What It Takes to Win as a Founder | Ben Horowitz

0:01

You're not a great entrepreneur unless you feel like you don't have a choice but to build a company. You don't take out a competitor with an equally good product. You need something dramatically better. We went public on $2 million in trailing revenue. $2 million going to $75 million. That was the forecast. That's clearly a bad idea. The doubts are going to be there.

0:20

Ignore the doubts. The worst doubts aren't the ones people put on you. It's the ones that you put on yourself. If your guts aren't boiling, you're not even trying it. I'll see you next time.

0:43

They discuss why AI companies can reach massive audiences faster than previous technology waves, whether billion-dollar businesses can be built with timey teams, and what actually creates defensibility when everyone has access to similar models. But they also get into the part of company building that technology can't automate, making hard decisions when you don't know if you're right, maintaining confidence through uncertainty, and continuing to bet on yourself when the doubts inevitably show up.

1:12

I don't know if you remember this, but many, many years ago when I first met you, so I visited Ben at the LoudCloud turned then Opsware offices. Every conference room was named after a hip-hop artist. I remember that, and I was like, all right, this is going to be a unique guy, unique culture. And I remember asking you, since you were about to sell the company to HP, what you were going to do next.

1:40

after and i remember you told me that you were going to retire next that's what you said i was tired and so the funny thing is of course ben has done exactly the opposite of that like literally the opposite of that so my first question is like yeah what happened you you decided not to retire you decided to do the opposite like how did how did that come about i had another idea You know, like that's a lot of what life is about is getting your ideas out.

2:05

So, you know, I had an idea. And I think that's what makes an entrepreneur, right? Like you have an idea and you believe in your idea and you want to get it out. You know, as an entrepreneur, that's who I am. That's what I got to do. I don't have a choice at that point. So you're not a great entrepreneur unless you feel like you don't have a choice but to build a company.

2:25

Because otherwise you're going to quit anyway. Right. Forget about it. You've seen so many stages of the internet. We've had desktop software, then the web, and then mobile and cloud. And then now this AI thing. What is unique and special about AI that makes it maybe similar or also just different to some of the other stuff? So the thing that's very reminiscent of the early days of the internet is when the internet first happened, like every day you would look out on the internet and there would be some very new awesome thing that was going on.

2:57

And that's definitely the case with AI. That's what's really similar. I think everything else is kind of different, though, in that, you know, AI is, so if you think about the history of computing, the history of the industry, it's always been networks and computers. And so, you know, we had microwaves and integrated circuits and, you know, mainframes and SNA and PCs and LANs and, you know, smartphones and the internet.

3:26

And they're very different technologically and very different adoption curves. But then they really enhance each other. And I think in this era, AI is the new computer, like very clearly. You know, it's a probabilistic computer where we, you know, previously had deterministic computers. And so, you know, in that way, it's very different than the Internet, which is definitely a network and networks.

3:50

Networks have these adoption curves that can start, like can get very high on the hype cycle too early because there's not enough people on the network. You can see where it's going, but until it gets there, it's not there. And so particularly with the internet, if you go back to kind of the great dot-com crash that led to the great telecom crash, what happened was, you know, there were everybody, every investor was like, oh, this is the biggest thing ever.

4:16

I'm going to put all my money into it. But the truth was there was only like at Netscape in 1996, we had 90% browser share and we had 55 million users. And so the whole internet wasn't that big. And then half of those people were on dial-up. So you could build, you could go build an internet app and it would cost you a lot of money because you had to use some microsystem servers and EMC storage and all this.

4:43

But there were, you know, like you could get to like 30 million people or something. So good luck with that. That's not a really a business. And so the whole thing kind of collapsed before it rebuilt, but eventually it was going to get there. Whereas with AI, like when it works instantly, you know, almost instantly you can get to a giant number of users.

5:03

We've seen companies grow faster than any companies we've ever seen because you don't need more people on the network. You know, like that's not a thing. The internet's already here. Everybody's on it. And all you have to do is put your thing up and they can get to it. So it's very different in that way. One of the amazing things that I think everyone in the industry is so shocked by is how good LLMs are at writing code.

