How a16z Growth Invests

One of the elements of people judgment is what is the right founder for the right market. I really like a certain

right market. I really like a certain archetype of founder. I call them the technical terminator. The thing that I

technical terminator. The thing that I like about these technical terminators is they start technical and then you never know if these people are going to become commercially minded excellent you

know sort of business people. And then

over time they learn the business side.

I think early stage investors can often give you an interesting opinion about what the distant future looks like.

Probably great growth stage investors like you can give a really interesting view on what the near to medium-term future looks like. the companies that you've backed are sort of a who's who of

leaders across different technology sectors. If you had to think like three

sectors. If you had to think like three to five years out, what are some of the most interesting ways you think the future will be different than the present based on your experience with the companies that you've backed?

>> Obviously, the big topic that we're tackling and trying to figure out in the near future is the impact of AI. We've

backed a ton of really exciting companies at every layer of the stack and we can talk about that and, you know, that's been part of our strategy.

uh you know from the model layer um infrastructure and tools applications I would break it apart into what do consumers do and what do enterprises do in the AI world and then I have a bunch

of views on how the world's going to be different as it relates to American dynamism you know hardware plus software robotics autonomy stuff like that on the AI side for consumers I think we need to

be really humble about where we are right now but I don't think that we have yet found the dominant in AI we may have the the dominant And you know, OpenAI and Chad GBT has grown faster than

anything in the history of technology.

You know, I think they reach the same scale as Google, something like four times faster.

>> You know, billion people using it. And

they're only monetizing a tiny piece of that, which I think is a really exciting dynamic.

But I don't think that the future of how we interact with AI is going to be a chatbot. Like I just think that's way

chatbot. Like I just think that's way too limiting. I think the big shift will

too limiting. I think the big shift will be uh a sort of what is reactive today to something that's proactive in the future and chat GPT may be able to capture that and I think they probably

have the best chance of doing so but I think the way that we interact with all this stuff is going to change dramatically it's going to have long form memory it's going to be multimodal um and it's going to be proactive it's going to offer us uh you know solutions

and how we do things so I'm super excited about that but I think the open-ended upside of what companies can capture in economics from that is kind

of endless in size. You know, I like to look at uh history of consumer internet companies and what were our perceptions and then what actually ended up happening reality. So I think it's

happening reality. So I think it's instructive to look back at Facebook and Google and I remember when we were in the private markets looking at investments in things like Snap and

Twitter you know 10 plus years ago and we would always sit and say well yeah but Facebook and Google only monetize at X certain amount and you know all the consumer internet businesses are sort of

Psq businesses and you know the P is you know quantity is has ended up being you know billions of users kind of two and a half two and a half billion users or more in each case. Uh, but we always said, oh, you know, Facebook or Google,

they make 20 bucks a user. So, like

that's kind of the upper bound. And fast

forward 10 years later and Facebook and Google make like 200 bucks a user in the developed world. And so when we look at

developed world. And so when we look at things like chat GPT, it's really fun to think about this. It's like, okay, how much time do people spend? What kind of value do they get? How much consumer

surplus is there? And how do we think about valuing that? And it's pretty open-ended, uh, which is which is really exciting right now. So the really interesting thing is, you know, if you look at JHPT and the consumer stuff,

there's like a billion users. They

monetize less than 50 million of them.

And how will they monetize the rest?

That's a really fun problem to try to tackle.

>> Uh I think I think it's hard to describe what it'll be. I think it'll be some form of like an affiliate thing that happens. It's like a new native thing.

happens. It's like a new native thing.

Like it's the the thing I always say to people is, you know, uh we again we got to be humble in how we think about this.

We never would have predicted what a feedbased advertisement is. Like no one would have known what that is because we didn't even know what the feed-based product was. It turns out it's probably

product was. It turns out it's probably the best advertisement format in history. Like it's really really

history. Like it's really really compelling. Um and so it's not

compelling. Um and so it's not surprising that it monetizes really high and and people actually really like it.

Like I really like Instagram ads. So you

know the a year ago this the sort of light bulb went off for me. Maybe it was 6 months ago. Um, I did deep research on, um, you'll probably relate to this, a new baseball bat for my son. And so,

you know, he's 9 years old, and it's pretty complicated. It's like, okay, it

pretty complicated. It's like, okay, it needs to be a certain length and drop and all these certain specifications.

Uh, and, you know, there's there's this year's version and last year's version.

And if I had to do that on Google, like, it would be a total mess. Like, I would I would struggle with it. Amazon, no

chance because of the ads. Deep Research

was really, really, really good at it.

and it kind of solved my problem for me.

Uh, and so light bulb kind of went off for me at that moment. One, the models are going to get so much better. And

two, to me, it's sort of an execution problem of building the capabilities to go execute that stuff on your behalf on the web. And so, I think that's a really

web. And so, I think that's a really exciting future. There's going to need

exciting future. There's going to need to be tons of guardrails built into it.

You got to build a ton of product and piping to do so. It's really hard. you

know, Instagram famously tried to do shopping kind of natively and it it it's just too hardly. But I think that's a pretty exciting future and shopping is just one category. Yeah. Um so, you know, if I take a step back and I think

about AI today, really active users spend almost 30 minutes a day in the products. Like for context,

products. Like for context, users spend like 50 minutes a day on Instagram and like 70 minutes a day on Tik Tok. They're monetizing only a

Tik Tok. They're monetizing only a slight few of them today. Consumers get

a ton of value. there's going to be a ton of consumer surplus available and I think that could lend itself to the creation of a a huge company, massive company. Uh and again I think Judge Bat

company. Uh and again I think Judge Bat is in the lead today. Uh but it's early >> in in that specific area of the world, the sort of pure AI part of the world.

Where do you feel the most different than your peers in what you think matters, what you think is exciting or or not exciting worries you have? Like

where do you feel most divergent >> from your friends?

>> Um I feel like I'm probably reasonably consensus on the excitement on the consumer side. Yeah,

consumer side. Yeah, >> I can put it into context around the sort of upside around price that you get P on the P times Q especially if time spent continues to go up which I think

it will as the models get better and they have memory and things like that. I

think on the enterprise side, one of the lessons I learned from SAS and cloud, which by the way, the advance the advancements of SAS and cloud are tiny

compared to the advancements of what AI is going to do, is I think maybe a little bit more expansively on what the companies can become on the enterprise side. Um, but maybe I'm slightly more

side. Um, but maybe I'm slightly more skeptical about what their ultimate business models will be. So one of the really fun topics that people debate

with with high degrees of confidence uh that I have very low confidence in uh is what is the ultimate business models of these companies and people put up these super compelling slides that are like

hey you know the whole software industry is only whatever $400 billion but look at how big white collar labor is and we're going to go get a ton of that. And

to me that's like a little bit handwavy.

So, you know, there's a couple of areas where the business model has progressed in a compelling way to go tackle that directly. So, customer support is one,

directly. So, customer support is one, but because there's a very discreet task with very simple completion analysis that you can do, it's kind of simple to price it on that.

Like you can shift a business model from a seatbased thing for Zenesk or something to a new business model where if you successfully complete the task, you can charge on that.

>> You know what it's worth. you know what it's worth.

Maybe the next furthest developed area is coding. Um, but it's not completion

is coding. Um, but it's not completion of a task. It's consumption driven. And

especially in the developer world, that whole world is used to plan paying things on consumption. Like it's kind of how it has all shifted over the last 10 years.

Everything else I think is pretty TBD.

It's going to be very hard. And I think when you see major technological shifts, it's very tempting to say, "Oh my gosh, there is so much economic value that all

these companies are going to capture um top down." The reality of doing it is

top down." The reality of doing it is much harder. And you know, I I always

much harder. And you know, I I always say to people like 90% of the technological surplus is going to go to the end users. Like just start with that as the assumption. whether it's

consumer, whether it's enterprise, you know, like a a funny analogy that I heard from somebody else is, you know, how would how is the steam engine ultimately priced? Like it wasn't priced

ultimately priced? Like it wasn't priced based on replacing like 50 laborers. The

competitive forces drove it to a certain price where there was an appropriate return on capital. Um, but the vast majority of those productivity gains went to the end users of those those machines, not the not the maker of the

machines. And so I think something

machines. And so I think something similar will probably happen in the enterprise.

Even with that, you can create the biggest businesses in the world. So, you

know, an analogy would be Apple, right?

Like what would you pay for your iPhone?

>> A lot more.

