Marc Andreessen: The real AI boom hasn’t even started yet

If we didn't have AI, we'd be in a panic right now about what's going to happen to the economy. We've actually been in a regime for 50 years of very slow technological change in the face of declining population growth. The timing has worked out miraculously well. We're going to have AI and robots precisely when we actually need them. The remaining human workers are going to be at a premium, not at a discount. >> How big of a deal is the moment in time that we are living through right now? >> This is a very, very historic time. AI is the philosopher stone. Now we have a technology that transfers the most common thing in the world which is sand converted into the most rare thing in the world which is thought. >> We spent a lot of time with the most cutting edge AI forward founders. The most leading edge founders are thinking of can you have entire companies where the founder does everything. >> There's all this concern that young people jobs are not going to be there for them. AI is replacing them. >> Everybody wants to talk about job loss but really what you want to look at is task loss. The job persists longer than the individual tasks. >> What's your sense of just the future of

three very specific roles? Product manager, engineer, designer. There's like a Mexican standoff happening between those three roles. Every coder now believes they can also be a product manager and a designer 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 and a coder. They're actually all kind of correct. What happens is the additive effect of being good at two things is more than double. The additive effect of being good at three things is more than triple. You become a super relevant specialist in the combination of the domains. >> People aren't fully grasping how much this changing. And people who really want to improve themselves and develop their careers should be spending every spare hour in my view at this point talking to AI being like, "All right, train me up." Today my guest is Mark Andre, one of the most seinal figures in tech and in business. He invented the web browser, built the world's largest venture firm. He's also a multi-time founder and an investor in essentially every generational tech company and is also one of the most clear-minded, lateral,

and insightful thinkers about both the past and the future of technology. In this very special conversation, we chat about how unique and significant the moment that we are all living through right now is, what skills he's teaching his kids to thrive in the AI future, what happens to product managers, designers, and engineers in the coming years. where moes exist in AI, what the most AI native founders are doing differently, and so much more that is just scratching the surface of this very deep and important conversation. You are going to walk away from this chat being smarter about what is going on in the world right now and where things are heading. A huge thank you to my newsletter community and focus on X for suggesting topics and questions for this conversation. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. It helps tremendously. And if you become an insider subscriber of my newsletter, you get a year free of over 20 incredible products, including a year free of lovable, replet, bold, gamma, nad linear superhuman devon post hog dscript whisperflow perplexity warp, granola, magic patterns, raycast,

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Mark Andre, thank you so much for being here and welcome to the podcast. >> Awesome, Lenny. Thank Thank you. It's great to be here. >> I want to start with just a big picture question. I have a billion directions I want to go, but I think this is going to give us a little bit of a frame of reference. How big of a deal is the moment in time that we are living through right now? >> This is a very very historic time. I think 2025 was maybe the most interesting year in my entire career and and probably life and I think I would expect 2026 to exceed that. >> Wow, that says a lot. >> Yeah, I've se I've seen some stuff. So, um it feels like two things are happening. one is the the the trust that a lot of people have had in kind of what you describe as kind of legacy institutions around the world is I I think in kind of full scale collapse right now. By the way, there's a lot of data data to support that. And so I think there's just there's there's like a lot of structures and orders and uh institutions that people have just relied on for a long time that have just proven to not be up for the up for the challenge. And then kind of corresponding with that is the national

and global conversation have become like let's say liberated. Um, and so, you know, this sort of incredible revolution that we have in in kind of, uh, you know, what I've described as freedom of speech, freedom of thought, um, ability for people to openly discuss things that maybe they couldn't discuss even a few years ago, you know, is just dramatically expanded. And I think that's that's now on 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 the US 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 in the into the daylight and and re-examined. And 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 increasingly upheaval, but you have AI is 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, uh, and being able to argue things out. So, it's it's kind of like those three kind of big mega things are kind of all colliding um at the same time. And I 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 II. Um you know, kind of moments like that. It certainly feels like that. >> Good God, what a time to be alive. >> Yeah. In terms of the AI piece, which is where a lot of people are trying to figure out what to do, what do you think isn't being priced in yet in terms of the impact AI is going to have on say the world or just people listening? >> The I think at I think at this point I think it's pretty clear with it with you know our technology hats on that like this stuff is really working now right and so there there was this you know kind of you know when when there was a chat GPD moment you know three years ago

it was only by the way only three years ago right? um was the chat GPD moment and and the big question was all right this this is like incredibly fun and creative and like we have machines now that can compose Shakespeare and silence and rap lyrics and like you know this is amazing but then there was there you know there's this big question like can you can you harness this technology for reasoning um and for you know problem solving in domains that like really matter you know medicine and science and and and law and so forth um and and you know it turns out the answer to that is yes right um and you know the the last 12 months and especially the last even just the last three months have really proven that like AI can really do like you know you're seeing it all now you know you can actually you know AI is now developing new math theorems um you know there you know over the holiday break you know there's sort of the what it feels like the AI coding thing you know really hit critical mass uh and the world's best you the world's best programmers right including like Lisbald's you know for for the first time over the holiday break basically said yeah AI is now coding better than

we can and so that you know that's that's incredibly incredibly powerful and I think we we all you know kind of I think assume that AI now is going to get really good at reasoning um in in any domain do in which there are verifiable answers and so that that you know that's going to include like many very important domains. So um so like for the technology feels like it's it's it's moving fast and and it's going to be working really well. Um I think the thing that is not well understood I I think a lot of people have a I think you know 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 not working AI just kind of sweeps sweeps the world and changes everything. And I think that's that's kind of the wrong that's kind of the wrong frame. I think it's based on an incomplete understanding of of the world that we live in or the world that we've been living in for the last you know 80 years and I would call out two things in particular. So one is it has 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 stat in statistical evidence of that analytical evidence of that like you basically can't find it. Um and in particular um economists have a way of measuring the rate of technological change in the economy that is productivity growth which which we could talk about what that means but basically it's it's a it's sort of the mathematical expression of the impact of technology uh 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 it's been very low and in fact the pace of productivity growth like in the US is 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 um that it ran in um 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 the economy has actually slowed way down. And so we, you

know, the AI thing is is going to hit, but it's hitting an environment in which we, 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 like just incredible thing that's happening, which is the the, you know, s the de demographic collapse, right? It's sort of a western phenomenon, an increasingly global phenomenon, which is, you know, the rate of reproduction of the human species is is in rapid decline. And you know there are many countries you know including the US where you know the rate of reproduction is you know under two you know meaning meaning that you know 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 um and so you have this kind of precondition that says there's actually been very little techn technological progress happening in the world um and the world is going to depopulate um and so AI is going to enter the world a world in which those two things are true and I think it's inc this is incredibly important because we actually need AI to

work in order to get productivity growth up, which is what we need to get economic growth up. And we actually need AI to work because we're going to need, you know, we're going to need machines to do all the jobs that we're not going to have people to do because we're we're literally going to depopulate we're going to depopulate the planet over the next hundred years. And so I I think the interplay of these factors is is going to be much more interesting and and frankly more more more complex than a lot of people have been thinking. >> 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? >> The way I think about this and you know, yeah, we we have a 10-year-old and so, you know, we and we actually homeschool and so we we we think a lot about this. Um so I think the way to think about the impact of AI on on people on specifically people as individuals I think it's it's 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 or 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 and 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 if they're pretty good at it today, they use they use AI and all of a sudden they're very good at it. And so there there's sort of that aspect to it. And I think the the the way the education system very large is going to teach is going to kind of teach AI is is going to be based, you know, 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. Um where the really great people are becoming like spectacularly great, right? Um and so you just you kind of use it use the term you think about like the supermpowered individual, right? So the individual who is like really good um 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 or you know or podcasting or you know hopefully venture capital you know if if you're very good at it and you can really harness AI you can become spectacularly great uh 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 the really really good coders are experiencing this right you know, my friends who are really good coders are 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 supermpowered individual such that

they're going to be really kind of deep in whatever it is they're going to do, but they're going to 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 like spectacularly great. Um, and and I think that that that's that's going to be the real, you know, that that that that that's the real opportunity and that, you know, at least that's what we're shooting for and that's what I would encourage parents to shoot for. >> So, what I heard there is essentially agency, this word that we see on Twitter all the time is building uh agency, them not waiting for someone to tell them what to do, figuring out what to do. >> Yeah. Yeah. So, this this this thing with this this term agency that's become very very um you know, very popular um certainly California for the last couple years. It's really interesting because it's it's I had a lot of trouble with this early on because I'm like agency. What are they talking about? And what what they're kind of talking about is like, you know, initiative, you know, um you know, willingness to, you know, you could just do things. Um you know, uh what is it? Uh the the demo

bird has the great term live player. Um you know, you you you can be like a primary participant in events. And at first I was like, well, yeah, like that's kind of obvious, right? like of course and and then I'm like oh actually it's not so obvious anymore because kind of your your point I think so much of our society is based on like there are all these rules and everybody gets taught kind of by default you're supposed to follow all these rules right and then everybody if you like break the rules like everybody gets freaked out it's like oh my god he broke the rules and so like we we we have somehow worked our our way our way kind of you know I don't know psychologically sociologically you know kind of into a state in which I guess the natural assumption for a lot of people is you know the thing that you for example you want to train kids to do is like follow all the rules. Um, and you know, you could argue that kind of you know, for example, the you know, the school system, the K through2 school system or whatever has gotten kind of more and more focused on that over time. And it's like yeah, it's like no, you you should actually and again, especially at unit

unit n equals one, like of your kid. It's like and look, there's there's something to be had. We I just had this conversation my 10-year-old last night actually. I I I rolled out uh uh the concept of uh you know, in order to lead, you must first learn to obey, right? In order to you know, issue orders, you must learn how to follow orders. and you know you kind of try to keep keep him with some level of structure in his life and not just and not just pure agency but yeah I mean and so look you know some rules are important and so forth but yeah no look there there is like a huge b there's just a huge premium in life on being somebody who is able to like fully take responsibility for things fully take charge run an organization lead a project create something new um and you know maybe yeah that that has been maybe a little bit diminished in our culture over the last 30 years it you know it's it's healthy you know that that you know that that there's now a term for that that that is coming back back into vogue and then and then and again that's how I view AI for kids is like okay AI should be the ultimate letter on the world for a kid with agency to be able to say okay

