20VC: Lessons from Investing $2BN and Returning $8BN in Cash | Why Most Venture Partnerships are Broken | We Sold Salesforce Early and Lost Out on Billions | Are The Best Deals Always Expensive and Competitive with Jake Saper @ Emergence Capital | The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch

We have deployed a little less than $2 billion in capital.

We've returned in cash a little over $8 billion.

That fund, I believe, was fund three, which is the same fund that has Zoom.

I think it's a 16 times DPI.

We did this analysis on how have our deals fared certain graduation metrics relative to market.

Nine out of 10 of our deals have gone on to raise successful following rounds.

One out of five have gone on to raise rounds at north of a billion dollars.

One out of 10 of our early stage investments have gone public.

This is 20VC with me, Harry Stebbings, and I thought it is time for a VCVC show.

It has been way too long.

So joining me in the hot seat today is Jake Saper, general partner at Emergence Capital, one of the leading venture firms of the last 20 years.

Their many wins include being early investors in Salesforce, Zoom, Viva, and many more.

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Jake, I am so excited for this, dude.

I loved our walk around London last night.

I actually walked around and I was like, you know what?

James Corden does carpool karaoke.

I should almost try and do this around London.

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.

Just like incredibly beautiful, such appreciation for the history of this thing.

So thank you.

It was when I took you down the prettiest street and I was just like nah, this is getting a little bit romantic.

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

Exactly.

Listen.

I loved it because I also got so much context that I wouldn't normally get even in, like you know, prep calls, which I think are generally bullshit, to be honest.

But I wanted to start with Zoom.

This was your first deal at Emergence.

I just want to start there.

Talk to me about Zoom.

How did it come 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 wasn't very good.

In fact, when I was interviewing at Emergence, the case they gave me to interview at Emergence was for a company called Fuse.

Fuse was video conferencing software, an early competitor to Zoom.

And I was supposed to diligence that case and then make the recommendation should or shouldn't invest.

And they were going to 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 Zoom.

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 two or three million in revenue, was growing very quickly but obviously very, very early and we believed in eric.

Eric was the vp of engine 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 going to be a 20 million check out of a 250 million fund, which is a lot of concentration.

That's a lot of concentration.

For people, that's what, 7%, 8%?

Yeah, it's huge.

That is huge.

It was going to be priced at $200 million post-money valuation.

And this, again, remember the company was at around $2 million in revenue.

And this was 2014.

100x revenue.

In 2014.

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 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 going to matter here just because of the scale of this decision.

I flew out to Boston because I was visiting my then-girlfriend, Dani 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, and 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 Olympia child kid.

And I was like, help me.

And Joe dove in and figured out that the numbers that Eric had given us around churn for the business were wrong.

Eric himself was miscalculating churn.

Specifically, he was counting upgrades from 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.

Was it very competitive?

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 how 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.

There are so many things that I have to unpack off the back of that.

The first is you mentioned he really chose you because you helped on GTM enterprise sales.

Honestly, I don't want a founder to need me.

I often think about Keith Robois, the best founders don't need you.

They're made better when they don't need you.

How do you feel about that?

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 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, and you're a politician.

We're learning a lot about each other.

Another thing, you said about the prepared mind around the space.

I honestly think that's kind of bullshit from large multistage firms who kind of like to present these packages, and actually they can lead you to the wrong conclusion.

How do you feel about the benefits of firms having prepared minds versus actually just packaging on a venture product?

Yeah.

So the reality is I don't think any venture firm makes all their money on prepared minds.

I just think 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, faster than others.

I mean, in the Zoom case, it's a great example.

They literally gave me my interview case on a competitor.

You must have just been like, ah, boom, I've done this before.

Yeah.

So when we got the real thing, I was like, oh, great.

I've already studied.

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 Chorusai was an early competitor to Gong that was acquired by ZoomInfo for a little less than 500 million.

We led the seed round.

We were 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.

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.

Can I be honest?

You make much money from a course.

You do the seed.

It gets bought for half a billion, which is great.

Is that in stock?

Is that in cash?

So many of these deals actually behind the scenes.

You kind of make 3x and it's not as good as it looks.

We made... I forgot the specific multiple.

It was definitely more than 3x in that one.

I don't remember the specific number, but I think it was north of 5x.

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 going to move the needle.

It's unfair to me because it's kind of in the details, but how much of the 16x DPI is Zoom?

By far 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.

The company was acquired for $2.3 billion, and we were the Series A investors there.

So that was a very good outcome.

But that returned the fund a few times.

I can't remember how many times it returned it, but Zoom returned it more than 10%.