>> I mean, yeah, that the sky's is the limit. Like 90% consumer surplus is

limit. Like 90% consumer surplus is probably low. Uh, you know, if the

probably low. Uh, you know, if the iPhone costs a,000 bucks or something like that. Um, so, you know, I'd say the

like that. Um, so, you know, I'd say the same for Google. I'd say the same for Facebook. It's going to happen in

Facebook. It's going to happen in consumer. Consumers are going to be the

consumer. Consumers are going to be the ones who realize the surplus. The same

is going to happen in business, but I think the next generation of business companies can still be much bigger than the previous generation of companies given the capability gains. Um, when I last ran into you a couple years ago in person in San Francisco, we were talking

about Whimo and you you were sort of in the mode of like intensely studying that company and thinking about it, which makes me very interested in this class of companies where you heard about Whimo

and self-driving as a service for a really really long time with sort of nothing happening and then all of a sudden, you know, last time I was in San Francisco a couple weeks ago, it's just every other car. And the explosive

nature of Whimo as an example is really cool to watch. There's all these other technologies. You might call them

technologies. You might call them American dynamism and horiz, you know, small modular reactors or like really exciting big technology ideas which are uh you understand the

potential like if we had an in-home robot that'd be awesome but it's really hard to figure out how long it will take maybe similar to how long we took or something. How do you think about

something. How do you think about investing in those kinds of companies where like it's incredibly exciting?

Clearly, if we had it and it worked, it would be really valuable, but it's really hard to know how long it's going to take to work.

>> It's often these are the ones that are the biggest market opportunity, >> right?

>> Like robotics is the biggest market opportunity. Like we we were all

opportunity. Like we we were all obsessed with LL.

>> Yeah, if you knew it was going to work in 5 years, you put all your money.

>> You put all your money into it. Uh I

happen to think it will take a little bit longer. Um, part of that is informed

bit longer. Um, part of that is informed by my experience with Whimo.

You know, if you think like I'd contrast maybe what Whimo does and and you know, increasingly Tesla and some others, uh, with what a robot needs to do. And it's

very different. Uh, you know, uh, a a car needs to basically stay in a lane, avoid anomalies, collisions, go a certain speed limit, find places to park.

>> Sounds simple. Like when I describe it that way, it's it's sort of, you know, it's sort of >> and it's more it's much more complicated than that. But, you know, simply put,

than that. But, you know, simply put, that's kind of what it has to do. I

contrast that with what a robot has to do. Like what does a robot have to do in

do. Like what does a robot have to do in your home?

>> Endless degrees of freedom. Like make a cup of coffee, uh, you know, go do my laundry. But it took Whimo 10 years and

laundry. But it took Whimo 10 years and you know if you go back uh to the DARPA challenge like the whole industry you know decades uh to get to this point two decades to get to this point roughly and

so my expectation is technology is advanced obviously the generative AI techniques can be applied to robotics to help it go much faster but I think it's going to take a long time.

>> So how do you invest in that? So

>> we have an early stage team that is studying all the robotics companies. We

meet them all. We're learning a ton.

we're waiting for them to find, you know, the team that they can do an early stage traditional kind of seed or series A investment in. Um, and then at the growth stage, ideally they find that and we can invest in it or one of these

companies that we're not investors in really starts to work and, you know, we've debated what does it what does it mean to work? Uh, I think we'll know it when we see it. You know, uh, like there

will be things that start happening and customers pulling their products that we will have not seen before. What's the

lesson from Whimo there on what it means to start to work? Like what what do you think in the history of Whimo was the point at which you would have said, "Okay, now like something happened and that makes this more investable."

>> So the interesting thing about Whimo for us, I'll tell you the history of of our Whimo investment. We originally invested

Whimo investment. We originally invested in 2020 in Whimo. They came to us uh to raise outside capital for the first time. So it's just purely funded by

time. So it's just purely funded by Google over time. They thought it would be helpful for employees, for hiring, all that stuff, outside council, all that, diversify the cap table, uh to to

bring on some outside investors. So, uh

some folks invested in it. We were the only VC firm that invested in it. Uh we

invested out of our first growth fund and it was really fun because and this is seeing the future like taking the ride in 2019. It was doing some pretty amazing stuff in in retrospect. uh you

know it could do unprotected lefts, it could avoid construction sites and uh the thing it didn't know how to do actually was like park. You know we got to a parking lot and it kind of like stalled and you know we had to override

and go drive up to the front. Uh but you could see signs that it was it was it was going to be pretty interesting but it wasn't on the road. Uh you know we knew they were going to be conservative

about rolling it out. So Mark and Ben came to me and they said, "Uh, hey, you know, we we got to do this whim way

investment." And I said, "Uh,

investment." And I said, "Uh, I no, like I don't like this at all.

Like this is crazy. It's going to take 10 years. Uh, you know, the valuation

10 years. Uh, you know, the valuation that we come in at is going to be really high." And they said,

high." And they said, >> you know what?

>> Don't care.

>> Don't care. Like this is autonomous driving. Like are you kidding me? This

driving. Like are you kidding me? This

is the mother of all markets. like if

they have the thing that can drive cars autonomously, it's going to be worth a ton. Like stop overthinking it. And you

ton. Like stop overthinking it. And you

know, my team, we had built all this analysis and why, you know, it would take forever and the economics were going to be strained. And so we compromised and we made a small investment in Whimo at the time and I

was excited to to be a part of it. I

just I I thought the returns would be stretched. Fast forward five years

stretched. Fast forward five years later, uh, at the end of 2024, they raised money again and at the end of 2024, they had cars on the road and it

turned out you, to your question, consumer preference slapped you in the face. Like anyone who was in San

face. Like anyone who was in San Francisco who had the choice was taken a Whimo. But at that time, we had the

Whimo. But at that time, we had the chance to invest more money, you know, and it was working. We took that opportunity to to write a much larger check and invest. By the way, one of the really interesting things about Whimo, so you said you see it, you're in San

Francisco, you see it everywhere.

>> Yeah.

>> How many cars do you think they have on the road in San Francisco? Because

they're everywhere, right? Like

everywhere you turn, you see them.

>> 10,000.

>> They have like 400.

>> Wow.

>> Yeah.

>> So, it turns out if your cars are driving optimal routes and uh sort of fully utilized and not running into some of the problems that drivers have, like it's pretty good. And so you can have a

lot of coverage. There are something like 50,000 lift drivers in the San Francisco Bay area and uh Whimo overtook them in market share. It

>> it feels like the appropriate time to disclose that you and I went to college together. The the reason I me the reason

together. The the reason I me the reason I mention that is usually when we get together we don't jump into talking about investing.

stuff >> which makes me realize I don't think I've ever actually asked you like what is your investment like philosophy or strategy or style or taste like like

like what what is it and how did it develop? My style and taste

develop? My style and taste is very much if I were summarized in one line, I like to pay fair prices for great

companies. Like everyone would say they

companies. Like everyone would say they would like to do that, right?

The art in that I think is recognizing where greatness may lie where other people don't recognize that. And so

>> unpriced greatness, >> it's priced but not to the fullest extent. Yeah.

extent. Yeah.

>> Right. Like and so I've studied, you know, the history of technology companies and why they outperform and how they outperform. Often in growth stage investing, >> it it's always on the growth side. It's

like, hey, the growth side is where you get things really right. uh I tell the team that it's like we can make a lot of mistakes on forecasting margins and business models and unit economics and all that stuff but lots of people know

how to do that analysis that's out there. So where can you actually get

there. So where can you actually get edge? You can get edge from product

edge? You can get edge from product insights, market insights, and people insights. And so how do we maximize our

insights. And so how do we maximize our likelihood of doing that on the people side? I'll start there because that's probably the hardest to do and I've gotten it right a number of

times and I think I have reasonably good taste in people. Like I really like a certain archetype of founder. I call him the technical terminator. I'm very close with with Ali from datab bricks. Ali is

the technical terminator. Like he

>> self-evident.

>> It's self-evident. Uh it wasn't self-evident, >> you know, all along. He actually wasn't even the CEO, >> you know. He he became the CEO later.

>> Uh >> but he started the open source project, right?

>> Yeah. He was one of seven. One of seven.

And so he was not the CEO. Uh there was a much more established uh guy who we've partnered with on a lot of companies.

He's he's been a co-founder of a lot of companies. Great companies have come out

companies. Great companies have come out of his lab. Yan Stoka uh in Berkeley.

The thing that I like about these technical terminators is they start technical and then you never know if these people are going to

become commercially minded excellent, you know, sort of business people.