5:27

And, you know, who would have thought? And so there's this idea that maybe building software, writing software becomes as easy as creating content on the internet. There's the idea that maybe you end up with a bunch of billion dollar companies being built with, you know, much smaller teams. Maybe it becomes even further geographically democratized or maybe there's going to be solopreneurs with, you know, billion dollar, you know, All those variations.

5:50

Do you agree with that? What risks do you think come with that? Do you think that's a lasting trend or do you think you need to still scale businesses ultimately? Well, I think we're going to see. You know, it's funny because I think Ray Kurzweil predicted like everybody was going to be a solo entrepreneur. Like it could get to there. I would say, you know, like Instagram was 13 people and sold for a billion dollars.

6:13

But like Meta's got like a ridiculous number of employees. You know, would Instagram have just been that many employees if they hadn't got bought by Meta? Probably. And so I think you can get to a giant audience and a ton of money with a very few number of people. Like I think that that's for sure true. And then the question is, can you sustain it or will you get taken out by somebody who's kind of doing more things? I would tend to think like just historically that, you know, people always want more.

6:46

Like the standard just goes up in terms of what people want. John Maynard Keynes had like this very famous or it was his worst paper, but he had this paper that he wrote in, I think it was like 1970.

7:00

which basically said as soon as people's needs are met, so once they had like shelter, food and clothes, people would start to work maybe no more than 15 hours a week. I'm not sure now to be spectacularly wrong because of course then all of a sudden everybody needed a car and then everybody needed a car for everybody in the family and everybody needed a television and then everybody needed television in every room in the house.

7:27

And now everybody needs a smartphone and everybody needs air conditioning. And none of that stuff even existed when he wrote that. And so now people are working like, I'm sure nobody here is working 15 hours a week.

7:42

I think like what people need does tend to expand almost infinitely. So to fulfill that need, sometimes you have to build a bigger company, but we'll see. Software gets so easy to build that you kind of have like fast fashion SaaS, you know, like you kind of get copycats all the time that kind of get cloned. The other version that has kind of been predicted is sort of, you know, sort of bespoke software.

8:06

Maybe everybody uses... a different, slightly different, you know, version of software that gets generated, that's instantiated at basically at runtime, that's personalized to you. I mean, this is all very sci-fi, but like, you know, maybe we'll get there. It's funny how humans are though, because like even in fashion, we do have fast fashion.

8:25

I'm looking at a lot of people are wearing kind of similar stuff.

8:31

And so, yeah, I'm not saying that that'll totally go. The other question on kind of software is, Like how much will be like what we consider software today and how much will just be like, okay, we'll just use the AI differently and it won't even be an application. Right. You just ask the AI to do it. And so I think that's a little bit TBD, but I think the paradigm of an application application maybe the thing that fades the most.

8:57

You organize your data and then you have agents that you ask to do stuff against the data. Right. And that's how business applications work and personal applications work too. How do you think about defensibility in kind of, especially for AI apps, You know, there's sort of an argument that, hey, a lot of the products right now, they don't really have very much in the way of, you know, network effects, maybe they're GPT wrappers, you know, there's all these kind of critiques.

9:23

And so what do you think of as kind of, you know, the durable advantages that, you know, founders should be? GPT wrapper thing was always a bit of a dumb idea in terms of not to build one, but to call it that. And what I mean, so if you go back, if you're as old as me, you remember when relational databases came out. And relational databases, right, oh, you've got this declarative language, and then you just tell the database what to do.

9:51

and then it doesn't. And so why the heck would you need SAP or, you know, in those days, Siebel or Salesforce or whatever? Like, that's ridiculous. There's nothing there. It's just a RDBMS wrapper. But of course, that turned out to be wrong. And when I look at the applications that are built on LLMs today, they themselves have many models.

10:17

You know, I think Cursor's is it 14 models now? Like fairly sophisticated models on top of, you know, that kind of foundation model. And so I don't think they're, like I think they're pretty sophisticated kind of models and applications and so forth. And those models have a lot of data and understand, you know, like if you're talking to like super high-end programmers all day about how to design their program, that's a lot of information into your system and into your model that nobody else has.