I was trying to understand, like in the power law dynamics, like just how much of fund returns are in those.

The cool thing about that fund though is, even if you took Zoom out, it would still be a top to sell fund.

Because of SalesLoft.

Because of SalesLoft, because of Chorus, and there's a bunch of others.

And there's some that there's still much of they're still 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 multibillion dollar distribution.

Can I ask, you mentioned Corsair and there's Outreach and there's also Gong.

When I enter markets, I often like to think about like the distribution dynamics within the market in terms of is it a winner, take all?

Is it relatively evenly distributed?

How does this market play out in terms of Uber, Lyft or actually multiple providers, all kind of distributed evenly?

Do you think about that?

And like I don't want to be in a market where kind of everyone gets a little bit like Corsair and Gong and Outreach.

No offense.

I don't think it's a great market.

Yeah.

I think you can make money both ways.

So let's take, 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 you familiar with this one?

Yeah.

It's a fucking beast.

Good company.

And no one knows about it.

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 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 boltnew 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 square space and the web flows and the et cetera, et cetera, et cetera.

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.

Help me understand, and we're so jumping around, but I love a conversation like this.

So help me understand what happens to those players.

Do they consolidate?

Do we have PE providers come in?

What happens to the WebFlows, the Wix, the Weebly?

There's a lot.

WebFlows, Wix, Weebly, Squarespace, just to name a few.

And then there's the unbundled providers who are much more vertically specific.

What happens?

There will be consolidation, there will be private equity and there will be a few 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 is 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 get your money back.

The sales loft 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.

Totally.

Yeah.

Thank God.

Love that.

I mean, I do look at your Ana plans and your Coopers and I think how the fuck are they going to get their money back?

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, you know 50, 100 million ARR.

This is what really worries me.

It 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?

How real is it going to be?

Are my customers going to 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 going to 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.

I spoke to him before this about you.

Rick is God.

He said you're a dick.

Rick 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 it's a knowledge management product that grew really quickly.

And then during COVID, 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 re-accelerated.

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, like these moments actually make the business...

Can I be a dick there?

Is that actually interesting?

And I mean interesting from a venture outcome perspective on impact on funds.

It's great.

But Glean is at 100 million an year.

Sauna is doing incredibly well and growing very fast.

Here we've got a company that's kind of re-architected itself and pivoted into a market with already growing fast players.

Yeah.

What the other fast growing players represent is market pull, right?

It's that 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.

How quickly do you 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 business starts to stall a bit.

But then we helped 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, so 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 wasn't necessarily like this, but 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'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, ooh, please tell me what it is.

And he goes, Zenefits.

This is a moment, obviously, where Zenefits was on an absolute tear.

I remember this.

He poured a ton of money in.

And he was... My tenure, I think, 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.

And he was like, I just made... This is going to be it.

And to be fair, Parker is and was amazing.

Parker's a monster.

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. 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 going to win.

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

Can you talk to me about market pool being the most important thing of all?

For people listening, founders or investors, how do you think about that?

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 do you try and unpick that when you're doing diligence on a B2B company?

So when you talk to users or prospective users, when you talk to users of the product, the things I want to 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, you know like holy shit, this has changed someone's day-to-day life.

There's real market pull for this.

Instantly think of linear.

Amazing, amazing tool, but I always hit that with that.

How do you think about defensibility in a wave of AI?

Because you could have market pull, but also not be defensible.

Yeah.

This is where the founder comes in, right?

So if you were to ask me to rank founder versus market versus traction, hypothetically the first one is market pull.

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, that's just tapping into 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 to provide some defensibility to the business.

It's still very early, so we have no idea how that's going to play out.

But I think when you're making an 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.

When did you think there was market pull 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 and build their own thing outside of their own thing.

You're laughing because it sounds- I'm going to be honest.

I could have told you That was a bad one.

So I should reveal something here.

My mother is a jazzercise instructor.

Do you know what that is?

I take it as like jazz as a sport.

It's kind of like jazz as a sport.

It's jazz as dance.

So this was a huge craze in the 80s in the US.

It was dancing and aerobics combined.

I remember Mr. Motivator.

Yeah, 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 etc.

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.

How much did you put in?

It was a series A. I think we put in like nine.

We 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 and returned the money.

Okay.

So my question to you on the back of that is I would, if I was your partner, go upside maximization.

It may not be a bad business.

I don't think it was a good business ever.

So it would have been like a hard block on that one, Jake.

Sorry.

But even if it works, the upside is highly questionable.

Maybe it's a $500 million business, which we say poo-pooing.

It's not at all.

It's amazing.