Um, and so you have the grounding, you have the products. Those are the people that are likely to figure out the next product area because they're technical because they're in the products. Um, you

know, Mark Zuckerberg is an example of this. Elon's a great example of this.

this. Elon's a great example of this.

Um, and then over time they learn the business side. So, it's it's been so fun

business side. So, it's it's been so fun to work with Ali because he knows more about like sales ops and hiring processes and reporting lines and all

these things you have to do as a manager uh than probably any of our CEOs, but he learned them all. Like he's just been a sponge. Like,

sponge. Like, >> you have a favorite counter example to the technical terminator like somebody that is completely non-technical?

>> Travis.

>> Okay. Interesting.

>> Yeah. At Uber.

>> Yeah. So one of the elements of people judgment is what is the right founder for the right market, right? And that market was just

market, right? And that market was just a pure battle. Like it was like you needs

battle. Like it was like you needs >> Yeah. Like you fight mayors, you fight

>> Yeah. Like you fight mayors, you fight competitors. And by the way, there there

competitors. And by the way, there there were competitors like you know and so you just needed to be ruthlessly competitive and driven and operationally

intense. And you know that's he's the

intense. And you know that's he's the perfect counterex example to that and we were we were I was an investor in Uber at GA. Uh and you know he he's the

at GA. Uh and you know he he's the archetype but there's a lot more of these technical ones that become great business people in my life. You know

George Curts from Crowdstrike is a great example of it. I I'll tell you one more example which is not as obvious. Dave

from Roblox. you know when we met him I met him you know maybe 10 years ago or something and early days of whether it was actually kind of working and he was technically brilliant and he was so deep

in the product and you know he's the kind of guy that on the surface if you didn't really know him well you would kind of be like oh is he a little bit he's a little quieter and it turns out like he's ruthlessly competitive and he

really cares about market cap creation and like his stock price going up and for the right reasons um you know Dylan from Figma is a great example of this.

Like he's so nice. He's one of the nicest guys in our industry, >> but he is brutally ruthlessly competitive. The new AI guys and and

competitive. The new AI guys and and women like it's been really fun to see them develop this. Michael from Curser, Shiv uh from a bridge who's practicing

practicing cardiologist who has then shifted his attention >> uh to you know building a technology company. He uh he lives in Pittsburgh

company. He uh he lives in Pittsburgh and he commutes to New York uh to work most of the time and uh I was with him in the office the other day and and he said, you know, he's showing me the office. I'm like, oh yeah, cool. That's

office. I'm like, oh yeah, cool. That's

great. That's nice. He's like, "Yeah, I'm going to put a bed over there. I'm

going to start sleeping in there." I'm

like, "Man, you're you're like a a doctor with kids and stuff." And he's like, "No, no, no. I just want to I want to be working all the time when I'm in town." Uh so you know I love that sort

town." Uh so you know I love that sort of relentlessness, intensity paired with you know technological capabilities, product understanding.

>> Um and you know backing people like that, >> they're going to like pour everything they have into winning, >> but they're also more likely to figure out the next things and navigate complex

markets and changing environments. If I

had access to your entire calendar for the last 5 years or something and saw all the companies and the debates where you ultimately didn't invest but almost did, what would I learn from like that

batch of companies and founders? This is

a very humbling job because we make so many mistakes. Errors of commission are

many mistakes. Errors of commission are really painful. Errors of omission are

really painful. Errors of omission are really, really painful, too. And they're

more costly just economically because you can lose one times your money uh if if you get things wrong on an error of commission. But you can forego making

commission. But you can forego making really high returns if you if you get it wrong. There are no common patterns. I

wrong. There are no common patterns. I

would say when we get it right on a on not doing an investment, it's typically for the right reasons. It's typically

because we see something that we don't love about the business quality. You

know, we feel really really really strongly about market leadership. Do you

know the Glengary Glenn Ross movie?

>> Yeah, I know the movie. Yeah. uh you

know the scene with Alec Baldwin, >> refresh our memories.

>> Okay, so Alec Baldwin comes in, there's the scene with Alec Baldwin where uh you know he's he's running like a sales contest. This like a boiler room setting

contest. This like a boiler room setting and he comes in, he's running a a sales contest and he walks in and he's like, "Okay guys, new contest. Here we go.

First prize gets Cadillac. Second prize

gets a set of steak knives. Third prize,

you're fired." Right? And so we've adopted that as a way of describing most of the technology markets that we live in. So we happen to think and I happen

in. So we happen to think and I happen to think strongly and my experience has been the vast majority of market cap creation is going to go to the market leader. And this is probably

leader. And this is probably underappreciated like we see this all the time with our peers in the in the growth investing industry where they say things like yeah you know even the number two player like is going to be

really viable like maybe but like more often than not that's not the case.

That's kind of obvious in network effect driven businesses, consumer internet companies, Google, Facebook, etc. It's it's less obvious in enterprise companies, but it happens just as often.

Like there's no number two to Salesforce. Like Salesforce is

Salesforce. Like Salesforce is Salesforce, workday is workday. Service

Now is Service Now. Like, and you'd feel a lot of pain if you did the number two or god forbid the number three in those markets. In early days of technological

markets. In early days of technological shifts, markets tend to fragment in ways that we don't foresee and they end up being less competitive in certain areas and people kind of settle into different

areas. So, you know, on the model side,

areas. So, you know, on the model side, so far the way it looks like it's played out is it will be more like the cloud industry like it's not going to be a winner take

all. Certain technical advantages seem

all. Certain technical advantages seem uh limited in time frame, right? like

there's kind of you know always this kind of constant leaprogging of the model industry. So I think it will look

model industry. So I think it will look like you know the the cloud industry in the sense that there will be multiple players there will be profit pools for them. It's it's sort of like uh early

them. It's it's sort of like uh early days we we were saying like is this going to be aircraft manufacturing or is it going to be airlines like those are the two extreme ends of the spectrum.

Aircraft manufacturing has high profit margins um because there's really high capital intensity and it's extremely hard technically.

>> So that like would seem to mirror the the model industry. Airlines on the other hand, you know, are horribly competitive industries and you know that they all go bankrupt in the fullness of time. So it seems like the model

time. So it seems like the model industry is going to be like aircraft manufacturers or the cloud industry.

>> Why did cloud play out the way it did?

Like is it just size of market? is that

>> I think it's size. Yeah, I think it's size market.

>> Is that is it that simple that if the market's big enough, you're just going to have multiple winners and winner take all.

>> Yeah, it's size and market. Um to me, it's all that one is all size of market.

Like it's just so vast. And cloud is such an interesting market because the cloud like if you could just independently own AWS, Microsoft, Azure, and GCP, like those would be some of the

most valuable companies in the world.

Like those would be awesome businesses to own.

on the other side of it. You know, my one of my partners, Alex Rampel, has this has this has this statement that he likes to say, which is like the best best businesses in the world don't have customers, they have hostages.

>> That's not actually the case in cloud.

Like, sure, there are some things like egress fees. Like, the clouds are

egress fees. Like, the clouds are anti-competitive with egress fees. Like,

they make it really hard to leave and get your data out and all that stuff, but that's kind of minor. Like,

generally speaking, the customers in that market are well served. Like,

they're happy. like it's been positive some for them you know and at the same time the clouds are really good businesses >> I think the same is likely to happen in the model space and so the market is

going to be so big it will fragment in ways that we don't yet expect and you know even if you're in a number two in terms of absolute revenue size or you

know sort of market awareness uh that's okay what's not okay probably I would think is being in the number two in something

like the dominant consumer, you know, chat interface or something like that.

>> I want to talk about competition in our industry for investment opportunities in the market leaders led by technical terminators or or others. It it's become in our collective careers, you've been

in this specific business much longer than me. Uh but in across your career,

than me. Uh but in across your career, it's become way more institutionalized.

There's way more players. There's way

more money. the people you're up against on a daily basis are probably more talented um sometimes by a lot. Uh so

you have to keep up with that. How does

the competitive describe the competitive dynamic when you are trying to make a big investment in a big exciting company led by a consensus amazing person in a big market like what does that feel like

now? And I'm also interested in how how

now? And I'm also interested in how how it's changed over time.