I can actually be a primary contributor right whether that's I can be a primary contributor in everything from you know developing new areas of physics to writing code to being an artist uh you know to writing you know to writing novels like you know whatever that thing is I I can fully participate in the world I can really change things and I and I that that feel that The combination of that idea combined with this technology feels very healthy to me. >> What is that quote about? Give me a lever and I'll move the world. >> And I'll move the world. Yeah, that's exactly right. Well, so it's actually funny you mentioned that. So the the um the uh the the early kind of scientists including like Isaac Newton were super obsessed with with you know this concept of alchemy, right? It's like you know they you know they you know they developed like you know Newton he's like developed Newtonian physics and he developed like calculus and all these things but the thing he was really obsessed with was alchemy which was the thing he could never get to work right and and and alchemy was the transmutation of lead into gold which meant the transmutation of something

that was very common which was lead into something that was very rare and valuable which was gold. And you know they there was this the he spent you know decades trying to figure out this thing called the philosopher stone which would be basically the the machine or the process that would would be able to transmute the rare you know the common thing into the rare thing led into gold and he never figured it out and you know it's incredibly frustrating nobody ever figured that out and now we literally with AI have a technology that transfers sand into thought >> just blew my mind >> right the the most common thing in the world which is sand converted into the most rare thing in the world which is Right. And and so AI is it is it is the it is the philosopher stone. Like it it is that it it actually is that and it's just this incredibly powerful tool. Um and and that's where I that's where I get so excited. I mean and again this is what we're doing with our 10-year-old which is like all right a primary thing that we want to make sure to to do is to make sure that he knows fully how to leverage and and get and get benefit out of the philosopher stone, right? Which

is uh you know which is to say AI and that that and then you know that's certainly central to everything we're teaching him. you know, there's there's this meme going around that um you know, Silicon Valley people don't let their kids use computers. And I I just I I there may be a handful of people who are like that. I I don't you know, I don't know. Um I I think it's more honestly the other way around, which is uh the you know, the more you're kind of plugged into stuff in Silicon Valley, the more important it is to make sure that your kids actually fully understand this and know how to use it. And that's certainly the mode that we're in. And that's that's certainly the mode that I would encourage parents to think about. >> I did not know your kid was homeschooled. That is super interesting. There it's almost a statement on, you know, education in today's day. Maybe is there any thoughts there? I'm just for folks that maybe aren't in your tax bracket that want to help their kids be successful, maybe homeschooled, maybe not. What what advice would you have? >> This is the challenge and again this this kind of goes to how you're you know kind of your original question which is

education there's two completely different ways to talk about think about education. The way that's usually thought about and talked about is kind of at the level of like a nation, right? So, so you know, it's like a national level issue or maybe a state level issue in the US, which is basically like how do you educate all the kids? And of course, that's incredibly important. And of course, you're going to need like some level of large scale system like the, you know, the national K- through2 school system or something like that, you know, in order in order to do that. Um, but then there's this other question which is like at n equals 1 for an individual kid like what can you do with with an individual kid? Um, and so I'll just give you kind of the ultimate, you know, 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 is with one-on-one 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-one tutoring. And 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 and you know, royal families and aristocrats and so forth, you know, over the course of centuries. Um, you know, kind of always had always had this approach. There's actually also statistical evidence, um, analytical evidence that this is correct. Um, there 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 will take a kid from the 50th percentile to the 99th percentile and that's oneonone tutoring right so again if you go back to like at n equals one you have 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 they you know they they can move incredibly past 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 for 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. Um, 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. Um, okay, now quiz me, you know, do I actually understand this? Like, people can just do this today, right? Um, and so I I think there's this like massive opportunity for for parents, you know, in in many walks of life to be, you

know, with with with a little bit of time and focus, uh, to be able to say, okay, you know, my my kid's probably still going to go through a traditional education system, but I'm going to augment this with AI tutoring. Um, and of course there, you know, and of course there's going to be tons of startups, right? And there already are that that are going to try to build on all the all the products and services for this. Khan Academy, you know, on the nonprofit side has a big push to do this. Um, and so, you know, I think the the broad answer might be a hybrid approach with schools plus onetoone tutoring through AI. Um, there's also this great, you may have heard there's this great school new private school system called Alpha, um, in which everything I just described is kind of the basis of their philosophy, which is, you know, it's a combination of in-person schools and teachers, but it's also, you know, heavily based on AI and AI tutoring. And so I I think there's like a there is a magic formula in here um that I think is going to apply much more broadly. Um and I and it really for parents interested in this I now would be a great time to really

start to think hard about that um and and to look at the options. >> It's interesting because there's all this concern that young people uh jobs are not going to be there for them. AI is replacing them. On the flip side, there's what you're describing here. It feels like people coming into learning today are going to be move so fast and learn so much more. And where where do you sit on this divide of like young people are in big trouble or they're actually going to be the ones winning in the end? >> Yeah. So the job the job substitution job loss thing is just it's very reductive. It's it's 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 you know again like I said it's like at a half the rate of of the previous era and then a third the rate of like 100 years ago. And so we're 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 turnurn as a result of that relative to 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 turnurn that was happening between 1870 and 1930. And if you go back and you read accounts of 1870 to 1930, people just thought the world was a wash with opportunity. Right? at that rate of technological transformation, kids were able to like develop new careers into new areas of of of the economy, building new kinds of products and services. I mean, you know, a huge part of our of everything in our modern world today was kind of invented and uh and proliferated kind of during that period. Um, 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 transfer translate to a much higher rate higher rate of job growth. And you know there there will 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 uh that will happen and that then corresponding to that there will be you know there there will be

hiring blooms you know I quite honestly I think all over the place and then again go back to the the other thing which is like this is all happening in the face of declining population growth and and and increasingly population shrinkage. Um 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 u literally because you're going to have shrinking population levels. You know we don't really want to get into you know politics particularly but it does feel like the world broadly is going is is going to reverse course on on on the rates of immigration that we've had for the last 50 years. it seems to be kind of a broad-based you know kind of thing happening um you know kind of with you know rise in nationalism you know concerns about the rate of immigration and immigration historically in countries like the US you know it's it's kind of eb and flowed over time based on kind of how you know kind of how the the national mood shifts and so if you sort of combine in a country like the US or any country in Europe if you combine declining population with less immigration you the the remaining human

workers are going to be at a premium not at a discount um and so I think I think that combination of kind of faster productivity growth, faster economic growth, and then slower population growth and less immigration. Um, actually means there's going to be much less of this kind of dystopian, you know, no jobs thing. I I just think it's probably totally outpaced. >> That is extremely interesting. So, what I'm hearing is you're not super worried about job loss. Is the key here that the timing kind of just works out, this population decrease, you know, like all these kind of have to line up for there not to be this massive job loss with AI? >> Yeah. Well, look, if we didn't have AI, we'd be in a panic right now about what's going to happen to the economy. Right? Because what we what we'd be staring at is a future of depopulation and like depopulation without new technology would just mean that the economy shrinks. Right? So so it would mean that the economy kind of itself kind of shrinks over time. You know the opportunity diminishes. There are no new there are no new jobs. There are no new fields. There's no new there's no new source of consumer demand for spending

on things. Um and so you you would you would you would be very worried about going into period of like severe decline of stagnation. Um, and you know, you know, essentially you'd be looking at these like very dystopian scenarios of like an economy kind of self- euthanizing itself uh over time. Um, and and so you'd be very worried about like the opposite of what everybody, you know, thinks that they're worried about. The only reason we're not worried about that is because we now know that we have the technology that can substitute for the lack of population growth and then, you know, also for the for the lack of immigration that's likely. And so, you know, I would say the timing has worked out miraculously well in the sense that we're going to have AI and robots precisely when we actually need them, uh, to keep the economy from actually shrinking. Um, and and I just think like that that's just like a a fundamentally a fundamentally good news story. Um, to get to the mass job loss thing that people are worried about, um, on the other side of things, you know, you have to you'd have to look at like far far far higher rates of productivity growth. you'd have to look at rates of

on things. Um and so you you would you would you would be very worried about going into period of like severe decline of stagnation. Um, and you know, you know, essentially you'd be looking at these like very dystopian scenarios of like an economy kind of self- euthanizing itself uh over time. Um, and and so you'd be very worried about like the opposite of what everybody, you know, thinks that they're worried about. The only reason we're not worried about that is because we now know that we have the technology that can substitute for the lack of population growth and then, you know, also for the for the lack of immigration that's likely. And so, you know, I would say the timing has worked out miraculously well in the sense that we're going to have AI and robots precisely when we actually need them, uh, to keep the economy from actually shrinking. Um, and and I just think like that that's just like a a fundamentally a fundamentally good news story. Um, to get to the mass job loss thing that people are worried about, um, on the other side of things, you know, you have to you'd have to look at like far far far higher rates of productivity growth. you'd have to look at rates of

productivity growth that are 10 20 30 50% a year, you know, something like that, which are, you know, orders of magnitude higher than we've ever had in any in an economy in the history of the planet. Um, you know, it's possible that we get that. I mean, look, I'm, you know, I I have my utopian kind of, you know, kind of, you know, temptation along with everybody else. If if AI like radically transforms everything overnight, then maybe you, you know, let's let's play out the kind of utopian scenario. Uh you get to a much higher level of of of productivity growth. You get to a much higher level of technological change. corresponding to that you'll have a massive economic boom. Uh you'll have a you know massive growth in the economy and then corresponding with that you'll have a collapse in prices. Um and so the price of goods and services that are that are that are sort of you know whatever you want to call it affected by or commoditized by AI the prices of those goods and services will collapse right there'll be price deflation and then as a consequence of price deflation everything that people are buying today gets a lot cheaper and that's the equivalent of a gigantic increase in

wealth right across the society right think it this way this is actually worth talking about because people I think get get kind of sideways on on this issue so if AI is going to transform the economy as much as the you know whatever or utopians or dystopians or whatever kind of think that it will. The necessary economic calculation of what happens is massive massive productivity growth. The consequence of massive productivity growth, what that literally means mechanically is more output requiring less input, right? So you get more economic output for less input, right? So you're substituting in AI for human workers or whatever. And as a consequence, you get like this massive boom in output which with much lower input costs. The result of that is you get lots of goods and services in all those affected sectors. The result of those gluts is you get collapsing prices, right? The collapsing prices mean that the thing today that cost you $100 now cost you $10 and now cost you $1. That's the equivalent of giving everybody a giant raise, right? Because now they have all this additional spending power. That additional spending power then translates to economic

growth, right? The development of new fields. Everybody's like materially like much better off very quickly. And then by the way, if you to the extent that you do have unemployment coming out the other side of that, it's it's now much cheaper to provide the kind of social safety net to prevent people from being emiserated, right? Because the prices of all the goods and services that like a welfare program has to pay from, they're all collapsing, right? And so the price of healthcare collapses, the price of housing collapses, the price of education collapses, the price of everything else collapses because this this this this incredible impact that AI is having. And so in this kind of utopian dystopian scenario that people have, it's not there there's no scenario in which like everybody's just poor. In fact, it's it's quite the opposite, which is everybody gets a lot richer because prices collapse and then it's actually much easier to pay for the social safety net for the people who, you know, for some reason can't find a job. And so, like like maybe we end up in that scenario. I mean, the the kind of optimistic part of me says, yeah, maybe AI is that powerful and maybe the

