The a16z Show

Ben Horowitz on Venture Capital and AI

69 min
Apr 27, 20262 days ago
Listen to Episode
Summary

Ben Horowitz discusses how Andreessen Horowitz reimagined venture capital's organizational structure to scale beyond the traditional partnership model, and how AI is fundamentally shifting the venture landscape by making capital and compute the primary bottlenecks rather than engineering talent.

Insights
  • Centralized control with shared economics enables organizational agility and scaling that partnership structures cannot achieve, particularly during market transitions
  • Network effects are the primary competitive moat in venture capital—building relationships across entrepreneurs, engineers, executives, and corporations creates defensible advantage
  • AI has inverted the venture equation: code and UI are no longer defensible moats, making capital availability, compute access, and organizational design the new critical factors
  • Culture is defined by specific behaviors and actions, not stated values—leaders must establish clear standards and enforce them consistently to prevent organizational drift
  • Dictatorial leadership structures outperform democratic ones in competitive business environments because speed of decision-making matters more than consensus
Trends
Capital deployment is becoming the primary competitive advantage in AI companies as code moats erode and compute becomes the limiting factorVenture capital firms are evolving from pure investment vehicles to operational partners providing supply chain relationships, regulatory expertise, and organizational designSaaS companies with defensible moats beyond code (supply chain relationships, regulatory barriers, channel advantages) are surviving the 'SaaSpocalypse' better than pure software playsIndividual founder productivity is accelerating dramatically with AI tools, enabling solo entrepreneurs to build products previously requiring large teamsPrivate capital markets are consolidating company lifecycles, requiring venture firms to provide capabilities historically reserved for public market infrastructureRegulatory capture and government relations are becoming core venture capital competencies as AI and crypto face policy uncertaintyNetwork effects are increasing in value as AI commoditizes software, making relationship networks and ecosystem access more defensible than codeLong-term founder thinking and mission-driven companies are outperforming purely profit-maximizing ventures in attracting talent and capitalThe bottleneck for AI progress is shifting from engineering talent to electricity, compute hardware, and organizational design capabilitiesYoung entrepreneurs have unprecedented advantage in AI era because incumbents struggle to unlearn old paradigms while new builders can adopt new mental models
Topics
Venture Capital Organizational DesignNetwork Effects as Competitive MoatAI's Impact on Software MoatsOrganizational Culture and Behavior StandardsLeadership Structure and Decision-Making AuthorityCapital Allocation in AI EraCompute and Energy as BottlenecksSaaS Company DefensibilityFounder-Market Fit and Problem SelectionRegulatory Policy and Tech Industry InfluencePrivate Capital Markets EvolutionBootstrapping Network EffectsFounder Productivity with AI ToolsMission-Driven vs. Profit-Maximizing CompaniesTalent Retention in Rapidly Changing Markets
Companies
Andreessen Horowitz
Ben Horowitz's venture capital firm, founded in 2009 with innovations in firm structure and entrepreneur support
OpenAI
AI company founded as alternative to Google's dominance; example of solving for world need that doesn't otherwise exist
Skype
Early investment by A16Z that returned 4X in 18 months, demonstrating contrarian thesis on network effects
Facebook
Network effects case study; early investors like Peter Thiel got favorable terms because market didn't understand net...
Twitter
Network effects example; early investors undervalued the company due to lack of understanding of network dynamics
Google
Incumbent AI player that was expected to dominate before OpenAI emerged as alternative
Databricks
A16Z investment with memorable pitch; founder Jan Stoica presented complex distributed systems concepts
Slack
Example of founder pivoting from failed product (Glitch game) to massive success; demonstrates resilience
Meta
Mark Zuckerberg's company; example of accidental discovery of major business idea while solving smaller problem
Dropbox
Drew Houston founded by solving personal problem of moving presentations between devices
Salesforce
Legacy SaaS company used as example of rebuilding vs. reimagining in AI era
Anthropic
AI company; example of how specialized channel relationships and supply chain advantages remain defensible
Navant
Travel management SaaS company with defensible moat through global supply chain relationships; survived SaaSpocalypse
Tesla
Elon Musk company; example of founder starting with smaller problem before scaling to massive impact
SpaceX
Elon Musk company; part of founder's progression from smaller to larger scope problems
Hewlett Packard
A16Z used HP's enterprise briefing center to bootstrap network relationships with corporations
eBay
Spun out Skype; IP ownership issues created investment opportunity for A16Z
Kleiner Perkins
Competitor venture firm mentioned in context of industry response to A16Z's innovations
Eli Lilly
Large pharmaceutical company; CEO Dave Ricks unable to get Biden administration meetings
Apple
Steve Jobs' iPad decision killed Flash, which affected Slack founder's previous company Glitch
People
Ben Horowitz
Discusses venture capital innovation, organizational design, and AI's impact on startup ecosystems
Anjani Midha
Host and interviewer; frames discussion around systems design and frontier innovation
Marc Andreessen
Co-founder of A16Z; mentioned in context of firm founding and partnership structure
David Swenson
Major LP who held traditional venture capital assumptions that A16Z challenged
Mark Zuckerberg
Example of founder who dropped out and evolved significantly over time; accidental business discovery
Elon Musk
Example of founder starting with smaller problems and scaling; co-founded OpenAI with Sam Altman
Sam Altman
Co-founded OpenAI with Elon Musk; Elon reportedly upset about direction of company
Peter Thiel
Early Facebook investor who got favorable terms because market undervalued network effects
Quincy Jones
Referenced as leadership exemplar; 'Quincy Jones of tech' comparison used to describe Ben Horowitz
Stuart Butterfield
Example of founder pivoting from failed product (Glitch) to massive success with limited capital
Drew Houston
Founded company by solving personal problem of moving presentations between devices
Jan Stoica
Databricks founder with memorable pitch; recommended by Scott Schenker to Ben Horowitz
Matej Zaharias
Databricks co-founder; Scott Schenker described as best distributed systems researcher in academia
Scott Schenker
Recommended Matej Zaharias to Ben Horowitz, leading to Databricks investment
Kamala Harris
Recipient of Ben Horowitz's $5M political donation; known to him for 15 years
Donald Trump
Discussed in context of tech industry political engagement and policy influence
Joe Biden
Biden administration's crypto and AI policies criticized; tech leaders unable to secure meetings
Tim Cook
Unable to secure Biden administration meetings despite tech industry concerns
Sundar Pichai
Unable to secure Biden administration meetings despite tech industry concerns
Dave Ricks
Unable to secure Biden administration meetings despite tech industry concerns
Dario Amodei
Quoted on job displacement concerns; Ben Horowitz argues his statements are misrepresented in media
Warren Buffett
Quoted on stock market dynamics: 'voting machine in short term, weighing machine in long term'
Lil Wayne
Ben Horowitz quoted Lil Wayne in controversial statement about competing VCs
Quotes
"Culture is not a set of beliefs, it's a set of actions."