>> Yeah. So Mark and Ben have told the stories about the origin of starting the firm and you know their experience with the venture capital product and you know why they built the firm the way they

they did and whenever they tell those stories I'm like that's great and man wouldn't it have been fun to compete in that time like that would have been awesome. The market is definitely more

awesome. The market is definitely more competitive now. It's become a lot more

competitive now. It's become a lot more institutionalized for good reason though. Like the thing that I'm telling

though. Like the thing that I'm telling our team and I talk about with my partners now is we're a grown-up industry now. Like this is no longer

industry now. Like this is no longer some little bespoke asset class. When I

started my career, there were, you know, you and I were getting out of college.

How many There were probably one or two technology companies in the largest 10 market cap companies in the world. Now

it's eight of 10. Eight of 10 and seven of the eight are West Coast technology venturebacked companies. Like I feel

venturebacked companies. Like I feel like that hasn't that realization hasn't really fully hit uh you know the finance industry. You know if you look at that

industry. You know if you look at that tech has kind of overtaken all of the market cap creation and is driving you mostly driving force of the stock market and the economy. The private markets

have become a real asset class. This is

something I'm studying now. Uh because,

you know, the venture industry, you know, is sort of seen as like this non small non-scalable thing. Turns out

there's 5 trillion of private market cap that is, you know, up 10x in the last 10 years. And it's honestly some of the

years. And it's honestly some of the best companies in the world. That market

cap represents almost a quarter of the entire S&P 500. It's more than half of the mag 7. So,

I think that we now are in the grown-up in the big leagues and we need to start acting like it. So, we've adapted our firm a lot to that realization.

Um, and oh, by the way, one other comment just on that industry, you know, and how it's changed. We just did this analysis. If you look at our public

analysis. If you look at our public universe, so where do we spend most of our time? It's like software consumer

our time? It's like software consumer and fintech stuff.

the public universe in those sectors, there's less than five companies growing 30%.

It's kind of staggering like that's a low number. Our our portfolio on average

low number. Our our portfolio on average dollar weighted is growing 112%.

And some of these companies are big enough to be you know the the large companies. And you know if you look at

companies. And you know if you look at the small cap universe and the public markets first of all public markets have shrunk by half in the last 20 years. And

if you look at the uh the the sort of composition of small cap public companies, the quality I would argue is so much lower than what is available in the private markets. So the industry is

real. It shouldn't be a surprise that

real. It shouldn't be a surprise that the competition has intensified. I think

about the competition similar to how our venture folks think about it, which is the market has sort of become a barbell.

um you know and so we're faced with the the large multi-stage firms that have very strong venture practices on the one hand and those are the fiercest competitors for us. I respect my peers

there. They're trying to play the same

there. They're trying to play the same game as us which is when we have something special at the series A or the seed like we want to hold it really tightly and they want to do the same

thing and sometimes they're effective at it. Uh sometimes we're effective at it

it. Uh sometimes we're effective at it but we have to kind of battle that out.

on the other side is you know on the venture side it's sort of bespoke kind of uh you know in the retail analogy there's like the the superstore like the Walmart and you know Amazon which is

sort of how we would get characterized and then the other side is sort of like the Gucci store you know or the Prada store which is like deep specialization so you know Nat and Daniel would have

been an example of that you know Ilad you know is an example of that and then there's many others that do a really good job, you know, at what they do. So,

you know, I have respect for a lot of the crossover folks, you know, who are in our world and and have built private businesses and and have done a good job with it. So, what do you do to beat

with it. So, what do you do to beat these people? Like the actual extreme

these people? Like the actual extreme versions of the answer, like the lengths that you're willing to go to to win. I

>> I think you would love to have some story that's like sensational in the moment where we did something crazy. The

reality of the growth stage business is we win deals based on years of relationship building. You know, we

relationship building. You know, we recently did a deal where the founder, we had sort of worked the founder so hard that, you know, he called us and uh and and he was like, "Hey, I'm ready to

do this. I'll just talk to you." And I'm

do this. I'll just talk to you." And I'm like, "Oh, wow. Okay, fruits of my labor. Like two years of this. This is

labor. Like two years of this. This is

good."

>> Then at that point, >> he's he it's one it's one of the best companies in the market. And the dynamic that we are faced with is okay, this is awesome. I got a clean look. I know for

awesome. I got a clean look. I know for sure if he was going to market, he would get a higher price than what he just told me, but can I bear the price? And

so that's often the exercise that we have to go through as growth investors is what do we know differently about the product or the market or what are our expectations

that will allow us to do it that maybe, you know, aren't as obvious. And so what what are you doing in those two years that earn you that right?

>> Maybe that's where the extreme measures are.

>> Helping them as if we were already investors in their company. And so

helping them with candidates, helping them, customers, spending quality time and showing that we understand their business. Like often that's the biggest

business. Like often that's the biggest thing. Honestly, the for the companies

thing. Honestly, the for the companies where we're not existing investors, oddly enough, sometimes it's easier because our platform is so strong, our brand is so strong. I'll give you

another fun example, which was, you know, Dylan at Figma. When we first invested invested in Dylan at Figma, you know, I was considering joining the firm from GA. This was 2018. You know, one of

from GA. This was 2018. You know, one of I knew all the guys already at the firm.

And so, I'm spending time with Peter Lavine, who was one of our partners. And

uh you know I come in and I'm like Peter what what's top of mind? You know how are you thinking about the growth business? What can I tell you? And he

business? What can I tell you? And he

was like we need this tomorrow. We got

to invest in Figma. Like we need this tomorrow. Like we I don't know how we

tomorrow. Like we I don't know how we didn't you know we we we missed it. We

you know I was late to it. Like we just need a growth business and it was a growth deal and we should have done it.

It's crazy. We did GitHub early. How did

we not do this one? And he was just like apoplelectic you know like I I need this. And so that was very encouraging,

this. And so that was very encouraging, exciting. So day one, you know, I told

exciting. So day one, you know, I told you I knew the six companies in the portfolio. I also knew like the five-ish

portfolio. I also knew like the five-ish companies that I really loved outside the portfolio. You know, Roblox was one

the portfolio. You know, Roblox was one that I was close to. Figma was another.

And so from the moment I joined, we had done the fullcourt press on Dylan. Like

he came to our summit. You know, it was Mark and Ben bear hugs. Like he was really into crypto. We bear hugged him on the crypto side. Like we did everything we could with him, helping him with a board search. who placed a

person in our network onto his board like we were trying to do everything and you know trying to catalyze a deal and he was like I'll let you know when I'll let you know when >> so co strikes and he calls us and he's

like now's the time like oh my god this was in the moment of co where we all thought the world was going to end you know everything was screwed >> stock market was way down you know I felt like oh great good timing uh so you

know at least we got the luck and so he you know he came and pitched we had done all the work and we're having the debate as a team, you know, was taking this traditional me and my team were taking this traditional growth lens looking at

it and we're like the market for designers is market for designers is not that big. You know, it's like really

that big. You know, it's like really small and if you do the math of the market size of designers and what they charge, you know, just I don't think that the price makes sense at $2 billion, like this is just it's too

limiting. And our venture guys were

limiting. And our venture guys were losing their minds in this discussion.

They're like, you guys are totally missing the point. like the number the ratio of designers to engineers is basically double for the modern

technology companies. So that's a

technology companies. So that's a leading indicator. Everyone is going to

leading indicator. Everyone is going to you know that ratio is going to change.

There's going to be double the designers in the world. More importantly, the whole engineering to design process is changing and there's sort of a a melding that's happening of front-end

engineering and design. And so thinking about this as the market for design is way too limiting. and so you're just missing the point. We were debating it and you know it was like speaking past

each other and finally Ben called it off. He's like, "Okay, all right." Like

off. He's like, "Okay, all right." Like

we're not going to solve this tonight.

You know, ultimately it was it was a call on the growth fund side and I slept on it and I woke up and I was like, "Look, this is an exceptional business model and we're kind of squinting to

believe enough on the market size, you know, great founder, great business model. Is the market good enough?" And

model. Is the market good enough?" And

I'm kind of happy to take that risk. The

risk I don't want to take is quality of business, quality of founder, but you really had to have a nuanced view of the market in order to get there as a like with a traditional growth investing lens. And so fortunately, we got there.

lens. And so fortunately, we got there.

You know, it worked out really well. I

bring up that story one to say that's an example of something where you kind of have to the price is the price and you kind of have to figure out if you can take it like if you're willing for the very best of the best companies. But

two, I think it speaks to the advantage that we have and what you need to be successful in growth investing. Like you

need those product and market insights or you're just going to live in a spreadsheet and die in a spreadsheet.

