, in some sense, if you had a strong enough relationship with the entrepreneur, you could help influence that entrepreneur and then also provide the capital to help that company be successful. I think out of Some learning of the past five to seven years. I think Osmo, by the way, as we mentioned, is a very good example of this. Having a diverse syndicate that has different points of view to the board, even if you don't a hundred percent always agree with the other members of that board, can actually make a dramatic difference in helping the company be successful long-term. So, as I think I mentioned before we started the podcast, you know, Mark Suster from Upfront, Manu from K-Nine, and myself are the three of the board members at this company, Osmo in the educational gaming space. And the three of us just come from different backgrounds, but I think each bring useful and complimentary perspectives, you know, to help the founder promote, be successful. And I very much enjoyed that interaction. Um, and it's one of the, one of the things I've, uh, I've greatly enjoyed in the past couple of years.

AI assessment note: “Having a diverse syndicate that has different points of view... can actually make a dramatic difference”

Q I'm interested. You said that a lot of companies scale maybe too early. I'd love to hear your thoughts on a time where you've seen a mistake being made with regards to scaling time, and what were the big takeaways for you?

A Right. This I'd point to, you know, many of my own personal mistakes. If I were to go back to my time before Excel, my open wave systems, you know, the fundamental landscape in telecoms was changing right as we were trying to make a transition ourselves, and we were continuing to invest in technologies selling to the big carriers and telcos, which were really starting to go away as key players in the market. If we had taken the time to think carefully about who our customer base should be, you know, we could have built technologies like Skype, like Twitter, uh, as opposed to just continuing to build technology, selling to Orange or Singular or Nextel or AT&T, the customers of that time. And so I think that was a example where we both, in some cases, were successful too quickly. And so the company scaled so quickly that we were trying to build our entire business on that one customer base versus diversifying and looking at other customer bases or other value propositions, which was a missed opportunity on, certainly on my watch.

AI assessment note: “the company scaled so quickly that we were trying to build our entire business”

Q Can I ask, a lot of people say in the ecosystem that large multi-stage funds have reverted to the batting average element of investing, kind of minimizing loss ratio and being happy with the five to eight X. How would you think about this? You mentioned there about the uncapped upside. How would you respond to that suggestion, probably with Excel lying in that multi-stage fund assertion?

A I think it very much depends on where you sit on the early stage versus growth spectrum. You Excel actually has two different vehicles in the U.S. One, a early stage, five hundred million dollar fund, and a larger billion plus growth fund. So you really have to be shooting for the unbounded upside opportunities on the early stage side. You're shooting for the metaphorical You know, obviously, we don't always get there in every deal, but you really have to believe that there's that upside opportunity in that side of the fund. But you're on the growth stage, you are still looking for the upside opportunities. The Qualtrics, the Rovios, the Alassians are all bets out of the growth fund, as it turns out. But I think it's more all right if you can sort of see the five to seven X opportunities, and you don't necessarily believe it can be 10 X plus if you're on that side of the capital spectrum.

AI assessment note: “it very much depends on where you sit on the early stage versus growth spectrum.”

Q Speaking of kind of identifying those really special companies, around them there's always an intense amount of competition, and one element that, that kind of affects your ability to get in is that competitive landscape. So I'd love to hear your thoughts on competition dynamics in the Bay today, and how do you think about staying relevant with the progression of time and the entrance of new funds?

A Right. I think all of us in the industry talk a lot about, you know, how do you find the signal out of the different noise that's out there and the volume of deal flow? You know, one of the first ways we do it is By not only focusing just in the Bay Area, as we talked about earlier, the fact that one can take advantage of the global nature of what's happening in entrepreneurship means that if you actually spend your time in Salt Lake, in Austin, in Dallas, in Seattle, other markets, and then of course, internationally, whether it's Finland or, or Australia or other markets, there actually is less noise in those areas relative to the amount of interesting companies that can emerge. So one of the ways to help reduce that to improve our focus is Is to look at areas where others are not, and those geographies are one example. You know, the second, probably heard this from multiple Excel people, is that we have this internal phrase called the prepared mind. It comes from Louis Pasteur, quote, you know, chance favoring someone who has a prepared mind. It's just an internal way of saying having a thesis inductive-based approach is another way to sort out what's interesting from all the different deal flow and activity that's out there. And I think we do practice this Quite well internally, whether it's around the API initiatives or around enterprise software, we've been able to build …

AI assessment note: “one of the ways to help reduce that to improve our focus is Is to look at areas where others are not”

Q What have you changed your mind about in the last few years, and why do you think you changed your mind on that?

