Marc Andreessen: The Real AI Boom Hasn’t Even Started Yet  ## Document Notes ## Highlights - **A Historic Convergence Of Forces** - Marc Andreessen says 2025–2026 mark a historic convergence of AI, institutional change, and geopolitical shifts. - He compares this era's significance to events like the fall of the Berlin Wall and the end of WWII. Transcript: Marc Andreessen This is a very, very historic time. I think 2025 was maybe the most interesting year in my entire career and probably life. And I think I would expect 2026 to succeed back. Lenny Rachitsky Wow. That says a lot. Marc Andreessen Yeah. I've seen some stuff. So it feels like two things are happening. One is the trust that a lot of people have had in kind of what you could describe as kind of legacy institutions around the world is, I think, in kind of full-scale collapse right now. By the way, there's a lot of data to support that. And so I think there's just, there's like a lot of structures and orders and institutions that people have just relied on for a long time that have just proven to not be up for the challenge. And then kind of corresponding with that is the national and global conversation have become like, let's say, liberated. And so, you know, this sort of incredible revolution that we have in kind of, you know, what I would describe as freedom of speech, freedom of thought, ability for people to openly discuss Things that maybe they couldn't discuss even a few years ago, you know, it's just dramatically expanded. And I think that's now on a one-way train for just a much broader range of discourse. And then, you know, there's also just these like incredibly massive geopolitical shifts that are happening. And obviously the U.S. Is changing a lot. Europe is changing a lot. China is changing a lot. Latin America, by the way, is changing a lot. Very dramatic, you know, events playing out down there right now, you know, kind of all over the world. Like I think a lot of assumptions are being pulled out into the daylight and reexamined. And then it's kind of the fact that all these things are happening at the same time. Right. And so you've got all of these countries and industries, you know, where things are kind of increasing upheaval, but you have AI as this kind of new technology that's going to really Affect things. And then you've got, you know, people, you know, citizens being able to fully participate, being able to argue things out. And so it's kind of like those three kind of big mega things are kind of all colliding at the same time. And I think we're probably just the very beginning of all three of those. And those all feel like kind of, you know, historical, you know, moment shifts, you know, comparable in magnitude to maybe the fall of the Berlin Wall in 1989. You know, maybe maybe the end of World War Two, you know, kind of moments like that. It certainly feels like that. Lenny Rachitsky Good God. What ([Time 0:04:50](https://share.snipd.com/snip/f2be1e02-58ed-42c1-9c35-4de0cb4b962f)) - **AI Meets Stagnant Productivity And Depopulation** - Productivity growth has been low for decades, leaving the economy starved for technological gains. - Andreessen argues AI arrives precisely when we need it to raise productivity and substitute for declining population growth. Transcript: Marc Andreessen And I think a lot of people in the industry have kind of what I would describe as this one-dimensional thing, which is, okay, as a result of the technology now working, AI just kind of sweeps The world and changes everything. And I think that's kind of the wrong frame, or I think it's based on an incomplete understanding of the world that we live in or the world that we've been living in for the last 80 years. And I would call out two things in particular. So one is, I think it's felt to us, like in the US and the West, for the last, you know, whatever, 30 years or 50 years, it's felt like we've been in a time of great technological change. But actually, if you look for actually evidence of that, like in statistical evidence of that, analytical evidence of that, like you basically can't find it. And in particular, economists have a way of measuring the rate of technological change in the economy that is productivity growth, which we could talk about what that means. But basically, it's sort of the mathematical expression of the impact of technology on the economy. And productivity growth for the last 50 years has actually been very low, not very high. So we all feel like it's been very high. There's been lots of technological change. What's actually happening is it's been very low. And in fact, the pace of productivity growth, like in the US, is running at like a half of what it, in my lifetime, in our lifetimes, it's been running at about a half the pace that it ran In between 1940 and 1970. And it's been running at about a third the pace that it ran between about 1870 to about 1940. And so statistically, in the US, in the West, technology progress in the economy, technology impact in the economy has actually slowed way down. And so the AI thing is going to hit, but it's hitting an environment in which we have actually had almost no technological progress in the actual economy for a very long time. So we could talk about that. And then there's this other just incredible thing that's happening, which is the demographic collapse, right? It's sort of a Western phenomenon and increasingly global phenomenon, which is the rate of reproduction of the human species is in rapid decline. And there are many countries, including the US, where the rate of reproduction is under two, meaning that many, many countries around the world, by the way, including China, which Is a really big deal, are actually going to depopulate over the next century. And so you have this kind of precondition that says there's actually been very little technological progress happening in the world, and the world is going to depopulate. And so AI is going to enter a world in which those two things are true. ([Time 0:08:32](https://share.snipd.com/snip/461e8bfe-3e98-4c97-9bb6-99542081fdf1)) - **Raise Super‑Empowered Kids With Agency** - Train kids to become "super empowered" individuals who deeply master a domain and fully use AI as a force multiplier. - Teach agency: let kids take initiative while learning to obey rules before leading. Transcript: Lenny Rachitsky I'm going to follow this thread about kids. I know you have a kid. And one of my most, my favorite lenses into how people think and what they value is what they're teaching their kids, what they're steering their kids towards. Are there specific skills or I don't even careers that you're steering your kid towards? Marc Andreessen The way I think about this, and you know, we have a 10 