But for a fund that's the size of Emergence, it is not going to make a dent.

How can you justify to me a $5 billion business on that business?

So if you think about this more broadly as a creator economy tool, like if you think that there's going to be more Harry Stebbings in the world who are 16 in their rooms who figure out I want to start my own business and you provide a business in a box for them, that's potentially interesting.

They will not.

There will be no more Harry Stebbings.

I will crush them.

I'm worried for the world if there is more Harry Stebbings.

But okay, so if there are far more, we are going to provide that business in a box for 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 indefinitely and we wouldn't be back in more concentrated areas.

And we made some bets that focused on that future.

We made some bets that focused more on an office future.

That's our job is to call the future.

I do want to go back to the element you mentioned about Zoom, which was freaking nuts, which was 100x revenue 10 years ago.

I mean, 100x revenue today is more normal.

I still think it's crazy and a lot people think it's crazy.

But then it was completely unheard of.

And so my question to you is, have the best always been expensive?

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.

Viva wasn't expensive because that was non-consensus at the time.

SalesLoft was also non-consensus at the time and was not expensive.

But she made that investment before the Zeitgeist, before people were like oh, this is obvious and this is going to happen.

And, to her credit, there was a lot of 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 did a Series B at a 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, more and more and more consensus deals, and you want to be in both.

Are the best always competitive?

No, I don't think so.

Viva 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.

You mentioned many names, but some were like Gusto and then another was Viva.

Gusto is a brilliant business, but it's raised a lot of money.

Viva, likewise, is a brilliant business.

It's raised next to no money.

Yeah.

Do you pre-investment think about dilution potential downline and what that does?

Yeah, we do.

So 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.

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.

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 will set those pre-diligence goals?

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?

You mentioned the reference calls there.

And when we chatted last night, you said that everyone is on at least one reference call.

Yeah.

That is supremely strange, bluntly.

Normally that's like an owner of a deal and they'll do all the work and they'll bring it back and you'll have a discussion as a partnership.

But bluntly, it's not a very efficient way to do it.

Super efficient.

Talk to me about that.

Yeah.

Well, it's important to understand that in the context of emergence and how we operate.

So we're a focused firm and we're 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. all we've ever done.

It's all we ever will do.

The first investment 20 years ago was Salesforce.

Then the vertical SaaS thing happened.

We did Viva.

Now the AI thing's happening.

We did Together and Bolt and Bland and Unified, much of others.

So we're very focused thematically.

And all of us just do that work, 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 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 a very high risk, but it's high conviction.

And if it wins, it returns the fund many times older, which we've been lucky to do with a number of funds.

That approach allows us to work collaboratively as a team when you're only doing a relatively small number of deals.

And the reality is this has largely worked.

Our goal is to... It has, but you've got to be really good pickers.

One a year.

I mean, no offense, I would not like to be you.

Yeah.

It's a hard job.

And it's an average.

Sometimes it's two, sometimes it's zero, et cetera.

Does it ever set the bar too high?

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 never lost a deal, which we chatted about last night.

And I would say that that means you're not taking enough risk.

No, what you mean is I've never, none of my deals have ever gone to zero.

Sorry, none of your deals have ever gone to zero.

That's correct, yeah.

That does mean I haven't taken enough risk.

And 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, given entry point and when- And assuming I've done the I and we have done the diligence well.

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 help after we make the investment.

I'm like the world's worst interviewer because I like just take everyone off on like a different tangent.

So go back into that like why everyone's involved because they're all in on the diligence process.

Yeah, yeah.

So let me explain the diligence process, but let me just finish that last thought.

I really do believe this helps change outcomes.

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 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 following rounds.

One out of five have gone on to raise rounds at north of a billion dollars.

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 so 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 week, 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 onsite visits where we actually go and we spend time with a team.

We see what's happening in the kitchen.

So we kind of pick up on all the less structured data points.

And by 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 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.

I think one of the biggest mistakes that firms make is when they get associates to just go and do the reference course.

Nothing against associates, but there's so much in tonality, in the pause, in the facial expression.

I completely agree.

It's a human business.

Completely.

One thing that really struck me there is that is time.

And we don't always have time, Jake.

I would love to do multiple onsite visits.

I'd love to do all the time compressions real in deals.

How do you do an engaged and diligent process when you have real time compression and the end of the week to make your decision?

Yeah.

So there are ways in which our process hurts us there and there's ways in which it helps.

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 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 been 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 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.

How do you do knowledge management across the partnership?

And so what we do, for example, is we record calls so that I can listen to the call.

Jacob with a customer and I'm there in the room.

