Lessons from Investing $2BN and Returning $8BN in Cash

It was great. I was thinking this is a PSA for anyone who visits London. You give the most enchanting walking tours of this place. Like, some might say romantic, just, like, incredibly beautiful. Such appreciation for the history of this thing, so thank you.

But we we were able to talk about my wife in that moment, which made it feel better.

to be? So we aspire to be a thesis driven firm. Before I even joined Emergence in 2014, in 2013, the firm had developed a thesis around the fact that there was an opportunity to replace WebEx. That WebEx was a tired product that didn’t wasn’t very good. In fact, when I was interviewing Emergence, the case they gave me to interview Emergence was for a company called Fuse. Fuse was video conferencing software, an early competitor to Zoom. I And was supposed to diligence that case and then make the recommendation should or shouldn’t invest, and they were gonna hire me based upon that.

Ultimately concluded we shouldn’t invest, made that case. Fortunately, I made the right call. That was also the decision they made. They hired me. Fast forward a few months, I joined the firm, and the very first deal that we’re pursuing where I’m tapped to lead diligence is him. So the good news was we had a prepared mind around the space. We also saw incredible early product led growth. The company was around 2 or 3,000,000 in revenue, was growing very quickly, but obviously very, very early. And we believed in Eric.

Eric was the VP of Engine at WebEx before, so knew a lot about the space. And he’d rebuilt the core technology called the codec and it worked really, really well. My partner, Santi, who ultimately led the deal, is from Argentina and he used the product to call his parents or to call his family back in Argentina and discovered like, Hey, this thing works way better than everything else in the market. This codec is real. We should take this really seriously. And we paired that with the growth and we’re like, Let’s dive in.

However, the deal was not straightforward. The reason the deal was not straightforward is it was going to be the largest check we’d ever written at amongst the highest prices we’d ever paid, and the company was incredibly early. So for context, it was gonna be a $20,000,000 check out of a $250,000,000 fund, which which is a lot of concentration. That’s a lot of concentration for people. That’s, what, 8%? Yeah. It’s huge. That is huge. It was gonna be priced at $200,000,000 post money valuation. And this, again, remember the company was at around 2,000,000 revenue.

And this was 20 peaks 14 revenue. In 2014. But This wasn’t 2021 peaks. This was pre AI, all the rest of it. But we really believed in the thesis. We believed in Eric and the the product led growth was really strong. Even though it was early, it was super strong. So I’m tapped to lead diligence, but the numbers are really gonna matter here just because of the scale of this decision. I flew out to Boston because I was visiting my then girlfriend, Danny Hertzberg, who was an employee at HubSpot at the time.

And I’m sitting in the HubSpot cafeteria frantically trying to build the financial model for this company to justify the investment. Brian Halligan walks over, who’s then the CEO of HubSpot and gives me a hard time. The first time I met him, that added to the stress of the whole experience. I don’t have a background as a banker. I was an operator and a consultant before, so I didn’t really know much about how to build a financial model. So I’m stressed out trying to build this thing, trying to make the numbers tie, and some numbers just won’t tie, specifically the churn numbers.

So Eric had given us a bunch of churn data on his business, and I was trying to figure out how that ticked and tied with the numbers that I was calculating. It was just off. Fortunately, the way our firm operates is a fairly collaborative approach. So I reached out to my teammate, Joe. Joe, who has a private equity background and was a math Olympiad child kid. And I was like, Help me. And Joe dove in and figured out that the numbers that Eric had given us around the churn for the business were wrong.

Eric himself was miscalculating churn. Specifically, he was counting upgrades from, you know, low tier to high tier as churn. He was counting pausing as a churn. He was unnecessarily burdening the business with churn. Eric thought the business was worse than it was. This is the only time in my venture career where that has been the case when you dive in and discover that the founder actually doesn’t know how good his business is. So we go to Eric and we say, look, we found this. The business is actually better than you think.

This was sort of an interesting choice because we did this before we had finalized negotiations. We gave him more leverage, but we thought it was the high integrity thing to do. Eric realized that and was like, I want to work with you. So we signed the deal. We were the first institutional investor. Life changing.

It was competitive. It was competitive both because there was early growth, but also because the company was profitable, and so we didn’t have to raise capital, which is part of the reason why the price got as high as it did. Ultimately, I think the reason why he chose us is because we committed to him that we would help him build out a proper enterprise sales motion on top of his product led growth motion. I think that’s a really important point, which is as exciting as bottoms up PLG is, all PLG companies eventually need to layer on enterprise software motions to be sustainable and enduring.

And Eric, while he was great technologically, didn’t know to do it. So we committed to helping him doing it. We hired a guy named Dave Berman after we made the investment from RingCentral, and we built out a proper enterprise sales motion, and the company’s off the races.

I think the reason why a founder chooses a VC is because they believe that you’ll help them bend the odds of success on the journey. It could be in helping them with something like go to market. It could be them, you know, helping bring them people to hire. It could be helping with advice. It could be because you’re a great therapist to the founder. There’s lots of ways where you can help bend those odds. Ultimately, that’s why someone chooses you because you need a reason. Right?

You need a reason to be chosen. I agree that in general, if the founder doesn’t need to rely on you a lot, that’s great. But the reality is the odds of success of these things are so low that if you can even bend the odds of success incrementally, it matters a lot. Was Eric good at sales? Eric was not an experienced salesperson. Wow.

Yeah. So the reality is I don’t think any venture firm makes all their money on prepared minds. I just think that that is bullshit. I do think because I’ve lived it that you can have a prepared mind and it can help you get there sooner or faster than others. I mean, the Zoom case, it’s a great example. They literally gave me my interview case on a competitor. You must have just been like,

Yeah. So, when we got the real thing, I like, Oh, great. I’ve already studied for They basically gave me the test before the test. So, it is true. We have had prepared minds, but sometimes it’s not always obvious. In the case of Chorus, for example, so chorus.ai is that was an early competitor to Gong that was acquired by Zoom info for a little less than $500,000,000. We led the seed round. We were the the early investors there. It was sort of the first voice AI company.

We had some prepared minds around like, we thought voice would matter. My partner Gordon really thought voice would matter in the enterprise, but we didn’t have like a full conception of what was going on. We just liked the young founder. We thought there might be something here. So we made the investment. Ultimately, it grew nicely and was acquired a little early, but it was acquired for a nice outcome. And that helped inform a broader thesis that we’ve since developed around voice AI. We made a bunch of investments in Bland and Regal and Assembled and a bunch of vertical specific ones as well.

So I personally, I think we more broadly develop prepared minds from the portfolio company investments we make. Like, what is the thing about what’s happening at Chorus that informs a broader thesis beyond the sales specific use case that Chorus was focused on that could help inform how we invest more broadly?

We made I forgot the specific multiple. Was definitely more than three x in that one. I don’t remember the specific number, but I think it was north of five x. The challenge with that is when you have a fund that’s of a certain size, even if it’s a 10X, it’s still not going to necessarily move the needle. That fund, I believe was fund three, which is the same fund that has Zoom. It’s the same fund that has some other really large outcomes. And so that fund is already at a, I think it’s a 16 times DPI.

Even with a 10x on the Chorus investment, it’s not necessarily

the most of it, but what’s interesting is that fund also had sales loft. It was the highest multiple ever paid by private equity for a software company. Companies acquired for $2,300,000,000 and we were the Series A investors there. So that was a very good outcome, but that turned returned the firm the fund a few times. I can’t remember how many times it returned it, but Zoom returned

out, it would still be a top decile fund.

Because of Salesloft, because of Chorus, and there’s a bunch of others. And there’s some that there’s still a bunch of their gestating. There’s companies like DroneDeploy and others in that company. We just had a big crypto outcome in that company called Zappo that just distributed large multi billion dollar distribution.

Yeah. I think you can make money both ways. So let’s take the winner take all market. So network effect businesses generally, obviously, winner take all. In our experience, we invested in a company called Doximity, which is like started as LinkedIn for doctors. Are familiar with this one?