Ben HorowitzCulture discussion section
"When I see another VC coming at me with the peace sign, all I see is the trigger and the middle finger."
Ben HorowitzEarly competitive positioning discussion
"Code is less of a moat. Capital matters more."
Ben HorowitzAI impact section
"The one thing that's interesting about the SaaSpocalypse is the barrier to entry on building software and user interfaces is getting much smaller."
Ben HorowitzSaaS discussion
"In the short term it's a voting machine, in the long term it's a weighing machine."
Warren Buffett (quoted by Ben Horowitz)Market dynamics discussion
"Understand the future and then the future is yours."
Ben HorowitzAdvice to young entrepreneurs
Full Transcript
If you share control, it becomes very, very difficult to change the organization because everybody's got to agree. I quoted Lil Wayne. I said, when I see another VC coming at me with the P sign, all I see is the trigger and the middle finger. And everybody hated me for that. There would only be 15 technology companies that would ever get to $100 million in revenue. And we really thought that was going to change because, look, at that time, we thought software was going to eat the world. and every new company was going to be a technology company, and therefore there were going to be more like 200 companies a year that would hit that bar, not 15. If you have a network with a billion people on it, it's going to be very valuable, but how did Alexander Graham Bell sell the first telephone when there was nobody to talk to? That part is actually really hard. The rules of venture capital were built for a different era. Recorded live at Stanford for CS153 Frontiers, This conversation explores how Ben Horowitz helped rethink the structure of venture capital as software expanded what startups could become. From network effects and firm design to leadership and culture, it traces how the system evolved and why it may be changing again. Now AI is shifting the equation once more. Code is less of a moat. Capital matters more. And the bottlenecks are moving toward compute, energy, and organizational design. Anjani Midha, founder of AMP PBC, speaks with Ben Horowitz, founder of A16Z. Please join me in welcoming Ben Horowitz. Thank you. So how many of you heard the song that was playing right before? Does anyone know the name of that song? We Are the World. Yes, that's correct. We Are the World is a 1985 single by a supergroup of musicians that all came together to raise. It was a charity single that was produced to help raise funds for the famine in Ethiopia, I believe, in 1985. Yeah, Lionel Richie made a good documentary on it, if you're interested. Correct. The reason I'm bringing it up is because Ben is known for many things. And he's the co-founder of Andreessen Horowitz. I'm very lucky to have called him my boss for a few years. He's also been a founder or CEO. He's built several technology companies. He's behind one of the reasons venture capital still exists today after many moments when there were times when it got threatened, including the SVB financial crisis. But the thing I've learned most about Ben is from a documentary that Ben told me to watch about a year and a half ago. Yeah, yeah, yeah. Triple OG. It's called The Greatest Night in Pop. And I would really recommend folks who haven't watched it to go watch it. We're going to put it in the reading assignment for this class. It's on Netflix. Anyone can go watch it. But it is the documentary about the making of that song you just heard, We Are the World. And there's somebody in the documentary that you'll observe if you watch it by the name of Quincy Jones. How many people have heard of Quincy Jones? Okay, about 30%. We need to school the kids a little bit on it. Yeah, he was the greatest. Great, great human being. Great human being. And more importantly, great leader. Yeah, well, that was the thing he could do. He was the best at handling super talented, difficult to handle people of all times. No question. And you can see it in the doc. Yep. There's a moment in the documentary where the camera is following Quincy around and he's walking into the studio where the musicians all are and he points to the top of the door and he says, read that. And there's a sign above the door that he's scrawled on a piece of paper and he's stuck up there. This is at like around midnight before the recording session supports his start. And it says, check your ego at the door. I think it says, leave your ego at the door. Leave your ego at the door, sorry. Yeah. Yeah. And if I had to summarize Ben Horowitz in sort of one line, I would say he's the Quincy Jones of technology. That's a lot. High bar. Yeah, that's hard to take that credit. He is amazing. Ben is known for many things, but I think the thing he will be most known for throughout history will be his leadership, the lessons he's left with a lot of people over the years. Many leadership lessons, which I think are still not legible to the world yet, and we'll only become clear over time. But today, Ben, I think it would be helpful to take everybody here a little bit behind the scenes of what it took for you to become the Quincy Jones of tech. You're not supposed to be blushing this hard, Ben. I mean, Quincy. Having known him, he's a very high bar. That's a high bar. Anyway, thank you for being here. Why don't we start with, let's zoom back all the way to the founding of Andreessen Horwitz. Let's start there. Yeah. This is a systems class. Andreessen Horwitz ended up being one of the most important innovations in the systems design of venture capital. Yeah. Of how capital should be deployed. Mm-hmm. Where we'd love to contextualize this is the students have heard that three or four of the largest bottlenecks to progress are data, you know, context feedback. Right. compute capital and culture. And we haven't talked that much about capital and culture. So today I hope you can take us a little bit to the frontier, what's going on in capital and culture, especially in labs, in startups, in teams that are pushing the frontier. But I think to get there, we should rewind a little bit and start with what was the system that you created to even allow capital to get to this point? Yeah, so we started the firm back in 2009. and at that time there were a couple of ideas about venture capital that I would say we thought were dated. One was like it was mostly an investment idea. So the product for investors, LPs, was really good in that they had very high returns. But the product for entrepreneurs I thought was like pretty bad in that they didn't do much for you other than give you money. So that was kind of idea one, that we thought we could just build a better product for entrepreneurs. And then the other idea that was very, very kind of prevalent in venture capital was this idea that, you know, in any given year, and the historical data really supported this, there would only be 15 technology companies that would ever get to $100 million in revenue. So the whole industry was just about getting invested in as many of those 15 as you could. and that kind of just limited the size of the whole industry and the capital in the game. And we really thought that was going to change because, look, at that time, we thought software was going to eat the world and every company that was going to be interesting, every new company was going to be a technology company and therefore there were going to be more like 200 companies a year that would hit that bar, not 15. And so we decided, you know, one of the things that I did as kind of the CEO of the operation was to say, okay, how do you scale this? Because venture capital firms kind of notoriously didn't scale because they didn't have to. It was, I remember Dave Swenson, who is the most famous LP, said, yeah, a good venture capital firm is like the size of a basketball team, you know, five guys and then a six man or something like that. And that was not going to be enough to have a great product for entrepreneurs and then also invest in such a large number of companies. And so to get to scale, there was a couple of ideas that we had that sound very, very simple, but ended up being important. The first was normally in venture capital, it's a partnership, and the partners share economics and control. And the problem with that idea, and you experienced this in your career at other venture capital firms, is if you share control, then it becomes very, very difficult to change the organization because everybody's got to agree. And if you know anything about running an organization, the one thing about a reorg is some people are going to hate it because it's a redistribution of power. And it's not necessarily the people who aren't good. It's just like some people are just going to hate it because nobody likes to lose power. And if people get a vote, then there's no way to like effectively reorg a business. And so our idea was like, you can't share control. We'll share economics, but we'll centralize control. And that ended up enabling us to reorganize and enabling us to get into many more kind of categories like American dynamism or crypto or bio or these kinds of things because we could change the organization and scale it and so forth. And that ended up being an important kind of systems idea. And then because investing is always a conversation and you need a very, very high fidelity conversation to get to the truth, you never want more people in the room than can have a conversation. And so you can't have a conversation with 30 people. It's not possible. That's a presentation. Over the years, what do you think is the optimal construct of a truth-seeking conversation when you're trying to understand the future of a technology that's super complex? Yeah, I think that, like, if you have really good chemistry and rapport, it can be like seven. But if you don't, then even that gets problematic. But, yeah, you just can't do it with a large group. And so what we ended up doing is we just kept kind of splitting the firm into smaller and smaller groups over time. And each group would address a certain part of the market. And that, you know, that ended up being very effective. And to contextualize for folks, so when you started the firm, the first fund was about 300 something million, 320? 