growth, right? The development of new fields. Everybody's like materially like much better off very quickly. And then by the way, if you to the extent that you do have unemployment coming out the other side of that, it's it's now much cheaper to provide the kind of social safety net to prevent people from being emiserated, right? Because the prices of all the goods and services that like a welfare program has to pay from, they're all collapsing, right? And so the price of healthcare collapses, the price of housing collapses, the price of education collapses, the price of everything else collapses because this this this this incredible impact that AI is having. And so in this kind of utopian dystopian scenario that people have, it's not there there's no scenario in which like everybody's just poor. In fact, it's it's quite the opposite, which is everybody gets a lot richer because prices collapse and then it's actually much easier to pay for the social safety net for the people who, you know, for some reason can't find a job. And so, like like maybe we end up in that scenario. I mean, the the kind of optimistic part of me says, yeah, maybe AI is that powerful and maybe the

rest of the economy can actually change to to accommodate that and maybe that'll happen. But the result of that is going to be a much better news story than people think it's going to be. Um, and again, everything I've just described, by the way, is like just a very straightforward extrapolation on very basic economics. I'm not making any like bold predictions of what I just said. This is just like a straightforward mechanical process that that that plays itself out if you have higher rates of productivity growth, which are necessarily the results of higher grade rates of technological growth. And so, I think we're I think we're looking at, and to be clear, I think we're looking at a world that's not like radically transformed the way that maybe the utopians think that it will be or the the dystopians think it will be. I think it'll be more incremental for races we can discuss. But I think that incremental is overwhelmingly I think that process is going to be a good news process. And then even if it's much faster, it's also going to be a good news process. It'll just be a good news process in the other way that I described. >> I love hearing optimism and good news. I

will also add that you've been I was researching you ahead of this chat and you've been right so many times about where the world is heading. That's why I'm especially excited to talk to you. I'll give you a short list. I imagine there are many more things. Uh okay. Okay. So, one, you were right about the web and web browsers becoming important. You were right about software eating the world. Check. You uh in 2011, you said that in 10 years we're going to have 5 billion people using smartphones. And I believe the actual number ended up being six billion. You also you had this debate with Peter Teal that I came across where you were debating whether technologies stop progressing or if new technology will continue to emerge. and you were arguing there is progress. Progress will continue. And he he was like, "No, I think we're done with cool technology." You were right. Uh imagine there are many more things you were right about. So, so again, I'm just I I love hearing your predictions because I feel like they're actually going to turn out to be correct. >> So, I should start by saying I've been wrong about tons of things, but you know, I buried those out back behind the shed.

>> Delete them from the internet. No web browser can discover them. >> Yes, I have them nuked out of the internet archives so they they're never seen again. Um, so, uh, you know, I'm wrong plenty of times also. Um, but yeah, I mean, look, I think, yeah, some some of those I got right. By, by by the way, I will say on the on the Peter one, I I have come I've come much more around to Peter's point of view. >> Um, I would probably argue that one like quite a bit differently today than I did, and I would give his view I think I think a lot more credit. Um, and and it actually goes to kind of the discussion that the kind of conversation we just had, which is the the real form of what Peter was arguing was we have lots of process in bit. We have lots of progress in bits, right? But we have we have very little progress in atoms, right? Um and and that's the real core of what he was arguing. And I think I I I think I I was a little bit I don't know missing that or kind of you know kind of glossing that over a little bit um because I was so focused on making sure people understood no there actually is still progress happening in in bits. But I think you know a lot of his critiques

around the lack of progress in Adams is real and and again this goes back to this thing of like in the and he you know he's talked about this for a long time. In the last 50 years there has just been very little technological innovation in most of the economy. there's been very little technological innovation in particular anything involving atoms that you know there's been very little real world technological change there just there just hasn't been like the the the built world is just not that different today than it was 50 years ago and if you and again if you contrast that you know if you if you compare and contrast 1870 to 1930 it was a dramatically different world if you contrast 1930 to 1970 it was a dramatically different world if you contrast 1970 today it's not that different right and look you just see that you could just like walk around and it's just like oh yeah there's a bunch of buildings that were built built in like 1960, right? And there's a bridge that was built in like 1930 and there's a dam that was built in like 1910 and there's a city that was founded in, you know, 1880 and like what have we done, right? Like where are new cities? Where are new dams? Where,

you know, where's where's the California highspeed rail? Like you know, you know, like what's going on here? And so like I think he is I I think he is right about a lot of that. Um, again, this is also why I think that AI is not going to have as rapid an imp. It's not going to be again this kind of utopian or dystopian view of like everything changes overnight. I think it just kind of can't happen because of the reasons that Peter articulates which is there's just there's so much about how the world works that's basically just like wrapped up in red tape like bureaucratic process, rules, restrictions. um you know the the the politics um by the way you know unions cartels opolies there there's all these structures in the world that are kind of economic or political or regulatory structures that basically prevent things from changing and so I mean let's take let's take a great example like a AI's impact on the healthare system like by rights AI is going to have a dramatic impact on the healthare system and in and in in very positive ways but you know large parts of the medical system today are they are cartels, right? And so there's like a there's the doctors

are a cartel and like nurses are a cartel and like hospitals are a cartel and then there's this push to like nationalize all the healthare systems and then you've got, you know, then you've got a government monopoly, right? And it's like and and and guess what cartels of monopolies don't like is they don't like like rapid change, right? Um and so, you know, you show up as a kid and you're like, "Wow, I've got like this new technology to do like AI medicine." And they're like, "Oh, well, does it threaten Dr.'s jobs?" Well, in that case, we're going to we're going to block it. So, and I think a lot of consumers, by the way, you know, I I I see this in my life and you you'll probably see this in your life also, which is, you know, like Chet GPT is like almost certainly a better doctor than your doctor today, but like Chad GPT can't get a license to practice medicine, right? So, it can't substitute for a doctor. It can't prescribe medications, right? It can't, you know, perform procedures, right? And so there there there are these any anyway so Peter Peter I think was very articulate and has been for a long time on like no there are actually real structural

impediments in the economy and in the political system that we have that actually prevent any the rates of change that are anywhere near the rates of change that people had in the past. And and you can maybe say optimistically you know maybe the presence of it of the new of the new magic technology of AI maybe it causes us to revisit a lot of these assumpt assumptions for the first time in decades to really say okay is this really the world we want to live in? Don't we actually want to get to the future faster? So maybe that would be the optimistic view. >> It's time to build. Somebody famously said, I uh in my calendar, I actually have that as my when I start to work. It's time to build. That's my block in the morning of the day. Thank you for that. >> Okay. I love I love the way you go from just like macro to just like end of one. And I want to go to end of one. A lot of the listeners of this podcast are product managers. They're engineers. They're designers. They're not a lot of There's a lot of founders, but there's also a lot of non-founders. There's a lot of people building product that aren't founders and uh obviously a lot of people are worried about where their

career is going. Is one of these roles going to disappear? Is one of these roles going to do really well? How do I stay up to date? You're close with a lot of teams, a lot of product teams. What's your sense of just the future of these three very specific roles? Product manager engineer designer. >> This I think is a really funny question. So these three roles in particular obviously are kind of the central roles for for building you know for tech companies. So, the way I've been describing it is, you know, you know the concept of the Mexican standoff, right? Which is the the movie scene where the, you know, the two guys have guns pointing at each other's heads. >> Um, 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 like, you know, and of course it's John Woo movie, they've got, you know, guns in both hands. >> So, they're all each each is aiming at the other two. >> Yeah. >> Um, and you 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 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, right? And a and a coder, right? And so people in each of those roles now, you know, know or believe that with AI they they don't need the other two roles anymore, right? they they they can do that because they can have AI do that. And then of course and then of course there's the real irony which is you know all the the all three of them are going to realize that AI can also be a better manager, right? So they're going to they're going to end up a aiming the guns up the order chart. But that's probably that's the next phase. And what I think is so fascinating about this Mexican staff is they're actually all kind of correct I think right which is AI is actually a pretty good you know it's now 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, right? It's actually good at doing all three of those things

or at least doing a lot of the tasks involved in in in those three jobs. And so again, this this goes back to the the the superower this kind of idea of the supermpowered individual. Uh where if 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 what how coding is going to change in the future. you know that that 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 of of you know coding bots you know you know there's there's a change in the actual job of coding itself which is which is happening right now but the other part of it is okay how do I become that superpowered individual how how do I become a coder that also then harnesses AI so that I can also be a great product manager and I 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 AI based design. And the same thing for the designer, which is how do I use AI to be be also

become a coder and also become a product manager. And then what you get is maybe the maybe the those individual roles change like maybe those are not anymore sort of stovepipe roles the way that you know they have been for the last 30 years or whatever. Uh but what happens is the the talented people in any of those roles become superpowered and they become good at doing all three of those things. Um and then and then those people become incredibly valuable because then those are people who can actually like you know build and design right new products right from scratch which is like the you know which is which is the most valuable thing. And so I I think I think that's I think I think that's the opportunity. >> So I love this answer. So what I'm hearing is essentially uh if you're amazing at any of these three roles you will do well. >> Number one if you're amazing at these roles that's great but also you part part of being amazing these roles is also being being able to fully harness the new technology right. So if you're if you're a master coder today and you you don't ever get to the point where you you figure out how to use AI to leverage your coding skills, you and and

do more, right? Like at some point you are going to hit an issue, right? Here's another way economists talk about this, which is there's the concept of the job, but the job is not actually the atomic unit of what happens in the workplace. The atomic unit of what happens in the workplace is the task. And so and and then what what the way the economists think about it is a job is a bundle of tasks. And everybody wants to talk about job loss, but really what you want to look at is is task task loss, right? Tasks changing. I mean the the the the classic the classic example of task changing. Classic example of task changing was once upon a time executives never used typewriters or personal computers themselves, right? You know, if you were a vice president of a company in 1970 or whatever, you did not have like a typewriter or computer on your desk typing things. You had a secretary who you dictated memos to, right? And then there and then there was this change where like emails started to show up. And what would happen was the job of the secretary then went from, you know, it went from, you know, the the job of the secretary changed from sending out letters with stamps on them

to like sending or receiving emails with the other admins. And then and then the secretary would print out the email and bring it into the executive's office. And the executive office would read the email and paper, scroll scroll the reply um and and and give and give that message back to the secretary who would go back and type it into the computer on on on his or her desk and send it as an email. Fast forward to today, none of that happens. Now executives just do all their own email. They still have secretaries or admins, but they're now doing different tasks. You know, they're travel planning and orchestrating events and like doing all these other things, you know, that that you know that the great admins do. And then and then the task the task set ironically of the executive has expanded to do actually more of the clerical work themselves actually like sit there and like type their own memos, which again 50 years ago they never never would have done that. And so the executive job still exists. the secretary job still exists u but the tasks have changed and and I think that's like a great example of what's going to happen in coding the tasks are going to change is what's