Yeah. It’s crazy. So we led the Series A there. My partner Kevin led that Series A. Kevin’s still on the board there, and that company is just absolutely hitting and it continues to hit in the public markets, like read up on it. It’s amazing. That’s a winner take all business because it’s LinkedIn for doctors. And so having, you know, a number two there doesn’t make any sense. So that investment, we definitely underwrote to that and it worked. But let’s take the Bolt lovable like that dynamic that we were talking about last night.

For folks who aren’t aware, these are companies that help you build web apps with no coding experience. So you can go to bolt.new and you can write, build me a website for the new 20 VC product and have it blue and put these buttons here and make it do this, this, and this, and then it just happens. It’s kind of astounding how easily it happens. And it puts a lot of questions around what are the knock on effects of that in our economy. But those businesses will clearly disrupt the Squarespace and the web flows and the etcetera, etcetera, etcetera.

And what’s fascinating about that space is that there are many, many very large players in the incumbency, which supports the fact that there could be multiple large players in this next generation as well.

Yeah. What happens? There will be consolidation. There will be private equity. And there will be a few that that reinvent themselves. There will be a few that are nimble enough to figure out how to adapt to the new era, but I think most will get consolidated. Do you think we overestimate private equity as a savior? It’s a really good question. Savior’s too strong of a word because most private equity outcomes don’t generate incredible returns for the VC. So savior is not the right. It may be savior in the sense that, like, we’d get your money back.

The SalesLoft outcome was an awesome one, but that was an exception where private equity is willing to pay whatever 20 times ARR. But most cases, they’re paying whatever three to five x. So it’s a different thing.

Yeah. Again, some of these companies, like, catch a second wave. And we talked last night, we talked a bit about, like, what about the even smaller ones? The ones that are at, 5,100,000,000 ARR? This is what really worries me. If funded in the last five to seven years. Yeah. What happens to those? I think all of those companies are in this existential moment to figure out, okay, what do I do? How much do I invest in agents? Real is it gonna be? Are my customers gonna adapt it?

How complimentary is that to my core product or am I just kind of, you know, shouting in the wind? And the honest truth is most of them aren’t gonna make it, unfortunately. Do you think they are structured for embracing the next wave of AI? Some of them are. So I work with one called Guru, which is a knowledge management software company. Rick. Rick. I spoke to him before this about you. Rick is a god. He said you’re a dick. Rick is like is one of the most amazing human beings I’ve ever met.

He looks like Jesus. He looks like a savior, actually, if you look at a picture of him. But we led Rick Series A probably in 2016. So I’ve been on the board there for almost a decade. And, you know, it’s a knowledge management product that grew really quickly. And then during COVID, you know, started to stall a bit. And to Rick’s credit and his executive team’s credit, they realized as AI started to pop up, if I pair a knowledge management tool with generative AI and build generative AI enabled search and offer both knowledge management and an AI enabled search product together, that’s a very compelling offering.

They’ve done that and now growth has reaccelerated. Through the journey, he did have to restructure the company, right? So he cut the company. I think now we have like 60 employees or something, but he’s doing that profitably and growing quickly again. So in some ways, these moments actually make the business

other fast growing players represent is market pull. Right? It’s that the the buyer wants this. And so the burden on a company like Guru is to figure out how can I offer something that is different than what those players have, but still tap into that market pull? In Guru’s case, it’s we have knowledge management and the AI enterprise search. In Glean’s case, we’re AI enterprise search only. And there’ll be a bunch of people who just want that, and there’s a bunch of people who just want this.

know your winners when you have them? So it’s not always obvious. And there’s a lot of humility, I think, that is important in this industry for lots of reasons, but that’s one of them. So bill.com, been around for a while. We were one of the earliest investors in that company as well. And that was not a straight into the right company. So it grew nicely before the financial crisis. Financial crisis happens and the business starts to stall a bit. But then we help them figure out the channel partnership strategy.

For them, partnering with banks, I think specifically Bank of America was the first one that unlocked, really accelerated that business to figure out like, Oh, we can sell through these banks whereas low ACV products. Doing traditional go to market can be expensive. If we find a channel partner, the whole thing can work. And that business absolutely took off and has been an amazing winner since then. That’s a great example of one that like wasn’t necessarily like this. It’s kind of like this and then this and then this.

That is very possible. And that company made fund one for us and that that’s part of the reason why that fund is so good. That’s one example. I think another example that comes to mind around this humility point is a conversation I had in 2015 with a peer investor at another firm. I remember he came to my office and he said, I just made my career defining investment. And I was like, Oh, please tell me what it is. And he goes, Zenefits. This is a moment, obviously, where Zenefits was on an absolute tear.

I

He poured a ton of money in. And he was my tenure, I think it was a principal or something at the time. So, really putting your neck on the line to really put a lot of money into it. He was like, I just made, know, this is gonna be it. And to be

Parker, AI is and was amazing. Parker’s a monster. Like, there wasn’t a bad bet. Obviously, things happened to that company that made it not a successful outcome. We had just invested in Gusto, which was a competitor that was growing not quite as quickly as Zenefits. But the reality is Gusto has endured and become a massive company and Zenefits didn’t. Now Parker went on obviously to build his own business that’s doing quite well now as we all know. But the broader point is just because something is a breakout right after you invest or early on doesn’t guarantee that it’s gonna win.

The breakout can indicate market pull, which is the most important thing of all, but it doesn’t necessarily indicate an enduring company.

You want people desperate for your product. That’s something that is so overlooked when someone’s starting a company. I think particularly when someone’s starting a company because they want to start a company, not because they’re trying to serve a specific need. You want people who have tried desperately to solve this problem themselves. It’s not a desperate problem if someone hasn’t, if your buyer hasn’t tried to hack together something on their own to solve it or if they haven’t bought an inferior product to solve it or if they’re not spending countless hours themselves dealing with it.

Otherwise, it’s nice to have. So, you need something that is just like, Oh my God, this is a massive problem I need to solve. How

on a B2B company? When you talk to users or prospective users, when you talk to users of the product, the things I wanna hear are things like, if my boss stopped paying for this, I’d quit. Or if my boss stopped paying for this, I’d pay for this out of pocket. When you hear phrases like that, know, like, holy shit, this has changed someone’s day to day life. There’s real market pull for this.

in. Right? So like, if you were to ask me to rank, you know, founder versus market versus traction, hypothetically Yeah. The first one is market pull. Like, that is the most important thing, I think, when you’re evaluating a potential investment or starting a company. The second is the founder because it’s the founder’s job to figure out how do you build something defensible in that world of market pull. It’s not enough to just build something obviously without that’s just tapping into the the zeitgeist. And that’s particularly true with a lot of the voice AI companies that are coming out right now.

There’s a lot of market pull for those companies, but their job is to figure out how they can parlay that landing wedge into something more durable. And different companies have different strategies for this. To go back to the Bolt example, the thesis we underwrote to is that Eric and his team had built this technology called Web Container that allows you to host a web app dynamically in a really robust way, and we thought that was going provide some defensibility to the business. It’s still very early, so we have no idea how that’s going play out.

But I think when you’re making investment, you have to have a hypothesis about how the founder is going to build defensibility if he or she hasn’t yet done it.

that there actually wasn’t? Oh, I’ve got a good one. So we made an investment during COVID in a company that helped exercise instructors go out on their own, like, and build their own thing outside of their own, like, thing. You’re you’re laughing because I’m gonna be honest. I

reveal something here. My mother is a jazzercise instructor. You know what that is? I I I take it. It’s like jazz is a sport. It’s kinda like jazz is sport. It’s jazz is dance. Yeah. So this is this was a huge craze in the eighties in in The US. It was, you know, dancing and aerobics combined.

I didn’t know. It’s it’s kind of like that. And my mom has been teaching this since before I was born, and she’s still teaching it. The woman’s almost 70. It’s amazing. So I have a soft spot in my heart for aerobics instructors in general. But the thesis was during COVID, everyone’s working out from home and these people need a business in a box to help them run their own show so they can do it on Zoom, etcetera. And the reality is there was market pull briefly for this product.

And then when people went back to more normal life post COVID, you know, the gym teachers often went back to the gym. And so there was less market pull.