300 million. 300 million. And you had all these sort of institutional folks like David Swenson and so on who had these like sort of long held, for whatever reason, priors and assumptions. Yeah. What did you find was the most effective way to realign them or get them to revisit those assumptions or update those priors in a way that was aligned with your mission? Well, succeed. I mean, like, that's all it is. Like, I think one thing, you think another thing. We're going to find out if I'm right. So the first thing that that happened was we invested, like, a quarter of that $300 million fund into the Skype buyout, which everybody thought was insane. But, like, we knew, there was a bunch of things we knew that other people didn't know. So the first thing that made it insane was like the deal itself. When it spun out of eBay, eBay didn't own the IP. They own the company, but not the IP, which how they ended up there is like a crazy, dumb story. But by the way, never do that. Never buy the company without buying the IP. So the founders kind of had this hold on them where they could have sued them and shut down the service. And so everybody was like, oh, that's an unbuyable asset. But, like, we knew the founders, Yanis and Nicholas, and we knew, like, the one thing they had in life that defined them was Skype. So they weren't going to shut that thing down. It was just a matter of, like, how much money did they want? Did they want to be on the board? The IP at the time was basically the Skype client and the user base? It wasn't the client. It was the underlying kind of library that controlled the protocol. Oh, sure. The communications protocol. Yeah, which was, you know, very hard to replace and all that kind of thing. So anyway, we bought it, and then 18 months later, we got like a 4X return on it. And so like you got a 4X on a quarter of the fund in 18 months, and everybody goes, okay, well, even though we thought you were nuts, like maybe you're not completely insane. There's so many interesting parallels to that era and now, but, you know, one property of that era was the explosion of networks. Yeah. The idea of network effects became legible for the first time as a systems concept. So can you talk a little, take us back, you know, I think it's hard for people now to just take these for granted. But at the time, can you talk about why was it novel? Why were people resistant to it? And what were the insights that then led to the architecture, the firm being a network effect driven firm? Yeah, I mean, I think that, I think people just didn't understand network effects as well. So the big era of networking kind of started with the internet. And then people thought the internet itself was just like a unique network. And it was weird. It was different because nobody, like people got value from things built on the Internet, but the Internet was not owned by anybody. It was like the kind of first real decentralized network. And so people didn't know what to make of kind of networks that like, I mean, Facebook early on had, you know, there weren't like a ton of people giving them money for the first round. That's why Peter Thiel was able to do it at a really good price. And then, you know, kind of the same thing with Twitter and so forth. Like people just didn't know that basically how invincible those things got when you kind of got them up to strength. So the bigger, you know, it's basically like an N squared value. So every node you add kind of increases the value by, you know, kind of N squared. So, like, if you have five people on the network, you know, that's 25. But if you have six, that's 36 and so forth. And the value, you know, if you get up to Internet size, it's just invincible. Like, nobody's going to ever build a rival to the Internet or very unlikely. And so, you know, at that point, you know, us being involved in the Internet and Twitter and Facebook and so forth, we had like a really good understanding of that. And so, you know, we always thought of the firm as a network. And so, you know, from the very beginning, we thought, okay, the more relationships that we have, the stronger our network effect. And so we ended up doing things that other firms didn't do. Like we tried to build relationships with like every engineer in Silicon Valley and, you know, every executive and every everything. And that and then every corporation that bought technology and so forth. And we were in our minds creating kind of this network effect that would just make us the best place to raise money from because we were like an automatic. You could tap into that network and become extremely powerful, like right off the rip. and, you know, I think a lot of people didn't understand, like, how hard that was to do and then the bootstrapping of any network is always the most difficult thing. So, like, yes, if you have a network with a billion people on it, it's going to be very valuable, but, like, you know, how did Alexander Graham Bell sell the first telephone when there was nobody to talk to? Like, that part is actually really hard and so figuring that out and how to bootstrap the network effect, you know, kind of coming from behind in venture capital was the idea. Well, I mean, could you say a little bit about how you bootstrapped it? What were the things that may be now lost to the annals of history where there were individuals or asymmetries? You know, one of the things we talked about in the first class is, you know, often the students get excited about the speakers like you up here, but we reminded them that one of the most valuable assets they have is the people sitting next to them, right? It's the relationships they build. When you were bootstrapping- That's getting more important, by the way. Exactly. If there's anything that's going up, it's that value, right? But if you zoom back, when you were starting that bootstrapping and you didn't have the largest firm in the Valley, you didn't have the most capital, you had no track record as a venture capitalist other than your angel investments, how did you boot, what were the moments where, that may not be legible to folks here, that you used something that was asymmetric that allowed you to bootstrap the network? Well, the really simple idea was we knew, like, venture capitalists made a lot of money, right? So they would take the fee money and then they'd pay themselves big salaries. And so we were like, well, what if we didn't pay ourselves anything. And we just took all the money and we basically spent it on building this network. So we would hire people to like bring people in. We, you know, with our kind of, you know, how do you get relationships with every big corporation, FedEx and this and that and the other And the trick that we had there was we had sold the previous company to Hewlett Packard And so we knew the people in their enterprise briefing center And so we would call them every week and say who's coming to the briefing center this week? And can we get their numbers? And we would call those companies and we would have them come to our briefing center and we'd just show them all the startups. So it would be like, you know, and we'd have everything they like, all the donuts and all that stuff, you know. So it was like very unventure capital-like, but, you know, the corporations loved it. So all of a sudden, we knew more big companies than VCs who had been around 50 years because we had this hack through the HP Enterprise Briefing Center. I think it's very poetic that we're sitting at Hewlett 200, by the way. This is the name of the auditorium. It all comes back full circle. So, you know, when you started doing that, usually when somebody new shows up on the block with an insight like that, from a systems perspective, what we've observed is often the antibodies come out. Yeah. Right? The immune response of the existing incumbent system comes out. At the time, I was across the street with Mike, actually a Kleiner. And I remember, you know, there was a, you know, A16Z was in the headlines