How do you do that shared knowledge across diligence process?

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 etc 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 we're processing all the information if we're doing that during the day they get compressed because we have 30 minutes and we're just getting into the meat of it in minute 27. 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 like the reality is we do a lot of late night calls discussing what we've learned and trying to synthesize you know the day you mentioned the on-sites the in-person yeah love that covert meant that that was impossible yeah do you think quality of investing went down dramatically in covert yeah it's a good question We actually still managed to do some onsites during COVID.

So I can tell you- Ah, 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.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 one and a half million in a year which pre-AI, was very, very good.

And founders were 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 get there both on both sides.

But it was the heat of COVID, so you couldn't find a way to do it.

To make things worse, it's not like they were in San Francisco and I was in San Francisco.

We go to a park and walk around.

The CEO was in Steamboat Springs, Colorado, and I was in San Francisco.

It's not an easy place to get to.

So what we agreed to do Alex Levin's 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.

Was it raining?

It was not raining.

That would have been really like cinematic.

Well, 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 we're walking through that.

We do this like four hour hike through literally a field outside of the Denver airport.

And I get completely just like horribly red, terrible.

But like the good thing was like, I really, 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 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... Do you ever get founders who are like, no, I'm sorry.

We're not going to do that.

That's too intense.

And like, we don't need the time.

Yeah.

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 it actually selects for the right founders.

You mentioned zero to one and a half and it being like, wow, 100%.

And I was so brought up in the like, Sasta, Jason Lemkin on what great companies are.

Zero to 10 in like two years, I think it was.

It was great.

Have we misled a generation of founders with triple, triple, double, double being great?

Yeah.

And now that is not enough with Bolts and Lovables and McCores.

Yeah.

The 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 LLMs 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 in 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, you know, which went zero to 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 15 months ago.

They were at 2 million revenue.

The business is now north of 100 million revenue.

These things can grow insanely quickly because there's just such market pull.

They have shit marketing.

Yeah, exactly.

Seriously, that is insane.

Together.ai.

It's really good.

So 2 to 100, right?

Yeah.

In like 15 months.

I mean, that's absolutely... They really have terrible marketing.

Yeah.

Well, you should tell people.

Deal, have brilliant marketing because theirs is so brilliantly Seriously, it's so brilliantly articulated.

That's insane.

So what's changed?

So market pull has changed.

And I think you're right that if we tell founders that the top decile is triple triple double double, it's just not true anymore.

It's more like the great companies are quadrupling year over year.

But the rooster that hasn't come home to roost yet, which I think is I don't know if that's the right way to say it or not is retention.

We still don't know for many of these businesses because they haven't had year two, three years of 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 120.

And what I mean by that is yes, you should be growing very quickly, perhaps quadrupling year over year, triple quadrupling, et cetera, but you should also have a net dollar retention of 120 or above.

Just for those that don't know net dollar retention, can you explain what a net dollar retention of 120 is?

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 120.

The customers that churn from that cohort are outweighed by the customers that upsell.

So the net there would be $0.20 gross.

Totally get that.

So we want quadruple an NRR of 120.

Yeah.

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

A couple of things there.

One, margin.

In a lot of cases, these are essentially funnels for open AI around Tropic.

How do you think about margin improvement over time?

Slash margin maintenance over time, given they are funnels for LLMs today?

Yeah.

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 the closed source models and you've already 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 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, et cetera, and I control my own margins.

You said earlier, we figure out what do you have to believe for this to be a good investment.

So for the Together, what did you have to believe?

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 open AI 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.

For me, it's like, obviously it will happen, but it's just to the extent that it will happen.

Like, is it a 90-10 or is it a 60-40?

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.

Totally different.

But even if it's 10, the market is the world of companies, in which case 10 is still really interesting.

Yeah.

And it's also a function of how good Together gets at helping companies spin this up.

How painless will it be?

If it becomes really painless, that 10 could be the whole world.

You're right.

Do you prefer market creation, market expansion?

How do you think about that?

What I want, so I borrow this from Mike Maples, 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 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, there was an increase in the use of video conferencing.

There was distribution of mobile.

You could actually run the stuff on the application, on the computer itself, on the phone itself.

Eric had a unique insight into how to distribute this stuff with a codec on the product.

It's a long way of saying.

I think in both replacement markets, which Zoom was, and in new markets, which Togetherai 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 a new market.

I actually use it on every call I have, which is what do you believe that the world around you doesn't agree with?

Which is kind of a similar way of getting to the unique inside.

So I totally agree with you there.

You mentioned like, hey, the thing that we haven't really figured out is retention.