It was a Series A. I think we put in like nine. Ended up getting most of the money back because the founder, to her credit, realized when the market pull declined and shut down the business

So if you think about this more broadly as a creator economy tool, if like you think that there’s gonna be more Harry Stebbings in world who are 16 in their in their rooms who figure out, wanna start my own business, and you provide a business in a box for them, that’s potentially interesting. There will not. There will not. There will be no more Harry Stebbings. I will crush them.

Yeah. That was the thesis. I mean, remember in the peak of COVID, you were making assumptions around how the economy would look going forward. And the reality is it’s hard to forecast. And there was a world where people would be remote, you know, indefinitely and we wouldn’t be back in, you know, more concentrated areas. And we made some bets that focused on that the future. We made some bets that focused more in office future. That’s our job is to call the future.

They are not always expensive, but they are often expensive. So if I look back at our portfolio, Gusto was expensive, Zoom was expensive, Yammer was expensive. Ironclad was expensive. But some of them weren’t. Veeva wasn’t expensive because that was non consensus at the time. SalesLoft was also non consensus at the time and was not expensive. More recently, my partner, Lotte, led an investment in a company called Federato, AI software to help insurers underwrite better, but she made that investment before the zeitgeist, before people were like, Oh, this is obvious and this is gonna happen.

And to her credit, there was a lot of, you know, questions and she pushed through and she got that deal done and she got it done at a pretty good price. And then the zeitgeist hit, and the company of the series beat at much higher price. So I do think that it is possible still in this world to be non consensus and right and get a good price, but it is also true that there are increasingly higher, you know, more and more and more consensus deals, and you wanna be in you wanna be in both.

No. I don’t think so. Veeva wasn’t competitive. There is still a world where you have a unique insight that other people don’t believe in, and or you get to the person first where you can have a better deal. Most of them are competitive.

the framework we use internally to figure out if we should do the investment, it’s called what you have to believe. The framework basically means you try to identify what are the three to five things that are specific to this deal that you have to believe for this investment to return the fund. And there’s a bunch of things that go into that. Like, you think of it, if you unpack that, there’s things like dilution. How much additional capital will they have to raise? Will the founder be able to raise that capital as well?

There’s obviously questions around defensibility, there’s questions around market, there’s questions around competition, there’s questions around team. Like, and all those questions depend on the company. So when we do the analysis, they’re always unique to the investment opportunity and to the fund we’re investing out of. So when we’re doing diligence, what we’re trying to do is identify what those three to five what you have to believes are specific for the company. So you

After you have the pitches, like after you’ve spent some time with the founder and you’ve looked at the materials, you have some hypotheses as to what those could be, and then as you’re doing the diligence calls and doing the actual work itself, you’re refining them, And importantly, you’re gathering the data to help support or negate each what you have to believe. So every diligence exercise results in a chart. And the chart is what are the three to five what you have to believes? What is the data supporting this what you have to believe?

And what is the data negating this what you have to believe? And then we can all stare at this and say, on balance, do we believe it?

Yeah. Well, it’s it’s important to understand that in the context of Emergence and how we operate. Yeah. So we’re a focused firm, we’re and focused in three ways. The first is in what we invest in. The second is in terms of how we invest, which relates to this question, and the third is how we grow our people. On the what we invest in side of things, all we do is B2B software. It’s all we’ve ever done. It’s all we ever will do. The first investment twenty years ago was Salesforce.

Then the vertical SaaS thing happened. We did Veeva. Now the AI’s thing’s happening. We did Together and, you know, Bolt and Bland and Unify and a bunch of others. So we’re very focused thematically, and all of us just do that work, just just focus on B2B, which means we are uniquely able to invest collectively as a team and have everyone do the work. So on the the how we invest, how we’re focused side of things, this is where this comes into play. Every partner on average makes one investment per year.

So we are super focused in terms of the amount of investing we do, which is obviously very high risk, but it’s high conviction. And if it wins, it returns the fund many times older, which we’ve had, you know, lucky to do with the number of funds. That approach allows us to work collaboratively as a team when you’re only doing, you know, a relatively small number of deals. And the reality is like this has this has largely worked. Like, goal is to

Yeah. It’s a hard job. It’s a hard job. And it’s an average. Sometimes it’s two, sometimes it’s zero, etcetera.

Potentially. Yeah. I think the good news is we’ve expanded our partnership, so we now have seven partners, and so we have more shots on goal. We have, like, when you think about it, less about me as an individual, just more as a firm. We’re taking a little more shots, which I think helps us with the averages. But the reality is, like, it’s been But you’ve

No. What you mean is I’ve never none of my deals have ever gone to zero. Sorry. None of your deals have gone to zero. That’s that’s correct. Yeah. That does mean I haven’t taken enough risk, that’s something I talk about with my partners a lot. Some of them may still go to zero, but you’re right. I think part of it is we’re investing in B2B software businesses that have recurring revenue models, and so in general There’s relative downside protection.

And assuming I and we have done the diligence well. Yeah. And also like back to the bend the odds of success, like I genuinely believe this and some other VCs more skeptical will doubt me on this, but like our job by making few investments and by having everyone involved in the investment means all of us do

Yeah. Yeah. So let me explain the diligence process, but let me just finish that last thought. I I really do believe this this helps change outcomes. Like, so we just raised our new fund and as part of that, we did this analysis on how have our deals fared, in terms of, like, certain graduation metrics relative to market. Nine out of 10 of our deals, our early stage investment, seed series A, have gone on to raise successful fall on rounds. One out of five have gone on to raise rounds at north of $1,000,000,000.

One out of 10 of our early stage investments have gone public. So we’re good at picking, and I also think we’re good at bending the odds of success. And I think part of it comes back to this model of the fact that we do the work together as a team. And so back to your question, the way we do the work together as a team, we have the founder come in and present to our partnership relatively early in the process, and also all the partners get to know the person, the founder.

And then we have this discussion afterwards, like, is this something that we’re excited enough about to make a priority deal? And those are holy words within Emergence. When you say the word priority deal, everyone’s calendar gets blown up. Everyone’s weak. Whatever you thought you were doing, you are now doing something different. It basically means everyone is focused on doing diligence for this deal. So what it means is that for every investment we make, every partner does reference calls.

Every partner calls customers, every partner calls management references, every partner does back channel references, and many partners do on-site visits where we actually go and we spend time with the team, we see what’s happening in the kitchen, so we kind of pick up on all the less structured data points. By And having multiple people make that trip, multiple partners make that trip, you’re collecting a bunch of first party data. So that when it comes time to make the decision, when you’re staring at that what you have to believe sheet, it’s not just two people in the firm who have made this what you have to believe sheet.

Literally, everyone has contributed to that. And one person can say, you know, I heard this customer say this, and the next person can be say like, yeah, but this customer I heard in their voice, like, they sounded a little more if wishy washy. And then there is this process of seeking truth. In contrast to most firms, and I’ve worked in other places, which tends to be much more an associate and a partner doing a bunch of work and then defending their investment against an onslaught of questions and doubters, and then if you survive that onslaught, you get to do the deal.

Our process truly is a process of seeking truth collectively that I think allows us to pick better and hopefully once we make the investment help the company better.

Yeah. So there are ways in which our process hurts us there, and there’s ways in which it helps. So, So it hurts obviously because you have to coordinate lots and lots of schedules. It helps because we can do seven diligence calls in the same slot. So, if you just have one person or two people doing diligence, then yeah, their calendar is booked out. But if I have seven of my partners plus principals and senior associates and so it’s everyone working on this, you can do an incredible amount of work in a day.

I’ve been amazed at how much work we’ve able to do in a day when you have seven people doing it or 12 people doing it, and you have one quarterback who’s the the diligence lead, which is the role I played at Zoom, pulling it all together. What it requires is trust. It basically means if I come in with a founder and you meet the founder for an hour, but you don’t know anything else about this person or the deal, you have to trust me that there’s enough there.

You are willing to blow up your schedule for the week, even though it’s not your sponsored deal.