10:47

And so that becomes, I think, part of the differentiation. And then possession is nine-tenths of the law and like competing on software. So if you get the customer, like how much better is ChatGPT than Grok right now? Like if you were starting from scratch, it's like kind of marginal. It's not like a massive differentiator and it's not a network effect yet.

11:08

Like just the fact that you're using that one, I'm used to it. It's not even a complicated interface. You're just talking to it, like to switch it. But it doesn't matter. If that's what you're using, that's very likely what you're going to continue to use. And to get you off that, you need something dramatically better. So, like, you don't take out a competitor with an equally good product or a slightly better.

11:30

It's like a 10 times better product. You know, if you take the market, I think that's... That's probably the most obvious, most significant thing. And then, of course, with AI, if you take the market, you do get more data about your particular kind of user. Yeah, I mean, it seems like maybe the market is just going to naturally evolve in phases.

11:51

And, you know, we're kind of in this like land grab phase where just the most important feature is the it works feature, right? And then we'll get to the unique UX innovations and to all the, you know, collaboration network effects features over time. You know, when you have a new computer and you can solve problems that nobody could solve before, then that's pretty interesting, regardless if there's a network effect.

12:16

I think in the network era, which is the internet era,

12:22

The network effect thing became super powerful for a lot of things. And it probably will again. But yeah, I think for right now, and it'll be interesting to see with like the rise of, like crypto is probably a money network for AI. So how does an agent pay another agent or get money? And, you know, because it turns out AIs aren't allowed to apply for credit cards.

12:45

So how does that work? And so, you know, does that become... a crypto network, and then do you have network effects from value exchange and that kind of thing? I think that'll start to emerge and

12:57

other ideas like that. Yeah, I think on the phases too, it's so interesting to see how the backgrounds of founders changes so much because, you know, for all the folks that were around then, it was like, You know, when the web first came out, you literally had Stanford PhDs building Yahoo, like a directory of links, right? Like that's, you know, because you had to write your own web server.

13:18

You had to write your own infrastructure, you know, like the whole thing.

13:22

There was no such thing as, yeah. I mean, in those days, there was no application servers, no load balancers. No, it was very hard to scale software to that size. And nobody ever had built, like the biggest piece of software, like the audience was however many employees they had at IBM. And so nobody thought about, okay, I got to build something that, you know, 500 million people are going to use.

13:41

That's right. That's right. And then it took like 10 years to get to the LAMP stack and, you know, kind of, you know, non-CS major just coders. And then eventually like Airbnb, you know, kind of design dominant, UX dominant people sort of, you know, building the most interesting applications. So you could, you know, maybe make the argument that, all these AI apps will follow some kind of a similar trajectory.

14:04

You have tons of PhD, CS talent right now, and then, you know, maybe years before. I mean, it's very interesting, obviously, you know, these days, like, I think the mainstream developer is actually able to build AI apps in a way that was not true five years ago. Yeah, and like, you know, and when do things plateau is a big question. So right now, like, you know, and so the language models are plateaued quite a bit in terms of, you know, you know, just the pure LLM.

14:30

And then the reinforcement learning side is scaling. So like code is getting way better, but the regular kind of, you know, chatbot is not that different. How many more AI breakthroughs will we get? And that'll, you know, every time there's a breakthrough, that's an architectural change. It'll change the entire application layer, the whole infrastructure layer.

14:52

You know, when will those plateaus happen? When will those breakthroughs occur? And that's kind of how the opportunities line up. You know, you could kind of make the argument that as the tech landscape has changed, like having social media, having, you know, podcasts and the whole thing, that's really changed the VC industry. And maybe these, you know, the landscape and the way that you reach founders is kind of very intertwined.

15:14

And so in this next phase of everything that'll happen with AI and maybe, you know, people being able to build big companies with small teams and that kind of thing, how do you think this might affect venture as an asset class or as sort of just the VC industry as a whole. Yeah, so it's funny because the VC industry kind of was the same from like 1970 to 2008, 2009.