And a lot of these companies, they just don't have the data to be fair on them yet.

It's too young.

Too young.

Do you think the retention cohorts will be worse, better, or as expected?

On the average, I think they'll disappoint.

And I think there'll be outliers that are better than we expect.

What will drive the outliers?

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

This is why we did Solve like deeply entrenched in patent lawyers very, very core to workflows across teams.

And so this is interesting.

And this is why, 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 era.

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 our first investment and 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.

And so when you think about where is sustaining value in a world of AI, how do you answer that question?

Well, part of it is if you can build something that people use every single day, if it becomes part of 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 you kind of build the muscle memory now to open that app instead of Google when you're searching.

I totally agree with you.

I think brand is the Trojan horse that everyone is forgetting.

Everyone has a consumer front end.

Anthropy has a consumer front end.

How many people go to Claude?

That's part of Anthropic's challenge going forward, right?

They've got an incredible coding machine.

Do you think we'll see the specialization of LLMs?

I mean, if I'm Anthropic now, I'm like, for fuck's sake, just appreciate that you have Cursor Codium and you have an unbelievable coding machine.

Be that, and that's a huge business.

Do you think we'll see that specialization or not?

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 co-pilot is a 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 going to have insights that even an open AI won't be able to have.

You mentioned Copilot there.

We see people like Klarna who say ah, we're replacing all of our SaaS tools and we're building them ourselves.

And AI allows us to build all of these tools ourselves.

And people are genuinely asking the question really, especially vertical SaaS are all of these tools dead and we'll be able to have very custom applications that we build ourselves?

How do you think about that?

So I have a strong take on this, and I realize 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 curses 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 opinionated perspective on how to solve a problem.

And that's a really important point.

Ultimately, if there is 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 to 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 that a closed source model is not going to have.

That you can't just get off the shelf.

So that's the first reason you're buying an opinionated perspective.

The second is the very factors that are making the software easier to build yourself also make it harder to maintain.

So you could spin up something in Bolt or Lovable or with Cursor et cetera yourself, and that thing becomes out of date in six months or even faster.

And so, unless you have someone and 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 it.

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 starts to move into the world where software pricing is evolving and could look more like outcomes-based pricing over time.

One thing you forgot there is creation.

Fundamentally, the majority of enterprises, especially in Europe, do not know what Slack is, let alone what Notion is.

So the fact that they're going to create their own verticalized AI tools is absolutely fucking moronic.

I mean, it's really stupid.

Maintenance, the average company has 172 tools.

Are you seriously saying you're going to maintain 172 tools?

Absolutely moronic again.

The accountability element, we need someone to blame.

That's why we have consultants.

Sorry, former consultant.

But we need to blame him.

It's not my fault.

McKinsey told me to do it.

Ah, McKinsey told you to do it.

Fine.

So I totally agree with those.

You mentioned pricing there.

Everyone's saying on the back of that, we're going to see this total shift.

I interviewed a lot of people.

I interviewed Anton from Lovable the other day and he said He didn't know which company he would short.

But he would short a company that has kind of archaic per seat pricing and doesn't adjust on a pricing model basis.

What do you think is the future of B2B pricing in an AI first world?

Yeah.

I think there's a spectrum of pricing.

So you have the classic per seat, then you have usage models which look like all sorts of things, and then you've got true outcome space.

And that could be usage-based obviously on how much tokens you're using, et cetera.

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... Do you think that's great?

Sorry, I'm interrupting you there.

Compare that to Finn, which is Intercom, who actually do it on outcome-based, which is solution-granted.

Yeah.

So I think that the direction that this world moves over time is solution-granted.

I've spent a bunch of time learning about the Finn approach.

It's hard for now.

And the reason it's hard for now is a 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...

So someone, a bot touches it, and then maybe a human weighs in a little bit over here.

And then how do you establish 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, no, you only did some of this.

I'm only going to pay you this.

And all of a sudden, instead of having an easy bill, it's like you're negotiating every month with the customer.

That sucks.

I think that 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.

It almost doesn't work when there's human in the loop.

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 to 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 invest 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 we'll 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 do it?

Do you have margin degradation on AI enabled, given the fact that you own the full vertical and you have to kind of ingest that all yourself?

It depends on pricing.

So this 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, if it's going to take me this long, then I'll charge you this.

But 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?

Can I ask you, when we look at this distribution in an AI wave, who does it benefit most?

Incumbents with incredible distribution advantages?

Is it startups with none of the technical debt, the ability to move fast, integrate quickly?

How do you think about that?

There's a third category.

And I don't know how to describe it.