Yeah. So, we do record the calls. We also send out really detailed notes from every conversation, and then every night, we send out an email with a summary of what’s going on. So, it’s like, here’s what we learned today. Jake did this call. Harry did this call. We talked to this customer. Here are the outstanding questions. Here’s what everyone needs to dive in on, we need help with, etcetera. And so it’s this constant stream of information that’s bookended with these nightly emails. The other thing we do is we have a lot of calls at night.

So one thing we realized is that if we’re having these diligence calls, like particularly the internal calls where we’re processing all the information, if we’re doing that during the day, they get compressed because we have 30 and we’re just getting into the meat of it in minute twenty seven and then we have to go do something else. The reality is like if you do the call at night after kids go to bed, after you’ve had dinner with someone, whatever, you have theoretically an unlimited amount of time on the back end, which means the reality is we do a lot of late night calls discussing what we’ve learned and trying to synthesize the day.

We actually still managed to do some on sites during COVID. I can tell you But you broke the law. Yeah, I know. So I’ll tell you kind of a silly, crazy story. So there was a Series A in a company called Regal dot ai. It was very hot. I think he had six term sheets from top venture firms. The company had grown from zero to, I think it was 1,500,000 in a year, which pre AI was like very, very good. And founder’s really credible, just great company.

So a consensus deal. We got to know the founder relatively late in the process, but really clicked with both of them, but felt like we needed to spend time in person to really, like, get there both on both sides. But it was the heat of COVID. So, like, you couldn’t find a way to do it. To make things worse, it’s not like, you know, they were in San Francisco and I was in San Francisco, we go to a park and, like, walk around. The CEO was in Steamboat Springs, Colorado, and I was in San Francisco.

It’s not an easy place to get So what we agreed to do, Alex Levins is his name, what Alex and I agreed to do was fly to the Denver Airport and meet in a field outside the Denver Airport and go for a long walk.

It was not raining. That would have been

the thing actually that made it worse, and you can see how fair my skin is, I didn’t put on sunscreen. So, we’re in this field and Denver’s at altitude and I didn’t put on sunscreen because I hadn’t been outside in like a year. I didn’t remember sun. And then we’re walking through, we do this like four hour hike through literally a field outside of the Denver Airport and I get completely just horribly red. Terrible. But the good thing was I really got to know Alex’s vision.

I got to really understand him as a person, I think vice versa, and we made the investment. I think the other thing that really helped with that, given that my partners weren’t able to take that same sunburn walk with me, is Alex and Rebecca, his co founder, did one on one Zoom calls with every one of my partners. And so it was like a

Yeah. There there are certain founders who aren’t looking for the product we sell. Right? We sell a low volume, high touch product. There’s some founders who really want that, and there’s some founders who are looking for a high volume, low touch product to get out of my hair. And I think the nice thing about our diligence process is actually selects for the right founders.

market’s changed. And back to market pull, there’s more market pull in general right now than there was in the pre LLM era. It’s just true. And that’s both because the LMs themselves are doing amazing things and also because everyone’s boss is saying, Go buy AI. Many of these products have tapped into these huge areas of market pull, but the reality is they still have to figure out defensibility obviously on the back end, which we touched on before.

But what that means is, yes, it is possible to grow faster and we’re seeing examples like Bolt, which went 0.20 in two months, and we’ve seen a bunch of others that like Together is a good one where we were in the A fifteen months ago, they were at 2,000,000 revenue. The business is now north of 100,000,000 revenue. These things can grow insanely quickly because there’s just such market pull.

Yeah, exactly. Seriously, that is insane revenue. It’s really good. So

Yeah. In, like, fifteen months.

That’s insane. So so what’s changed? So market pull has changed, and I think you’re right that if we tell founders that, like, the top decile is triple triple double double, it’s just not true anymore. It’s more like, you know, the great companies are quadrupling, you know, year over year. But the thing that we rooster that hasn’t come home to roost yet, which I think is, you know, I don’t know if that’s the right way to say it or not, is retention. Right? We still don’t know for many of these businesses because they haven’t had year, two, three years of, you know, retention data how that’s going to look.

And so if I were to posit a replacement for the triple, triple, double, double phrase, maybe it’s something like quadruple one twenty. And what I mean by that is, yes, you should be growing very quickly, perhaps quadrupling year over year, triple, quadrupling, etcetera, but you should also have a net dollar retention of 120% or above.

Yeah. So there’s different ways to calculate it, but in general, the way to think about it is if I had a dollar from a cohort of customers that I sold last year, then when they renew this year, they’re at a 120 they’re a dollar 20. The customers that churn from that cohort are outweighed by the customers that upsell, so the net there would be 20¢ growth.

Yeah. I think that like, if these companies prove to have net dollar retention of 120% or above and maintain this growth, these are generational companies.

I don’t know if this is a commonly held belief or not, but I, and I think we in general, are not super concerned about the margin that OpenAI and the closed source models are commanding for two reasons. One is there’s a lot of competition amongst closed source models and you’ve seen pricing decline a lot. So most of our application layer companies that are providing applications on top of these products are seeing gross margin increase over time because of that competitive dynamic. The second reason I’m not that concerned about it is open source LLMs are really, really good and getting better.

And so the reality is if you’re an application provider and let’s say for whatever reason OpenAI comes to you and says, You know what? It’s 10 times the price and that eats into your gross margin, you now have a credible ability to go and spin up an open source model and have almost no gross basically have a 100% gross margin. And that’s actually what Together.ai does. So part of the reason why they’ve grown so quickly is because companies are like, You know what? Actually, we’ll spin this up on my own.

I’ll have complete security, data privacy, etcetera, and I control my own margins.

Yeah. The clearest what you have to believe for that investment was that open source LLMs will be a dominant part of the market over time. That enterprises, that businesses are going to want to buy and use open source models and not just Anthropic, OpenAI, and the closed source ecosystem. And the reality is, we made the bet, like, that was trending positively. I think it’s trended more positively, but it’s still frankly a little TBD.

That might be the right way to put it. So you need that’s why I use the word dominant. You need to be a dominant part of the market. It doesn’t necessarily mean it’s the majority, But if it’s 1% of the market and not 20% of the market, then the outcome looks different.

And it’s also a function of how good Together gets at helping companies spin this up. Like, how painless will it be? If it becomes really painless, that 10 could be the whole world you’re at. Do you prefer market creation, market expansion? How do you think about that? What I want so I borrow this from, Mike Maples, our our mutual friend. So I read his book Pattern Breakers, which I highly recommend. One of his core insights is that you should be looking for a business that itself has a unique insight on an inflection that’s happening.

An inflection could be a technological inflection. It could be, for example, open source LLMs are a thing. And so what is Together.ai’s unique insight on how to deploy that? And, you know, I won’t go into the specifics, but theirs is really about how you maximize inference within that context. But in Zoom’s case, obviously, you know, there was an increase in the use of video conferencing. There was distribution of mobile. You could actually run the stuff on the application, the, you know, on the computer itself, on the phone itself.

Eric had a unique insight on how to actually put the model or rather Eric had a unique insight into how to distribute this stuff with a codec, on the, on the product. It’s a long way of saying, I think in both replacement markets, which Zoom was and in new markets, Together.ai is, you can find a situation where the founder is playing off of some sort of inflection happening outside of their business and has a unique insight on how to take advantage of it. So I would use Maple’s framework, and I care a little bit less if it’s a replacement or or a new market.

On the average, I think they’ll disappoint. And And I think there’ll be outliers that are better than we expect.

Yeah. I think that there will be businesses that find some sticky wedge that enable them to endure.

So this interesting. And this is why, like, while adding AI into SaaS has differences, there’s a lot of learnings from the previous SaaS eras that we have to take into this next One of which is workflow is sticky, right? All those lawyers who, the majority of them will exist at least in the medium term, if they spend their day in this piece of software, it’s really hard to rip out. Salesforce isn’t the best CRM now, and I say that with a lot of love as that was first investment and love, love for Benioff.

The reason why Salesforce is dominant is because there are tens of millions of people that work in that thing on a weekly basis.