And so uh you know everything that we've done or I've you know I have done and our our team has done to design a process of tightly integrating with our

early stage teams has been in the spirit of optimizing insights around people products and markets and I think that's where you actually get success. One

thing that I'm trying to do more of because I'm just interested by it is the to hear about like the minutia of your day and life like the in in this

incredibly competitive environment. I've

become interested in how some of the best investors literally just like run a given day.

>> Yeah.

>> And what that looks like for you and and I think you'd be surprised like how in the weeds I'm interested in learning about. And so like air on the side of

about. And so like air on the side of detail, like I'm just I'm just curious what the actual life of your job feels and looks like. You know, Bob Swan, who

is a a longtime mentor and friend of mine and and an operating partner at our firm, gave me this really good advice that he and John Dano at the end of every year always went through an

exercise where they spent like two hours looking at their calendar from the year and then they had an objective of cutting 30% of stuff that was on their calendar and that, you know, there was a

way for them to make sure that they were giving responsibility down to the people on their teams. but also that they would get leverage. So, he's given me that and

get leverage. So, he's given me that and then he reminds me of it when he can tell I'm too busy uh with things that I shouldn't be. And so, I think I'm like

shouldn't be. And so, I think I'm like not very good at this, but I'll I'll answer the question anyway. I try to make sure I'm spending

adequate time meeting companies. So

right now our investment business looks something like 2/3 relatively known companies and one-third like kind of newer stuff. But I want to make sure my

newer stuff. But I want to make sure my time is spent pretty differently than that. Like I want my time to be 20% on

that. Like I want my time to be 20% on those known companies and spending time with people like Ali and you know the founders Vanderol like whatever it may be flux safety but I want most of my time spent on the new stuff like because

I need to be learning about those new markets and so constantly meeting with AI founders talking to to smart AI employees and making sure that I'm deep and conversational and have an understanding of those markets. So I

spend a lot of my day on that. I've

started to kind of move away from like doing one-on ones and I'm like, you know what? I don't need to schedule one-on-

what? I don't need to schedule one-on- ones. I talk to my team all the time.

ones. I talk to my team all the time.

I'll call them after hours. I've started

to very deliberately block off hours and days. So, I block off two hours every

days. So, I block off two hours every Tuesday, two hours every Thursday. Um,

and then I also put an hour and a half block twice a week in afternoons.

And that often gets consumed with things that are pressing and you know I need to make calls or whatever it may be. But I

find that I learn a lot and develop a lot of my own thinking just by having think time. You I'm the kind of person

think time. You I'm the kind of person that has 20 things open in the browser and I want to read them all and then I don't get to them. Uh so unless I block off a bunch of time I actually just don't find that I'm spending the time

learning as much as I should. You know

that's I'd say trying to learn about companies, spending time with entrepreneurs. I want to be 80% of my

entrepreneurs. I want to be 80% of my time and then 20% is spending time with founders, you know, internal management.

Um, you know, time shift when we're fundraising.

>> How many new companies do you think you meet a week?

>> We as a growth fund probably meet 30 >> companies a week. Now, not new, probably 30 companies a week. I personally

probably meet 10 maybe somewhere around.

>> How do you run those meetings? Like if I came into one of those 10, what is the structure of the meeting?

>> I keep the introduction super brief. I

like to jump in and say, "Hey, why don't you please spend, you know, five minutes explaining to me the strategy and your vision?" Because I've read your website.

vision?" Because I've read your website.

I know a little bit about the company.

I've talked to some customers maybe, but like I need to hear the vi like the what is the bigger thing. Like what do you want to tell you? tell me uh and then I just ask questions for 20 minutes.

>> Okay, so what do you think about this?

What do you think about that? This may

be a stupid question, but can you tell me about this? And I find that to be a lot more effective. Um and you know, the ultimate compliment that we get from a founder is like, >> thanks, you've done your research or you

know, hey, thanks for asking that question. That's pretty that's pretty

question. That's pretty that's pretty smart.

>> If you think about the reasons why you do this versus something else, what are the most important ones? Like why why don't you why aren't you a founder? Why

don't you work in some other industry?

Why don't you have your own firm? Like,

there's other things that you could do.

What are the most important reasons why this is the thing you do?

>> So, my wife would say that I have a low attention span. What she means by that

attention span. What she means by that is I'm interested in a lot of different things. And this is a really cool way of

things. And this is a really cool way of getting to learn about tons of new stuff. I suspect this is the same reason

stuff. I suspect this is the same reason that you like to invest is how lucky are we? We get to sit and spend time with

we? We get to sit and spend time with the entrepreneurs who are building the most interesting companies in the world right now. We get to learn about the

right now. We get to learn about the most cutting edge technology stuff that if you were in the public markets or just in a job, you would never get a chance to learn about. So I love to

learn and I love to be around, you know, kind of great founders as they're exploring really interesting things. So

that that part of it is really really attractive. There's another part that

attractive. There's another part that plays to a totally different side of me which is this business is a scoreboard business and like I convey this to our

team all the time. There's a scoreboard in this business and our expectation is that we win. Now, it's a very longdated scoreboard, you know, especially in the venture side, but on the growth side even, it's a pretty longdated

scoreboard, but at the end of the day, like we have to put up returns like our customers are our founders and our LPs.

And on the founder side, we need to make sure we do a great job with them and they're sort of a virtuous flywheel if we do.

On the LP side, like it's pretty simple.

Are we doing a good job generating returns? So we A16Z, we're known as sort

returns? So we A16Z, we're known as sort of running ourselves a little bit differently as a firm. Mark and Ben really drive that. We do things like, you know, Ben runs every new employee on

boarding and he runs through our culture document. When you sign an offer letter

document. When you sign an offer letter at our firm, you sign your offer letter, but you al also have to sign our culture document, which lays out our cultural principles. I also created a subset of

principles. I also created a subset of principles that I wanted to convey for our growth fund. the scoreboard and we expect to win is a very direct way of

saying like we better be competitive.

I have one that is we are the Yankees and we're going to act like it. And what

I mean by that is not, you know, we're going to be arrogant or, you know, we think we're the best team or something like that. What I mean by that is we're

like that. What I mean by that is we're lucky enough to be a part of a firm that has an incredible brand.

And so we're going to run our team very, very high performance. Like if you're on the Yankees, you better be performing.

Like this is the big stage. And so our expectations for our team, we're very collaborative. We care about winning as

collaborative. We care about winning as a team, but you better be good. Like you

better be doing your job really well.

You better be working hard. This is one of the things that maybe is not as obvious to people. It wasn't as obvious to me actually until I joined the firm.

It's so funny when I when I was considering it, my perception from the outside before I really started the process was like Mark and Ben, I don't know, they're kind of they're like celebrities semi-seleelebrities like

do they really work hard? They got all these other interests. And I got in and man, it is a competitive place. Like we

are very intensely competitive. We want

to win. And everybody works really, really hard. like no one is resting on

really hard. like no one is resting on their laurels. We're all constantly

their laurels. We're all constantly chatting non-stop like late at night.

We're all working hard. We're kicking

around ideas. And I love that. I love

the dynamic of of partnership. Uh but

high expectations around performance on the, you know, why am I at A16Z? Why

don't I run my own firm? I always tell people kind of have a dream job. Like

this is awesome. I got to join a firm that was on the top of their game. They

were on the ascent. Um, but there was a a real latent opportunity for us to build a franchise on the growth side and I came from a place with a really strong

culture at GA. Uh, but I joined a place that is full of optimism and I think you need that in in growth investing. Like

that is the number one ingredient is you got to be optimistic. You got to be able to see what can go right.

But I also got a chance to hire the team. I got to set the strategy, set the

team. I got to set the strategy, set the investment process, take what I felt, you know, were some of the learnings that I had, which were great and, you know, bring those things with me and

leave some things behind. And so, for example, one of the things that that we set up at the outset, was a a bit of a different investment decision-making process than a traditional growth equity

investment firm, right? So, most growth equity investment firms have an investment committee. It's central. you

investment committee. It's central. you

go, you present, you kind of battle to get the votes, >> they they disappear and then the smoke comes out and like here's the decision, here's the decision. What we decided to do at the firm in the growth fund was do

it totally differently. So, we were going to actually make the decision process just like our venture process, which is single trigger puller.

>> The expectation I have set with our team and that and that Mark and Ben have sort of conveyed and and and I think we do a pretty good job of is you got to be intellectually honest. You've got to be

intellectually honest. You've got to be transparent and we openly expect disagreement. But once you disagree, you

disagreement. But once you disagree, you disagree and then you commit. I think by doing it this way, you encourage people to fully explore the risks of investing

and fully explore the rewards. You're

never in this temptation to sell or to politic for a vote or try to influence someone's decision for the wrong reasons. like you really like

wrong reasons. like you really like something and you really want to push.