all the time. And like our CMO at the time, great lady. But, you know, I remember taking one of the headlines to her and saying like, you know, we should do this too. And she said, on this executive briefing side, oh, that's just marketing. Yeah. And I said, yeah, that's your job. This is working. And I've been consistently shocked by the number of times A16Z has done something from a product insight, deliver that to the entrepreneur, and then everybody else just says, oh, that's just marketing. Am I being overly facetious or is that true? And what were the immune responses like that that you were experiencing and how did you deal with them? Yeah, well, it was funny because every time we'd meet with our investors, our LPs, they would say, every time we meet with another venture capital firm, all they want to do is talk about you and say mean things. And I'm like, well, that's fantastic. That's great. That's great. They used to call us Aho. That was their nickname, the other VCs. You know, they hated us. Some of it was my fault, though. You know, like, because when we started, I was coming from enterprise software, which is like a very competitive bare knuckle kind of, there's no such thing as coopetition in enterprise software. It's just like kill or be killed. So I did a, I did it like, I wrote this blog post called Four Things That VCs Do That I Don't Like, where I just like attack them all. And then I did this big, there was this, Sarah Lacey had this big, big event, and she interviewed me on it. And she's like, well, you know, you seem like kind of, you don't like other VCs. And I quoted Lil Wayne. I said, when I see another VC coming at me with the peace sign, all I see is the trigger and the middle finger, you know. And everybody hated me for that. But it kind of worked because they hated me so much. they weren't willing to copy what we were doing, even though what we were doing was working. So it kind of backed. I don't know if I would have been that antagonistic again, but, you know, it worked, so you can't argue with it. Well, okay, well, I think we should come back to that later. I don't know what you do differently. But, so, great, you bootstrapped the network effect. That allows capital deployment to start scaling into a bunch of startups. Now, it really does feel like a back-to-the-future moment a little bit, right? Yeah. Yeah, what's going through your mind right now? Yeah, I mean, I think so. So the big thing that's changed is that, or the kind of most fundamental thing that's changed from a VC standpoint in my mind is, it used to be, I mean, for my entire career, the one thing that you knew about technology companies is you couldn't throw money at the problem. So if somebody had a two-year lead on you, you could not hire 1,000 engineers and catch them. That, like, was never going to work because, you know, nine women can't have a baby in a month. Like, there were just things you could not parallelize, and then the communication overhead would kill you. And my favorite joke used to be, you know, what's a man year? It's like 700 IBMers before lunch, right? Like that, you know, it's nothing. You can't catch that that way. With AI, that's really changed and that you can throw money at the problem because if you have enough GPUs and enough data, you can basically solve most problems right now. Like that just is what it is. And so now, you know, the capital race becomes a real thing and you have to think through, okay, code is not really a moat the way it was in the past. And like user interface isn't really a moat. And so, like, what is, like, your barrier to entry? Like, what is the thing that differentiates you over time? These have become, like, really, really different. And it's happening at the same time that, you know, demand for the technology is unlimited because the products work so much better than anything we've built before. Like, these, I mean, many of you are too young to remember the products of old, but, like, none of them worked this well before. Like, this is, like, wild how well this works. So you mean companies didn't always go from $9 to $30 billion in run rate in like six weeks? Well, but the reason they go that fast is like you use them and you go, wow, this works perfectly. You know, how can I do more with it? Whereas in the old data, like if you bought Siebel System software, it took two years to deploy the thing and a million dollars at minimum. And like, so that's going to limit demand. There is no limit on demand when technology works as well. So you would say, Ange, that the technology is working in a way that collapses the sort of gap that existing incumbents might have as a result of their human capital investments over the last, whatever, decade of software. There's willingness to pay at levels that are extraordinary. Yeah, I mean, the return is crazy, right? Right. So, I mean, if you make an engineer 20 times as productive. Right. And you're paying that engineer. Well, if you're a Zuck, you're paying that engineer a billion dollars. but you know like if you're paying whatever it's going to be at least several hundred thousand dollars a year that's a hell of a return. Right. So that creates this the final project for the class for the students is the one person frontier lab because what we're trying to get everybody to realize is there's actually an extraordinary amount they can accomplish with the right tools. Yeah. Right. But we have an entrepreneur like that right now building a global VPN by himself. Yeah, and this started to become more common, I would say, when we were seeing pitches, I mean, almost a year and a half, two years ago now, right? Yeah. What does that mean for folks here who don't have necessarily access to the most capital, may not have access to a ton of compute either? What would you say is, but want to make a difference to the frontier, right? Well, I mean, I think saying, I just be careful, a little careful with like people don't have access. Okay. Like, anybody with a great idea these days has, like, trust me, you have access in that there's, like, unlimited money for good ideas currently. You know, maybe that changes over time, but, like, it's definitely there. And I would just say this, you know, the world is changing. And you can just think of it as like the jobs we had before the Industrial Revolution are all gone. And we've been kind of living with the post-Industrial Revolution and then the post-computer age jobs since then. and we're going to get to like a whole nother class of jobs and a whole nother class of companies over the next 10 years that replace most of what we have now. And so if you're young, like that's the best thing possible for your career and for your life because in the opposite scenario where it's all the same companies, then you got to start at the bottom and work 30 years to get yourself to be a mid-level manager, you know, and you've got a politic, and then, you know, the old people who aren't as smart as you, like, get all the money, and, like, that sucks. But in this world, it's the old people who have the challenge because they know how to do the old thing. They don't know how to do the new thing. And you can walk in and learn anything. And trust me, when you're old, it's harder to learn new things. Like, it just is something about your brain stops functioning as well. It's all filled up with old stuff you don't need anymore, and you can't learn enough new stuff. And so I think that, you know, the main thing is just like understand the future and then the future is yours is the way I would think about it if I was, you know, 19 or 20 years old. Well, you said something pretty important there, which is for the right ideas, there's unlimited capital, right? Could you talk a little bit about what do you think is the shape of good ideas today that's emerging in your mind? Well, look, I mean, I think that, you know, it always comes down to, like, can you build something, a product, an organization, a culture, an offering that people want? And then if you don't build it, is it getting built by somebody else? Or do they need you to do that? Does the world need you to do that or it doesn't exist? It's always the best entrepreneurial idea. And so anything that needs to exist that doesn't otherwise exist is a good idea. And look, that was the whole story with a venture capital firm. Now, did the world need another venture capital firm? Generically, no. Did it need a different kind of venture capital firm? Absolutely, it did. And so that's what we built. Now, I think that's kind of true for, I mean, if you look at OpenAI, they weren't the only ones trying to do AI, right? Like Google, it was assumed like Google was just going to own AI. It was panicking everybody, and that's why Elon, by the way, co-founded it with Sam. And Elon's still mad about what Sam did with it, but that's a different, longer story. But it was one of those things, well, we need an AI, we need an alternative. The world needs this alternative to Google, and that becomes a really, really good idea. So anything, and like the world, the world is changing so fast that the needs are going to, the new needs