product management the tasks are going to change designer tasks are going to change and so the the the job can p 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 at the level of 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, right? I can I can really adapt, use the new technology, you know, get really good at AI coding, for example. I can, you know, and then 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, you know, 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 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

that that's the track that the best people are going to be on. Um and and I think that that's the thing to lean hard lean hard into. >> I think people aren't fully grasping just specifically software engineering and how much that is changing. Like it's pretty clear we're going to be in a world soon where engineers are not actually writing code, which I think a year ago we would not have thought. And now it's just clearly this is where it's heading. It's like there's going to be this artisal experience of sitting there writing code which is so crazy how much that job is going to change. >> Yeah. So again here I go back and again pardon maybe the history lesson but like I go back like coding. So the first you may know that do you know the original definition of the of the term calculator. Do you know what that referred to? >> No. >> It referred to people. Right. So back before there were like electronic calculators or computers or any of these things um the way that you would actually do computing the way that you would do calculating like the way an insurance company would calculate actuarial tables or the military would like calculate you know I don't know

whatever troop logistics you formulas or whatever it was the way that you would do it is you would actually have a room full of people um and by the way these like big rooms you could have hundreds or thousands or tens of thousands of people doing this and you would actually you would actually figure out you have somebody at the head of the room who was like responsible for like whatever the mathematical equation was and then they would parcel out the individual mathematical calculations to people sitting at desks who were doing them all by hand, right? And and those that that job title was those people were calculators, right? Um and so we've gone from a world in which you literally have people doing mathematical equations by hands by hand. Then we got the first computers. The first computers of course didn't have programming languages, right? They they only had machine code, right? So the first computers were programmed with ones and zeros. And so the task of the programmer became do the ones and zeros and then that became punch cards and you can still you know there's still people you know kicking you know today who you know whose job as a programmer was to like deal with the

punch cards and then you got actually this big breakthrough which was called assembly language which was basically the way to do machine code but like with some level of like English kind of added to it and then the best programmers did assembly language and then you know when I was coming up it was higher level languages like C that compiled into machine code and that's what programmers did and then I still remember when when scripting you know when scripting languages you know we developed JavaScript at Netscape and then you know Python took off and Pearl and these other scripting languages but scripting languages you know took off in the in the in the in the in the 2000s there was this big fight in in the technical community which is is scripting real programming or not right because it's it's like it's kind of cheating right because real programmers write code that compiles to machine code and like real programmers like do like memory management themselves and they do all you know this this this whole craft of writing writing uh you know writing writing C code and you know these these JavaScript or Python programmers are is doing this kind of lightweight thing and

does it even really count as as coding and of course the answer is yes it very much counted and now most coding is done with the scripting languages right um which have you see my point the scripting languages have abstracted away like five layers of detail underneath that that people used to do by hand and they don't anymore and then and then there's and then to your point like AI coding is the next layer on that AI coding actually abstracts away the process of actually writing the scripting code right and so in one sense this is a really big deal for all the obvious reasons but on the other hand it's like okay this is the next layer of the task redefinition under the job of programmer right now what's the job of the programmer it's to your point it's not necessarily to write the code by hand but what it is now is all right now you know if you talk to the world's best programmers today what they'll tell you is oh my job is I'm sitting there and I'm orchestrating 10 code bots right coding bots that are running in parallel right and and literally they sit there and they shift from browser you know browser to browser or terminal to terminal and they're and they're they're

watch their their day their day job now is kind of arguing with the AI bots trying to get them to like write the right code, right? And then and then debug it and and fix the problems and change change the spec and and do all these things. And so now now the job of the programmer is to argue with the coding bots, but like if you don't know how to write the code yourself, you don't know how to evaluate what the coding bots are giving you, right? And so, you know, you asked about the 10, you know, our 10-year-old is, you know, super into computers and super into programming. And what I'm what I'm tell, you know, he's he's using claude and chat GPD and co-pilot and all these things. What I'm telling him is like, look, and by the way, he lo coding. He's on Replet all the time doing vibe coding, you know, doing g doing games, you know, he's sitting there, you know, it's hysterical, right? Because he's sitting there, it's a 10-year-old basically who's, you know, spends two hours at dinner arguing with an AI for fun, right? Um, right. But but what I'm telling him is, no, look, you need to still fully understand and learn how to write and understand code because the

coding bots are giving you code. If it doesn't work or if it's not doing what you expect or it's not fast enough or whatever, like, you need to be able to understand the results of what the AI is giving you, right? in in the same way that somebody who's writing scripting language code does need to understand ultimately how the microprocessor works. Um, and so again, it's it's kind of this upleveling of capability where you actually want the depth to be able to go down and be able to understand what the thing is actually doing even if you're not spending your day actually doing that by hand. And again, I look at that and I'm like, okay, now programmers are going to be 10 times or 100 times or a thousand times more productive than they used to be, right? And and and that is overwhelmingly a good thing. The the the the tasks are definitely changing. The nature of the job is changing. Um, but are human beings going to be involved in like in the coding process and overseeing the the AI coding and all that? And and the answer is of course absolutely 100%. Like no question. >> So you're in the camp of still learning to code, still a valuable skill. >> Oh yeah, totally. Well, again, if you

want to be one of these super Look, look, if you just want to put your like self 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 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 if 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 like really matter then yeah you 100% want to still be you want to go all the way down you want your skill set 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 and 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 understand how the AI works are able to they're clearly able to get more value out of it somebody doesn't

understand how it works, right? I mean, you're always more productive if you know how the machine works, right? When you use the machine and so yeah, the the supermpowered 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? And and and when something doesn't work or when something isn't right, you want to be able to really quickly understand why that is. Um, by the way, again, this goes back to education. AI is your best friend at helping you learn all that, right? because it's like, oh, I need to understand, I don't know, like this isn't fast enough. Um, I need to go I need to figure out as a coder, I need to figure out how to do a different approach to memory management or something. And you can be like, well, you know, like I, you know, I don't quite know how to do that. Okay, AI, let's spend 10 minutes. Teach me how to do this, right? Teach me what this all means, right? So, all of a sudden, you have this like incredibly synergistic relationship with the AI where it's also helping you get better

at the same time as doing a lot of work for you. >> By the way, I was going to say I was a big Pearl uh programmer. I was an engineer for 10 years and that was my my language of choice. >> You do you remember I don't know when you were doing it but do do you remember at the at least early on do you remember did you ever did you ever hit this where like coders were like looking down their nose at you being like >> for sure for sure it's like this is so slow it's not going to scale what are you what are you spending all your time on this thing? Yeah, exactly. And of course, you know, and again, it was sort of this thing where, you know, they were they were sort of correct, which is at the beginning it wasn't, you know, fast enough or whatever. By the end, they were definitely wrong, right? Which is it got much better, much faster, and you know, it's it swept the world. U you know, most coding today happens as scripting languages. And and then by the way, the people along along the way, the people who really understood the scripting languages and the people who understood all the lower level systems, they were the ones who were able to actually make the scripting languages

actually work really well, right? And so that that was that was a great example of this kind of adaptation. And then and then again the result of that was you know a far higher number of people writing code with scripting languages than were ever writing code with lower level languages. And I I think this will just kind of be a more dramatic version of that. I love that Pearl was designed by a linguist. I don't know if you remember that part and that's what made it so nice to to code with. >> Well that's funny because of course it was so notorious for being impossible to understand. So how ironic. >> Yeah. >> This episode is brought to you by Data Dog, now home to EPO, the leading experimentation and feature flagging platform. Product managers at the world's best companies use Data Dog, the same platform their engineers rely on every day to connect product insights to product issues like bugs, UX friction, and business impact. It starts with product analytics where PMs can watch replays, review funnels, dive into retention, and explore their growth metrics. Where other tools stop, Data Dog goes even further. It helps you actually diagnose the impact of funnel

drop offs and bugs and UX friction. Once you know where to focus, experiments proved what works. I saw this firsthand when I was at Airbnb, where our experimentation platform was critical for analyzing what worked and where things went wrong. And the same team that built experimentation at Airbnb built EPO. Beta do then lets you go beyond the numbers with session replay. Watch exactly how users interact with heat maps and scroll maps to truly understand their behavior. And all of this is powered by feature flags that are tied to real-time data so that you can roll out safely, target precisely, and learn continuously. Data Dog is more than engineering metrics. It's where great product teams learn faster, fix smarter, and ship with confidence. Request a demo at dataq.com/lenny. That's data dogq.com/lenny. Coming back to these this kind of triad, the other element that I hear more and more of is just as is the skill of taste and design and user experience. It feels like that's a very hard skill to learn and to me tells me design is going to be much more valuable in the future. >> Yeah, that's right. And again here this this is a great example. So the again

the task level the the the the task level of like design the perfect icon, right, is going to be like all right, the A's going to do that all day long. is g 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 AI is going to get really good at that. But like what are we trying to do? Like the, you know, kind of capital D design of like, all right, what is this thing for? And how does this how is this going to function in a world of human beings? And like, you know, what what's going to is this going to make people happy when they use it? Is it's going to make people feel good about themselves? Um, 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? You know all these kinds of higher level questions that the great designers have always thought about like that the the job of designer right will involve much more of those higher level more important components and and then again with with AI doing a lot more of the

underlying tasks. And so, you know, one way to think about it is, you know, I don't know, you you think of like, I don't know, the world's best designers, you know, Johnny Ibe or whatever, you could be like, "Wow, like if I'm a designer today, if I'm a 25-year-old designer and I and I aspire to be, you know, Johnny Ibean in a decade, um, it's it's all of a sudden I have a new path that I can use to kind of get to to get there, which is I, you know, because Johnny I 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. Um, and then so much more of my time and attention is going to be is going to be able to be focused on these higher level things that most most designers never get to. And I think that that's going to be another great example of that. >> So maybe what I'm hearing here is kind of this T-shaped strategy of be if you want to be successful in any three of these roles, be very very very good at

underlying tasks. And so, you know, one way to think about it is, you know, I don't know, you you think of like, I don't know, the world's best designers, you know, Johnny Ibe or whatever, you could be like, "Wow, like if I'm a designer today, if I'm a 25-year-old designer and I and I aspire to be, you know, Johnny Ibean in a decade, um, it's it's all of a sudden I have a new path that I can use to kind of get to to get there, which is I, you know, because Johnny I 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. Um, and then so much more of my time and attention is going to be is going to be able to be focused on these higher level things that most most designers never get to. And I think that that's going to be another great example of that. >> So maybe what I'm hearing here is kind of this T-shaped strategy of be if you want to be successful in any three of these roles, be very very very good at