We don't have that dynamic. So I think it I think it allows us to more openly explore the merits of an investment and I think it's been you know a reasonably good process and and we're small and so

we you know we move very fast. We do

this you know very iterative iteratively. It's not like we need to

iteratively. It's not like we need to have a Monday investment committee process. Like my first investment

process. Like my first investment committee uh decision was, you know, before I even joined the firm and it was, you know, Mark Scott and I having breakfast and we were deciding on an investment at breakfast. I like to keep

it informal, but we want to make it rigorous at the same time. The other

thing I did that's a little bit different is when we hired the team, by the way, my I feel very lucky. It's one

of the most special parts of the job for me. It's about 10 investors. So, it's

me. It's about 10 investors. So, it's

pretty small. The reason we can be so small is because we have the early stage teams. But, you know, a cultural trait that I think we've done a pretty good job of building is just collaboration and and the willingness to roll up your

sleeves and help people as part of the team's sort of promotion criteria, evaluation, etc. I put in there contribution to collective investment

judgment. Like entry level, like from

judgment. Like entry level, like from the start, this is part of your job. you

better be contributing to our collective investment judgment and it's something that we're going to evaluate you on from the start and so it's a little bit different you know for a junior person to be faced with that a lot of times the junior folks when they join they have to

find their footing and you know when do they chime in when do they not but I think it's made us you know better as a as a team at making decisions >> if you think about the environments that are better or worse for growth investing

of the type that you do what are those conditions like if you could cook up in a in the kitchen like the perfect environment for you to be deploying dollars. What are the features of it?

dollars. What are the features of it?

>> Well, the optimal would be early product cycle, bad capital cycle, >> but those rarely happen in, you know, coincide with one another. If I had to pick, I mean, it's it's all early

product cycle for the style of growth investing that we do.

>> What does that mean early product cycle?

>> It means we're at the outset of a new technological change, >> beginning of that is going to propel.

Yeah. A new market wave. And so maybe it's easiest to highlight uh in retrospect.

>> It turns out that when you and I were starting our investing careers like we started at a really good time like >> you did I was in public markets.

>> Well you were in public markets and so you had to deal with GFC and stuff.

Notwithstanding that that's capital it's capital cycle that one.

>> It turns out and it's it's obvious in retrospect. It's really hard to feel it

retrospect. It's really hard to feel it in the moment maybe less so because AI is so well covered and you know the question is are we in an AI bubble now?

not is there a good product cycle ahead of us? Um but you know it turns out that

of us? Um but you know it turns out that we had at the same time we had the mobile uh we had cloud SAS e-commerce all at the same time. Uh and that was a great setup for us. If you look at all

the mistakes that we've made, you know, as an industry 2021 is very well covered. I always tell people the

covered. I always tell people the biggest mistake from 2021 is that we were actually kind of late product cycle. And we just didn't realize it at

cycle. And we just didn't realize it at the time. There was a bit of a head fake

the time. There was a bit of a head fake with COVID. We didn't realize we were

with COVID. We didn't realize we were late product cycle. And what that means, you know, in practice is the ideas are just worse. The market opportunities are

just worse. The market opportunities are worse. It's just harder to go be

worse. It's just harder to go be successful right now. You know, when I talk to our investors, our LPs, they're all ask me like all of the questions are, you know, are we in a bubble? Like

is the market too hot? How are you dealing with valuations? And I'm like, look, we're we're trying to be very balanced about this. At the same time, 10 years from now, there's going to be a bunch of really, really great companies.

And so, we got to be in the market on the field. Uh, it turns out that, you

the field. Uh, it turns out that, you know, the last two years coming out, you know, 22 to kind of early 25, I think we're a really good period. I think this is going to be a great a great vintage

of time to have been investing. You

know, we also have been surprised at how long the companies have stayed private.

Like, it's they've stayed on the they've stayed on the bingo card for us longer than we expected. Got it. And that's

been great because we've converted those in a really, I think, in a really, you know, attractive way. You know, if you look at the last year of our activity, our portfolio dollar weighted is growing

112% and we entered at 21 times revenue.

And so I'll have this debate. First of

all, I recognize that revenue multiples are flawed and all that. Uh, especially

for traditional investors. If I could invest for the rest of my career in 112% growing companies that are really really great and good in markets at 21 times revenue, >> I would do it in a heartbeat. I would do

it in a heartbeat. I think that's way less risky than something where you're buying, you know, a 12% grower in PE for 15 times Ebatop because growth just

takes takes care of so much for you. I

think above 30% growth, the market still doesn't fully value the growth rate.

>> You know, it's Why why is that the case?

>> I think it's just hard to model uh you know my conclusion. I' I I've studied all these companies that are you know I called them the model busters but like I've studied all these companies. It is

just so hard for any investor to build a five or 10 year model where where high growth persists. It's just not natural.

growth persists. It's just not natural.

like the natural inclination, you know, no one built a financial model for Google or Visa that had them growing 20 years into existence at, you know, 15 or

20%. Like that just it would just be

20%. Like that just it would just be totally unnatural to do. So, you know, if you look at the moment of the iPhone, and this goes back to the point about product cycles and how much you can get

surprised in 2009, if you looked at consensus estimates for Apple and then compared for for 2013, so 2009 consensus estimate

for the year 2013 and compared it to actual performance in 2013, consensus estimates were off by 3x.

Like, that's a massive number. And

that's like the most covered company in the world.

>> So I think you can be surprised on growth on these things. Like I get a big kick out of that. I try to learn a lot about it. But I think it's it's not natural to

it. But I think it's it's not natural to model anything that way. Like it's so natural to just say, "Hey, this company's growing 80%." You know, then they're going to grow 65, then 50, then 40, then 30, then a terminal growth

rate. And it's very different than a

rate. And it's very different than a company if it grows 80 and then the growth rate persists 75, you know, 65 like it's like a 3x difference in your valuation. And so you can just get it

valuation. And so you can just get it massively different. So that's why I

massively different. So that's why I love high growth. I mean, it's obvious that's the math behind why why I love it. But, you know, again, it's it's it's

it. But, you know, again, it's it's it's actually just hard to appreciate it because it's not natural uh to build a model that way.

>> You and I have talked before about this idea of like push versus pull companies.

Can you describe that difference and how that's an idea that you care about when evaluating them? It's it's magic when

evaluating them? It's it's magic when you find a pull business. I have a post-it note on my computer in the office that says, "Is the market

demanding more of your product?"

It's the most special thing when it happens. And and by the way, a lot of

happens. And and by the way, a lot of these AI companies, like what's so magical about the way ChatGpt has grown?

It's a billion users. Like it's organic.

It's all brand. And the shocking thing about that one, by the way, is it doesn't have a network effect. Like that

was that was one of the more surprising things for us. Is the market demanding more more of your product is probably the most important question that we can answer because when it happens,

especially in consumer, it it tends to create the most special companies in the world. So, you know, we've seen it in

world. So, you know, we've seen it in companies like Roblox, you know, when it really works. And that one has sort of

really works. And that one has sort of two network effects and so it's it's super special. Um, we also see it in in

super special. Um, we also see it in in companies that aren't network factor consumer. Like in the case of Anderol,

consumer. Like in the case of Anderol, like turns out the market really really really is demanding more of their product. And there's many reasons for

product. And there's many reasons for that. We've sort of reached all at the

that. We've sort of reached all at the same time this confluence of AI capabilities, autonomy, you know, sort of knowhow and how to navigate

governments mostly from alums of companies like Palunteer uh in SpaceX at the same time that we have a desperate geopolitical need. And so the

market is demanding more of their product and that's really special. One

of the things that I say about push businesses which is you know you got to go sell it like sometimes those are really successful and there's industries where this is the case like cyber security and things like that they don't

tend to get easier over time >> like they tend to get harder like if you have to go sell or market your product the bigger you get often it gets harder >> and so that's not always the case.

Sometimes you get sort of increasing returns to scale from brand and things like that. Um, but especially on the

like that. Um, but especially on the consumer side, it almost always gets harder if you're a push business. Tik

Tok maybe is the exception to the rule where they pushed it early.

>> They pushed they pushed it early and so aggressively.