We talked about a bit earlier, which is like these like growthy stage companies.

Which is like your notions of the world?

Notions, the ironclads, like the companies that are above 100 million 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 oversimplifying.

The biggest thing I've changed my mind around in the past 12 months relates to this question, which is I was fearful, when the power of LLMs 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, helping with the go-to-market stack in a much more narrow way than Salesforce is, you're going to run just way, way faster and customers are going to want your product more.

We're seeing that play out.

And so The thing I've changed my mind on is I'm less fearful that incumbents will be able to accrue most of the value.

The reality is it's still early days in this game and things could change.

But thus far, the 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.

I've been phenomenally impressed with the speed of incumbent shift.

When you look at your Adobe's of the world, I think we always said, oh, that's so slow.

Actually, incumbents are shipping faster than ever.

I've been very impressed by that.

How do you think about that?

Oh, Google could just build this.

We've been investing for years.

Everyone's like, oh, email auto complaint.

Oh, Google could build that, whatever it is.

How do you feel when you hear that?

Yeah, this is where I go back to solving a narrow problem.

Like start by solving a narrow problem, because Google is not going to solve that narrow problem as well as you will.

And you can expand from there.

I mean, Viva is a great example.

When we made the investment in Viva, a CRM for pharmaceutical companies, the entire market for that was 400 million globally.

That's not big enough to build a multi-billion dollar business.

For context, Viva today is a $35 billion market cap.

That's right.

So they obviously found a way to expand.

So they started narrowly, 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 Viva has now upsold all sorts of stuff to these massive pharma companies and has a 35 billion market cap as a result.

The same is true in the AI era, right?

If you're building an autocomplete 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.

I also find that you continuously underestimate how big the landing wedge is.

Yeah, that's right.

Particularly if you're really good at solving a problem.

And if the pain point is really big?

If the pain point's really big, you not only 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.

Do you buy that?

You know, Sarah Tavel's written before about paying for the work, not just for the software.

Do you buy that?

And I'm not disagreeing or agreeing with her, but I'm saying, do you buy that transition?

I think a lot of buyers will find it difficult in their minds to justify paying for labor when it is software.

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? reduced.

And they're like, none.

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.

We mentioned Salesforce multiple times.

In the next wave of AI.

Respectfully, everyone on the show has said that Salesforce would be one of their biggest shorts.

It's not mine.

Why?

What would the bull case be for Salesforce?

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.

For 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 500 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 host it in a much more efficient manner.

And so if companies like Mechanical Orchard succeed in doing that, the IBMs of the world are in trouble.

Given, as you said there, the dominance of still companies, as you said, with refrigerators, then running their software, do you think we overestimate adoption of AI in the short term?

Good question.

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 enduring value are going to 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 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 shouldn't.

It's not hard to imagine what could happen.

And there could be a bit of a backlash to say, oh, wait, this isn't good.

We shouldn't do it.

The reality is, we do need to figure out the guardrails for these products so that they're deployed safely.

You mentioned disillusioned there.

We've seen a huge amount of disillusioned talent within venture firms leaving.

What a transition.

I'm pretty good at this.

I've done a couple of these shows.

Impressive.

Honestly, it's like 3,000 in.

I can do a transition.

I'm glad you noticed that one.

But there is a huge amount of disillusioned partners.

We've seen it with new firms.

We've seen it just with departures, with fundraising.

And my question to you is, you've never lost a partner, which is nuts, right?

What do you do that no one else has been able to do?

We grow them from within.

Why is that important?

So I'll explain how most venture firms work and 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 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 these dynamics, it is really really bad for our founders, because what happens is these founders become orphaned deals.

No one talks about this and it is really- It's a big deal.

Yeah.

It's a big deal.

Why is it a big deal and what should founders know?

So unfortunately I've been part of a lot of boards now with orphan 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 going to get it are lower.

All of a sudden that founder has to start to scramble and figure out what do I do?

Or a new person comes onto 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 can feel.

Kind of tricked isn't the right word, but it's like they signed up for something.

It'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 vetting process is so important.

That's why I flew to get sunburned in Denver and, you know, with Alex etc.

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

10,000%, is signaling a real risk?

Or do you agree with the multistage funds who say that's not really, it's just used by seed investors and instrument to keep their jobs?

It comes down to the topic we talked about before, which is focus.

So most multistage 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 way 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 a round 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.

I mean, we did Zoom at 10%.

So it's all like, it also depends on the stage.

But is that the bottom?

How do you differentiate between, oh, it's a stretch, but we'll do it.

And I'm sorry, that is too low.