15:37

We started in 2009. kind of a little bit the way VCs were set up, they were kind of built not to change. And that's just kind of how it rolled. And so companies got easier to build with the internet. Like that was the first big change is that, like if you're talking about building some microsystems or tandem computers and so forth, like before you even sold product one, you needed to build manufacturing, you needed to build professional services, you needed a kind of direct sales force and so forth.

16:11

Like that was a pretty complicated just corporation to build. Now, you know, and then like if you fast forward to Twitter, you know, five people with laptops and AWS and Very different. And then, okay, with AI, there's kind of the next step of that. So I think that it's almost certainly going to change the VC landscape again. You know, in the old days, like the, you know, you could only do so many, every bet was very expensive.

16:40

It was hard to do. They were very likely to fail and so forth. And then kind of, The hit rate, at least for the promising companies, went up. So that's a big change. And then kind of how, you know, like a big value in a VC is, okay, you have company A and company B, and they have both the exact same idea and both really good teams, which one wins.

17:05

It turns out that you're kind of traveling as an entrepreneur through this complex adaptive system, you know, path dependent system. And so whoever gets more momentum ends up winning. And so a big role of a VC is to kind of help you get that momentum. So, oh, I raised money from the best VC. Therefore, like smart engineers will join my company and not their company.

17:28

So then I have better engineers and have a better product. Then I pick up more customers and then like I have more money and I get raised the next round faster and away I go. And that's how you win. If there are like. just dramatically more companies or they don't need as much money or that kind of thing, then that'll be an interesting change.

17:48

But I think like a lot of it is still, like a lot of the function of VC is going to be how do you give momentum? And that's like momentum and, you know, how do you help them build a higher quality company? How do you make that company more attractive to customers and employees and follow-on investors and so forth? And that part will be the same, but I think that everything underneath the feature set is going to be different.

18:14

Well, and we often encounter companies that are you know, wildly profitable or doing very well. Yeah. But they still want to work with, you know, VCs for, yeah, for all the reasons that you're... Yeah, because you have to win. I mean, like the...

18:29

Building, you know, the greatest thing is kind of having a great idea that makes the world a better place and doing something larger than yourself and building a team and building a company. Like if that works, like there's nothing better than that. Like it's so awesome. But if it doesn't work, like that's like very high degree of misery.

18:49

Like it's just tough. Like you hired all the smartest people you know. Like you went out and raised money. Your mom invested in the company. She's pissed. You know, like it sucks. It really does. So, you know, anything to kind of help you succeed at that, I think is always going to be attractive. So most of the speed rent companies here in October, they're going to be doing their demo day in front of 1000 investors in San Francisco, and they're going to be kind of speed dating a ton of angel investors and seed funds and all that.

19:20

Do you have any tips and thoughts on how to evaluate, you know, who the best partner might be at that seed stage? The thing that you always don't have is you don't know how to do that CEO job. No founders we work with who haven't been CEOs of giant companies like know how to do that. And it turns out to be like a really complicated skill set because you're, you know, you have to select the right talent.

19:45

Sometimes you're selecting talent for jobs, you know, like I had never been a CFO. I didn't know what the hell that was. Like what's a control structure? What's a... Like, how do you talk to Wall Street? Like, how would I know any of that? Right? Like, so, but you still have to hire that person, which I always liken to, it's like hiring a Japanese interpreter if you don't know Japanese.

20:02

It's like, they all sound good, you know? And so, like, you have that problem and then you've got, you know, like, and everybody's got their own career ambitions and, you know, and then, you know, Mark Zuckerberg's offering your people a billion dollars, you know? Like, so it's a really hard job and you don't know how to do it. A lot of the times, like, when I watch founders who kind of fail at kind of doing that job, it always comes down to a crisis in confidence.

20:33

So... You know you don't know what you're doing, you know it's hurting the company, but yet you still have to make decisions. Having the confidence to make that decision when you don't know what you're doing and you don't know if that decision is right, but not like hesitating. And then, you know, when you hesitate, It makes the company nervous.