are going to multiply. There's going to be many, many, many things that need to be done. I mean, if you look at, I think, you know, kind of the old, nobody, the one thing that's interesting about the SaaSpocalypse is, it's definitely true that like the barrier to entry on like building software and user interfaces is getting much smaller. But by the same token, like, kind of the most boring thing in the world is to just, like, rebuild Salesforce. Like, you know, like, Salesforce at half the cost or a quarter of the cost isn't nearly as interesting as, like, what do you really want for your sales organization? Because it's not that. I mean, I don't think, you know. And then the question is, can you build it before they can? But do you really want your salespeople entering data in a crap user interface and then most of the things that they work on aren't captured in the system and this and that and the other? So going to the future, figuring out what, in a world of AI, what does that look like? One of the traps that students often fall into is, I call it the dorm room problem, right? which is you've got sort of direct visibility into problems that are in your kind of cone of, the light cone, so to speak, of your visibility, which is quite narrow when you're still a student, right? Yeah, and sometimes like when your friends are high in the dorm room and you have that conversation that sounds really good, it's not actually that good. You should at least sleep for one night. I've seen a lot of those over the years. Yeah, make sure it sinks in and you still think it's a good idea. At least one night of sleep. Yeah, yeah, yeah. But, you know, just because you're a student at a dorm doesn't mean you don't want to have an impact on big problems and work on things that have an impact at scale, right? And sometimes these things are mission-critical things, healthcare, financial services, the economy, the excelling to enterprises. But these things are not directly in your sort of line of sight, right, when you're very young. and how would you advise folks to, in particular, to bring it back to these AI systems, you know, the context feedback loop we've talked about is quite critical, but getting access to those context feedback loops when they can make a huge difference is challenging when you're young in your career and you don't have a big network and so on. So how would you go about bootstrapping that problem? Yeah, like I think the main thing is to just solve a problem. And what tends to happen is when you go to solve a problem, particularly if it's a hard problem, you find some other problem that's more important. I mean, and this is well-known in scientific discovery, right? Like penicillin was like an accident. They weren't trying to solve that one. It just kind of rolled off of the side. And then, by the way, like Meta was an accident. Right. He was building Hot or Not. And, you know, he kind of stumbled into like this much bigger idea. And, you know, my friend Drew at Dropbox, you know, he was like literally tired of having USB where he'd have to move his presentation from one thing to another. He was just solving a problem for himself. So I think the best way to come on a good, a really important idea is to go try and solve something. Not necessarily build a company, just try and solve a problem. And then in that problem, if it's like a problem that you have, then that means it's probably real. and then in solving it, you'll probably or you'll likely find something much bigger. And then that may like kind of force you to build the company. And those are the things that work the best that we've seen are these big things. I mean, it's really hard to, and even like Elon Musk didn't start his career trying to build Tesla, right? Like he was solving a much smaller problem. And, you know, that's generally how you build up to that. But I think trying to swallow the earth from the beginning with no experience doesn't usually work. It's good for your pitch deck, but it's not good for your company. I think Elon's first attempt was like a class of Yellow Pages competitors. Yeah, yeah, yeah, yeah. A little bit more mundane than that. Yeah, Yellow Pages and then PayPal and then, you know, Tesla and SpaceX. Well, so on that point, you know, the time horizon on which sometimes you find entrepreneurs sort of may have an impact on humanity is quite long, right? They bootstrap sort of the impact. I would say, or let me put this, one of the old ways we've seen the generation of entrepreneurs that belong to Elon's generation is that they feel like they have to start, you know, somewhat with a narrow scope. Yeah. And then bootstrap like bigger and bigger scope with every successive project. but just a few minutes earlier you said actually you know things are going through a lot of change you can have a lot of impact very quickly relative to incumbents who may have had to be a little bit more measured in their approaches how you resolve these two I think it's I think thinking of it like how big a thing am I going to do is the wrong way to think about it you have to start with like what problem can I solve and then you solve if you can solve that problem that's where to start. Like, you have to size it to you. Not everybody is the same. Like, different people have different capabilities. You become kind of your full, like, most effective self at a different age. Like, some people are really good when they're... By the way, like, Zuck is way different now than he was when he was 20 years old. Like, I know when he was 20 years old, like, he was... It's a miracle if he didn't have a network effect business like that when it worked at all. He just wasn't very good. You know, but he developed that, like, entirely over the year. And because he had that kind of business that had a vertical takeoff, he could develop into that. And, like, so if he didn't have that, like, he might have been better off, you know, finishing Harvard or whatever. You know that was just one of those things where he happened to solve a problem at that age that was important enough that it created a company So I want to take it in a slightly different direction which is or analogous which is you know when Zuck when Facebook was getting started it had a very unique culture Some good, some bad. Yes. And it's not always clear what is good and what's bad until much later. I think my friend Sean got in trouble with the law for that culture, but yeah. What, did he get in trouble for Napster? Wasn't that one culture earlier? No, he got in trouble at Facebook also. At Facebook as well. That was a different problem with the law at Facebook. I see. Yeah, he generally tends to get into trouble a lot. He is a genius, though. Well, this is the thing, right? With genius, sort of where you often find outlier technical and or any kind of outlier capability, often you find one of the problems I'm discovering today in the field is that you often have really talented teams try to start a new lab or a new company, and sometimes they fall apart. you just don't get very far. From the outside, you'd be like, oh, this is totally going to succeed. Star entrepreneur, lots of capital, you know, great problem. And then like six months in to 12 months in, teams are just struggling a lot to make progress, you know, and sometimes people leave. They got to, why is that? You know, what do you think is it is about the right cultural initialization that sets apart teams that can do this and hit that takeoff versus stumble along? And how do you skip the painful parts? Yeah, so I think there's a few things. Like, first of all, building a company is hard. And no matter what era or whatever, like, the press always makes it seem easy because they hate entrepreneurs. But it's not easy. It's always extremely hard. So some are going to fail. Like, I just say that up front. But in terms of, like, the team and the dynamic and so forth, Yeah, it's a combination of leadership and culture. And culture is a very kind of amorphous thing, but it ends up being very important. So basically, the way to think about it is it's not like people think of culture as like, you know, corporate values or some bullshit. But it's not that. You know, it's not we have integrity. We have each other's backs or like some of these like whatever platitudes people say. it's like how do we behave exactly? Like what are the behaviors? The samurai have a great kind of line which is a culture is not a set of beliefs it's a set of actions. And so what do we mean by behaviors? Well, like do we come to the office or not? Do we like, do we go home at five or do we stay longer? Do we, if somebody asks me a question do I get back to them like instantly or in a week? You know, like all those kinds of things end up mattering. Like, do we believe the best idea wins or does it like matter who was the founder? You know, all that stuff, you kind of have to agree on as a team and like very specifically, not like just like some highfalutin idea, and then you have to live by it. And then if you have that, if you have a standard, if you have a cultural standard, then if somebody's not living up to that