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 going to be Salesforce and it's not going to be super dilutive going forward, then I have to raise 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 to convince yourself that all of them are outliers.

But the lower ownership you have, the more the onus is on it.

Do you buy that it has to return the fund thesis, that we really just have such a fixation around in venture?

Yeah.

When actually part of me is like, A, if it returns half the fund, that is still very good.

And B, we always underestimate the size of our winners.

Yeah.

So both of those are true.

So we've been around for 20 years.

We have deployed a little less than $2 billion in capital.

We've returned in cash a little over $8 billion 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 billion 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 thus far is the Zoom fund, which is our fund three.

Over a Salesforce fund?

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.

Let's talk about it.

Let's talk about public sell.

Which is like public sell.

When do you sell?

Yeah.

So it's a really hard, it's a hard question.

When did you sell Salesforce?

So very early, shortly after we went public.

Yeah, it was bad.

I wasn't there for that.

You were six.

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 Viva?

I've been there for a lot of the more recent ones.

Do you have a formula or framework?

Yeah, we do.

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 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, etc.

In some cases we buy.

So in the case of Doximity, we were huge believers.

We invested at the A, accompanied really well.

We actually bought more at the IPO and that's been a great investment.

We've already returned three X from where that was.

But it's a hard decision because every quarter you look at it and you say okay, I know what's going on with the company.

I don't know what's gonna happen in the macro.

There's all sorts of uncertainty in the macro, so that weighs into it.

And you do your best.

Do you feel pressure from investors when they are less liquid times and you could liquidate positions?

For 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, I need cash right now.

They really want us to maximize the size of the outcome.

And we've returned, as I said, over $8 billion on $2 billion deployed to them.

And so they trust us generally.

We did an analysis recently on... how good we have been at the Publix.

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 done so far?

So basically our track record of selling.

Which is case by case dependent.

Case by case.

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 Viva, we've distributed 90 of our position, but we still have a meaningful stake in it, just because we owned 30 something percent.

What i mean?

Number three sell peak price is obviously going to 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, you'll massively fuck yourself.

Yeah yeah, that's like our salesforce alone.

You just kill yourself.

So the numbers are this if we had sold them all at lockup, we would have returned two billion dollars less to our lps.

What's interesting and this just is totally coincidental if we had sold all of our shares at peak price of whenever the peak price was for that stock, we would have made 2 billion more for our LPs.

No.

But it's just like, I mean this in a nice way.

That's not true.

Salesforce.

Salesforce would have been another $200 billion gain.

Yeah, yeah.

So, to be clear, we excluded Salesforce in the analysis just because 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.

Because I was like, it sells, wasn't it?

I can't believe it.

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 is we made you $2 billion more than if we'd just given you all right now.

Do you agree with Roloff's thesis that actually us, as venture managers with inside information, are best placed to manage companies, even in public markets?

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 insight.

The downside, honestly, is just time.

You're 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, which 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.

We mentioned the signaling earlier.

I think one thing that we don't talk about enough, but is really important is reserve investments.

How do you think about reserves, reserve allocations and the decision making attached?

Yeah, it matters.

You know, some of the secondary purchases, both in terms of actual secondary and like third and 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've 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 companies grown really quick.

You can fool yourself into thinking this company has incredible product market fit.

But there's a couple of different downside cases where you think you 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, I've 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 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 sort of 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 to charge you 15% less than the incumbents and I'm using AI.

And so it's going to be even better, higher quality, et cetera.

So faster, better, cheaper, et cetera.

Well, yeah, of course, customers are going to buy that because it's cheaper and faster and better.

So you're going to 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, $1.50 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 of 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.

You have unanimous decision-making on the initial check, which I think is strange, but it clearly works.

On reserves, how does that look?

Yeah.

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

Do you worry that it's bias?

Yeah.

They like the founder.

It's their name on it.

They want to keep it alive in a lot of cases.

Yeah.

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, et cetera.

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.

I remember Mike Maples, our mutual friend, said on the show 99 of the time bridge rounds are a bridge to nowhere.

Yeah.

Do you agree with that in your experience?

You know.

So there's a business that was actually bought by a British company called Sage, called Intact.

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, because 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 to nowhere.

When do you think IPOs will return?

I tend to think next year.

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 the beginning of next year.

I've peppered you with so many different questions.

I do want to do a quickfire round.

Let's do quickfire.

Okay.

Are you ready?

Hit me.

You can buy and hold one public stock for the next 10 years.

Which one and why?

I think Microsoft, and the reason that's the case is because I'm obviously long B2B software and that's probably the best index for that category.

They just price so richly.