that specific role, product management, engineering, design, and then get good enough at these other two roles. >> Well, so I think that's great. I think that's really really relevant. And then you know the Scott you know Scott Adams unfortunately just passed away um you know which which is a real tragedy but um I was always I I referred for years to actually Scott's Scott Adams he had this famous um he had this famous kind of career advice he would give people which I I think makes a lot of sense which which doveetails with what you're saying which is he he used to say he used to say it's like look he said um you know I I could he he said you know I could have been a pretty good cartoonist um or I could have been like pretty good at business but the fact that I was a cartoonist who understood business made me like spectacularly great at making Dilbert, right? Because even the world's best cartoonist who didn't understand business could have never written Dilbert. And then the world's best business people who didn't know how to do cartoons couldn't have done Dilbert. It took somebody who actually had both of those skills to be able to make Dilbert, right? Which is one of the most

successful cartoons in history, right? And so so the the way Scott always described it was that that the from a career development standpoint that the additive effect of being good at two things is like more than double, right? um the additive effect of being good at three things is more than triple, right? Um because you you you be you become a super relevant specialist in the combination of the domains. Um and and you you look you see this all I mean you see this all over you know you see this all over the economy. Yeah. I mean you see this all over the economy but I'll you know give you an example Hollywood you know just Hollywood as an example you know there are a lot of writers who can't direct a movie and they can be very successful writers. There are a lot of directors who can't write a movie. They can be very successful directors. But the superstars in the entertainment industry are the people who can write and direct, right? And you know they they have a term for those. They call those auras, right? And that's you know those are the people who are like the real creative forces that move the field. And so and so again and by the way Hollywood actually it's really funny

spend been spending a lot of time talking to Hollywood people about AI. Hollywood has the same Mexican standoff going um right now that we that we described in tech except in Hollywood for example for filmm it's the director it's the writer and the actor right because the director is now thinking wow I don't need the writer anymore because the AI can write the script and I don't need the actor anymore because I can have AI actors the writer is saying I don't need the director because AI can direct the movie and the AI can do the actors and the actor is saying I don't need either one of these guys I can have the AI direct the thing I can have the AI write the thing and I'm just going to show up and do my performance right and so so it's it's it's the same it's the same kind of tri triangular configuration. And again, what what's great about it is they're all correct, right? Each person in each of those three fields is going to be able to expand laterally and pick up those other those additional skills. And then as a consequence, you're going to have more people who can write and direct or write and act or direct and act or do all three. And and I think, you know, to

your point like your your your T-shift thing, like I I think that's going to be true basically across the entire economy. And and and if you think about the T is if you think about the T configuration, it's like yeah, the bre the breath the breath the top of the tea is like how many individual domains are you familiar enough with to be able to use the AI tools to be able to do really good work. And then the the this part of the tea is how deep can you go in at least one of those domains so that you really really deeply know what you're doing. But like if you're like super deep on coding and you can use AI to do design and you can use AI to do product management, right? That that's your T right there. and and you're a triple threat at the top of the tea, but with this level of technical grounding underneath that. And I mean, at that point, you're again, you're the superpowered individual, you're going to be able to just perform like feats of magic, uh, for example, in terms of designing and building new products, you know, that people in my generation couldn't have even dreamed of. And so I I I think I think that this is a universal kind of theory that I think

could can apply across the entire economy. >> I'm going to invent a new framework right now. Okay, forget the T framework. Uh, I'm picturing an F sideways or an E where there's three two or three I don't know, downward parts. And so what I'm hearing is get good at least two. >> I think that's right. I think that's right. Yeah. The combination. Yeah. Um my my friend Larry Summers had a had a different version of the Scott Adams thing which is he he used to tell people he said the key for career planning is he said don't be funible, >> right? And you know that's he's an economist and so that was economics speak and and what that means is what that means essentially is don't be replaceable. And so don't be a cog. Right? So, and what that meant was don't just be one thing, right? So, if you're if you're if you're quote unquote, you know, again, just a designer, it's just a product manager, just a coder, like then in theory, you can be swapped in or out. But if if you have this if you have this Yeah. to if you have this E or F, you know, laying on it side kind of thing. And if you have if you have this combination of things that's actually quite rare, then all of a sudden you're

not fungeible. Not not only you're not funible, like you're actually massively important because you're one of the only people in the world who can actually do that combination of things. Um, and yeah, that that your ability now to become one of those people is like just titanically enhanced uh with AI as compared to anything we've ever seen before. >> This is so interesting because I've worked with people that are good at these two skills and they were always called unicorns at the company. She can code and design. Oh my god. And what I'm hearing here is this is what you need to become. You need to become really good at at least two things there. I think you use the term smoke stack or something where it's like PM over here, engineer design. And what I'm hearing here is you need to get good at at least two of these skills. the silos of these two roles are disappearing. >> That's right. That's right. And again, I can't I can't overstress the following for for anybody listening to this. 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

not fungeible. Not not only you're not funible, like you're actually massively important because you're one of the only people in the world who can actually do that combination of things. Um, and yeah, that that your ability now to become one of those people is like just titanically enhanced uh with AI as compared to anything we've ever seen before. >> This is so interesting because I've worked with people that are good at these two skills and they were always called unicorns at the company. She can code and design. Oh my god. And what I'm hearing here is this is what you need to become. You need to become really good at at least two things there. I think you use the term smoke stack or something where it's like PM over here, engineer design. And what I'm hearing here is you need to get good at at least two of these skills. the silos of these two roles are disappearing. >> That's right. That's right. And again, I can't I can't overstress the following for for anybody listening to this. 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, right? So it's 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. is like, okay, what am I going to try to get it to do for me? Right, which is of course very important, but the other side of it is what can I get it to teach me how to do, right? And it's it's just as good at that, right? Um, and so again, this is this level this level of latent superpower like you know, people who really want to like improve themselves and like develop their career should be spending every every spare hour in my view at this point talking to an AI being like, "All right, train train me up like tell me tell supermpower me, tell me how to, you know, train me train me how to be, you know, I'm a coder. Train me how to be a product manager." It will happily do that. It's it knows exactly how to do that. You know, run me, you know, make me problems, you know, make me assignments, then evaluate my results, right? And it will it will do that just as happily as it will do work quote unquote for you. >> Two tricks I've heard along those lines.

One is uh to watch the output. What the agent is doing and thinking as it's doing the work. So, if you're not an engineer, is just sit there and watch it think and make decisions. And it's almost become this like layer on top of learning to code is learning to see what the agent is doing and thinking because that teaches you about architecture. And the other is uh a couple podcast guests have mentioned this. When you get stuck and then you figure out how to unstuck yourself, you ask it, "What could I have done differently? What could I have said that would have avoided this error in the first place?" >> Yeah, that's right. That's right. Yeah. Look, on that first one, and this again, this is what I'm doing with my 10-year-old. Yeah. Look, if if if you ask an Yeah, this is this is a really good point. So, if you ask an AI, write me this code, and then and then it doesn't and it comes back and it doesn't work right. Like if if all you know is like single function I asked and it gave me back something that's not good like what do you like what do you even do with that right like you don't understand why it gave you that result do you really understand even what do

you even understand what to tell it to try to get it to do something different but to your point like if you actually w if you actually watch what it's doing um and and and then and then you you have the grounding you know kind of that leg of the of your ear or your F um if you have that grounding then you can be like oh I see what it's doing I see where it made the mistake I see where it went sideways and then you're all of a sudden able to intervene and able to say no no that's not what I meant do this other thing right and so and again this is this this this is a big part of having having the actual kind of you know synergistic relationship um is that you understand and by the way look I mean this is like everything I'm saying is you know everything everything that we're saying right now also is the same as if you're working with human beings right like you know if you and I are colleagues and I you know ask you to do something you'd come back with something completely different like I I do need to understand what was happening in your head right in order to in order to be able to get do need to give you give you feedback right if I just tell you oh

that's wrong it doesn't like nothing happens. I need to actually understand I need to have theory of mind, right? I need to understand what you were thinking in order to really give you the right feedback. Um and so and and you know and again the great thing with AI is AI will happily sit there and explain all day long why it's doing what it's doing. It'll you know it'll happily critique itself. You know, you can do this. By the way, this has a very fun thing where you can have have one AI critique the other AI, right? Um, which is another thing, which is like you have one AI write the code, you have another AI debug the code, and so you can actually use you can play the AIs off against each other and get them to argue with each other. Um, and yeah, the these are all these are all the kinds of skills that are going to become, I think, incredibly valuable. >> I think people call those LLM councils. Yes. >> They're talking to each other. >> Yeah, that's right. That's right. >> I do feel like if I were like I'm I have no design background. I've always wanted to design. I would I've always wanted to be a great designer. Uh, it feels like that's the hardest one to learn of all

these three by just watching and talking, right? Because there's a lot of exposure hours as as folks have used this term just like how do you learn to be a great designer? That feels like that's going to be really hard and valuable. >> So, my my true confession is I've always kind of wanted to be a cartoonist, >> but I have no like art skills, but as we're talking, I'm like, it might be time. >> Their time has come, Arc. >> Yes. >> I want to pivot to founders, your maybe your bread and butter. You spent a lot of time with the most cutting edge AI forward founders. I'm curious to what you see them do, how you see them, some way they operate that's maybe blowing your mind about how the future of starting a company looks, how the future of AI forward companies look. >> Yeah. So, this is a great very, you know, topical topic that's all playing out in real time right now um on on the leading edge. So, I I think there's like three layers of it and see 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 how does AI redefine the products themselves right um and and this is kind of the this is kind of the timehonored you know

kind of thing that happens at technology transitions and this is kind of what you know a lot of venture capital is based on which is um you know okay there's a new technology that comes out and you know maybe it's the personal computer or the iPhone or the internet or now it's AI and it's like all right um 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 software business and now you got your you know PC version of it and now you 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 um you know it's kind of another ingredient into an existing formula and and of course you know a lot of new technologies are like that right um 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 you didn't really redefine the the software industry because people just went from using you know hard disk using flash storage or something um uh but when the internet came out like basically old school onrem software for the most part you know not not entirely

but like a lot of it died and just got replaced by like web software um right and so so sometimes you get the kind of it's additive to an existing thing sometimes you get the actually it redefineses an entire product category redefineses an industry the actual 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 a 40-year franchise in image editing. Um, okay. 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 your 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 edit an old one. So I think you know there's many areas of of tech in which that question is being asked and you know the answers I think will vary by domain but u you know obviously as as a venture firm we're batting hard on many of these