Well, part of it is like if you can build something that people use every single day, like if it becomes part of their the way they go about their lives. I think it’s part of the reason why OpenAI is powerful, right? Because they’ve built a little bit more on the consumer side of things, but they built a situation where like, you kind of build the muscle memory now to, like, open that app instead of Google when you’re searching.

That’s part of Anthropic’s challenge going forward. Right? They’ve got an incredible coding machine.

I can’t speak for Anthropic. And it seems like Dario is focused more on the long game of like, how do I do this AGI thing safely? And so my guess is his ambitions are focused there. But I do think that you’re going to see a lot of specialized LLMs. And I think that a lot of them will come from open source, back to the earlier point. You’re going to see people who say, You know what? I’m trying to solve a problem in the mortgage world and I’m going to build on top of an open source LLM a tool that helps me analyze and make recommendations on how to write the best mortgages in a very specific way.

And the cool thing about that, and this ties into So we had a thesis back in 2017, my partner Gordon started it called Coaching Networks, which was a poorly branded, but I think correct insight that the way AI will take place in business software is as a coach that’ll show up and say, Hey, I see that you’re about to write this mortgage. Here’s all the data you should actually be using and here’s some suggestions on how to do it. It learns on what actually happens. You write the mortgage, you don’t.

Does the person take it or not? Do they pay their loans or not? And then based upon those outcomes, it makes better recommendations to anyone else in that situation in the network. So, we call that coaching networks. The reality is Copilot is the term that took off. But what’s cool about that is it’s domain specific and if you build domain specific large language models using that data, you’re gonna have insights that even an OpenAI

this and I realise that it is a self serving take in that I am an investor who invests in B2B software vendors. And so I obviously hope that B2B software vendors continue to exist in this world. But I believe that B2B software, I believe software vendors have an important role in the future even if the bolts of the world, the cursors of the world make coding cheap, easy, in some cases free. And there’s three reasons why I think that’s the case. The first is when you’re buying software from a vendor, you’re not just buying the code.

You’re buying an opinion perspective on how to solve a problem. And that’s a really important point. Like ultimately, if there’s a software vendor who has dedicated their lives to figuring out the best way to solve a problem across a bunch of different use cases, they’re going have a lot more insight on how to solve it and they’re going to have that proprietary data, sort of like I mentioned in the mortgage use case, a closed source model is not going to have that you can’t just get off the shelf.

That’s like the first reason you’re buying it, you’re buying a opinion perspective. The second is the very factors that are making the software easier to build yourself also make it harder to maintain. Right? So, you could spin up something in Bolt or Lovable or with Cursor, etcetera, yourself and that thing becomes out of date in six months or even faster.

And so unless you have someone and, you know, some process to constantly keep it up to date, the software is out of date immediately, which is often why enterprises start with build and then go back to buy when they realize, oh, yeah, we built it, but we can’t maintain But the third and most important reason why I think software vendors still have a role in the future is because the buyer wants a throat to choke. Ultimately, when you buy something from a vendor, I am getting a guarantee that you will serve me well.

That the software will not have downtime. You’ll be there when I have questions around support, and perhaps that you’ll guarantee some outcome. And this is part starts to move into the world where, you know, software pricing is evolving and could look more like outcomes based pricing over time.

Yeah. I think there’s a spectrum of pricing. So you have the classic proceed, then you have usage models, which look like all sorts of things, and then you’ve got true outcome space. I think we’re sort of in a world right now where most of the forward leaning AI providers are experimenting with usage based. And that could be usage based obviously on, you know, how much tokens you’re using, etcetera. But it could also be if you have an AI agent, like we work with a company called Assembled in the support AI space, and they’ll charge you based upon basically how many interactions the support bot is having with your customers.

Then over time

Yeah. So, I think that the direction that this world moves over time is solution granted. I spent a bunch of time learning about the Finn approach. It’s hard for now. And the reason it’s hard for now is There are few reasons. One is back to the accountability part. It’s hard to establish causality if many support tickets, particularly higher level support tickets have multiple touches, right? Like so someone, you know, a bot touches it and then maybe a human weighs in a little bit over here and then how do you establish, you know, who was the winner?

You don’t want to create an antagonistic relationship with your buyer. If you’re like, Okay, I did all this. And they’re like, No, no, You only did some of this. I’m only gonna pay you this. And all of a sudden, instead of having like a monthly, like an easy bill, it’s like you’re negotiating every month with the customer. That sucks. I think that like over time, we’ll start to figure out some of those hiccups and bumps, but I think we’re still in kind of early land on outcomes.

There are certain situations So, the easiest form of outcomes based pricing today in AI is AI enabled services. And, this is a business that takes on the whole delivery of a product. So, they say, not, I’m going sell you an AI tool to help you do support. It’s, I’m just going to do all your support. I’ll do the people. I’ll do everything else. We invested in a company called Mechanical Orchard that does this moving mainframes into the cloud using AI. They built a tool that’s basically Cursor for mainframes, but what they don’t do is sell that tool to Bank of America and say, Hey, use this tool to move all of your use AI to move all your stuff into the cloud.

What they instead do is they sell a service. So, we say, We’re going to use this really cool AI tool we built and we’re going to move your product into the cloud. It’ll take 50% as long and will charge you only 80% as much as the incumbent. And if it doesn’t work, you don’t pay. And that’s outcomes based pricing. So if you’re moving kind of in that direction, it’s easier to establish outcomes based pricing because there’s no questions. Did you do it or did you not

pricing. So, is a really interesting question. So, if you’re pricing on labor basis, which is generally how most services are priced today, you in some ways are taking the risk upfront. Right? Because you’re saying like, okay, it’ll charge if it’s gonna take me, you know, this long, then, you know, I’ll pay you I’ll charge you this. But if you if your AI doesn’t work, then you could be in a world where your margins are really degraded upfront. If the AI does work, then you actually capture way more margins.

And so you have to be really thoughtful about how you price, and you’re basically taking a bet on yourself. Like, how good is my AI?

There’s a third category, I and don’t know how to describe it, but we talked about it a bit earlier, is these growthy stage companies.

Notions, the Ironclads, like the companies that are above 100,000,000 ARR, growing nicely, and still dynamic and young enough to make changes, but they’re not startups anymore. I sort of segment the world into those three kind of buckets, just way The over biggest thing I’ve changed my mind around in the past twelve months relates to that, to this question, which is I was fearful when the power of LMs came out that most of the value would accrue to the incumbents because of their data and distribution advantages.

What I underappreciated, which is just the recurring lesson of startups, is the value of focus. The reality is it doesn’t matter how much distribution Salesforce has, how much data they have. If you are a startup who’s just focused narrowly on solving a very, very specific problem, if you’re Unify, you know, helping with the go to market stack in much more narrow way than Salesforce is, you’re going to run just way, way faster and customers are going want your product more. We’re seeing that play out. And so the thing I changed my mind is I’m less fearful that incumbents will be able to accrue most of the value.

The reality is like it’s still early days in this game and things could change, but thus far, focus startups are outpacing the incumbents. The growth ones, it’s more of a mixed bag for lots of reasons. There’s ones that are a little more ossified and aren’t necessarily taking advantage of the stuff, and there’s ones that are still young and dynamic enough to actually pivot and take advantage of it.

Yeah. This is where I go back to solving a narrow problem. Like, start by solving a narrow problem because Google’s not gonna solve that narrow problem as well as you will, and you can expand from there. I mean, Veeva’s a great example. When we made the investment in Veeva, a CRM for pharmaceutical companies, the entire market for that was $400,000,000 globally. That’s not big enough to build a multi billion dollar business. The context Veeva today is a $35,000,000,000

That’s right. So, they obviously found a way to expand. So, they started narrowly. Yeah, they Right? And then they became the board level vendor to the world’s largest pharmaceutical companies. And that’s a really important phrase I think most startups don’t think about. How can you become so important to your customer that you’re discussed at the board level? And if you achieve that, your ability to upsell is obviously much higher. And so Veeva has now upsold all sorts of stuff to these massive pharma companies and has a $35,000,000,000 market cap as a result.