year old and so, you know and we actually homeschool and so we think a lot about this. So I think the way to think about the impact of AI on people, on specifically people as individuals, I think it's actually, you know, a lot of people just focus on kind of this, you know, This kind of very, I would say, straightforward and overly simplistic view of just literally job gains, you know, job losses, which we could talk about. But there's two specific things at the level of like an individual person or an individual kid. So I think it's pretty clear that AI is going to take people who are good at doing things and it's going to make them very good at doing things. Right. And so it's going to be a tool that's going to sort of raise the average kind of across the board. And, you know, look, you see that playing out already. You know, anybody who's in a position where they need to, you know, write something or design something or write code or whatever, if they're pretty good at it today, they use AI, and All of a sudden they're very good at it. And so there's sort of that aspect to it. And I think the way the education system at large is going to teach AI is going to be based, hopefully, a lot on that. But then there's this other thing that's happening, which we're also starting to see, and we're really seeing it particularly in coding right now, where the really great people are Becoming like spectacularly great, right? And so you just, you kind of use it, use the term, you think about like the super empowered individual, right? So the individual who is like really good at coding or really good at making movies or really good at making songs or really good at designing, you know, making art or whatever, whatever Those things are, or, you know, or podcasting or, you know, hopefully venture capital, you know, if you're very good at it and you can really harness AI, you can become spectacularly Great and like super productive. Right. And, you know, I'm sure you have a lot of friends in this, in this category as well, but like, you know, the really, really good coders are experiencing this right now. My friends are really good coders. Like, oh, my God. All of a sudden, I'm not twice as good as I used to be. I'm like 10 times as good as I used to be. And so I think at the at the unit of like N equals one of like an individual kid, I think the question is kind of how do you get them in a position where they're kind of this kind of super empowered Individual such that they're going to be really deep in whatever it is they're going to do, but they're going to be deep in a way that's going to let them fully use the power of AI to be not Just great, but to be spectacularly great. And I think that's going to be the real opportunity. At least that's what we're shooting for, and that's what I would encourage parents to shoot for. ([Time 0:11:15](https://share.snipd.com/snip/6425fbff-b2c0-4d81-a9fc-8338cb920f6c)) - **Use AI To Deliver One‑On‑One Tutoring** - Augment traditional schooling with one‑on‑one AI tutoring to approach Bloom's two‑sigma gains. - Use AI tutors to give instant feedback, quizzes, and adapt explanations to the child's level. Transcript: Marc Andreessen And so I'll just give you kind of the ultimate answer to that question, which is, it's been known for centuries that the ideal way to teach a kid at the unit of N equals 1, by far, the ideal Way to do it is with one-on tutoring. Like if you just have an individual kid and the goal is to maximize an individual kid, by far, you get the best results with one-on tutoring. And this is something that, like, every royal family knew in history. It's something that every aristocratic class knew in history. There's all these amazing examples. Alexander the Great was tutored by Aristotle. He took over the world, right? Like, you know, many of the great kings and queens, you know, royal families and aristocrats and so forth, you know, over the course of centuries, you know, kind of always had this approach. There's actually also statistical evidence, analytical evidence that this is correct. There's this, you know, massive question in the field of education, which is how do you improve educational outcomes? And basically, it turns out it's just, it's very hard to improve educational outcomes, except there's one method that always does it, which is called the, it's called the Bloom Two Sigma effect, which is there's one method of education that routinely raises student outcomes by two standards of deviation. And we'll take a kid from the 50th percentile to the 99th percentile, and that's one-on tutoring, right? So again, if you go back to like, N equals one, you have like a kid and a tutor, and they're in this like, you know, very tight loop with each other, you know, where the kid is able to constantly Kind of be on the leading edge of what they're capable of doing. And they can, you know, they can move incredibly fast, and they get kind of correction in real time, you get these better outcomes. But you know, to your question, like, it's never been economically feasible for anybody other than the richest people in society to be able to provide one on one tutoring kids. AI provides the very real prospect of being able to do that, right? Because obviously now, right? If you have a kid that's like super interested in something and they can talk to, you know, an LLM about it and they can ask an infinite number of questions and they can get instantaneous Feedback. And in fact, you can even tell an LLM, it's like, you know, teach me how to do the following. And you can say, you know, wow, that's like, I don't quite understand what you're saying. Like, dumb it down for me a little bit. Okay, now quiz me. You know, do I actually understand this? Like, people can just do this today, right? And so I think there's this, like, massive opportunity for parents, you know, in many walks of life to be, you know, with a little bit of time and focus to be able to say, okay, you know, My kid's probably still going to go through a traditional education system, but I'm going to augment this with AI tutoring. And, of course, there's going to be tons of startups, right? And there already are, that are going to try to build on all the products and services for this. Khan Academy, on the nonprofit side, has a big push to do this. And so I think the broad answer might be a hybrid approach with schools plus one-to tutoring through AI. ([Time 0:19:21](https://share.snipd.com/snip/c14a141f-216c-4947-81da-2dabef6ec1b3)) - **Task Change, Not Total Job Loss** - Fear of mass job loss is reductive; task substitution matters more than job disappearance. - Andreessen expects faster productivity growth plus shrinking populations will keep human labor valuable. Transcript: Marc