20:53

It slows everything down. It creates politics because people try and fill that void. So how do you do that? How do you kind of get to the right confidence level where you can make high quality decisions on time? If there's an investor that can help you do that, like that's invaluable. So, you know, those are probably the two things I'd look for.

21:10

Somebody who can really give you momentum in hiring and getting to the next round and all that. And then somebody who you can work with who goes, wow, like this person, not only knows what they're doing, but like it's helpful. Cause like every, by the way, every angel investor, every VC will give you advice, even if they like, motherfuckers who had never been CEO.

21:30

I see telling people how to be CEO and they give them these crazy ideas. You know, like, you have to build a whole executive team right now. And it's like, what are you talking about? That's an incorrect accompaniment. You know, but they have, like, they have great confidence with their advice. One of my favorite pieces of advice I got is, and I got it like 27 times, they're like, look, here's the key, you know, like, hire eight players.

21:53

And I was like, okay. It's like, yeah, my plan was to hire a bunch of fucking morons.

22:00

But now I'm going to hire eight players. So like, you know, that's not a, it's just like the level of like not good insight that's out there is high.

22:12

Well, and I really think it's part of a strength of the Bay Area tech ecosystem that over the last 20 years, it kind of went from, you know, like a lot of VCs, especially out in Europe and other places are often really like former finance people. you know, folks. And that's kind of like all, like, that's really their background. And they're often coming in from maybe private equity.

22:35

And so then they decide, oh, I'm going to also do some VC. And one of the big strengths, I think, of the Bay Area is that you end up working with a lot of former operators. And the whole industry's kind of moved towards that model of, you know, trying to mostly get investors that have done something. Mostly. Not universal. And different levels.

22:59

There are levels to the game. For you, how has A16z changed and evolved, you know, kind of the biggest beats of kind of evolution? And what are you most excited to build at the firm over the next decade? I know it's a long time, but... Yeah, I mean, so when we started, like the idea, the idea was very simple, which was, you know, the VC product we thought was very good for investors, but not nearly as good for entrepreneurs in that.

23:27

The kind of model was, OK, you get like a very smart person on your board, not much more than that. Like they, you know, they had a network, but it was that person's network. You know, a lot of them were very smart at product, but product advice runs out, you know, really in the first three months because, you know, when you're doing the initial kind of product.

23:47

And then once you get past that, the knowledge gap increases. between you who's been working on it like all day, every day, and a person showing up at a board meeting, be it once a month or once a quarter or whatever, it's just so vast that it's hard to get good advice in that way. I had thought of it as like, okay, as a founder who had tried to build a company and build a company, like, what did I actually need? And I was like, well, I could use a whole lot more than that.

24:13

And the biggest thing, you know, and I keep, I go back to it is just like confidence. And so like, could I, like, what would make you feel like a CEO? And so like, we did a lot of things. So like, how do you make somebody feel like it's, well, what if you could call like any senior executive who might buy your product, like at FedEx or Citibank or wherever, like, could you do that? So we built like a whole team to make it easy to do that.

24:37

And then, you know, how could you, like, know how to hire an executive and, like, what was the process for doing that? And so, like, we built a team to kind of help with that. Like, how do we introduce you to, like, five great CFOs and you can just sit down with them and say, hey, what would you hire in this position? And, like, why would you do that? And how would you test for it in an interview? And

25:02

and that kind of thing, and kind of like skill you up so you knew how to do the job. So that was kind of like the first idea. And then, you know, as we got into it, one of the things, you know, and Mark wrote about it in, I think, 2011, he said, like, software is going to eat the world. Our takeaway from that was, okay, if that's going to happen, then kind of VC up until that point was this idea that there were 15 companies in a given year that would ever get to 100 million in revenue.

25:32

And the whole idea of the firm would be to kind of get into as many of those 15 as you could. But we're like, well, if software is going to eat the world, that's not going to be 15, that's going to be 150. And so how do you actually scale a VC firm

25:45

you know, kind of without losing all the things that make it a VC firm, like very, very personal, but can scale up. And so that was kind of the verticalization idea. So we're like, well, can we build like a firm that's better than Andreessen Horowitz original in infra, in apps, in crypto and bio and, you know, in games and, you know, and kind of defense and public safety and that kind of thing.