The same is true in the AI era, right? If you’re building an auto complete tool in Gmail, if it’s a horizontal tool, yeah, you’re probably gonna have your lunch eaten. But if it’s for a very specific use case and it works really, really well, you earn the right theoretically to expand to sell that same buyer some other thing. So you can use it as a landing wedge and then expand to sell something that perhaps is more defensible.

Yeah, that’s right. Particularly if you’re really good at solving a problem and if the pain point is really big, the pain point’s really big, you have customer demand for it, people are willing to pay a lot of money for it. The other thing that’s true is that in the AI era, a lot of these businesses are able to capture some labor spend in addition to software spend. And so that narrow wedge, while it may be narrow from a software spend perspective, may not be narrow from a total spend perspective.

So, what I’ve seen thus far, and it’s still early days, is that most buyers of this stuff aren’t firing people. What they’re doing is not hiring new people. And so, they’re trying to be more efficient with whatever they currently have. Like, I just invested in a voice AI company in healthcare, and we talked to a bunch of their customers. The customers were like, We love this thing. It’s amazing. And we’re like, Okay, great. How many headcount did you reduce? And they’re like, None. And I’m like, Wait, why do you love this thing?

And he’s like, Well, I love it because I’ve grown my business three times with the same headcount. And so I think right now, and I think part of it’s emotional, people don’t want to fire their people, understandably. Businesses are able to grow more efficiently than they were in the past because of this stuff, and therefore these software vendors should be able to capture some of that labor.

So I think that the incumbency advantage of Salesforce that we talked about before is very real. The fact that millions and millions of people use that product every single day, you can’t underestimate that.

such core workflows. That’s not the one I’d short. If I were to short a stock publicly, it’d be IBM. IBM still makes so much money from selling these refrigerator sized mainframes. I think the thing that people don’t realize is that 75% of the Fortune five hundred still run their core applications on refrigerators in their closet. It’s written in a language called COBOL that no one writes anymore and IBM makes a ton of money selling maintenance and new servers every year, billions of dollars every year to support these massive companies and their legacy code.

It’s been trapped on these machines And AI is, I believe, the critical enabler to get this spaghetti code into the cloud and hosted in a much, you know, more efficient manner. And so if companies like Mechanical Orchard succeed in doing that, the IBMs of the world

My guess is there’ll be a little bit of a trough of disillusionment just like there always is in technology adoption. Everyone’s trying everything right now. The good news is there’s a lot of movement from experimental budget into real budget in these enterprises, but the bad news is a lot of these companies that aren’t actually delivering and doing value are gonna get cut, and there’ll be some buyers who say, This thing didn’t work as well as I want. So I’m a little disillusioned. The other thing that could happen is there could be sort of an FTX moment in B2B AI as these agents come out.

These agents are incredibly powerful and they do things for you. They send emails. They buy things. They, you know, they can take action, which is very powerful, but with great power comes great responsibility. And it’s very possible, in fact likely, that some big enterprise is going to deploy an agent and the agent’s going to do something really bad. They’re going to send a bunch of emails to customers or prospects that they shouldn’t. It’s going to buy a bunch of things that It’s not hard to imagine what could happen.

And there could be a bit of a backlash to say like, Oh, wait. This isn’t good. We shouldn’t do it. The reality is like we do need to figure out the guardrails for these products so that they’re deployed safely.

What a transition.

We grow them from within.

So I’ll explain how most venture firms work, I’ll explain how we work and the difference. So the way most venture firms work is when you’re looking to hire investors, you hire two profiles. You hire either seasoned, often ex CEOs into the business who have, you know, presumably a great network and a great brand and what have you, and or you hire an army of junior people and you give them a checkbook and you say, You’ve got two years. Prove to me that you’re good. And the incentive that creates is those people write as many checks as they can.

Of course, that’s the incentive. And at the end of the two years, you know, one of two things generally happens. It’s almost always never enough time to really see if these investments are good or bad. And so, the person often leaves. They either leave because the firm says, These investments aren’t trending, so you’re out. Or their investments are good and the person looks up and says, You know what? If I build my career here, there’s no chance I’ll ever be an equal partner. Because that is how most firms work.

Most firms don’t have an equal partnership. Most firms have founders that retain carry after they depart. And as a result, if you’re really good and you pour your entire career into something, you make great investments, you don’t ever get to capture a portion that’s fair. And so what you’re seeing is a merry-go-round in venture capital. And what that means is that you’ve got a bunch of people that leave. They go from firm to firm or they start their own firms because of these dynamics. It is really, really bad for our founders because what happens is these founders become orphaned deals.

really It’s a big deal.

Why it a big deal, what should founders know? So, unfortunately, I’ve been part of a lot of boards now with orphaned deals where the original investor who made the investments leaves the firm and then that company doesn’t have support within that firm. So when it comes time for a new round, time comes to the pro rata, the odds that you’re gonna get it are lower. All of sudden, that founder has to start to scramble and figure out what do I do? Or a new person comes on the board who maybe is less constructive than the person that was chosen by the founder and that could have negative implications.

There’s so many ways in which the founders, you know, can feel kind of tricked isn’t the right word, but it’s like they they signed up for something that’s not what they bought. When you buy, an investor, like when you buy a board seat, you’re really hoping to buy that firm, but also that person. Right? These journeys last a decade. You’re hoping to sit across the table from that person for a decade plus, and you kind of know that’s why the the vetting process is so important, that’s why I flew to get sunburned and, you know, with Alex, etcetera.

If there’s a merry-go-round where people are leaving, it sort of strands these founders without the person that they originally wanted.

It comes down to the topic we talked about before, which is focus. So most multi stage firms treat their seed programs as an option program. They write small checks. Often, it’s their junior people writing these small checks. They use it as a way to track the company to see if it breaks out. If it does, then they try to pour in and get proper ownership. That’s the way most seed programs are run-in multistage, and it’s not great. It does provide signaling risk. It also doesn’t help the founder as much because they don’t get much love from the firm.

The way we try to do it is the same we try to do everything else, which is with focus. So when we make a seed investment, we treat it like a core bet. It’s a partner that’s doing the deal. We’re generally owning double digit percentages so that we really care. It also allows the founder to raise around from someone else if they need to because we already have our ownership. How ownership sensitive are you? It depends. It depends on the context. I mean, we try to be pretty ownership sensitive.

Will you do a deal with 8%? Sure. Mean, we did Zoom at 10%. So it’s

It comes back to that what you have to believe framework. So if you have to believe this investment will return the fund. And, ultimately, if it’s a low ownership investment, but we think this company is gonna be Salesforce, and it’s not gonna be super dilutive going forward. There’s a ton of capital going forward, and it can return the fund, then we’ll do it. This is a game of outliers, and you have to convince yourself that this one’s an outlier. I mean, you have convince yourself that all of them are outliers, but the lower ownership you have, the more the owners Do you

are true. So we’ve been around for twenty years. We have deployed a little less than $2,000,000,000 in capital. We’ve returned in cash a little over $8,000,000,000 in cash, and that doesn’t include all the private holdings, obviously, that are worth a lot more. The reality is the bulk of that $8,000,000,000 has come from a handful of companies. And so the outliers really have driven those returns. But what’s interesting, as I said before, is even if you did remove some of those outliers from some of our funds, they would still be top decile funds because of those, the choruses of the world.

They get bought for 500, but you invested the seed and so it’s still good money. What was the best fund? The best fund as far is the Zoom fund, which is our fund three.

Yeah. We sold Salesforce too early. Like, exit matters, and that’s something else that doesn’t get talked about enough in venture. I actually had this written down when you mentioned it earlier. Public sell.

it’s a really hard it’s a hard question. When did you sell Salesforce? So very early. Shortly after I went public. Yeah. It was bad. I wasn’t there for the last You were six. Yeah. Yeah. Exactly. I was young. But I was there for a lot of our more, like, when do we sell Bill? When do we sell Zoom? When do we sell Blend? When do we sell Veeva? I’ve been there for a lot more recently. Do you

Yeah, we do. We, every quarter that there’s earnings, we do an analysis that’s led by the sponsor, and in almost all these cases, we’re still on the board of the company. And so we have inside information, which is the reason why we hold the position. If we if we didn’t have inside information, we’d have no defensible reason to hold the position. But as long as we’re on the board, we have that information, you know, we can hold it. And so the sponsor takes that inside information and basically updates the partnership and says here’s what’s going on.