A Well, I think when we first started out, it was when I first started out, there was very much a belief that, I very much had the belief, it was unclear what the value was of having a large syndicate or a very strong syndicate of fellow board members that, in some sense, if you had a strong enough relationship with the entrepreneur, you could help influence that entrepreneur and then also provide the capital to help that company be successful. I think out of Some learning of the past five to seven years. I think Osmo, by the way, as we mentioned, is a very good example of this. Having a diverse syndicate that has different points of view to the board, even if you don't a hundred percent always agree with the other members of that board, can actually make a dramatic difference in helping the company be successful long-term. So, as I think I mentioned before we started the podcast, you know, Mark Suster from Upfront, Manu from K-Nine, and myself are the three of the board members at this company, Osmo in the educational gaming space. And the three of us just come from different backgrounds, but I think each bring useful and complimentary perspectives, you know, to help the founder promote, be successful. And I very much enjoyed that interaction. Um, and it's one of the, one of the things I've, uh, I've greatly enjoyed in the past couple of years.

AI assessment note: “Having a diverse syndicate that has different points of view to the board”

Q So in terms of starting on the sourcing of great deals, you've spoken before about the globalization of VC. What do you really mean by this, and how are we seeing a fundamental shift in mindset, do you think?

A Yeah, absolutely. So when I started in the VC industry, I guess it was 11 years ago now, I think the historical conventional wisdom at the time was that you would only want to invest in companies that you could quote unquote drive to or that were very local here to Silicon Valley. And I think that was relatively logical and empirical in that, you know, most of the big outcomes of the previous era, whether in the software, the internet, or the networking space, were all largely, Microsoft being obviously the exception, largely either on the west I think it's pretty obvious now, whether it's companies like Spotify or Supercell or Atlassian or other companies of that form, that that is now an outdated view. And I think it's simply put all the innovations that we've all spent time on, whether it's broadband telecoms or mobile or the ability to do distribution over the internet, whether it's through search words like, you know, AdWords or Or social distribution through Twitter or Facebook. It allows companies to start far from Silicon Valley and actually, in many cases, grow to multi-billion dollar companies not based in the Valley. And so I think it's a true renaissance that's been happening of Silicon Valley going from being a physical place to being, in some cases, an entrepreneurial mindset that's not physically based here. And so I think broadly, it's a very positive and good t…

AI assessment note: “Silicon Valley going from being a physical place to being, in some cases, an entrepreneurial mindset”

Q You mentioned the two different elements of the fund structures there. I'd love to discuss the two different elements of decision making with regards to initial investment to follow on. How do you think about reserve allocation with Excel, and what's the thought process around allocating reserves effectively? How does that look?

A Right. It's not obvious to me we necessarily do it all right, but I'm happy to describe what we do, what we do do. You know, of course, things are often very cycle dependent and company dependent, but I would say when you do an early stage investment, On average, we at least reserve an equal amount of capital. So if you put in an eight million dollar series A, one might reserve eight, 10, eleven million dollars, you know, for follow-on rounds to support the company as it grows. I would say that ratio decreases the later stage one is involved as you spend those reserves. Obviously, if you were to do a series B or a series C as the initial investment, you know, I would say that ratio declines somewhat as the company moves further along. Historically, 10 years ago, when I first came to Excel, I would say, historically, we would do the standard pro rata or slightly below pro rata as our standard way of following on to any of our early stage investments. I think that mentality has changed in a smart way, meaning we can actually see the companies that have the chance to scale to these multi-billion dollar opportunities, and it is just illogical that we wouldn't use those investment opportunities to then do pro rata or, in some cases, super pro rata behind these growing investments. Qualtrics that we've spoken about a couple of times here is a good example of that, where we invested p…

AI assessment note: “when you do an early stage investment, On average, we at least reserve an equal amount”

Q I'm interested. You said that a lot of companies scale maybe too early. I'd love to hear your thoughts on a time where you've seen a mistake being made with regards to scaling time, and what were the big takeaways for you?