categories being being totally reinventsted and a lot of the a lot of the best founders are trying to figure out how to do that. So that so that's kind of AI you know 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. Um, and so it's, you know, a lot of what we've already talked about, but like, okay, if I'm a founder of a company and I've got, you know, if I have, you know, 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 100, 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 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 and again here you've got this

concept of the superpowered individual which is like okay um 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 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 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 um 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 some 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 most software companies obviously end up with you know huge numbers of employees um and So I I think you know some the most leading edge founders are thinking of like okay how how do I reconstitute

the actual varied definition or idea um of a um of having a company and and you know can you have a company that's that's literally basically just all AI um and so and and if you're doing so you know if you're doing anything in the real world that's hard but if you're doing software like that that that seems like it might be feasible in some cases and then you know there's like the ultimate example of that which is like you know can you have like AI can you have like autonomous like AI economy stuff happening where you have like AI bots on the blockchain or something you know that are out basically out there like functioning as a as a as a business and like making money and just you know literally where the the AI does all the work itself and just get you know issues me dividends and so you know maybe that that you know maybe that maybe that's the the final outlier result we have we have a few founders who are chasing that kind of thing. Um so I would describe that as I would describe that as kind of the the latter that the best founders around. >> Super interesting. this whole idea of a oneperson billion-dollar company. I think it depends on your definition of

what this is like an outcome I could see. Uh having run running my newsletter uh as one person with some contractors, there's so many little annoying things that I have to deal with with just support tickets and issues and bugs and like it's hard for me to imagine actually a oneperson billion-dollar company even if AI is handling so much of your support because there's just so many random edge cases that I'm just const like filling out forms. Uh and so I guess depends on do you have contractors? Does that count? You know, like what does it count? What does it mean to be a one person? But I'm just like I can't see that happening. >> Yeah. I mean, look, Bitcoin's Satoshi pulled it off. >> But like, you know, the open source community, you know, like does that count? I don't know. I guess I guess guess it counts. Okay. >> Yeah. Exactly. Right. So, yeah, that that Yeah. And I would say I don't propose to have answers here, but more just like >> the smartest people I know are are many of the many of the smartest people I know are are thinking hard about this. >> Yeah. What do you think about Moes? a big question constantly in AI, you know, the fact that everything's changing.

Just what's your guys' thesis on Moes in AI? Does is that even a thing? Do you care? >> My experience with like really big technological transformations, and of course, I I kind of lived this directly with the internet, and I saw this happen, is the really big technological transformations, they they take a long time to play out, and there's there's all of these structural implications that just kind of cascade out over time. And then there's kind of this this there's this like rush to judgment up front where people kind of say, "Oh, it's therefore obvious that you know XYZ. 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 it's obvious that there's economic opportunity and this kind of startup and not in these others. Um it's obvious that the moes are going to be in this area of the technology but not in this other area. And and there and you know what everybody does is they they kind of state those things with like just an enormous amount of self assurance where they they you know where they really sound like they have all the

answers. And then you know what happens is this these these ideas kind of saturate the media right because the the media naturally prizes like definitive answers over open questions because you know you want you know like when CNBC is like 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 like debate it from like eight different angles. And what I found is if you look back on those predictions a few years later and you 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 were wrong again generally like quite badly wrong and so I just I think the process I think with massive with 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 like structural change that will play out over time and and again a lot we've talked about a lot of

answers. And then you know what happens is this these these ideas kind of saturate the media right because the the media naturally prizes like definitive answers over open questions because you know you want you know like when CNBC is like 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 like debate it from like eight different angles. And what I found is if you look back on those predictions a few years later and you 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 were wrong again generally like quite badly wrong and so I just I think the process I think with massive with 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 like structural change that will play out over time and and again a lot we've talked about a lot of

this but like it the implications on like what are the definition 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 inter 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 um you know uh and So it's just like there's just there's there 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 I'll just give and it's just I'll just run this as a thought experiment you know see what you think on this but it's like you know like do do AI models the are AI models themselves like defensible like is there a moat uh on AI models and on the on the one hand you'd be like wow it certainly seems like there is or should be Because like if something takes you know billions of dollars to build um and you need you know you need this like incredible critical mass of like comput

and data and there's only a certain number of engineers in the world that know how to do this and you know they are getting paid like NBA stars um and you know 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 100% you know I don't know whatever 5050 for 30 3030 or 90101 or whatever it is market share and then they're going to have whatever profitability they have and it's going to be a kind of a classic igopoly and or or maybe you know maybe one company's going to definitively it'll be it'll be a monopoly and that and by the way those outcomes have happened in software many times before and so may 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 basically, you know, exactly capable products. Um, 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. Um, I would have been like, wow, like it, you know, the thing that seemed like it was Blackmagic all of a sudden, you know, has has become like commoditized really fast, you know, which which by the way is exactly what happened, right? Like, you know, within within a year of GPT3 coming out, there were their open source GP3s running on a fraction of the hardware, right? That were available for free. Um and then there were and then you know there were five you know now now you've got you know in the game you know 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 you know all these other companies that are and then DeepSeek and you know Kimmy and all these other Chinese companies. Um and so like even at the level of like LLMs or you know AI models like you can squint and make that argument either way. By the way same thing at the level

of apps right it's like you know one school of thought is you know the apps apps are not a thing because like the model's just going to do everything. Um but another way of looking at it is no actually like actually adapting the model as kind of the engine into a into a domain involving human beings u where you need to like actually have it fit for purpose to be able to function in the medical industry or the legal industry or you know or whatever u or coding you know no you actually need like the application level is actually going to matter enormously and maybe the LLM's commoditizing maybe the value goes to the apps um and and and again you can kind of squint either way on that one and I and I know very smart people who are on both sides of that argument um and so I my honest answer on this is I think we're in a process of discovery over time um which is you know in 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 um in you know actual individual choices made by entrepreneurs um you know matter a lot um you know the

economics matter a lot availability of investor capital varies over time that matters a lot um and this is a this is a complex system and so we we actually don't know the the outcomes on this yet and and we need to basically be we need to be open to surprises at the structural level uh of what happens and of course as a as a VC this is very exciting because it means we you know we're doing this now we should kind of make bets along every one of these strategies um and kind of see and see how this plays out and I just say like there may be like one I don't know there may be like one particularly brilliant I don't know hedge fun manager or something who has this all figured out but I I guess I would say if if if they exist I haven't met them yet. So what I'm hearing here is don't over obsess with moes at this point because we have no idea what it'll end up being and as much as it may feel like okay there's no way OpenAI will lose this lead clearly we're seeing a lot of competition GPT rapper point is really great a lot is such a derogatory term I don't know year ago just like you're just GPT rapper now it's like the companies that are the biggest companies

fastest growing companies in the world >> yeah well it's it's like a little bit like I don't know I mean even just like with you know you know the you know this has been the you know the the holiday if you know three years ago was the holiday of Chad GPD this last, you know, month or whatever has been the holiday of of Claude, particularly Claude Code, right, for for coding, but it's like, you know, it's pretty amazing because it's like, okay, there was Claude, which is, you know, obviously a great accomplishment, but then there's Claude Code, which which is an which is an app, right? It's a cloud rapper, >> right? It's, you know, agent harness. Um, and then um and then they did this amazing thing where they came out with was it co-orker? >> Co-work. >> Co-work um and uh and remember they said coowork, which is a club code wrote co-work in a week. >> Yeah. A week and a half. Yep. 100%. Well, and that's and there's two ways of looking at that, which is like, wow, that's really imp obviously that's really impressive that cloud code was able to build co-work in a in a week and a half. That's great. That's amazing. The other way to look at it is co-work

was developed in a week and a half like like h how much complexity could there be? How much of a barrier to entry can there be in something that was developed in a week and a half? And so and and then you know and then again it's this it's this it's this push and this pull thing where it's like it's like wow it's incredibly val it's incredibly functional incredibly valuable and people are like all over the world every day now are like wow I can't believe what I can do with this is like the most magical product ever but at the same time it took a week and a half right and so right and so every other every other model company you know I'm sure you'd have to expect is sitting there being like okay obviously we need to build you know an Asian artist and then obviously we need to build a co-work you know thing for for for regular people and obvious you know I I don't I'm not even saying I know anything, but just like obviously they're all going to do that, right? Um and so, you know, how defensible is that? And you know, in six months, you know, and we've seen this happen before, like in is quad code going to get lapped the same way that you know, GitHub copilot got lapped. You

know, the the history in the last three years has been everything that looks like it's like the fundamental breakthrough gets gets basically replicated and lapped very quickly. Like many of the smartest people I know in the field when I when I really kind of talk to them kind of, you know, get a couple drinks into them, they're like, "Yeah, they're basically, you know, one theory is like there really aren't any secrets among the big labs." like the big labs kind of all have the same information and they kind of have all the same knowledge and they you know they're kind of they lap each other on a regular basis but you know there's not a lot of proprietary anything at this point and then and then you know again evidence of that is you know deepseek you know came out of left field and basically was like a you know re-implementation of a lot of the ideas under American big labs and you know and had some original ideas of its own um but like you know wow it wasn't that hard for you know some you know basically a hedge fund in China to do it and so like how much defensibility is there but on the other side of it you've got wow all these big labs are now

paying you know individual engineers like they're rock stars um and they're you know incredibly bright and creative people um and you know maybe there's you know a dozen nent ideas in any one of these labs that it's actually going to be a huge breakthrough that's going to be hard to replicate and so again it's just like I think we just need to I don't know my views I my view I need to put like a big discount on my forecasting ability on this one like it for me it's much less interesting to try to say okay as a consequence industry structure in five years is going to be X the big winner in the category is going to be company Y the big you know product killer app is going to be It's like I this is to say I don't think I can predict that. Um I I think I I think a much much better use of my time is is being being very flexible and adaptable at a time like this. >> So with all this in mind, do you feel like there's something you're paying attention to more to help you decide okay this is where we want to place our bet or is the answer essentially the strategy you guys have which is place a lot of bets. You guys raised the the largest fund in history. Is that is that