And then we make a decision, and because we’re on the board, we can only make that decision within a specific window after the announcement for legal reasons, obviously, of whether or not we hold, you know, sell, etcetera. In some cases, we buy. So, in the case of Doximity, you know, we were huge believers. We invested at the A, company did really well. We actually bought more at the IPO. That’s And been a great investment. We’ve already returned 3x from where that was. But it’s a hard decision because every quarter you look at it and you say, Okay, know what’s going on with the company.

I don’t know what’s going happen in the macro. There’s all sorts of uncertainty in the macro, so that weighs into it. And you do your best.

sure. The nice thing is the vast majority of our investors are big charity foundations and endowments. And these folks aren’t as concerned with any cash right now. They really want us to maximize the size of the outcome. And we’ve returned, as I said, over $8,000,000,000 on $2,000,000,000 deployed to them. And so they trust us generally. We did an analysis recently on how good we have been at the publics. Oh, what did that show? So the analysis was if we had sold all of our shares and all of our public companies at lockup, meaning like once the lockup expired, we sold it immediately.

So, that’s scenario one. Scenario two is we did what we did. So, what have we actually, you know, done so far? So, basically, our track record of selling. Which is case by case, depending. Case by case. But, like, we basically just took what we’ve done so far, like how much gains we’ve returned from those those deals. And then the last thing we looked at was what is the value if we had sold at the very peak price of those stocks, which was often in 2021. Any guesses?

You’ve got a fourth option, which is just hold in perpetuity. We could hold in perpetuity. We’ve done that to some degree. Like in the case of Veeva, we’ve distributed 90% of our position, but we still have, you know, a meaningful stake in it just because we owned 30 something percent early on. But I mean, number three, sell peak price is obviously gonna be the optimal return. For sure. But any guesses as to the swing between, like, what we’ve actually done and peak price versus what we’ve actually done and if we Sold sold,

Yeah.

the the numbers are this. If we had sold them all at lockup, we would have returned $2,000,000,000 less to our LPs. What’s interesting, and this just is, like, totally coincidental, if we had sold all of our shares at peak price of whenever whenever the peak price for that stock, we would have made $2,000,000,000 more for our LPs.

Yeah. So to be clear, we excluded Salesforce in that analysis just because, like, it was so it was so long ago and also we made such a bad decision. That analysis is on the stocks we’re managing now. Okay. It’s the stuff that’s currently public. Including Zoom? Yeah. Including Zoom. Wow. Yeah. Exactly.

So, like, basically, what we’re trying to say to our LPs is, like, this is how good we are currently at doing this, like, over the past, whatever, five years we’ve been at managing our public stocks. And the answer we made you 2,000,000,000 more than if we just given you all right now. Do agree? Could have made you 2,000,000,000 Do

Well, obviously, to some degree I do because we’re still managing a lot of those positions. I think that if you believe that if you stay on the board and you’re super active, then you do have more more insight. The downside honestly is just time. Just taking away from new investments. There’s huge benefit to the firm to have the connectivity to those incredible companies. And one other thing that we’ve started to do, I mentioned last night on our walk, has been pretty cool, is we’ve been funding really early stage AI companies, particularly within specific verticals, and trying to pair them up with these giants.

And so if we pair you up with a really big company that has great distribution and you can do some sort of deal, which may involve some equity where the big company gets to buy a little bit of the small company, but the small company gets the incredible distribution advantage of these massive companies we’re already a part of, There’s this beautiful symbiosis that has been playing out for both sides so far.

It matters. You know, some of the secondary purchases, both in terms of actual secondary and, like, third and, you know, second, third investments that we’ve made in some of these winners have been huge, hugely important from a returns perspective. In retrospect, it’s always hard to know because we definitely made some really bad third check investments in companies that we thought were trending that didn’t end up trending. What’s an example of that and what did you get wrong? Yeah. One of the big examples, like when we look back at failures in our portfolio over time, it’s been when we thought there was product market fit, but there wasn’t.

The term I’m using for now is I’m calling it mirage product market fit, where it’s like, company’s grown really quick. You can fool yourself into thinking this company has incredible product market fit, But there’s a couple different downside cases where you think you’d have it and you don’t. One of the cases in traditional SaaS is you’re selling a product to a very diverse audience who’s all using it for different things. And so you think like, oh, got product market fit, but the reality is like someone’s using your thing for this over here and another person, a completely different type of customer is using it for this.

And so how do you figure out your go to market motion? How do you figure out your product development motion when all these people want completely different things? That’s like what can help companies blow up. There’s a second dynamic that’s now happening with these AI enabled services companies where let’s say you go out and say, Hey, I’m going to be an AI enabled accounting firm. I’m going charge you 15% less than the incumbents and I’m using AI and so it’s going to be even better, higher quality, etcetera.

So faster, better, cheaper, etcetera. Well, of course, customers are gonna buy that because it’s cheaper and faster and better. So you’re gonna grow really quickly. What that doesn’t tell you is have you used AI to provide a high margin service, right? You can sell a lot of something, but if you haven’t figured out a way to have a good business model around it, then it’s not really product market fit. And this happens in consumer businesses as well, right? Where people, you know, sell a dollar for whatever, you know, a dollar 50 or whatever.

And then like, you know, you’re underwater from a gross margin perspective. The same thing can be true in AI enabled services, and all that can lead to a situation where you as an investor, you as a founder think, oh my god, I’ve got product market fit. You pour more cash and you don’t.

Yeah. It’s similar, but in that case, the deal sponsor is so much closer to it that we trust their judgment more.

I think when it’s a keep it alive scenario, we’re a lot more thoughtful, and we’ll often get someone else involved. Because every reserve situation is different, right? If it’s a reserve where it’s like it’s pro rata on a Series B, where we did the A, company’s performing well, It’s a little more straightforward. The hard thing comes into play where it’s a Series C and you need to put an inside round together to figure out what to do, etcetera. In those cases, we actually have the founder come back in and present to our full partnership.

We are all up to speed on what’s going on and we can check the founder because you’re right, there is a bunch of emotional investment. There is bias involved. But if the founder comes back to us and gives us the story, we’re able to poke and prod a little bit.

You know, so there’s a business that was actually bought by a British company called Sage called Intact. Yeah. So Intact was the kind of number two cloud ERP player. We were the early investors there and that company ERP is a tough thing because it’s the most mission critical system of all. So, it’s really hard to rip out someone’s ERP. But by definition, once you get in, it’s really sticky and so you can stay. That business grew slowly and then had some cash problems. We decided to bridge the company and that saved it.

We figured out that business also figured out a channel partnership motion. They figured out through accounting firms actually, and that business took off and was bought by Sage. I think it was for a billion dollars or something. And we made a ton of money on that whole thing, but also on that bridge That bridge was obviously in favorable terms given the condition the company was in. And so that’s obviously a cherry picked example, but there are examples where it’s not a bridge nowhere. When do you think IPOs will return?

I tend to think next year. Like, I think there’s enough uncertainty in the market right now, particularly in the macro and the political situation, that there’s a lot of people that are nervous. So my best guess would be, like, the beginning of next

I think Microsoft, and the reason that’s the case is because I’m obviously long b to b software, and that’s probably the best index.

Yeah. But if you, like, if you believe that they’ll continue their dominant position, then it’s just it’s sort of an index on the growth of Sure. But you’re going a 30 to 40 to 50% price increase. Yeah. But you’re asking me to hold one stock, and so I’m putting my entire portfolio in something. I’m gonna put it in something that’s safer.

Come on. I generally like the stage specific firms. So, like, on the on the late stage, I like the Meritech folks, and I like the Green Oaks folks, and, like Series A? On Series A, I mean, similarly, like, I like the folks that tend to be more thematic and focused. So, like, Mavoron is great in the consumer side of things. USB, I had a ton of respect for. They tend to be, like, deeply focused, obviously, crypto and other things. And on the seed front, like, it’s similar.