26:13

You know, that was kind of like, I would say, quite the major change in the firm. And then, you know, the kind of thing that we've run into now is like companies are getting very big as private companies. And there's a whole other layer of stuff that they need how to do. How do you go... international, like efficiently. You know, can we walk you into Japan and get you your first three deals? You use our brand and we'll enable you to lever off that so that you can win.

26:45

You know, how do you add channels? Because you have to be kind of multi-country, multi-channel, multi-product as you go. How do you do all that? And what can we as a firm do to enable that kind of thing? So we're, you know, playing with a lot of those ideas and other things that'll hopefully make us better. Well, I think we have maybe 25 minutes to do some audience questions.

27:06

Yeah, so I think the biggest thing that I have concluded that I'm feeling pretty sure about is AI

27:17

kind of video and entertainment and so forth is a new medium. So there was kind of like plays and then there was film and then there's going to be AI film. And I think it'll be as different from film as film was from plays. So in the beginning of the movie industry, they would just film plays. And, you know, they'd like fix camera, do the play, and we'll record it.

27:42

And that was the idea. And then it obviously changed dramatically over the intervening decades. And I think that's going to happen. I think that's what Like in the beginning, it'll just be using AI to kind of generate certain scenes and movies and this kind of thing and so forth. But I think what's going to happen is there's going to be a whole new set of creators using the new medium to do things.

28:06

You know, like it's interesting, like if you think about it in the context of social media, social media is like storytelling where the main character is always you, right? So that kind of carves out a lot of people who are either less comfortable or less narcissistic, however you want to say, who doesn't want to be the main character, you know, all over social media like that.

28:28

kind of as a constraint. With AI, you know, you can have characters that aren't you and be telling stories. So it's a new storytelling medium is the way I would think about it. And so I think it's a mistake to try and just completely replicate the movie experience or the TV experience or that kind of thing and kind of move it. And like it may start off being more interesting in like podcasts and like how do you jazz up podcasts or whatever.

28:56

But I don't know exactly. But the one thing I'm pretty sure about that I don't think we really covered in that podcast was this is a new thing. This isn't the same. This isn't just generating the old thing automatically. This is a new thing. I think a lot of it, you know, for me, it was always like, can you bring the focus back to... you know, what you can do, because like the thing that overwhelms you is what you can't do and like all the problems and everything.

29:23

When I think about like the decisions I made as

29:26

CEO, the ones that I'm most proud of and would have cost us most weren't actually difficult decisions. They were just difficult to make. And that was like a psychological thing. So for example, when we went public, like we went public on $2 million in trailing revenue, trailing 12 months revenue, $2 million, like IPO, 2 million going to 75.

29:49

That was the forecast. That's clearly a bad idea. And we were only 18 months old, 18 months from founding, 2 million trailing revenue, like we went public. The other choice, and we had kind of gone through, we talked to like literally every investor in the private markets, was bankruptcy. So that was obviously a worse choice than going public.

30:13

To be able to do such a bad choice like going public and not hesitate, just go, okay, I'm going to do it. That was the, like, that was the magic of that decision. By the way, like I saw so many of, like, I can't tell you how many companies went bankrupt at that point because they didn't go do that. Like a lot of it is like, okay, just do the thing you can do.

30:34

And it may look horrible. But don't, you know, you got to trust your eyes. You have to go do it and not hesitate. And I see like, this is where, you know, kind of people really get into trouble with their psychology. So they'll be like, oh my God, you know, like I kind of know that we need to re-architect the product. but like that's going to make it very hard to raise money.

30:57

That's going to, you know, we're going to miss our numbers. We're going to like not have any features and this and that. But I know we're wrecked if we don't. So then they hesitate and then they're going to be wrecked. And so it's like all these really, or like something simple, like I really need to fire the head of sales, but like I don't even want to have that conversation.