standard, then it's a simple thing. If you have no standard and people aren't living up to the way you want them to, then you're pissed. But then that just starts infighting. Then it gets political, right? Because it's like, well, why the fuck is he going home? well we never said he needed to be here we never agreed on that like he you know has a date or whatever or like you know he's got a family he's got to go home like we never like said what that was and then you know people stop liking each other and then you hit the first hard issue and it's like you know F it I'm out OpenAI is going to pay me a lot of money screw you guys screw you guys I'm going home as Cartman would say so but what happens if you started by standardizing on some set of beliefs, set of actions. Yeah. And then the world changes. Right? And what you thought was going to be the right standard six months ago, in a world where stuff changes so fast, needs to be updated. Yeah, yeah. Look, cultures can evolve. But, you know, you kind of have to evolve together. And you need a leader. You need, like having, this is why I hate the idea of like co-CEOs or like we're all equal or like we're going to run a communist organization, it doesn't actually work in a company because you need somebody who's going to break the tie. Okay, yeah, you want it to be that way. You want it to be that way. We're going this way. If you don't like it, get the fuck out. Like that's how you have to run an organization in order for it to succeed. And I think people are, you know, we culturally got away from that idea in Silicon Valley a little bit, you know, in the end of the fat, happy network effect era, but, like, it's back now, so. Could you say more? What do you mean by that? Well, you know, everybody wanted, like, a vote on what the company's values were and this and that, and, you know, and then, like, CEOs caved to that, and that ended up not working well for any of those. Right, right. Companies are not democracies. They are culture. Yeah, well, I think a dictatorship always beats a democracy in a competitive battle, And so because it takes a long time to decide things in a democracy. Now, look, for a country, it's different. You know, there are things when you have to last several hundred years that, you know, when no matter how good the monarch is, if they die and a worse monarch comes into play, that could be an issue. Well, I'm going to push a little bit on this assumption that it's different for countries versus companies, because something I've learned from you is the way you approach, you know, the most exciting, the businesses I look up to the most, especially the ones in the A16 portfolio, are often leaders who are thinking so long term. The way they talk about their impact on humanity is not that different from the timescale sometimes of political leaders. In fact, arguably some of the entrepreneurs are thinking longer term than political leaders these days. Well, it is longer term, but so like if you have a king, let's say you had a king running the United States. Right. If it's a great king who was not interested in their own like enrichment or their family or their friends and so forth, that works like— Who cared about the public benefit, basically? If it cares about the public benefit, I think, you know, that works better than our current system. The problem with it is as soon as you get somebody who's not like that, that's just too much power. So you're better off decentralizing power so that the system is resistant to bad leadership. Like, I think a country has to be resilient to bad leadership in that, like, if a company goes away, like, okay, fine, whatever. Like, so, you know, the, well, Dave Packard and Bill Hewlett, you know, like, they're gone. They passed away. The new leaders weren't so good. Like, that's the end of the company. Fine. Whatever. It's a company. They did their thing. They did their job. They fulfilled their mission. You know, a country has to persist beyond that. And so, like, I think we already see that, you know, here, be it, like, you know, on the nation level, on the state level, on, you know, even on the city level, you can see, like, eventually you get politicians who just start giving stuff to their friends. And then, like, everybody suffers. At least you can vote them out. At least you can do something. Whereas, you know, I think in a company, you want to be as efficient as possible while, you know, while the sun is shining. I know I could keep going forever, but we probably have a bunch of questions piling up. So I'm going to ask you one more question, then we're going to switch to students, yeah? Which is, you know, you talked about David Swenson, right? And he had some strong assumptions that then you felt, these were leaders of the previous generation that you felt just didn't get it? Well, I just think that, you know, not that he, like, by the way, Yale is still like an investor in us today. So I just think, like, you can't let your investor, by the way, including us, like, run your company. Because you're on the ground in real time seeing what's happening. They have knowledge of the past, and they have a light knowledge of what you're doing, but not full context. So they can be, like, it's an interesting conversation, but, you know, the investor can't run the company. And that's just what it was with him and us. Well, sorry, and my question for you is what prior do you feel like you now have to update so that, you know, given that you felt like Yale at that time needed to update their price faster today, what do you feel is like the biggest assumption that you've changed about the venture capital industry that maybe was a strong belief you held, you know, 10 years ago? Well, I mean, like I said, I think, well, one, I mean, there's so many things that are changing. But, you know, and I talked about, like, you can throw money at the problem. That's a massive change. I think that, you know, the bottlenecks have moved. So, you know, we used to have a bottleneck on software engineers. I think, like, you know, we've got bottlenecks on, like, things like electricity now. So, I think that changes how we think about investment. And then, you know, companies are so big in the private markets that they now require things that venture capital firms didn't, you know, previously provide. Like, so when you get up to, you know, a billion dollars in revenue, then you have to be like multi-country, multi-channel, multi-product. You know, these capabilities, most VCs just have never had. Right. Right. But I think now we have to have them. And then I think the private capital markets don't have all the functions of the public markets. So that needs to be addressed. So there's a lot of things that are changing. This is technically not a new question. It's a follow-up to that, which is you said culture is a set of actions, right? Yes. By the way, this is on the wall at A16Z and I every day would go to the office in San Francisco and I'd rent one of these. We could all book our own offices and the one that was my favorite was in the back corner near closest to the bathroom because I could dash to the bathroom between meetings. But in that corner, it says, you know, from the Bushido, you know, culture's set of actions, not just beliefs. Yeah, I'm like, I tell people when they come in, like, I don't care what you think. I don't care how you feel. I don't care what's in your heart. I just care what you do. And like what you do matters. And that's the way you have to run an organization or like you get into this bullshit. So, I mean, that's my follow-up. A culture is often also what you don't do. what you say no to, right? Yeah. What are the things that you've had to say no to because you're like, well, that's just not, that could be an interesting opportunity. It might even help an entrepreneur out, but that's just not in our mission. That's not us. Yeah, well, so I'll just give you one example. So the biggest one that got proposed to me like 18 times was, well, with AI, AI is very much like when the spreadsheet happened, that kind of launched private equity, right? because all of a sudden you could go in and make all these big companies much more efficient by like having them adopt this new technology and AI even more so, right? You can go in and you can go into an old company and you can make it much more efficient with AI. And there's like many VCs who are kind of going with that idea. And for me, like there's, I would say two big reasons I didn't want to do it. One is it's culturally the opposite of venture capital. You don't like leverage buyouts, basically. Yeah, LBOs. So, like, look, venture capital is about investing in entrepreneurs with new ideas and focusing on how they can grow fast. Leverage buyouts are about, you know, entry price, making it more efficient, firing people. I don't really want to grow it. I just want to make more money out of what it is. And so, like, if you're in the venture capital mindset, you're looking for the great entrepreneur to go build something amazing. If you're in the leverage buyout market, you're caring about, like, okay, I'm going to bring