Andreessen Yeah. So the job substitution, job loss thing is just, it's very reductive. I think it's an overly simplistic model. And again, it goes back to what I said at the very beginning, which is we've actually been in a regime for 50 years of very slow technological change in the economy. And so, and again, like I said, it's like at a half the rate of the previous era and then a third the rate of like 100 years ago. And so we're coming out of this kind of phase where we've had like almost no technological progress in the economy. We've had remarkably little job churn as a result of that relative to any historical period. And so even if AI like ticks up, even if AI triples productivity growth in the economy, which would like be a massively big deal, it would take us back to the same level of job churn that Was happening between 1870 and 1930. And if you go back and you read accounts of 1870 and 1930, people just thought the world was awash with opportunity. At that rate of technological transformation, kids were able to develop new careers into new areas of the economy, building new kinds of products and services. I mean, a huge part of everything in our modern world today was kind of invented and proliferated kind of during that period. And so even if AI like triples the pace of economic change in the economy, it's going to just translate to like a much higher rate of economic growth is going to translate to a much higher Rate of job growth. And, you know, there'll be some level of like task level and job level substitution that will take place, but that will be swamped by the macro effects of economic growth and innovation That will happen. And then corresponding to that, there will be you know, there will be hiring booms, you know, quite honestly, I think all over the place. And then again, go back to the other thing, which is like, this is all happening in the face of declining population growth and increasingly population shrinkage. And so human workers in many, many, many countries over the next, you know, 10, 20, 30 years are going to be at more and more of a premium, literally because you're going to have shrinking Population levels. We don't really want to get into politics particularly, but it does feel like the world broadly is going to reverse course on the rates of immigration we've had for the last 50 years. It seems to be kind of a broad-based kind of thing happening, kind of with the rise of nationalism, concerns about the rate of immigration. And immigration historically in countries like the U.S., it's kind of ebbed and flowed over time based on kind of how the national mood shifts. And so if you sort of combine in a country like the U.S. Or any country in Europe, if you combine declining population with less immigration, the remaining human workers are going to be at a premium, not at a discount. And so I think that combination of kind of faster productivity growth, faster economic growth, and then slower population growth and less immigration actually means there's going To be much less of this kind of dystopian, you know, no jobs thing. ([Time 0:22:37](https://share.snipd.com/snip/dcaed957-9a32-462b-b7f9-308711da5452)) - **Become A Rare Multi‑Skill Specialist** - Become excellent at one role (engineer, PM, or designer) and use AI to gain competency in the other two. - Combine skills to become a non‑fungible "E/F‑shaped" specialist who orchestrates AI to build products. Transcript: Marc Andreessen This, I think, is a really funny question. So these three roles in particular, obviously, are kind of the central roles for building, you know, for tech companies. So the way I've been describing it is, you know, the concept of the Mexican standoff, right, which is the movie scene where the, you know, the two guys have guns pointing at each other's Heads. And then there's, if you watch like John Woo movies, he loves to have, he does the three-way Mexican standoff where you've got like a triangle, you know, people and like, you know, John Woo movie is they've got, you know, guns in both hands. So they're all, each is aiming at the other two. And you've got this kind of standoff situation. And so the way I've been describing this is there's like a Mexican standoff happening between those three roles, between product manager, designer, and coder. Specifically of the following, which is every coder now believes they can also be a product manager and a designer, right? Because they have AI. Every product manager thinks they can be a coder and a designer. And then every designer knows they can be a product manager, a coder. And so people in each of those roles now know or believe that with AI, they don't need the other two roles anymore. They can do that because they can have AI do that. And then, of course, there's the real irony, which is all three of them are going to realize that AI can also be a better manager. So they're going to aim the guns up the work chart, but that's probably the next phase. And what I think is so fascinating about this Mexican staff is they're actually all kind of correct, I think, which is AI is actually a pretty good, it's actually now a really good coder, It's actually now a really good designer, and it's also a really good product manager. It's actually good at doing all three of those things, or at least doing a lot of the tasks involved in those three jobs. And so, again, this goes back to this kind of idea of the super empowered individual, where if I'm a coder, like, you know, I mean, step one is like, I need to make sure that I really understand AI coding and like what that means and how coding is going to change in the future. You know, I need to, you know, specifically how to go from being a coder who writes code entirely by hand to being a coder who, you know, orchestrates, you know, a dozen instances of, you Know, coding bots. You know, there's a change in the actual job of coding itself, which is happening right now. But the other part of it is, okay, how do I become that super part individual? How do I become a coder that also then harnesses AI so that I can also be a great product manager and I can also be a great designer, right? And then the same thing for the product manager, which is how do I make sure that I can now use coding tools? How do I make sure I can also, you know, do AI based design? And the same thing for the designer, which is how do I use AI to also become a coder and also become a product manager? And then what you did is maybe those individual roles changed. Maybe those are not any more sort of stovepipe roles the way that they have been for the last 30 years or whatever. But what happens is that the talented people in any of those roles become super empowered and they become good at doing all three of