31:19

So I'm going to look this way, you know, and that's, you know, running at the problem, like, Yeah, it's going to be bad. You're not going to have a head of sales. Like you may whiff the quarter. There's going to be nobody to blame but you, blah, blah, blah, blah. All that is true, but it's not as bad as leaving that motherfucker in place, right? Like, so you got to go do it.

31:36

And so I always kind of came back to that, that what can I do? And I better do that right now. And that's a lot how you work your way through those. Very bad. And the worst thing is like, you think about like, what are all the implications of it? It doesn't matter. It's like, is that the best choice I have? If that's it, I'm doing it. You know, like if I think about all the things that are going to happen to me when I went public, and they all did happen to me, by the way, like I would have just shot myself in the head.

32:05

I mean, that was... That was a bad time. When you're a CEO, when you're founding, you're the boss. So like, you know, you do have to keep that in mind. So like, I do think that nobody's going to train you to be a CEO. Like there is no training for that. You know, and actually the reason I wrote the book the way I did was it does tend to be very situation specific.

32:26

I spent a lot of time on like, this was my situation. And the reason for that was, So that people could go, okay, if you're there, then you do this, as opposed to here's the five steps for being a CEO. There are no five steps. I think that what you look for in a mentor is not, it's not really instruction. It's like somebody to have a conversation with who knows what they're talking about.

32:48

You know, when I talk to CEOs, I'm just like, okay, like what's on your mind? What do you work on? That kind of thing. You know, we get to... like something that they're stuck on. And then I like, the good thing is I've made all those mistakes before. So like I can go, okay, like this is how it went. As an example, like I had CEO and he said, well, you know, like I need your help on this.

33:12

You know, my, how would you think about this? You know, my CTO is an asshole. And I said, OK, you know, like and there's a lot of ways you could react to that. Right. You could imagine how like many advisors react to that. And I said, well, you're not asking me if you should fire him because he's a good CTO. Right. Like I mean, like everything I've heard from you is he's like executing way better than everybody you've had before.

33:33

He's like, yeah, yeah, I'm not going to fire him. So I said, you're you're really asking me, how do you talk to him? And he goes, yep. And I said, well, because you don't want to lose him. So you don't want to like say something has pissed him off. You're not going to fire him, but you don't want him to be an asshole. So like, how do you deal with that? And I said, well, tell me why he's an asshole.

33:52

And he says, well, you know, the other day he was talking to a young woman in finance and he made her cry. And I was like, okay, that's kind of asshole-ish.

34:05

And I said, look, here's the way I would have the conversation if I was you. I would just sit him down. I would say, look, you're a great director of engineering.

34:13

amazing, ship products on time and so forth. But you're not like really effective as a CTO. And like at some point I'm going to have to hire somebody who is an effective CTO until you can do that. And by that I mean like you can't just work with your own people effectively. You have to work with other functions. You've got to orchestrate the company effectively.

34:36

to get the technology part of the company what they need. And if you go into a meeting and make like a little kid cry, like you're never getting what you want out of her or her boss or her boss's boss. Like that's just totally ineffective. So like if you want, like we can work on helping you get more effective or like that's going to happen one day.

34:56

And so like that's the kind of conversation, I know it's a lot of detail, but you kind of want somebody who can have a conversation like that where you can go, okay, like that's actually like some functional advice that makes sense that I can use as opposed to just no asshole rule, you know, or like some dumb ass shit that they fucking heard at Harvard Business School.

35:18

It's very situational. Like everything is situational. Everything is your company, your product, your people. How do they work? Can you get to that? And so, like, I would like to just, you know, people who you know who you can talk to about that. They could be a peer. You know, it doesn't have to be, like, an old person like me. It could be, like, somebody who's just one step ahead of you.

35:39

Yeah, so, you know, everything's so easy now compared to when I was building LoudCloud. Pushing the company forward, you know, gets harder in some ways because you have a lot of people who have been there a long time who did a good job. you know, a great job at one time, but maybe like we're in a new era that's passed their skillset. Venture capital is very like that, you know, We don't invest in any consumer internet companies anymore, you know, like mobile apps or, you know, SaaS company.