in a professional. I'm going to have them run this more efficiently and so forth. So it's the opposite motion. And so for me, I was like, well, I don't want to split the culture that way. Like, I think that's, you know, not going to be a good idea. And then the other thing is, like, I don't want to do that with my life. Like, I have the opportunity to fund, like, the greatest new ideas that are going to push humanity forward. I don't want to, like, you know, leverage buyout, seize candy, and fire all the old ladies who work there. Like, I'm not doing that with my life. I'm like, fuck that. You know, like, go to another VC if you want to do that stupid shit. Or like that. Like, I mean, it's not stupid. I think it's a good business. But it's not a business for me. So sometimes you're saying it's okay to impose bottlenecks on your own growth because that's just not what is fine. Yeah, like you don't have to be in every business just because there's money there. You know, look, I believe in like you build a company to kind of do something larger than yourself and make the world a better place. And then if you do that, you will make money. But if you are in business just for making money, like that's not for me. Like, that's, there are a lot of people who think that way, like, and I'll let them do that. But, like, I think that great companies don't think like that to me. Like, companies that you would want to be part of, that I would want to be part of, don't work that way. And so, I'm not going to build that thing just because, like, oh, there's money over there. Let's go run to the money. We're going to switch to questions. So, the way it's going to work is they even bring their questions in Discord. All right. And they're all voting on each other's questions. And the top ones that get voted by each other, we'll go through them one by one. First question. The question is, if I was a college student, where would I put my energy and effort? And what do I think about encouraging people to drop out of college? So, like, I think that if I was in college now, I would put a tremendous amount of... I would view AI as, like, a very powerful tool set. So almost think of it like, I think the best analog is electricity. So, like, okay, if you knew electricity was coming and you wanted to do something interesting in life and you were in the pre-electricity world, right, like, you know, where, like, it's 6 o'clock, we got to be at home because it's going to get dark. We're not going anywhere. Like, that world. Sounds like San Francisco. Yeah. Well, yes. you know, so then, okay, this whole new world is coming. Let me really understand this technology. And then, like, what is interesting to me in the world? And that could be biology. It could be material science. It could be, you know, rocketry. It could be anything. But, like, you want to have those tools in your bag when you go do that. Or it could be, you know, like, by the way, it could be in the creative field. So, you know, people, I think, misunderstand what's about to happen in the creative world. But, like, somebody who used to be, like, who in my era would have been, like, a pretty good guitar player can now make a sci-fi motion picture scored and everything by himself. And, like, the world is really, really different. So I would definitely kind of figure out what I'm interested in and then master this new tool set and kind of apply it together. I think that's probably the thing that's definitely going to work. In terms of dropping out of school, I think that this is very individual-based. So you'd mature at different points in life. You know, like, I think that I finished college myself, and that was good for me. Like, I think, you know, it was good for Zuck to drop out, given the idea he had and given the kind of company he was able to build And you know so I think that with career advice let me just say this that nobody can give you good career advice. They can give them good career advice. So I can give you good advice for me. I can't give you good advice for you. And particularly your friends are going to give you good advice for them, not for you. And so don't listen to your friends and, you know, figure out who you are. and, you know, what the best path for you is, I would just say on that. Yeah, so, by the way, so just on political donations, I also donated $5 million to the Kamala Harris campaign. Important fact. Yeah. Often not reported on. Just so you know, well, it is reported on Twitter every time the MAGA people get mad at me. Look, on politics, let me kind of just tell you where that came from and how I'm thinking about it in general. tech had, like, very little voice in Washington, D.C., and that had extremely severe negative consequences for tech. And specifically, so I can go through a few things in the Biden administration. One is they basically almost ended the crypto industry by enforcing things that weren't even in the law to shut down companies. And then they were, like, the same thing was happening with AI. So the last Biden administration executive order was to require for all sales of GPUs worldwide that they, any time you sold one, you'd first need government approval, U.S. government approval. So that would have basically taken us out of the AI race entirely. And the issue behind that was basically that we had no voice. Like the whole industry had no voice in Washington. So we kind of launched a very, very big effort to have a voice in Washington. And I would say that it's worked very well. So we have much better AI policy, much better energy policy, and much better crypto policy now than we did before we got involved. So I'd say I'm like very happy about that. And then all the kind of money and conversations have been about that. But look, I mean, the other thing is, like I said, I gave money to Kamala because I know her. I've known her for 15 years. She's been to my house 17 times. My wife sat next to her in church the whole time. So I knew her. So I knew I could talk to her. Biden, like we never could get a meeting with Biden for the whole time he was in office. and if you speak to Tim Cook or Sundar Pichai or Dave Ricks who runs Eli Lilly, none of them got a meeting with him in four years. Now, we all know why now, but at the time we didn't know and the result of that was like tech had no voice in Washington for those times. So, you know, it was a correction that we had to make. I'm not going to defend everything that Trump does or everything that Kamala would have done because, like, there's a lot wrong with both of them, and, like, I know them both. But there's a lot, like, the things that we needed to influence to kind of both make the country stronger and make the tech sector stronger I think worked out well. So I guess the answer is yes, I'm happy with that. Oh, here we go, man. That's a good question. So the question, to repeat the question for the podcast is, how do I think being in a rap group in college kind of affected me? And then can I rap for us now? So the story of that was, you know, I had a friend who got shot in the face and became blind. And so we started a, and he was very, very depressed. So I would send him rap music. And in those days, rap had just kind of gotten started. and that kind of cheered them up over time. So we started a rap group called The Blind and Deaf Crew, D-E-F. And we became a group, and I wrote some rhymes. So, like, one of the rhymes was, The blind, deaf, crew, you know where fly. Three of us, but we got four eyes. Plus he got his eyes. All right. Thank you, Ben. There are so many... Very memorable and intriguing pitches. For one of the most memorable was actually Databricks because it was so bad. So the pitch was that Jan Stoica, who is a professor at Berkeley, presented the company. And the slides he made, it was like going to like a computer science lecture that you couldn't understand in college. That's what the Databricks pitch felt like. So that was very memorable. It was memorable because of that. And then it was memorable because of what it turned into. But there were so many. Well, why'd you invest? If you couldn't make sense of it, why'd you invest? Well, the whole reason I had him come into pitch is because Scott Schenker, who was another professor at Berkeley who I knew, had called me and said, Ben, I have the best distributed systems guy that we've seen in the last 10 years in academia. his name is Matej Zaharias you know do you want to meet him and I knew as soon as he said that to me I was going to invest in the company but that pitch kind of scared my partners thank god they didn't talk you out of it yeah yes it's funny so the question is about Cluelly and you know what do I think about it now in terms of momentum and this and that and the other. Look, I think that an easier way to think about it is we invest in founders. And, you know, you want founders who are original thinkers and have kind of breakthrough thinking on whatever it is they're working on. And I think those guys, you know, had a bunch of breakthrough ideas, including marketing. Like, I think, you know, they are kind of marketing geniuses in a sense. And that, like, you