those things. And then those people become incredibly valuable because then those are people who can actually build and design new products from scratch, which is the most valuable thing. ([Time 0:36:09](https://share.snipd.com/snip/d5ae0405-fccf-40ee-8ce8-e064f0b4b748)) - **Learn To Orchestrate AI, Not Just Code** - Treat jobs as bundles of tasks and adapt by learning the new AI‑shifted tasks. - Learn to orchestrate AI (argue with and evaluate code bots) rather than only write code by hand. Transcript: Marc Andreessen And I think that's a great example of what's going to happen in coding. The tasks are going to change. Product management, the tasks are going to change. Designer tasks are going to change. And so the job persists longer than the individual tasks. And then as the tasks change enough, then that's when the jobs change. And so at the level of an individual, you kind of want to think of like, okay, I have this job. The job is a bundle of tasks. I need to be really good at making sure that I can like swap the tasks out, can really adapt, use the new technology, get really good at AI coding, for example. And then you want to kind of add skills. I can also get really good at design. I can also get really good at product management because I've got this new tool. So you want to kind of pick up more and more scope as you do that. And then 10 years from now, is your job title coder or coder designer product manager? Or is it just, I build products? Or is it just, I tell the AI how to build products? It's like, whatever that job is called, who even knows what it's going to be. But it's going to be incredibly important because the people doing that job are going to be orchestrating the AI. And so that's the track that the best people are going to be on. ([Time 0:41:11](https://share.snipd.com/snip/493b0c51-57d3-48e2-b6d7-41e083debe67)) - **Go Deep In Code To Supercharge AI Leverage** - Still learn to code deeply if you aim to be elite; depth helps you evaluate and fix AI outputs. - Use AI to accelerate learning but maintain low‑level understanding down to assembly and chips. Transcript: Lenny Rachitsky You're in the camp of still learning to code, still a valuable skill. Marc Andreessen Oh, yeah, totally. Well, again, if you want to be one of these super, look, look, if you just want to put yourself on autopilot and like, I can't be bothered and I'm just going to have AI write the code and it's Going to generate whatever it does and that's fine. And I'm going to be, you know, I'm going to be, if the goal is to be a mediocre coder, then just let the AI do it. It's fine. The AI is going to be perfectly good at generating infinite amounts of mediocre code. No problem. It's all good. If the goal is I want to be one of the best software people in the world, and I want to build new software products and technologies that really matter, then yeah, you 100% want to go all The way down. You want your skillset to go all the way down to the assembly, to assembly and machine code. You want to understand every layer of the stack. You want to deeply understand what's happening at the level of the chip, right? And the network and so forth. By the way, you also really deeply want to understand how the AI itself works, right? Because you want to, right? Because if people don't understand how the AI works, they're clearly able to get more value out of it than somebody who doesn't understand how it works. I mean, you're always more productive if you know how the machine works, right, when you use the machine. And so, yeah, the super empowered individual on the other end of this that wants to do great things with the new technology, yes, you 100% want to understand this thing all the way down The stack because you want to be able to understand what it's giving you, right? ([Time 0:47:22](https://share.snipd.com/snip/13007979-8990-49ae-80fe-f946b0a4adec)) - **Design Shifts From Execution To Human Context** - AI will automate many design tasks but free designers to focus on higher‑level human questions. - Great designers can become vastly more powerful by combining design judgment with AI tooling. Transcript: Marc Andreessen Design the perfect icon, right, is going to be like, all right, A is going to do that all day long. It's going to give you a thousand icon designs. It's going to be great. Like, it's going to be fantastic, like whatever, you know, and there will still, by the way, there will still be some level of human icon design or whatever, but like A is going to get really Good at that. But like, what are we trying to do? Like, you know, kind of capital D design of like, all right, what is this thing for? And how is this going to function in the world of human beings? And like, you know, is this going to make people happy when they use it? Is it going to make people feel good about themselves? Is it going to fit into the rest of their life? Is it going to, you know, I don't know, challenge them in the right way? All these kinds of higher level questions that the great designers have always thought about, like the job of designer will involve much more of those higher level, more important Components. And then again, with AI doing a lot more of the underlying tasks. You think of like, I don't know, the world's best designers, you know, Johnny Ive or whatever, and you could be like, wow, like if I'm a designer today, if I'm a 25-year designer and I aspire To be, you know, Johnny Ive in a decade, it's all of a sudden I have a new path that I can use to kind of get there, which is, you know, because Johnny Ive did everything he did without AI. Now, you know, a young designer can be like, wow, if I really harness AI in a decade, I'm going to be like the best designer the world's ever seen because it's not just going to be me. It's going to be me plus being so super empowered by this technology to be able to do so much more. And then so much more of my time and attention is going to be able to be focused on these higher level things that most designers never get to. And I think that's going to be another great example of that. ([Time 0:52:01](https://share.snipd.com/snip/eeb023d9-85fb-442c-9c24-ec8d929fdba0)) - **Use AI To Train Yourself Constantly** - Spend spare hours training with AI: ask it to teach, give assignments, and evaluate your work. - Use AI as a personal tutor to expand skills across domains and accelerate career growth. Transcript: Marc Andreessen The thing about AI that I think people are just like not getting enough benefit out of yet is just it will teach you. Like, this is amazing. Like, there's never been a technology before where you can ask it, like, teach me how to do this thing. So I always feel like it's like, it's like people spend too much. It's one of these things