36:08

Like there's a whole category of experts that we've had in the firm that that expertise is no longer relevant. So if they don't become, you know, world-class experts in something else, like that's a problem. The whole way we did marketing originally, You know, that doesn't really work well for most companies and definitely can't work for us because we're too big.

36:28

You know, like nobody's writing a puff piece about Andreessen Horowitz. They're, you know, like where Rupert Murdoch could be easier to get a puff piece than we could. Like it's that kind of thing. And so like that's not going to work. So how do we market? And that turns out to be like a whole new skill set and going direct and like, you know, building relationships.

36:46

you know, a massive podcast network and presence and so forth. And so making those changes and just going, look, you know, you did a great job, but now we got to go this way is probably the thing that I enjoy the least. But, you know, you got to do it. Too many times I think people look at what the technology is as opposed to what it's going to be.

37:09

That's tricky because sometimes you can extrapolate things that shouldn't be extrapolated. So like a big example of that is, you know, when we looked at 3D printers, everybody was like, oh my God, this is the future. You're going to be able to print anything. But it turned out like 3D printers don't follow Moore's law. So more compute power didn't make them better.

37:30

Like you had to get into like really complicated material science, which doesn't kind of follow that trajectory. So actually, 3D printers weren't going to change that fast or that much. So it was a little harder to kind of build a new company that was going to be giant in them. looked at AI and they're like, oh, well, like fine, but it hallucinates on this and that.

37:50

And we're like, yeah, like that's not that tough a problem to deal with. And sometimes the hallucinations are good. If you go, okay, these things that seem like a problem aren't really a problem. Or like, you know, with a smartphone, It's like, well, this thing, great. It's a bad phone. Like, if you look at the 2007 reviews of the iPhone, it's a bad phone.

38:11

It's a way worse computer than normal computer. The keyboard is much worse than a BlackBerry. Like, it's like, and you can go through all the things it was bad at. There was a camera and a GPS in your pocket, right? Like, so... you can't build Uber on a PC even now, right? Like, so you only need one feature or one thing that kind of makes a breakthrough and creates a new future.

38:35

Like it just has to be unbelievable at something. It doesn't have to be better than the last thing at everything. And so a lot of times when we think about it and we think about entrepreneurs, But I always say it's like, we're not looking for lack of weakness. Like every, there's something wrong with every entrepreneur. And like, you know, including all of you, including me, like there's something like horribly wrong.

38:58

But that's not the question. The question is, are they world-class entrepreneurs? at a thing, are they the best in the world at something? Do they have a secret that nobody else has? Do they have something really special? So you're always looking for like, what's really special? What's the magnitude of the strength? Not like, is there something wrong with them? And I think the future is a lot like that.

39:21

Like, how strong is the strength? How different is this technology? Oh, we now have a computer that you can talk to in English? Like, that's kind of important. You know, like, that's a hell of a thing.

39:34

Any parting words of wisdom in many of the kind of year one projects here? I would just say this. Congratulations on betting on yourself because that's what this is all about. You know, your job is to like make your bet pay off. So like you believed in yourself enough to do it. You got to, there are going to be many times when you question that bet and you question that belief, but like that gets you nothing.

39:58

Don't worry about it. Like it's, It's a nothing. You just got to do your thing and keep going and focus on what you can do and not worry about You know, like the doubts are going to be there. Ignore the doubts. And the worst doubts aren't the ones people put on you. It's the ones that you put on yourself. Every entrepreneur has them. Like there's nobody, you know, I spent a lot of time with Mark Zuckerberg when he was like 22 years old and like he had a tremendous doubt about whether it was going to make it.

40:29

So that's not... Everybody has that. It's not what you feel, it's like what you do. And so just focus on what you do. Like you're gonna feel scared. If your guts aren't boiling, you're not even trying at this thing. Don't worry about it. All right, what about you Dan?

40:51

Thanks for listening to this episode of the A16Z podcast. If you liked this episode, be sure to like, comment, subscribe, leave us a rating or review, and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts, and Spotify. Follow us on X and A16Z and subscribe to our sub stack at a16z.substack.com. Thanks again for listening and I'll see you in the next episode.

41:16

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41:35

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