A Right. This I'd point to, you know, many of my own personal mistakes. If I were to go back to my time before Excel, my open wave systems, you know, the fundamental landscape in telecoms was changing right as we were trying to make a transition ourselves, and we were continuing to invest in technologies selling to the big carriers and telcos, which were really starting to go away as key players in the market. If we had taken the time to think carefully about who our customer base should be, you know, we could have built technologies like Skype, like Twitter, uh, as opposed to just continuing to build technology, selling to Orange or Singular or Nextel or AT&T, the customers of that time. And so I think that was a example where we both, in some cases, were successful too quickly. And so the company scaled so quickly that we were trying to build our entire business on that one customer base versus diversifying and looking at other customer bases or other value propositions, which was a missed opportunity on, certainly on my watch.

AI assessment note: “the company scaled so quickly that we were trying to build our entire business on that one customer base”

Q I'm so glad you said about kind of benefiting from others in the portfolio in terms of scaling. It leads perfectly to my next question, which is actually from Manu Kumar at K-Nine, who says that, you know, you've seen many incredible companies go through the scaling process. How do you decide when's the right time for a company to scale? Let's start on that.

A Sure. You know, I think it's pretty basic in terms of the question of when do you start pressing on the gas pedal or not. It relates to the simplistic and straightforward points around value prop market fit and the proof of unit economics and the Belief that one can start to see the scalability of those unit economics. In general, I think most companies, especially in a capital rich VC environment in Silicon Valley, most of companies are largely make the mistake of stepping on the gas too quickly. And I think wasting precious capital or founder dilution, depending which way you want to look at it in a way that's unnecessary. So I think most companies will know if you have the discipline and patience of when you're starting to see repeatability and that repeatability is the time to step on the gas.

AI assessment note: “repeatability is the time to step on the gas”

Q So let's start with your favorite book and why. What should I read on the next plane ride?

A My favorite book is The Big Short by Michael Lewis. The reason why I really enjoy that book is, first of all, I've enjoyed Michael Lewis's writing all the way back to Liar's Poker when I was I guess still in college, you know, back when you first wrote that, but I really like when you read the big short, it's a great discussion about how to perceive something that's different than the conventional wisdom. And I think, of course, the wonderful story there is how few people saw what was happening and the mania of the crowds in terms of bidding on mortgage backed securities. And how do you recognize when you're in that bubble and how do you recognize how to get out of the conventional wisdom of what everybody else thinks? Because fundamentally, I think what we partially do as venture capitalists is, you know, riding the up cycles and riding these secular waves of technology. But of course, the great money and the great upside can be made also from trying to figure out where everybody else is wrong, where the conventional wisdom is wrong. And so that's what I really like about, you know, that, that story of the big short.

AI assessment note: “My favorite book is The Big Short by Michael Lewis.”

Q and B from my analysis. So talk to me, being too late to not be price sensitive, like the first checks, and too early to be overly price sensitive, how would you respond to, say, Peter Fenton on the show, who said never turn down a company based on valuation, it's a mental trap. How do you think about price sensitivity and your feelings towards it when making those deals?

A Well, I would say I mostly agree, but not completely. I mean, I think certainly at the early stage, you're purely, you're betting on team. I see that the company called Mopub, there were a couple of engineers and product managers that came out of a previous investment, AdMob, and so they were, you know, entrepreneurs that completely understood the category they were working in, had a authentic understanding of the problem still to be solved. That was one where you were purely betting on team, and it really wasn't a debate about your valuation at all. That is also true of companies being pricing Insensitive and not worrying about that too much. It's also true of companies that you believe have some unbounded or uncapped upside, and we'd like to say that all companies do, but the reality is not all of them have that truly uncapped, unbounded upside. So, a company like Atlassian, I think we were not on the low end of how we put in our term sheet in terms of the valuation that we ascribed to Atlassian at the time. That said, I think there are other companies that the category or the nature of the competitive set, you have to have some amount of Price discipline in order to achieve true good returns. And I think those are in categories that you, there's just simply not a completely unbounded upside is where you have to be somewhat price conscious. That is largely true of almost ever…

AI assessment note: “Well, I would say I mostly agree, but not completely.”