Your upside there is just going to be like...

Yeah, but if you believe that they'll continue their dominant position, then it's sort of an index on the growth of software.

Sure, but you'll get like 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 going to put it in something that's safer.

You don't want some super risky GameStop shit?

Yeah, it's not my style.

Jesus, Jake.

Come on.

You've got a seed fund, you've got a Series A fund, and you've got a growth fund.

Which do you invest in for each?

And you can't say emergence.

Yeah, you've got to bet on yourself.

No, you can't say emergence.

Come on.

I generally like the stage-specific firms.

So like on the late stage, I like the Meritech folks and I like the Green Oaks folks.

Series A?

On Series A, I mean, similarly, like I like the folks that tend to be more thematic and focused.

So like Maveron is great in the consumer side of things.

USV, 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 Zulo 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 and who 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 was 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, I think as the only external investor in the next round.

At a C?

Yeah.

What was the price of that?

Somewhere in the 300s, something like that, maybe 400.

I don't remember specifically.

The company's now north of 100 million revenue.

It's doing quite well.

How do you think about that?

So I don't mean to pick on them, but if we actually pick on them.

Yeah.

Okay.

It's like a three, $4 billion company.

If we want to be really generous.

Yeah.

In the public company.

Yeah.

Really generous.

I think it could be much larger.

I mean, I'm obviously biased, but like DocuSign.

300 million entry price with dilution.

We're like a five X.

Yeah.

I think it has a potential to be much more.

I think in part because if you look at DocuSign as a comp, that business got very large and was just literally signatures.

We now do that as well in addition to contract management, which is a much bigger thing.

We also have this AI product that we've built called Jurist, which is a Harvey competitor.

Pretty cool.

And it's grown real quick.

And so I do think there's a 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 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.

What's been your worst deal and what did you learn?

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.

Actually quite cool.

The business grew really quickly from a bookings perspective.

They would have these big seven 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 up selling the business to Siemens.

We actually made a little bit of money on the deal.

And Andrew, the CEO and 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 outcome.

He ended up making a good amount of money.

Anthropic at 60, Grok at 50, OpenAI at 300.

Which do you buy and which do you sell?

So I sell Grok.

I don't yet know what niche they've carved out in the market.

OpenAI feels expensive, but they have a strong consumer brand.

I probably buy Anthropic, assuming they can figure out the app stuff more.

I 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, is AI for support teams.

We led the series A there.

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, oh, this thing is bigger than just one company.

We could spend 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, 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, and 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 blissed out and 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 then I got a phone call at 9 PM from the CEO.

And he said, so good news.

You've made it top listed into the top three.

The way we're going to decide this we're going to have a mock board meeting.

In one hour I'm going to 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 11 pm he sent me these materials I prep and then we have a board meeting and 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 them as being on a deal, are you like, oh shit, I need to get my game?

The reality is 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 13 months before we made the investment.

We know it matters.

Penultimate one, very often older partners hog carry pools.

How does the carry distribution look in the partnership?

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, Loti 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 a 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.

Final one.

When you look at the next 10 years and you think about excitement.

I like to end on a theme of positivity.

When you think about the exciting things that come.

I'm very excited by like drug discovery, especially around MS.

My mother's got MS and what will be enabled.

What are you most excited by when you look forward to the next 10 years?

I don't know if this is an answer to your question, but I'm going to say something that's been on my mind.

And obviously 35 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 him to code.

And then he was like what I mean by that is like teach them the logic of how to 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 you're the future.

And I'm grateful that I had kids with you, because it means that our girls are going to get this just inherently by being you know, having you 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.

I can connect with you more and spend more of my time understanding, 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 I played for you before, like moments where like my three-year-old sings what was the song um 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 focus on her and elevate her jake i so appreciate you coming to london i so appreciate the walk around london and the loveliest thing is like it kind of making a new friend you know it sounds strange but it's a really cool thing i feel the same way dude i really enjoyed it so i so appreciate you and thank you for being so great thanks for having me So I have a real debate.

That was one of the best shows I think we've ever done.

And I think it was so good because we had a two-hour walk around London the night before and so really had a chance to get to know each other.

I want to hear your feedback.

Do you think that's one of the best that we've done?

And do you think we should do walks the night before instead of say prep calls, to really build the context?

If you want to watch the full episode, you can find it on YouTube by searching for 20VC.

That's 2-0-V-C.

But before we leave you today, turning your back of a napkin idea into a billion dollar startup requires countless hours of collaboration and teamwork.

It can be really difficult to build a team that's aligned on everything from values to workflow.

But that's exactly what Coda was made to do.