where it's like so much focus on figuring out how to use like a large language model. It's like, okay, what am I going to try to get it to do for me? Right. Which is first very important. But the other side of it is what can I get it to teach me how to do? Right. And it's just as good at that. Right. And so again, this is this level of latent superpower. People who really want to improve themselves and develop their career should be spending every spare hour, in my view, at this point talking to an AI, being like, all right, train me Up. Super empower me. I'm a coder. Train me how to be a product manager. It will happily do that. It knows exactly how to do that. Run me, make me problems, you know, make me assignments, then evaluate my results. ([Time 0:58:42](https://share.snipd.com/snip/a73f8e27-f739-4084-b8d3-cd84992ea8c0)) - **Founders Rethink Products And Company Shape** - Founders are rethinking products, jobs, and company structure because AI can redefine each layer. - The ultimate question: can a founder orchestrate AI bots to run an entire company or product alone? Transcript: Marc Andreessen Yeah, so this is a great, very you know, topical topic. That's all playing out in real time right now on the leading edge. So I think there's like three layers of it and see if this makes sense. I think there's like three layers of it. I think layer one is they're thinking, all right, how does AI redefine the products themselves? Right. And this is kind of the, this is kind of the time honoredhonored kind of thing that happens when technology transitions. And this is kind of what a lot of venture capital is based on, which is, okay, there's a new technology that comes out. And maybe it's the personal computer or the iPhone or the internet, or now it's AI. And it's like, all right, is this a new capability that gets added to existing products, right? So all of a sudden you've got, I don't know, an existing, you know, software business, and now you've got your, you know, PC version of it, and now you've got your iPhone version of it, And you just kind of keep on going. And, you know, you kind of add, the new technology kind of gets kind of added into the mix, you know, it's kind of another ingredient to an existing formula. And of course, you know, a lot of new technologies are like that, right? You know, I don't know when, I don't know, when Flash, when Flash storage came out or something, you know, it didn't really, didn't really redefine the software industry because people Just went from using, you know, hard disk using flash storage or something. But when the internet came out, like basically old school on-prem software for the most part, you know, not entirely, but like a lot of it died and just got replaced by like web software, Right? And so sometimes you get the kind of, it's additive to an existing thing. Sometimes you get the, actually it redefines the entire product category, redefines an industry, the actual company, you know, in many cases, the companies themselves turn over. And so, so, so, you know, so there's sort of this question and like, you know, an example, you just mentioned nano banana. So like a great example is there, you know, there are these businesses like, you know, just take Adobe, like, you know, Photoshop is built a whatever 40 year franchise in image editing. OK, is AI a sort of a feature now that gets added to Photoshop to be able to do AI based image editing? Or, you know, do you just like stop editing images entirely because you're using Nano Banana and all images are just being generated? And it's just easier to just have AI generate a new image than it is to try to edit an old one. So I think there's many areas of tech in which that question is being asked. And the answers I think will vary by domain. But obviously as a venture firm, we're betting hard on many of these categories being totally reinvented. And a lot of the best founders are trying to figure out how to do that. So that's kind of AI changing the definition of the product. I think the next layer is actually a lot of what we've already talked about, which is AI changing the jobs. And so it's a lot of what we've already talked about. But like, OK, if I'm a founder of a company and I've got, you know, if I have room in my budget for 100 coders, you know, how do I get those coders to be super empowered AI coders? Not, you know, not the kind of coders I used to have. And if they're super empowered AI coders, then does that mean, you know, do I still need the hundred? Maybe now I only need 10 or does that mean I still want a hundred, but now they're doing 10 times more. Right. And so that, you know, as you know, like a lot of the best founders are working on that right now. And then I think the third shoe to drop hasn't quite dropped yet, but it's, it's, you know, it's kind of the big one, which is like, all right, like the, the, the, the basic idea of having A company, right. You know, does that change? And again, here, you've got this concept of the super powered individual, which is like, okay, you know, can you have entire companies where you have basically the founder does everything, Right? Because what the founder is doing is like overseeing an army of AI bots. And there's sort of this, you know, there's kind of this holy grail in our industry that's been running for a long time, which is like, can you have the, can you have like the one person Billion dollar outcome? And, you know, we've had a few of those over the years. Bitcoin is probably the most spectacular example, you know, with Ethereum right behind it, you know, which wasn't quite one person, but, you know, a very small team, you know, you had, You know, kind of Instagram and WhatsApp that had very big outcomes with very small teams. You know, every once in a while, you get one of these things where you just, you know, something hits and you just have a, you know, very small number of people associated with it. You know, but that said, you know, most software companies obviously end up with, you know, huge numbers of employees. And so I think, you know, the most leading edge founders are thinking of like, okay, how do I reconstitute the actual very definition or idea of having a company. And can you have a company that's literally basically just all AI? And if you're doing anything in the real world, that's hard, but if you're doing software like that, that seems like it might be feasible in some cases. And then there's the ultimate example of that, which is can you have autonomous AI economy stuff happening where you have AI bots on the blockchain or something, you know, that are basically Out there like functioning as a business and like making money and just, you know, literally where the AI does all the work itself