Q So in terms of starting on the sourcing of great deals, you've spoken before about the globalization of VC. What do you really mean by this, and how are we seeing a fundamental shift in mindset, do you think?

A Yeah, absolutely. So when I started in the VC industry, I guess it was 11 years ago now, I think the historical conventional wisdom at the time was that you would only want to invest in companies that you could quote unquote drive to or that were very local here to Silicon Valley. And I think that was relatively logical and empirical in that, you know, most of the big outcomes of the previous era, whether in the software, the internet, or the networking space, were all largely, Microsoft being obviously the exception, largely either on the west I think it's pretty obvious now, whether it's companies like Spotify or Supercell or Atlassian or other companies of that form, that that is now an outdated view. And I think it's simply put all the innovations that we've all spent time on, whether it's broadband telecoms or mobile or the ability to do distribution over the internet, whether it's through search words like, you know, AdWords or Or social distribution through Twitter or Facebook. It allows companies to start far from Silicon Valley and actually, in many cases, grow to multi-billion dollar companies not based in the Valley. And so I think it's a true renaissance that's been happening of Silicon Valley going from being a physical place to being, in some cases, an entrepreneurial mindset that's not physically based here. And so I think broadly, it's a very positive and good t…

AI assessment note: “Silicon Valley going from being a physical place to being, in some cases, an entrepreneurial mindset”

Q To what extent do you define repeatable? Is it kind of continuous for a couple of months? How do you gain comfort in seeing those repeatable revenue streams and cycles?

A Generally, I would say, you know, on median, it's a couple of quarters, three to six months of repeatability, and more important than just the time dimension is whether you can see the, you know, the atomic level of the unit economics working. It's very powerful. For example, if you can start to see an expansionary cohort of either usage or Dollar expansion. Once you've acquired a customer, it's the metaphorical land and expand success, and so I think while every situation is slightly different, there are certain magical moments you look forward to see that while the core unit economic is really starting to work, and I think that's the time you really want to pour on the gas.

AI assessment note: “on median, it's a couple of quarters, three to six months of repeatability”

Q I'm intrigued. In terms of Excel's portfolio, there's a lot of companies raising big rounds and a lot of exciting opportunities ahead. How does that internal decision-making look in terms of allocating dollars into the highest performing companies? What does that look like?

A Just like everything in hopefully good, healthy partnerships, there's a fair bit of debate about all of this. You know, there's times that we certainly have debates about, is there a good opportunity to exit if there's a, at least part of our position, if there's a huge round. And then similarly, you might have part of the partnership arguing, this is one of those unique special companies. So we look at all the opportunities that are out there investing in this round, even though we already own a substantial percentage, might be one of the best investment opportunities we would see. So there's often never consensus, and we often Debate this quite vociferously. That said, if you were to take an objective assessment across the Excel partnership, we all know who the top 10% companies are and which ones are quote unquote special. And so I think those are the ones we try to direct a chunk of our follow on dollars towards, as opposed to just spreading it peanut butter across, you know, everything in the portfolio. I think this is a still a working process for our firm as, as well as others, but you certainly, we're not sure we have it completely right, you know, ourselves today.

AI assessment note: “we all know who the top 10% companies are and which ones are quote unquote special”

Q I'm so glad you said about kind of benefiting from others in the portfolio in terms of scaling. It leads perfectly to my next question, which is actually from Manu Kumar at K-Nine, who says that, you know, you've seen many incredible companies go through the scaling process. How do you decide when's the right time for a company to scale? Let's start on that.

A Sure. You know, I think it's pretty basic in terms of the question of when do you start pressing on the gas pedal or not. It relates to the simplistic and straightforward points around value prop market fit and the proof of unit economics and the Belief that one can start to see the scalability of those unit economics. In general, I think most companies, especially in a capital rich VC environment in Silicon Valley, most of companies are largely make the mistake of stepping on the gas too quickly. And I think wasting precious capital or founder dilution, depending which way you want to look at it in a way that's unnecessary. So I think most companies will know if you have the discipline and patience of when you're starting to see repeatability and that repeatability is the time to step on the gas.

AI assessment note: “relates to the simplistic and straightforward points around value prop market fit and the proof”

Q I'm intrigued. In terms of Excel's portfolio, there's a lot of companies raising big rounds and a lot of exciting opportunities ahead. How does that internal decision-making look in terms of allocating dollars into the highest performing companies? What does that look like?