Our friend Rick Zulu runs a fund called Equal Ventures, which is a seed fund that is super duper thesis driven. I respect it. He makes contrarian bets super early. What deal have you lost,

did you lose to? The first deal I lost I think I’ve lost two or three deals in my career so far. The first deal I lost was Ironclad, and I lost it to Jess Lee at Sequoia. It was super painful. So the context is I had gotten to know Jason, the CEO there, before he started the company. So he was at a coffee shop and met my wife because she was wearing, I guess, a HubSpot shirt and he was curious to learn about sales. This is what they tell me.

And they talked. And Danny was like, my wife Danny was like, This guy’s amazing. You should meet him. So, I met him. I really liked him. He started the company at the time. We weren’t doing much seed investing, so I didn’t look at the seed. And then at the A, we had invested in a company called Simple Legal, which was like billing software for lawyers. And on their roadmap, they had contract management. They hadn’t built it yet, but it on their roadmap. And so we made the investment, and then I called Jason and was like, Listen, man, I really love spending time with you, but I think I should not be part of the Series A because of this.

He agreed, and so we didn’t participate in the Series A at all. And then the Series B came super quickly, and to Jess’s credit, she ran fast and got in front of him first and put the term sheet in and won it. Obviously, the happy story is I ended up investing in the next round. Think as the only external investor in the next round and Oh, this is.

Yeah. What was the price of that? Somewhere in the 3 hundreds, something like that, maybe 400. I don’t remember specifically.

I think it could be much larger. I mean, I’m obviously biased, but like, documenting But I’m

Yeah. I think, I mean, I think that’s potentially much more, I think in part because if you look at DocuSign as a comp, like that business got very large and was just literally signatures. You know, we now do that as well, in addition to contract management, which is a much, you know, bigger thing. We also have this AI product that we’ve built called Jurist, which is a Harvey competitor. Pretty cool. And it’s growing real quick. And so, I do think there’s real upside to it, but we’ll see.

What’s your biggest win and what did you learn? Like, obviously being involved with Zoom very early was was huge. I think the two learnings I had there are market pull, incredible market pull, and then founder insight. If you can find something like that, founder insight around creating something differentiated, it’s a recipe for success.

Thus far, I haven’t had any zeros. I’m sure I will. The exit I’ve had that was the worst exit was a company called Comfy, which was building energy efficiency software. So basically, it provided employees within an office the ability to change the lighting and temperature from their phone wherever they were and would actually follow them around and remember their preferences and change the building accordingly. It’s actually quite cool. The business grew really quickly from a bookings perspective. They would have these big 7 figure contracts from Salesforce and others, but the people in charge of deploying the product didn’t care.

And so, there was a huge incentive issue between the buyer and the implementer in that business, and so we have huge bookings and we didn’t have great deployed ARR. And that gap bit us in the ass. We ended selling the business to Siemens. We actually made a little bit of money on the deal. And Andrew, the CEO, I stayed close. He actually bought me a gift certificate to the French Laundry, which I still haven’t been able to use because the reservations are so hard to get.

To thank him for helping navigate through the the outcome, he ended up making a good amount of money.

Grok. I don’t yet know how what niche they’ve carved out in the market. OpenAI feels expensive, but they have a strong consumer brand. I’d probably buy Anthropic, assuming they can figure out the app stuff more. Think that the underlying stuff happening there with the model seems quite promising. What’s the craziest thing you’ve done to win a deal? Assembled, which I mentioned before, AI for support teams. We led the Series A there. It was a very, it was also a very consensus deal in the sense that the three founders came from Stripe.

They had built the tool at Stripe to serve Stripe, and they were like, this thing is bigger than just one company. We could spin it out and start the company. So Stripe did this seed. I think it was the very first deal that Stripe did as a seed investment. As you can understand, like, the Series A was very frothy because everyone and their sister wanted to invest in these hot Stripe founders. I’d gotten to know the founders for a while, had tried to push Brian, the then CEO, to let us invest, he wanted to run a process.

And I get a text message from him, I think, as I’m coming back from my honeymoon, and I’m all blissed out. And he’s like, hey, man. Process is live. Do you have time? And I’m like, blissed out and like not in a place where I’m running after deals. And I was pissed because I had been in front of that one for a while, And I was really excited about the company. But I flew back, worked really hard. My partner, Yaz, who was then an associate, did an insane amount of work to get us up to speed.

And we got into the top three of the bidding process with them. And then they went silent. And I was like, That’s not good. And I got a phone call at 9PM, from the CEO, and he said, so good news. You’ve made it top listed in the top three. The way we’re gonna decide this, we’re gonna have a mock board meeting. In one hour, I’m gonna send you a bunch of materials as if this is a board meeting, and then we’re going to hold a board meeting, the three of us and you, and we’re going to see how you perform.

And this is exactly what happened. At like 11PM, he sent me these materials, I prep, and then we have a board meeting and he show he saw how I showed up as a board member and ultimately chose us. I’m very passionate about board service and the right way to show up as a board member. Do you know who you beat? I think Index. Who when you hear

The reality is like there’s not a specific person or brand where I’m like, oh, shit. I’m fucked. That’s part of why my job is to get to know people early. In our last fund, in fund five, we did this analysis. We knew the founders on average thirteen months before we made the investment. We know it matters.

Yeah. I am so, so grateful for this. So, as I mentioned, we grow partners from within. We think it’s one of the things that makes us different. Part of the reason we’re able to retain incredible people like my partners, Lotte and Yaz, and others who have come up behind me and me and Joe and Santi and Kevin, all the people that have been grown within the firm is because our founders made the very generous choice when they step away from the business and retire to forfeit their carry.

This is not something that’s talked about in venture, and I had no idea about this when I was considering which firm to join. But the vast majority of founders of firms, when they retire, they retain a meaningful portion of the ownership of that firm. That creates really bad incentives for the really high performers. Because if you’re a really high performer, why would you stay at that place? You’d go start your own thing. Right? And that’s part of the reason why you’ve seen such proliferation of new funds pop up.

The amazing thing about our place is I have no reason to leave because the generosity of the founders who stepped down and said, you know what? We want to empower the next generation. We’ve made enough money. Here’s our carry. It means like it’s ours to run. And it means I can look you in the eye if I’m recruiting you to be a principal and groom you into my next partner and say, you have a real chance to be an equal partner alongside me.

is an answer to your question, but I’m gonna say something that’s been on my mind. I had a conversation with Sam Altman three months ago where he was talking about the cognitive dissonance that he lives with every day, knowing that the gains that took place, the improvements that took place between GPT-two and GBD-three and a half, which just took a few years and were incredibly exponential, and obviously three and a half was the moment that the world changed, are very likely to be the same or probably dwarfed by the improvements that we’ll see over the next two or three years.

So how do you make decisions right now about what to invest in, about how to live your life, about how to raise your kids, knowing that that change is coming? That cognizance is very hard to live with for all of us and certainly for Sam who has a courtside seat. And so I asked Sam, how should we think about raising our kids knowing that this is changing so quickly? And his first reaction was don’t teach them to code. And then he was like, what I mean by that is like teach them the logic of how to, you know, think like that, but you don’t necessarily need to teach them the mechanics of coding because that’s obviously likely going away.

But what he said was very specific. He said, You need to teach them how to understand how people are thinking and feeling and how to influence that. And I excitedly came home and told my wife, who is a career leader of big revenue teams and who is now teaching the course on sales and persuasion at Stanford Business School, I was like, You’re the future. And I’m grateful that I had kids with you because it means that our girls are gonna get this just inherently by being you know, having you as as their mom.

So when I think about the future and what I’m excited for, I’m excited for all of the things that are more rote and less creative to go away. And I’m excited for the fact that we can hopefully be more human. Like, we really can I can connect with you more and spend more of my time understanding, like, how are you actually thinking? How are you feeling? How do I make you feel better? How do you make me feel better? Hopefully, we’ll have more as as I played for you before, like, moments where, like, my three year old sings, what was what was the song?

Shake It Off. Yeah. Shake It Off. This is the Taylor Swift song. We can have the machines put the music behind it, and we can, like, you know,