and just get, you know, issues made of it as. And so maybe, you know, maybe that, you know, maybe that, maybe that's the final outlier result. We have, we have a few founders who are chasing that kind of thing. ([Time 1:02:56](https://share.snipd.com/snip/ee4113be-5945-49b4-b48a-47b386a3fbfc)) - **Moats Are Unclear In A Fast‑Moving AI World** - Moats in AI are uncertain; models, apps, and business fit could all win or be commoditized. - Treat the AI era as a complex adaptive system with many interacting structural unknowns. Transcript: Marc Andreessen Experience with like really big technological transformations, and of course, I kind of lived this directly with the internet, and I saw this happen, is the really big technological Transformations, they take a long time to play out. There's all of these structural implications that just kind of cascade out over time. And then there's kind of this rush to judgment up front where people kind of say, oh, it's therefore obvious that, you know, X, Y, Z. It's therefore obvious that this kind of company is going to be the company of the future, not that kind. It's obvious that this incumbent is going to be able to adapt and this other one isn't. It's obvious that there's economic opportunity in this kind of startup and not in these others. It's obvious that the moats are going to be in this area of the technology, but not in this other area. And what everybody does is they kind of state those things with just an enormous amount of self-assurance where they really sound like they have all the answers. And then what happens is these ideas kind of saturate the media, right? Because the media naturally prizes definitive answers over open questions. When CNBC is booking guests, they want a guest who's going to come on and say, yes, this is the way it's going to be, X. Not like, you know, I think that's a really good question, and let's debate it from eight different angles. And what I found is if you look back on those predictions a few years later, and you can do this, by the way, if you pull up like coverage of the internet from like 1993 through like 1997, Or even through like, for that matter, even through like 2005 or 2010, and you look at like the kinds of confidence statements people were making in the first 10 or 15 years, like I would Say like almost all of them are wrong, generally like quite badly wrong. And so I just, I the process, I think there's going to be a massive amount of technological change. It's going to be like, I don't know, five or six layers of structural change that will play out over time. And again, we've talked about a lot of this, but the implications on what are the definitions of products? What are the definitions of companies? What are the definitions of jobs? What are the definitions of industries? How does this play out at the national level? How does this play out at the global level? You know, how does this, by the way, how does this intersect with politics? How does this intersect with, you know, unions? How does this intersect with, you know, war? You know, what's China going to do? You know, and so it's just like, there's just, there's, there are just a tremendous number of unknowns, like a very, very large number of unknowns. And I think it's just like really, really dangerous to prejudge these things. And so I'll just give it, I'll just give it, and it's just, I'll just run this as a thought experiment. You know, so you can see what you think on this, but it's like, you know, like do AI models, are AI models themselves like defensible? Like, is there a move on AI models? And on the one hand, you'd be like, wow, it certainly seems like there is or should be because if something takes billions of dollars to build and you need this incredible critical mass Of compute data and there's only a certain number of engineers in the world that know how to do this and they are getting paid like NBA stars and then these companies have to deal with all These like crazy, you know, political issues and press issues and reputational stuff and regulatory and legal, like all of that translates to like, you know, okay, probably at the End of this, there's going to be two or three companies that are going to end up with like, you know, a hundred percent, you know, I don't know, whatever 50, 50 or 30, 30, 30, or 90, 10, one, Or whatever it is market share. And then they're going to have whatever probability they have. And it's going to be a kind of a classic oligopoly and, or, or maybe, you know, or maybe one company's going to win definitively it'll be it'll be a monopoly in that and by the way those outcomes Have happened in software many times before and so maybe that that will be the outcome you know the other side of it is you know if you had told me three years ago um you know that in the uh You know kind of Christmas of chat gpt that like within basically a year to year and a half there would be you know five other american companies that would have basically you know capable Products. And then there would be another five companies out of China that would have exactly capable products. And then there would additionally be open source that was basically the same. I would have been like, wow, the thing that seemed like it was black magic all of a sudden has become commoditized really fast. Which, by the way, is exactly what happened. Within a year of GPT-3 coming out, there were open source GPT-3s running on a fraction of the hardware that were available for free. Now you've got fully in the game, you've got Google and you've got Anthropic and you've got XAI and you've got Meta and you've got all these other companies that are, and then DeepSeek And Kimmy and all these other Chinese companies. And so even at the level of LLMs or AI models, you can squint and make that argument either way. By the way, same thing at the level of apps, right? It's like one school of thought is the apps are not a thing because the model is just going to do everything. But another way of looking at it is no, actually adapting the model is kind of the engine into a domain involving human beings, where you need to actually have it fit for purpose to be able To function in the medical industry or the legal industry or whatever, or coding. No, you actually need, the application level is actually going to matter enormously. And maybe the LLM's commoditized, and maybe the value goes to the apps. And again, you can kind of squint either way on that one. And I know very smart people who are on both sides of that argument. And so my honest answer on this is I think we're in a process of discovery over time, which is, you know, the way I think about this kind of structurally is it's a complex adaptive system. The technology itself, you know, provides