A Just like everything in hopefully good, healthy partnerships, there's a fair bit of debate about all of this. You know, there's times that we certainly have debates about, is there a good opportunity to exit if there's a, at least part of our position, if there's a huge round. And then similarly, you might have part of the partnership arguing, this is one of those unique special companies. So we look at all the opportunities that are out there investing in this round, even though we already own a substantial percentage, might be one of the best investment opportunities we would see. So there's often never consensus, and we often Debate this quite vociferously. That said, if you were to take an objective assessment across the Excel partnership, we all know who the top 10% companies are and which ones are quote unquote special. And so I think those are the ones we try to direct a chunk of our follow on dollars towards, as opposed to just spreading it peanut butter across, you know, everything in the portfolio. I think this is a still a working process for our firm as, as well as others, but you certainly, we're not sure we have it completely right, you know, ourselves today.

AI assessment note: “those are the ones we try to direct a chunk of our follow on dollars towards”

Q Speaking of kind of identifying those really special companies, around them there's always an intense amount of competition, and one element that, that kind of affects your ability to get in is that competitive landscape. So I'd love to hear your thoughts on competition dynamics in the Bay today, and how do you think about staying relevant with the progression of time and the entrance of new funds?

A Right. I think all of us in the industry talk a lot about, you know, how do you find the signal out of the different noise that's out there and the volume of deal flow? You know, one of the first ways we do it is By not only focusing just in the Bay Area, as we talked about earlier, the fact that one can take advantage of the global nature of what's happening in entrepreneurship means that if you actually spend your time in Salt Lake, in Austin, in Dallas, in Seattle, other markets, and then of course, internationally, whether it's Finland or, or Australia or other markets, there actually is less noise in those areas relative to the amount of interesting companies that can emerge. So one of the ways to help reduce that to improve our focus is Is to look at areas where others are not, and those geographies are one example. You know, the second, probably heard this from multiple Excel people, is that we have this internal phrase called the prepared mind. It comes from Louis Pasteur, quote, you know, chance favoring someone who has a prepared mind. It's just an internal way of saying having a thesis inductive-based approach is another way to sort out what's interesting from all the different deal flow and activity that's out there. And I think we do practice this Quite well internally, whether it's around the API initiatives or around enterprise software, we've been able to build …

AI assessment note: “to look at areas where others are not, and those geographies are one example.”

Q I'm intrigued. How do you think about, you know, a GP and Excel? How do you think about it Effectiveness of GP time when building those relationships, and what makes one highly worthy of that time, and another not so worthy?

A Right. The internal joke, I suppose, that we sometimes say internally, or that I say internally, is that the longest flight you'll ever take is to the deal that's not working, or that it's not special. And the point being, whether it's just down the street from you, or whether it's 14 hours away, of course, in our business, what matters is the unique or special company. And even if it takes 12 hours or 14 hour flight to Find it. I think I'd far rather spend that time than to spend all your time reacting to the noise. This is easy to say and hard to do, but to the degree that you can divine out what you think is a special or interesting company, recognizing that we'll be wrong a substantial percentage of the time, trying to have that high bar, that high standard is where you should spend 90% of your time, even if that company you identify as a long ways away from where you work or where you live.

AI assessment note: “what matters is the unique or special company”

Q I'm intrigued. How do you think about, you know, a GP and Excel? How do you think about it Effectiveness of GP time when building those relationships, and what makes one highly worthy of that time, and another not so worthy?

A Right. The internal joke, I suppose, that we sometimes say internally, or that I say internally, is that the longest flight you'll ever take is to the deal that's not working, or that it's not special. And the point being, whether it's just down the street from you, or whether it's 14 hours away, of course, in our business, what matters is the unique or special company. And even if it takes 12 hours or 14 hour flight to Find it. I think I'd far rather spend that time than to spend all your time reacting to the noise. This is easy to say and hard to do, but to the degree that you can divine out what you think is a special or interesting company, recognizing that we'll be wrong a substantial percentage of the time, trying to have that high bar, that high standard is where you should spend 90% of your time, even if that company you identify as a long ways away from where you work or where you live.

AI assessment note: “what matters is the unique or special company... spend that time than... reacting to the noise.”