>> And obviously, you know, if you're if you're Facebook, you probably sit around and think about that decision, >> you know, forever. Maybe it's not even a decision. uh I wasn't on the inside

decision. uh I wasn't on the inside obviously but you know obviously the growth of Tik Tok was fueled by advertising on Facebook in large part which is is is kind of crazy to think

about but you know especially if you're a sort of Google or Facebook driven ad business like it almost never gets easier uh it it always gets harder and and Google and Facebook are the ones who have kind of accumulate better economics

over time you know at the expense of the people who advertise on them. So yeah,

the push versus pull thing especially like so right now we talk about this in the age of AI. If you gave us I think there's sort of like how do we assess AI businesses right now is an interesting thing. One is ease of customer

thing. One is ease of customer acquisition and we see this with like the really really special ones like cursor you know which is sort of been largely viral growth. It happens even with things that need to be sold like a

bridge like you got to go sell to hospital systems. It turns out like hospital systems are dying for this because the doctors love it. It's really

good. It saves them a lot of time and it's really valuable. So, ease of customer acquisition is something that, you know, is sort of a must for us in this AI wave. Um, the second is customer behavior, customer retention, customer

engagement. There are some head fakes

engagement. There are some head fakes that we've seen of things that grow really fast and then they kind of fall off and they're experimental. So, you

know, the the things that have sort of durable behavior, things like cursor, you know, where the users really really use it ideally or increasingly use it over time. Harvey is an example of a

over time. Harvey is an example of a company where as the models have gotten better, customer engagement and usage has actually really grown. It actually

took kind of a step change which which we've seen. Uh which is interesting to

we've seen. Uh which is interesting to see because it kind of happened at the same time as reasoning the reasoning breakthroughs. We were like oh that

breakthroughs. We were like oh that makes sense actually like lawyers need to reason and turns out like models got really good at reasoning and people use the products a lot more. And then

there's gross margins. And we kind of give a little bit of a pass on gross margins. Right now, we're in this funny

margins. Right now, we're in this funny environment where, you know, latestage SAS cloud. We would look at a company

SAS cloud. We would look at a company and it's like, oh man, if you're not 70% plus gross margin, you're not really a SAS business or cloud business, whatever. And, you know, that's going to

whatever. And, you know, that's going to be a knock and people will trade you differently. And that's when you get

differently. And that's when you get valued as, you know, revenue versus gross profit or whatever. Now, it's like a badge of honor to have low gross margins because we're like, oh, at least people are using your AI products. you

know, if we see like we get these pitches and they're like, I'm an AI thing and I got 75% gross margins. I'm

like, well, no one's using the AI stuff then. Like that's doesn't really seem

then. Like that's doesn't really seem like an AI product to me. You know, we give a little bit of a pass on that. The

expectation is the cost, you know, is going to continue to go down.

>> Just the inference cost.

>> Inference cost is going to go down over time. I mean, there's

time. I mean, there's >> so many existential questions about market structure, you know, that will predict inference cost. Uh, but, you know, history of technology would would suggest that it's going to go down over

time. um you know it's been the the cost

time. um you know it's been the the cost of you know inference has gone down at the same time that reasoning happened and so token token usage has gone way up

uh so you know you haven't yet seen any improvement in gross margins but I think you know over time that's that's likely to happen >> you basically just not care like if a company has 0% gross margin for example

but the revenue growth and the customer love and all this kind of stuff the poll is all there does it round to we don't care So there's a big difference between having 30% gross margins and 70% gross

margins. So we do we do care. Our

margins. So we do we do care. Our

expectation is if you're producing a lot of customer value and if the models get a lot better over time, you're going to increasingly produce customer value that the cost is going to go down. There's

not going to be so much market power the model providers that it's going to settle out where these businesses are probably higher margin businesses. I

think they'll be lower margin businesses than SAS businesses. You know, maybe they end up as 50% margin companies as opposed to 80, >> but the size of the impact and the usage and the amount that they'll be able to

capture to our point on business model earlier is probably so high that it it's fine.

>> How much do you care that the way the product behaves and the way it's distributed is like truly singular and different than competitors versus just like the best of a class of company?

There's sort of a foundational point which is every great company either has unique product or unique distribution.

The best companies in the world have both. The best companies in the world

both. The best companies in the world have such unique product that it leads to unique distribution.

But if you don't have either of those, >> what's your favorite example of that?

I'll use a a recent one um that you know the the product you know is so good that people just naturally have gravitated to it is cursor like you know and again maybe in the fullness of time that'll

get harder uh you know but GitHub GitHub is a great example of this right uh I'll tell a funny story about GitHub too so GitHub GitHub was so special of a

company that for a long period of time they never actually talked to customers so the first time I ever met GitHub They were like, "We got to tell you

this. This is so awesome. We sold to

this. This is so awesome. We sold to Walmart and they're paying us 400,000 bucks and no one ever talked to them on the phone." We were like, "Wow, this is

the phone." We were like, "Wow, this is an incredibly magical product and an incredibly magical market." Just imagine if you had talked to them on the phone.

Like what would they have paid you if you just called them on the phone? Like

they probably would have paid you $4 million. you know unique product that

million. you know unique product that leads to unique distribution with a founder that wants to optimize the situation. So, you know, the AI the AI

situation. So, you know, the AI the AI founders like I'm I'm not the one involved with cursor uh but you know Michael is a very special founder and his team they recognize what they have

and then they are aggressively pursuing the enterprise at the same time and so that's a really good combination where you have unique product you have great product people love you know that leads to some uniqueness of distribution and

then you can build on that advantage by saying hey we have all this bottoms up use like we're going to go sell enterprises and so you know a big part of what we do as a firm is we you know help to facilitate co you

know customer introductions customer new business we call our go to market function they're referred to as EBC's you know sometimes and we get notes after everyone and this is the most fun

thing in the world of AI because we get these notes and like in the case of cursor every single time it's like immediately to Pac immediately to Pac you know proof concept whatever uh

immediately to Pac and like oh immediately to you know fullale And like the C you can see that like that's actually incremental data for us in making decisions but you can see it like

it is magic uh when when it happens. Um

and so Martin led the A of uh Kurser you know one one of my partners who leads our infrastructure fund and after one of these emails he chimed in and it's a big

it's a big list. It's like 100 people on the list or something. Um he he wrote product market fit. And so now we're like, "Oh, you know, PMF is now

PFMF." Uh, and so you kind of you when

PFMF." Uh, and so you kind of you when you see that, you know, that's unique product, that's unique distribution, and like you have a founder, founding team or, you know, full full set of employees

who really wants to optimize it. Like

>> what are the tradeoffs of the way that Andre is structured? Like no firm is perfect. Like there's there's choices

perfect. Like there's there's choices for how you have structured and nested the team. Lots of different groups,

the team. Lots of different groups, leaders of of groups like you. What are

the negative parts or the negative parts of the trade-offs for how Andreson is structured versus like a more monolithic structure or something that was just different? Our strategy for scaling is

different? Our strategy for scaling is pretty well covered. But effectively,

we think scale allows us to bring more power to the entrepreneurs and give them a greater chance to be successful in the market. That's the fundamental that's

market. That's the fundamental that's the fundamental thesis be behind the scaling for us and with more resources you can bring you know more resources to

bear for the entrepreneur. So for us when I joined every single Monday and every single Friday we used to sit in the room together all of us and we'd hear all the

pitches and then we'd have long meetings to talk about each of them all as a group and so you know Dixon was leading our crypto fund and you know we'd have bofund pitches and we'd all listen to

all of them and then we'd all debate and then we realized at a point like that was not the optimal use of time you know like Dixon weighing in on a like you know bio investment and vice versa like

probably doesn't make sense and you could extrapolate that out to a bunch of our you know a bunch of our investment processes. So we decided to decentralize

processes. So we decided to decentralize Benmark decided to decentralize the firm sort of put you know more power down into the investing teams that ran each

investment fund and uh the reasoning behind that is twofold. one, we thought it would allow us to have better expertise around the table. Like if

you're only just fully deep in infrastructure or applications or American dynamism or crypto or bio, that's an advantage. It's both an advantage in making decisions but also an advantage in go to market with the

entrepreneurs. And then secondly, if we

entrepreneurs. And then secondly, if we are going to scale, you can't scale an organization with like 25 or 30 decision makers around a table. It's too hard.

like you can't make a trade-off between should we put an incremental dollar into a bio fund investment or a crypto investment or um how should we think about reserving this verse that it's too hard and so we we shrank the size of

decision makers by doing this to a smaller group who's in charge of their own funds um and so far that's working really well and I think that's mostly a function of the fact that our early stage folks they're really good and

we're all really collaborative the only trade-off that we have at the growth fund is selfishly that process that I described where we all sit around the table. It's kind of valuable for me

the table. It's kind of valuable for me like you know it's good for us to have access to all information at all times because we sit across all of our early stage funds. The way we operate is we

stage funds. The way we operate is we invest across all of our sectors.