one of the inputs. The legal and regulatory process, you know, is another input. You know, actual individual choices made by entrepreneurs matter a lot. The economics matter a lot. Availability of investor capital varies over time. That matters a lot. And this is a complex system. And so we actually don't know the outcomes on this yet. And we need to basically be open to surprises at the structural level of what happens. And of course, as a VC, this is very exciting because it means we're doing this now. We should kind of make bets along every one of these strategies and kind of see how this plays out. ([Time 1:08:45](https://share.snipd.com/snip/79efc0d9-3c42-4174-98c7-4040bcc47c3d)) - **Back Many Determined Optimists** - As a VC, back many bets and favor indeterminate optimism to let many founders pursue bold, determinate plans. - Seek founders who are determined optimists with specific, executable visions. Transcript: Marc Andreessen So for us, yeah, for us, we obviously have a very deliberate strategy. One way to think about this is the Peter Thiel, you remember the Peter Thiel formulation of, he said there's a two by two, there's optimism and pessimism, and then there's determinant, And is it indeterminate and indeterminate, right? And so, and he always argued, like, there's, he always argued that, like, Silicon Valley is characterized by too much, what he calls indeterminate optimism, right? And what he always described, what he meant by that is, basically, I think the way he would describe it is, an indeterminate optimist who thinks the world is going to be better but can't Explain why. Right. Like some combination of things is going to happen to make the world be better, even if we don't know what those things are. And and, you know, I think he at least historically would say, like, that's that's basically, you know, that that that that risks at least being just like wishful thinking or delusional Thinking. And what the world needs more is determinate optimists, which are people who are like, no, the world is going to be better because I'm going to do this specific thing, right? And he would classify, for example, Elon, you know, he would sort of maybe say, you know, VCs are indeterminate optimists. And then he would say, you know, Elon is the determinant optimist where it's like, no, I'm going to build the electric car. I'm going to, you know, solar, and then I'm going to, you know, Mars, you know, right? And I mean, these very concrete things. And I think there's a lot, I think there's a lot to Peter's framework, but the way I would describe it is I think maybe if you and I disagree on part of that, it would be I think the indeterminate Optimism is a stronger phenomenon than at least I think he's historically represented it as, and I would put myself firmly in the indeterminate optimist category, and that's the strategy That we have at A16Z. And the reason for that is hopefully it's not so much wishful thinking, it's more, no, what the indeterminate optimism of venture capital, or the indeterminate optimism of A60Z or Silicon Valley is very, it's actually very specific, which is, there are these extremely bright and capable people, like Elon, and many others, who are founders, right, and product, And, you know, kind of product creators, right, and each of those individual people is a determinant optimist. Each of them individually has a very strong view of what they're going to do. But the great virtue of the capitalist system, the great virtue of the American economy, the great virtue of Silicon Valley is we don't just have one of those. We don't just have 10 of those. We have 100 and 1,000 and then 10,000 of those. The way to optimize the outcome is to have as many of those as possible, be as good as possible, run as hard as possible. And then just the nature of the future is like, we just don't know all the answers and that's okay. And the right way to deal with that is to run as many experiments as possible and have as many people try to do as many interesting things as possible. And so, yeah, I would put myself firmly on the side of the indeterminate optimist. ([Time 1:18:23](https://share.snipd.com/snip/7ddfae00-c00a-4f89-bb2d-5862c5b2b39c)) - **A Barbell Media Diet: X And Old Books** - Andreessen follows a barbell media diet: real‑time X plus timeless old books, and he values practitioner content. - He finds direct creator newsletters and podcasts offer underrated alpha from domain experts. Transcript: Marc Andreessen Yeah. So what I read is basically, I mean, I would say I read basically three categories of things. So like in terms of like general media, it's basically, I sort of, I always describe it as I have like almost a perfect barbell strategy, which is I read X and I read old books. Right. So it's basically either like up to the minute what's happening right now or it's like a book that was written 50 years ago that has stood the test of time. And then, you know, we're presumably there's something timeless in it. And then it's sort of everything in the middle. I'm always like much more skeptical about. And it's particular, it's kind of what I already said, which is, I think if you go back and you read old, nobody ever does this. It's actually really funny. Nobody ever does this. There's no market for it. But if you go back and you read old newspapers, and by the way, you can, you can do this. Just read last week's newspaper, right? I'd say we're taping on Friday. So read last Friday's newspaper, right? And just go back and read it and be like, oh my God, like none of this happened. Like none of what they predicted played out the way that they said that it would. None of this turned out to actually be that like relevant or correct. Like they didn't understand, like, you know, they, by the way, they had no view of what was going to happen this week. Then they couldn't know. And so they were making predictions and forecasts and so forth based on like not having information. But it's just like, wow, like, you know, like none of this happened. Like, I wish I had never read this. Like, oh, my God. And then, you know, it's kind of the same thing with magazines. They go back and read old magazines and just like the level of, you know, just the endless numbers of predictions that they make. And kind of, you know, the problem with, you know, newspapers, at least they're going day to day. The thing with magazines is like every, it's like a week or month, you know, kind of a long cycle. And so it's even, the time an article even hits publication, it's often out of date. So I just have a big problem with kind of everything in the middle. And so it's either of the moment or timeless. But then, yeah, you mentioned newsletters. So the other thing, and this is maybe