know about them. They're not, you know, they're not the biggest company in the world, but they're the one that you know about. There's something to that. So, you know, what it becomes from here and where it goes, we'll see. But, like, I always say, you know, these things are early and there's only one unforgivable sin in business. And that's running out of money. and until you've run out of money, like I don't count any of these companies out, by the way. Like I've seen, like Slack was in dire straits before he figured it out. You know, he had built a game on Flash called Glitch and Steve Jobs outlawed Flash on the iPad and it was an iPad game. And like that's how dead he was, you know, and he had like $6 million left and he turned it into Slack. But that's Stuart Butterfield. You know, he's a great entrepreneur. So, like, companies go through changes and this and that. If you've, you know, like if you're a special founder and you don't run out of cash, I'm still for that and would bet on that. Question is, you know, given the SaaS apocalypse and given that we have a long time horizon, how do you think about, like, how can you invest in anything? Because Xanthropic is just going to one-shot it all. This is the Wall Street view. By the way, anytime Wall Street thinks one thing and Silicon Valley thinks another thing, that arbitrage is worth a lot of money and Wall Street's always wrong. So, I think there's actually a lot of opportunity now in that case. Like, I think, you know, some of these things are, you know, the whole moat is the code and the UI, and I think that's a difficult position to be in right now for sure. But there's a lot of companies, one, like most of the new companies, like nobody's coming in with like new SaaS companies at this point. Like people kind of know like, okay, that's not that defensible. Like, you know, you can build it and so forth. So that's not the new idea. So then if you go to the old ones and you go, well, you know, are they all dead? Like Wall Street thinks, I think, you know, not really. So like for a guy, I'll just give you one example of a company that I'm on the board of. So I'm on the board of a company called Navant. and Nivan is like a software travel agency for businesses. So, you know, in a company, your biggest kind of variable expense is travel. So you need to have like very tight policies around it and so forth. And then to build a travel company, you actually need to have supply chain relationships with not every airline in the United States, but every airline in the world, every hotel in the world. and like if you scrape their websites and do that kind of thing, they literally cut you off. They send you a cease and desist and they sue you and like you're out of business instantly. So it's not that hard to build all those global supply chain relationships and then you can't sell to any significant company that travels worldwide if you don't have all of them because like I need to be able to travel everywhere and then you've got to like integrate with all their whatever they're doing for their, you know, credit other systems in their company. And then the channel to sell it, you're actually selling to somebody called the travel manager, which, by the way, like Anthropic is, like the chance that Anthropic would build a channel to sell to the travel manager, like there's gold bricks everywhere. They're not going to pick up a silver brick. Like they're just not going to do it. Like I can tell you, Ange can tell you, Like, that's the last fucking thing on their mind. In fact, they've got an open rec now to hire a travel manager at Anthropic to manage the Navon relationship. Nonetheless, Navon lost two-thirds of its value in the SaaSpocalypse, and it's, you know, accelerated revenue since then. It's, you know, I think, I mean, it's, I got to be careful because it's a public company and so forth. But, like, I think they'll be fine for a very long time. So, you know, it's just one of those things where, and there's a saying on Wall Street, When the paddy wagon backs up to the House of Ill-Repute, which is, by the way, for those of you too young to know what that is, that's a whorehouse, everybody goes to jail, you know, not just the people who are committing crimes. And so in the Sasspocalypse, everybody's in jail, whether or not they should be in jail. So, like, just be aware of that. What do you think it's going to take for the markets to realize that not time? So I think what's happened, so if you look at the Navant stock, it was at like $25. It went to $8. It's now at $15. If they put up two more quarters in a row, it would probably be at $30. It's just like that kind of thing. It's just time. And education, I guess. Yeah, yeah. And you learn, Paul, so the way Wall Street works is, and Warren Buffett always says, you know, in the short term it's a voting machine, in the long term it's a weighing machine. Well, why is that? Well, the reason is it's a narrative. They buy the narrative. They don't buy the facts. They buy the narrative. So the story, if the story is this is a victim of the SaaSpocalypse, barring any new results from that, that's going to be a winning story because it's like such a good story. And by the way, all the portfolio managers who own SaaS companies got fired. So like nobody wants to jump into that, you know, kind of thing if you got the new job. And so that story is going to hold for a while. But eventually when the quarters come in, the Wang machine will go, well, maybe that narrative wasn't right for that company because why are they making so much damn money if they're a victim of, you know, if Anthropics can one-shot them? Like, that doesn't make any sense. Don't the customers know the one-shot is coming? And so then the narrative will change and a new narrative will win. And then it becomes a Wang machine. And that's true for, by the way, every company. What strata advice is super overrated today? I don't know what advice. That's a good question. I'm not sure. Like, what kind of advice are you getting? What did I get? I mean, look, I think you have to pay much more attention. Like, I think the thing that is true is, like, you can't ignore AI. I remember kind of before the internet came, which I was also alive for. You know, there were a lot of tech companies and anyone that ignored the internet was just gone. Like, you can't ignore a change that big. Like, there's no way that something that worked before AI can ignore AI and survive. So, like, that part is true. And so, if you're starting a company and you're not... dealing with not only AI today, but what's likely to happen, you know, as the models get bigger and so forth, like, it's just not going to be a very interesting company. So that part of advice is very correct. I think the part of the advice that's wrong is there aren't going to be any employees and there's going to, you know, companies aren't going to hire people and it's just going to be AI bots running everything. Like, by the way, like, all the data kind of is going in the opposite direction of that. Like, even, like, software engineering jobs are growing, like, very fast, despite what Dario says. And by the way, they're growing very fast at Anthropic. So it's like, you know, at what point do you call, like, bullshit on that idea? So... I think sometimes things get taken out of context, right? Like, with the political donation question, like, what was missing context was that there are donations to both sides. I think one of the things that gets taken out of context for Dario is he's often saying, hey, during the transition, some types of jobs that are low-skilled will get, those will go away, and those people will then have to, you know, take new jobs. Yeah, so there will be a job, so Dario is very right on that, there will be a job change. So not the advice Dario gives, but how he gets written up. Exactly. It's the tweets. It's the tweets. The tweets are the problem. Yeah, so those tweets turn out to be, I would just say, like, very overblown and not kind of representative of what's likely going to happen. So, you know, don't... And in general, like, the doom and gloom, I just think that's overstated, you know, a lot on AI. By the way, the most dangerous thing, I think, on AI by far is that we kind of fail as a country. We get too scared. We overregulate. We do what Bernie Sanders recommends. And some of you are Bernie Sanders fans. but like we put a moratorium on data centers and then China wins. And like I think a world where, by the way, either China has like super intelligence and we don't, or we have it and they don't is a much more dangerous world than having some kind of balance to the power. You know, concentrations of power historically have been the worst thing for humanity. And so I think that that would be the thing to be scared of. So I think the fear could cause actually a worse problem than what people fear. Well, here at AI Coachella, we are rational optimists. All right. So thank you for coming to AI Coachella, Ben. All right. Thank you. Thanks for listening to this episode of the A16Z podcast. 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