>> What what percent of the investments you make did the firm have a prior investment in? a little over half. And

investment in? a little over half. And

then if you take the number of investments, so if you just do it by dollars, it's a little over half that are pre-existing venture investments.

And then if you add the dollars that we're investing in pre-existing investments that were pre-existing growth fund originated investments, >> it's something like followons, it's something like 70%. So like 70% of the

dollars that we're investing, >> like we got deep knowledge on on the companies. Uh, I call it game film. Like

companies. Uh, I call it game film. Like

we just get like I talk about game film all the time. You know, we it's so important when assessing an investment, when assessing a founder, you know, game film is not just numbers. Like it's

>> How do you do reserving in the growth fund? Is it materially different than

fund? Is it materially different than elsewhere?

>> When we first started the growth fund, I was like, Scott, zero reserves. Let's do

it. Every single dollar is going to have to be, you know, scrutinized for literally every dollar. It turns out that's not really practical. Like, you

need to reserve a little bit. So, we

reserve a tiny amount. And this is for small follow-ons where, you know, our participation is important, but we're not a lead. We do zero reserving for large investment amounts that we think

we're going to make in a company because I think that would lead to lazy decision-m, >> you know, we'd say, "Oh, well, we reserved for it. Let's do it."

>> So, you just treat it as a new investment.

>> Every single thing is a new investment.

So if you look at our largest investments in the growth fund and just run down the list, you know, uh data

bricks, uh SpaceX, Andrew, OpenAI, XAI, Flock Safety Figma Stripe Coinbase like they're across all they're most of them are across multiple funds. That's

kind of by design. Like we want it we want we want to be flexible and say, "Hey, if we're super excited about a new investment, it's fine. Just keep going."

We have no target metrics for inside the inside the fund verse outside the fund.

>> We have no target metrics for industry like you know infrastructure versus American dynamism versus crypto or whatever. It should always be best ideas

whatever. It should always be best ideas when but I you know manage the fund and so I closely track like how are we doing on those metrics and and and generally speaking like thematically do we feel

like the fund is a good reflection of what we see as the opportunity set for the next 10 years. C

>> can we talk about selling? This is such an interesting topic to me because you can ask lots of investors that invest in private markets like when and how they sell and most of the answers you hear

are fairly simple heristics like one you hear a lot is you know when there's a crystallization you sell a third hold a third hold a third forever Fredson yeah like now later that'd be one example

there's lots of you know similar heruristics how do you think about especially because you're investing at the growth stage probably closer to the opportunity to sell to to another investor or the thing going public. Talk

talk about what you've learned about selling and just how you've done it so far.

>> Selling is it's so hard to do this job.

We've tried a number of different variations. So I think it's different at

variations. So I think it's different at the venture stage. So like your Fred Wilson model like the third third I think it's totally sensible you know cuz he's coming in extremely early and so you know for him that's relatively

simple. You know, we have our own

simple. You know, we have our own version of it's not algorithmic but semi-algorithmic decision- making for the early stage and you know we take

some very simple qualitative things like is the founder still running the company which we >> value a lot >> value a lot and then a sort of qualitative are they the market leader that we feel great about and if so we

would buy bias to hold longer and if not we would buy bias to you know exit sooner. We also try to overlay an

sooner. We also try to overlay an assessment of how it's valued versus performance, which is really, really hard. Um, and so I would say we've been

hard. Um, and so I would say we've been fortunate in that generally we've gotten it pretty right.

>> Why don't you buy whole companies?

>> One of our folks in IR asked me yesterday like, why haven't we done a buyout fund? I think culturally

buyout fund? I think culturally it's totally different than what we do.

Like all that we want to do and all that we stand for is helping the next generation of companies go beat the incumbents.

>> And so culturally buying the incumbent and trying to make them last as long as possible and squeeze as much as they can out of their customers or or whatever it may be, it's just culturally

antithetical to what we do.

>> What are the most interesting strategies or things that Upstarts do to beat incumbents? Like what are your favorite

incumbents? Like what are your favorite ways that company compan companies beat incumbents?

>> Business model shift is a super powerful thing that's very hard for incumbents to react to. That's part of what is so

react to. That's part of what is so exciting about the customer support industry and decagon. It's like the odds are so stacked in their favor because the business model is going to be very hard for incumbents to react to and it's

on the customer side better, faster, cheaper by an order of magnitude in you know in each case. So business model shift is one. The two simple components that I'm looking for, which generally

we're not really seeing yet, is completely re reimagined UI and then completely new sources of data. So,

we're large investors in data bricks.

We're very optimistic about the data layer. I think they'll have some success

layer. I think they'll have some success in, you know, enabling applications built on top. But the UIUX thing and the data thing, I think, are what paired with a business model shift, I think,

are what are going to give the startups the best chance against the incumbents.

the more dramatic the shift in those, the harder it's going to be for the incumbents. So, take salesforce.com.

incumbents. So, take salesforce.com.

Like, I use this as an example. Like,

it's a good company. I never would have thought it would be as big as it is.

It's a it's a good company. So, maybe

they'll be one of the incumbents that survives and, you know, reacts.

What do people do in Salesforce.com?

It's basically like a sophisticated form checker with some an with with some analysis and it's like brutal. It's it's

painful to use.

The future with AI is not going to be anything like that. Like it's just going to be to my point earlier about proactive versus reactive. It's going to be a proactive thing. Yeah.

>> Like you a salesperson, you're going to log into your Salesforce and it's going to be like, "Hey, these are the five customers that you, you know, have business that you should be doing. Oh, by the way, I've been

doing. Oh, by the way, I've been monitoring what they've been doing online. There's a shift in this group.

online. There's a shift in this group.

You got to be aware of it. I've drafted,

you know, a call script. This person

actually likes to be talked to on the phone. this person wants just to engage

phone. this person wants just to engage via your AI email. I've drafted one for you. I've already taken a bunch of

you. I've already taken a bunch of action on your behalf. Here's what you need to do.

>> Like that's going to h that that's going to be the future. I think the data that goes into informing that is no longer the database that makes Salesforce so powerful. It's all the unstructured data

powerful. It's all the unstructured data that's getting pulled from every interaction that everyone has everywhere.

And so my hope is that the fullness of the new product has that entirely reimagined UIUX. The fact that it's

reimagined UIUX. The fact that it's pulling, you know, all this new data from different places is an advantage to incumbent because Salesforce is so sticky because of the column or database that they have. Um, and then if you like

on top of it have a new business model that's attached to it. Like I think that's a really good shot for a startup to be able to finally >> go rip Salesforce out. I mean if you look at the SAS and cloud wave basically

the whole story was a 7xing in the amount of revenue in the market there's this question of like who wins the incumbents versus startups it basically

split like 50/50 so 7xed more revenue incumbents grew a bunch like they grew they took half of the new share startups to took half the new share I think the more dramatic the shift especially with

the more dramatic the shift in in potential business model the more likely it favors the startups that's the bets we Um, you know, my hope is that's what happens, but we'll see.

>> It's incredibly fun to explore all this with you in like a formal way, having done it like so informally for 20 years or whatever it is. I think you might know my traditional closing question.

What is the kindest thing that anyone's ever done for you?

>> I do know that question and I I've thought a lot about it because there's a lot of things that I consider, you know, in my life that have kind of broken my way. You know, I grew up in Kentucky,

way. You know, I grew up in Kentucky, far away from this world, and uh you know, a lot a lot of lucky breaks kind of went my way. The thing that I reflect

on the most is, you know, we spent the whole time talking about work. The other

thing that I do in my life is my kids, you know, um and something has become really clear to me with my kids age that they are now, which is the sacrifices my

parents made for me are extraordinary.

They're incredible. My dad always brings up like, "Oh, I was on the sidelines in the rain watching you and driving you from, you know, soccer to baseball to basketball, you know, sports and all the

activities that I was able to participate in as a kid." I think made me into the person I am in a lot of ways. And now I see it with my kids cuz

ways. And now I see it with my kids cuz I have to do that work and I have such a greater appreciation for what my parents gave to me and the sacrifices they made.

>> Amazing. Simple thought. Thanks for your time man.

>> Yeah, great to be with you.