the way you win in this world? >> Yeah. So for I mean for us yeah for for us we have we obviously have a very very deliberate strategy. One one way to think about this used the Peter Teal for you remember the Peter Teal formulation of uh 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 um and so um and he always argued that like there's he always argued that like Silicon Valley is characterized by in too much what he calls indeterminant optimism right and what he what he what he always described what he meant by that is basically um I think the way he would describe it is an indeterminant optimist who thinks the world is going to be better but can't explain are 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 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 determinant 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 s sort of maybe say you know VCs are indeterminant optimists um and then he would say you know Elon is the determinate determinate determinant optimist where it's like no I'm going to build the electric car and I'm going to you know solar and then I'm going to do you know Mars you right and I'm these very concrete things and I 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 I think maybe he and I if you disagree with part of that it would be I think the indeterminant optimism is a stronger phenomenon than at least I think he's historically represented it as and I would put myself firmly in the indeterminant optimist category and that's the strategy that we that we have at A6Z which is and and the reason for that is It's not hopefully it's not so much wishful thinking. It's more no what the indeterminant optimism of venture capital or the indeterminant optimism of A6Z 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 and and each of those individual people is a determinate optimist like each of them each of them individually has like a very strong view what they're going to do but the great virtue of the capitalist system the great virtue of the American economy the great virtue Silicon Valley is we don't just have one of those and we don't just have 10 of those. We have a hundred and a thousand and then 10,000 of those and and 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 and then just the the nature of you know the nature of the future is like we just don't know all the answers and that's okay and then and the right way to deal with that is to run as many experiments as possible and have as many smart people try to do as many interesting things as possible. Um and so yeah, I would I would put myself firmly on the side of the indeterminate optimist. I'm uh I'm wondering if the answer to the question of what you look for now more and more is this determinate optimistic founder. Yeah. That has this massive

ambition and is actually working on achieving it. >> Yeah. Yeah. No, that's right. That's right. I mean, look, the founders need to be deter determined optimist. Like they need to have a very specific plan now. And look, the the critique the critique always, you know, the critique from the founders is, oh, UVC's have it easy because like you don't have to like you don't actually have to commit, right? You don't actually have to like make you you don't actually have to like, you know, you don't have to make the bed you lay in. You can like place multiple bats. you can operate a portfolio, you know, you should have a lot more sympathy for us as founders, you know, because we, you know, we only get to make the one bet. Um, you know, and there's there's truth to that. You know, the counter-argument on that is the founders get to run their companies. We don't. So, so, you know, we we don't we don't get to put our hand on the steering wheel. And so, you know, the great virtue of being a determined optimist is you actually get to get to single-mindedly execute against that goal. And and and you look, in the long run, who who does history remember? History remembers Henry Ford, right? not

you know whoever was the you know whatever the seed investor who seated at Ford Motor Company and you know 10 other car companies have failed right um and so you know the determinant optimist is the per you know the founder is the founder and the company builder and the engineer I mean these are the people who actually do the thing and you know deserve 99.99999% of the credit but uh you know having said that I I do think there is a role for having having some indeterminate optimist in the uh in the background helping along the way and helping keep the whole the whole cycle going >> do you think about AGI in shifting your investment thesis like as we approach AGI and hit AGI as an investor, how do you think about your investment thesis changing? >> Yeah. So, I've always kind of had a little bit of an is I've always kind of struggled with the concept of AGI um because it at least well there there's those defined terms which is where I kind of struggle with it which is there's like the prosaic there's the there's the prosaic uh definition of AGI and then there's like the I don't know cosmic definition and the way I would describe it as well let's start with the

cosmic one. So the the cosmic one is basically it's the singularity, right? Um and so AGI is the is the moment where you enter the singularity, which is to say that where the world fundamentally changes and like the the rules of the old world are gone. We're now operating in a new domain and then you know the kind of the full definition of singularity is like it's a world in which you know human judgment is no longer really relevant because the you know you get this self-improvement loop. The AI the AI is improving itself and it's sort of racing you know so-called takeoff scenarios. you can see at this takeoff thing where the AI is improving itself and the machines are making decisions so much faster than people and people are just sitting there watching the the machine do its thing you know and I kind of described I don't really I don't really think that's I don't I don't think we live in that world like whether you could call that utopian or dystopian like I don't think we're lucky or unlucky enough to live in that world we could debate that we can talk about that more but um the the the pros definition of AGI that at least I think the industry participants have kind of

cosmic one. So the the cosmic one is basically it's the singularity, right? Um and so AGI is the is the moment where you enter the singularity, which is to say that where the world fundamentally changes and like the the rules of the old world are gone. We're now operating in a new domain and then you know the kind of the full definition of singularity is like it's a world in which you know human judgment is no longer really relevant because the you know you get this self-improvement loop. The AI the AI is improving itself and it's sort of racing you know so-called takeoff scenarios. you can see at this takeoff thing where the AI is improving itself and the machines are making decisions so much faster than people and people are just sitting there watching the the machine do its thing you know and I kind of described I don't really I don't really think that's I don't I don't think we live in that world like whether you could call that utopian or dystopian like I don't think we're lucky or unlucky enough to live in that world we could debate that we can talk about that more but um the the the pros definition of AGI that at least I think the industry participants have kind of

converged on and tell me if you agree with this is uh it's when the AI can do every economically relevant task as good as a The way um the co-founder of Anthropic put it is like a basket of the most valuable economic task. So it's like 10 15 not every single economically valuable task. >> Okay. Got got it. Yeah. So it's maybe even a slightly reduced slightly reduced definition. Um and by the way we're you clearly getting close to that if we're not already there. >> And so on that one I kind of feel like so I kind of feel like the cosmic one overstates what's going to happen. And then I kind of feel like the kind of AGI definition that you just gave I think it kind of understates what's going to happen. like it's almost too reductionist and and the reason for that is I don't think there's any reason to assume that human skill level is the cap on anything right and so the way we say that is AGI always is you know the definition you gave the definition I gave it's kind of in it's always kind of relative in comparison to a human worker right and it's like I don't know like human skill level caps out at a certain point but that's because of the inherent

like biological limitations of the human organism right like we're you know human I give you example human IQ human IQ Q, you know, kind of what they call fluid intelligence or the the sort of G factor of kind of uh, you know, fluid intelligence. Uh, IQ, I think, tops out in in humans as a species, it tops out around 160, right? Where at at like 160, it's like Einstein level, Einstein, Fineman IQ, >> in terms of IQ. Like, you just tops out at 160. The the 160 IQ people are the ones who come up with new physics. There's only a small handful of those. the generally speaking when we run into somebody in the world who's like incredibly smart who's like a best-selling author or like a you know one of the world's best I don't know research scientists or one of the world's best doctors you know or whatever um it would be probably 140 um is kind of the IQ that you're looking for there. Um if you're looking for like a really good lawyer it's probably 130. Um if you're looking for like a really good like line manager in a business it's probably 110. um you know if you're looking for like an accountant like a small business accountant who's good at doing the books for small businesses is

probably 105 right and so the the kind of scope of like impressive human you know the the the ability of the human organism to do intellectually impressive things you know it's sort of that 110 to 160 is kind of the spectrum and you know good news is there's a lot of those people running around but like there's not that many at 140 150 160 but it's like that's just that's like the limitations of what can fit in here right and it's like there's no theoretical limit on where this goes if you release the limitations of human biology, right? And so can you have a you already have people running these experiments to kind of do human equivalent, you know, kind of IQ uh uh you know, for for existing AM model. And by the way, existing AI models right now are kind of testing around the 131 140 level, which means they're going to get to the 160 level and they're, you know, they're arguably on the mass high starting to get to the 160 level now. But like I I think we're going to have AI models relatively quickly that are going to be like 160, 180, 200, you know, 250, 300, by the way. And I think that's great, right? Like I feel I feel I feel as great about that as I do about

the fact that we occasionally get an Einstein, right? It's like would the world be better off or worse off with more or fewer Einsteins? And the answer is of course the world would be better off with more Einstein. And of course the world would be better off with machines that have IQ, you know, more IQ like Einstein are greater than Einstein. But like I think IQ's IQ of the machines is going to exceed that in the humans. I think that's that's really good. Um, and then the performance, you know, again, it goes back to like the AI coding thing is happening. The performance against task is going to get better also. Like I I think, you know, this is where Line of Stars in particular is like, yeah, okay, like this thing is starting to generate better code than I can. Okay, so now we're going to have AI coders that are actually better coders than the best human coders. I think that's great. I think we're going to have AI doctors that are better than the best human doctors. I think we're going to have AI lawyers that are better than the best human lawyers, which actually is going to be very interesting to see. Uh, which we can talk about, which I think is also

great. Um, and so like I don't think there's a I think we're used to living in a world where we just don't understand how good good can get because we've been capped by our own biology and we're going to get to experience what it's like when you have the capability at your fingertips that's actually better than human in these domains. Um, and so I I you see what I'm saying which is like I think this idea of like human equivalent is just going to be like a footnote. It's like, oh yeah, that was just on Tuesday, you know, in in 2026 is when they hit that and it kind of didn't matter because the the next question was like, okay, what are we gonna what are we gonna what do we get to do in a world in which we actually have machines that are better than that, right? And so so so I think this is going to be much more of an exploratory process for actually exceeding human capability than it's going to be any sort of particular singular singularity moment or whatever that happens just that just happens to coincide with the human threshold. >> 200 IQ. I uh just like that frame of reference is such a uh mindexpanding way to think about just how fast and how

great. Um, and so like I don't think there's a I think we're used to living in a world where we just don't understand how good good can get because we've been capped by our own biology and we're going to get to experience what it's like when you have the capability at your fingertips that's actually better than human in these domains. Um, and so I I you see what I'm saying which is like I think this idea of like human equivalent is just going to be like a footnote. It's like, oh yeah, that was just on Tuesday, you know, in in 2026 is when they hit that and it kind of didn't matter because the the next question was like, okay, what are we gonna what are we gonna what do we get to do in a world in which we actually have machines that are better than that, right? And so so so I think this is going to be much more of an exploratory process for actually exceeding human capability than it's going to be any sort of particular singular singularity moment or whatever that happens just that just happens to coincide with the human threshold. >> 200 IQ. I uh just like that frame of reference is such a uh mindexpanding way to think about just how fast and how

smart these things are going to get and and quickly. >> Well, I don't know if you have this experience. I I have this experience all the time. Well, two two experiences I have all the time. One is just like I'm just like like I know I ought to be able to do this, but like I just can't like it's going to take too long. You know, I I want to write this thing or I want to like whatever. I want to have this theory on this thing or I have a plan or whatever. And it's just like like I I don't have the eight hours or or by the way the eight weeks or the eight years, right? And like I just don't know enough yet and I'm just like I can't do the math in my head and my memory isn't perfect and like I can't remember and I read you know after you had this you get interested in something you read 10 books and then you're like I forgot almost everything that I just read. Like I I wish I could retain it all but I can't. It's just like I you just have this I I sort of live in this kind of state of like endless frustration. So, it's like I like if I could just be smarter than I was, like I'd be so much better at what I do, but I'm not. So, so, so there's that. And I don't know

how often you have this, but I have this on a regular basis. It's just like, you know, I, you know, because of what we do. Like, I know a bunch of people who I know for sure are smarter than I am. And I know it because when I talk to them, I just find myself at a certain point, you know, it's like for the first half of the conversation, I'm just taking notes the entire time. And for the second half of the conversation, I'm just like, Like, me. like this person is just smarter than I am and they're just outthinking me and they're going to keep outthinking me and I just can't and I'm just like all right god damn it like I gotta go home and I gotta like have a drink because I'm just not, you know, I'm just not whatever that is. I'm not that. And so we're just so used to having those limitations um that the idea of having machines that work for us that don't have those limitations. I I just I think that's much more exciting than people are giving you credit for. >> Oh man, I could talk to you for for hours, Mark. I'm thinking to close out the conversation, I want to ask about your media diet and your product diet. You just talked about books, reading 10

books. I I think you famously read constantly. I saw a interview with you where you're just like AirPods changed my life. I'm just listening to audio books now all the time. So, in terms of media diet, what do you what are you reading? What are you paying attention to these days in terms I don't know podcasts newsletters blogs things like that. And then any books in particular? >> Yeah. Yeah. So, what I read is basically I mean I would say read basically three categories of things. So like in terms of like general media um it's basically I I sort of um I always describe it as I have like a almost a perfect barbell strategy um 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 um 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. Um, and and then it's sort of everything in the middle I'm always like much more skeptical about. And 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.