obvious, but I think it's probably still underrated, which is the actual practitioners in the field who are actually creating content, I think Probably is still like dramatically under underrated. And I think this is a huge part of like the Substack phenomenon and the newsletter phenomenon and the podcast phenomenon is like direct exposure to the people who are actually principals In the field who actually know what they're talking about is probably still dramatically underrated. And I think, again, the reason for that is like we're used to being in this mass media kind of culture in which basically everything is mediated, right? Everything got filtered through TV interviews or newspaper interviews or magazine interviews. And obviously now more and more, it's just, no, you actually want smart people who are actually working on something explaining themselves. And then you have new kinds of intermediation, like podcasts that kind of open that up for people to make that possible. And so, yeah, like domain practitioners are, you know, really great. I mean, just to state the obvious in AI, you know, it's obviously your stuff, but also like, you know, Lex, you know, the fact that like Lex Friedman can have, you know, the world's leading Or, you know, whoever the, you know, any of you guys, you know, there's a small handful of you guys who have access to these people, you could have the world's, you know, kind of leading Experts in the domain actually show up. And by the way, it's, you know, it looks, the critique always is people talk their book, like if I'm running a startup or whatever, I'm just selling. And there's always a little bit of that. But it's also, my experience is people love to talk about what they do. And they fundamentally want to express what they do, and they want to explain it, and they want people to understand it. And everybody kind of enjoys that, and they get to contribute to human knowledge by doing that, and they they get ego gratification by doing that. And so I think there's just actually just tremendous amounts of alpha in listening to the world's leading experts in the space who actually just like show up and talk about what they're Doing. And of course, like the world is awash in that today in a way that it wasn't as recently as 10 years ago. So yeah, I do as much of that as I can too. ([Time 1:30:25](https://share.snipd.com/snip/3c1006a3-5132-4052-b824-5f4027b83c5a)) - **His Son Builds Star Trek Games On Replit** - Marc's 10‑year‑old discovered Replit and spends hours vibe‑coding Star Trek simulators. - The child uses AI tools to build interfaces inspired by Next Generation's LCARS design language. Transcript: Marc Andreessen So one is my 10-year My 10-year right now is 100% obsessed with Replit. And by the way, it was not from me. Do you have kids? I do. Lenny Rachitsky I have one two and a half year old. Marc Andreessen Two and a half. Okay. So you haven't run into what I'm running into now, which is whatever it is you do is not cool. Right? It's two and a half. Whatever daddy does is like the coolest thing in the fucking world. I can tell you by the time he's 10, whatever you do is like deeply uncool. Right? And I'm highly aware of that. And so like if I mentioned, oh, yeah, we work on XYZ, you know, he's like, OK. But when he discovers something, then then it's cool. Or when his friends tell him about it, it's cool. And so he threw no interference on my part. Discovered Replit about about three months ago and discovered Vibe Coding and is like completely obsessed with Vibe C games and all kinds of all kinds of things and like literally do It for hours and so i'm seeing that phenomenon play out uh which is super fun um uh that's one two is i am just completely in love with all the ai voice stuff um i think it's just absolutely Amazing hysterical uh my favorite uh party trick at dinner parties now is to pull out uh grok uh with uh which is, if you've seen, it's a foul-mouthed raccoon avatar in the Elon's Grok App. So I think that's super fun. We have this company, Sesame, that went viral last year for these just incredibly intimate, emotional kind of voice experiences. So I think the voice stuff is fantastic. I'm also super fascinated by all the voice input stuff. And so, you know, one of the most recently, a company recently sold, but, you know, that all the, I think like the pendants, the wearables, like all that stuff is going to be big, the metaglasses. I think there's going to be a whole wearables revolution here. I love the voice input stuff. I have this app on my phone now called Whisperflow, which is voice transcription, which works staggeringly well. It's like a voice transcription function, but you can actually talk to the AM model while you're doing voice transcription. So it kind of understands when you're telling it, no, no, I want bullet points over there and I want this and that. And it understands that you're not telling it to type in the words, I want bullet points. It just actually understands that you want bullet points. And so like, that's a great example of a super useful thing. And so I think the voice mode stuff is going to be, is going to be, it's going to be really great. Lenny Rachitsky Subscribers in my newsletter get a year free of Replit and Whisperflow. So there we go. What's the, what's the most memorable thing your son built with Replit Oh, so he's gotten super into Star Trek. Marc Andreessen And so, so far, he's writing Star Trek simulators. So like all the, you know, all the, by Next Generation, they actually had a- Next Generation, okay, I was going to ask. Well, actually, we like them all. We watched the new Starfleet Academy last night, which actually is quite good. But we watched the original, you know, we watched them all. But it was in Next Generation where they actually developed an actual design language for the computers. Because if you watch the original series, they just had like basically, you know, nods with lights. And they didn't really, you know, they just like were like, you know, fucking around on set and trying to pretend they were doing it. But by Next Generation, they actually had designed, they actually had a UI design language. And so, one of the fun things you can do vibe coding is you can say, give me a Star Trek next generation, you know, user interface for, you know, whatever this, that, or whatever. And it actually uses the, they call it the seven, a nerd out, they call it L cars, um, uh, design language. And, um, it'll, you know, it'll actually build you like Star Trek next generation bridge consoles, um, using that design language, but, you know, with your choice of like a Star Trek Game, for example. ([Time 1:39:51](https://share.snipd.com/snip/a5e85f7b-c740-4055-b772-7ab6d5eef594))