books. I I think you famously read constantly. I saw a interview with you where you're just like AirPods changed my life. I'm just listening to audio books now all the time. So, in terms of media diet, what do you what are you reading? What are you paying attention to these days in terms I don't know podcasts newsletters blogs things like that. And then any books in particular? >> Yeah. Yeah. So, what I read is basically I mean I would say read basically three categories of things. So like in terms of like general media um it's basically I I sort of um I always describe it as I have like a almost a perfect barbell strategy um 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 um 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. Um, and and then it's sort of everything in the middle I'm always like much more skeptical about. And 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 guess 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 n that 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 that they couldn't know and so they were making predictions and forecasts and so forth based on like not having any information but it's like wow like you know like none of this happened like I wish I had never read this like oh my god. Um and then you know it's kind of the same thing with magazines like go back and read old magazines. Um and just like the the the the level of the you know the just the endless numbers of predictions that they make. Yeah. And and kind of you know the problem with you know newspapers at least they're going dayto-day. The thing with magazines is like every it's like a week

or month you know kind of long cycle and so it's even you know by the time an article even hits publication it's you know it's often out out of date. So I just I just have like a big problem with kind of everything in the middle. Um and so it's either it's either it's either of the moment or timeless. But then yeah you mentioned like newsletters. I mean, so the the other thing and you know, 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 principles 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 we're we're used to being in this mass media kind of culture in which basically everything is mediated, right? everything got filtered through like TV interviews or like newspaper interviews or magazine interviews and and you know obviously

now more and more it's just no you actually want like smart people who are actually working on something explaining themselves and then you have you know you have new kinds of intermediation like podcasts that that that kind of open that up for people to make that possible um and so yeah like domain practitioners are um you know really great I mean just to state the obvious and AI you know it's obviously your your stuff but also like you know let Lex you know 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 can have the world's, you know, kind of leading experts in the domain actually show up and and by the way, it's, you know, it looks the critique always is, you know, people talk their book, like if I'm running a startup or whatever, I'm just selling, but it's like and there's always a little bit of that. Um, but it's also, you know, my experience is people love to talk about what they do and and you know, they they fundamentally like want to express what they do and and 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 kind of human knowledge by doing that and they get ego gratification by doing that. Um, 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 a wash in that today in a way that it wasn't as recently as 10 years ago. So I yeah I do as much of that as I can too. >> And there's also just this culture in tech Silicon Valley in particular of sharing of not trying to keep these secrets. Everyone on LinkedIn is always like how is this free like it's just the way it works. >> Yeah. It's somebody said Silicon Valley is a company town but the the the company is Silicon Valley >> right and but and again at the level this goes again there's one of these great n equals one at the level of n equals one is somebody you know and I've run startups before run companies before. um at the level of n equals one of like running a company that's just a giant pain in the butt like because you know your secrets are

walking out the door and your employees are walking out the door and the whole thing sucks. But you know the other side of it is you also benefit from that right because you get to hire people with all these skills and experiences right and you you're in this you're in this ecosystem that that adapts right and channels talents and and and skill and knowledge and people into into the new fields and so you know so that you know there's kind of the push and pull of that at the level of just being an individual individual CEO um at the level of of just being in the ecosystem to your point like yeah it's it's an absolutely magical phenomenon and by the way like you know one of the one of the you know for all the for all the issues in Silicon Valley um you know I think AI I did the comment once I AI is the ninth major technology platform in the history of Silicon Valley, right? That, you know, Silicon Valley is Silicon Valley is still called Silicon Valley. We haven't made Silicon here in decades, right? Uh we used to actually, you know, it's called Silicon Valley because they used to make chips, right? They used to have the like the actual fabs were in

Silicon Valley and then they and they designed them and they made the chips. Um and and so and that was you know wave one starting in the 19 actually that was like actually no actually more or less like wave three or whatever but like it was you know that was when the the indust the the area was named like in the 1950s but now we're on like wave nine right um and and the the company town phenomenon where the company is the industry like the the the again the indeterminate optimism the nobody had nobody had to sit and plan and say okay in the 1990s Silicon Valley is going to do the internet in the 2000s they're going to do the smartphone in the 2010s they're going to do the cloud in the 2020s they're going to do AI It it just the the the the right the indeterminant optimist optimism of ecosystem flexibility of the ecosystem met that the the the Silicon Valley could could morph um into all these categories and and again maybe a testimony to indeterminate optimism. >> This reminds me of the meme of how we're all just rappers over sand. Everything we're building is just rapper wrapper rapper rapper. >> The rapper thing is hysterical. Yeah. Yeah. I'm a I'm a software company now.

I'm I'm a chip rapper, right? Um uh Yeah. I'm a I'm a I'm a I'm a business application. I'm a database rapper. >> Um Yeah, exactly. I'm a sand Yeah. You and I are you, we're all now sand rappers. >> Sand rappers. >> Perfect. >> Okay, one more question. Along the media diet, I asked your partner Ben Harowitz uh what to talk to you about? Uh the Z and A16Z if people don't know him. And he said that you're really into movies these days. >> Yeah. >> And so I don't know any movies. Any movies you're really into these days? Any movies you've absolutely loved recently? >> Yeah. So the movie that blew my socks off uh last year, which I think is the best movie of the decade for sure and maybe of the last like 15 years, is this movie. Unfortunately, it's one of these things. Not a lot of people have seen it, but I would highly encourage it. It's called Edington. >> Not heard of it. >> Have you not heard of it? Okay. So, Ed, you're going to really enjoy it. So, I won't I won't spoil too much of it. So, at at at at the surface level, this the following spoils nothing. At the surface level, it's set in a small town in New Mexico called Edington, which is a small

town of about 600 people. Um, and um there's a sheriff uh who's played by Waqen Phoenix, who's like an old crusty basically right-winger. And then there's a um uh there's a mayor uh played by Pedro Pascal who's basically a young hip progressive. And uh and then the movie starts I think in March of 2020. And so it starts when COVID first hits and then it sort of as it plays out over the next few months it it then it intersects and it it sort of extends into the summer of 2020. So you know kind of the the George Floyd moment and then the you know the the protests and riots and kind of everything. So sort of the convergence of COVID and then the um and then the uh and then and then the uh the all the all the BLM stuff and and and and then um it and then and then there's a third kind of element to it which is um there's a company which is basically a loosely disguised version of meta if you read the backstory of it which is building an AI data center on the outskirts of town. So they kind of pull that in uh as sort of a thing that looms larger and larger over time. And then um the thing it really is great at is it really shows um you know this is a small town in New

Mexico and so everybody in the town gets kind of fully wrapped up in all the co stuff and they get fully wrapped up in all the BLM stuff and they get fully wrapped up in all the like you know tech anxiety stuff but they're all experiencing it basically through the internet right which which is which is you know what what actually happened right and so so it it's it's so so the reason I love the movie so much is one one is it's the first movie that directly grapples with 2020 of what happened in 2020 and it just like fully fully engages and grapples with like all the dynamics that were playing out in the country. But the other reason is it's the first movie that does a really good job of showing what it what it what it was like especially in that era to live in a world in which there were things happen in the real world and people were kind of experiencing events online, you know, like in a way that was like very central in their lives, right? Um and so it does like a really good job of pulling in like smartphones and social media um in a way that um uh in a way that movies really really really struggle with. And then the whole thing comes together in an incredibly

entertaining way. Um, and so, and I won't even say I I I won't even say I completely agree with the movie or whatever, and I think the director of the movie and I would probably disagree about a lot, but he really tries hard to like really grapple with like what is actually like to live like a human being in the 2020s in America in a way that I think many other filmmakers who are very talented have just been very scared of touching. And and this guy, for some reason, he's just like, "Yeah, I'm just going to find all the third rails and I'm just gonna like grab them." >> I can see why that's your favorite movie of the year. >> It's great. It's great. It's great. Everybody should see it. >> Oh, man. Okay, final question I want to ask about your piet uh your product diet. Are there any products you use that maybe are less known that you love that you want to recommend? You can, you know, mention products you're investors in if if you use them constantly. >> I mean, we have, you know, we have so many that it's really hard to, you know, I always feel it's like, you know, who's your favorite children? So, it's it's really hard to to to uh to uh you know,

entertaining way. Um, and so, and I won't even say I I I won't even say I completely agree with the movie or whatever, and I think the director of the movie and I would probably disagree about a lot, but he really tries hard to like really grapple with like what is actually like to live like a human being in the 2020s in America in a way that I think many other filmmakers who are very talented have just been very scared of touching. And and this guy, for some reason, he's just like, "Yeah, I'm just going to find all the third rails and I'm just gonna like grab them." >> I can see why that's your favorite movie of the year. >> It's great. It's great. It's great. Everybody should see it. >> Oh, man. Okay, final question I want to ask about your piet uh your product diet. Are there any products you use that maybe are less known that you love that you want to recommend? You can, you know, mention products you're investors in if if you use them constantly. >> I mean, we have, you know, we have so many that it's really hard to, you know, I always feel it's like, you know, who's your favorite children? So, it's it's really hard to to to uh to uh you know,

to to to pull out specific ones. Um, but I'll, you know, I'll talk about a few. Um, I mean, just I'll just observations. So, one is my my 10-year-old. Um I my 10-year-old my 10-year-old right now is 100% obsessed with Replet. Um and and by the way, it was not from me. Do you have kids? >> I do. I have one two and a half year old. >> 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? Like two and a half. Whatever daddy does is like the coolest thing in the world. I can tell you by the time he's 10, whatever you do is like deeply uncool, right? And and I'm highly aware of that. Um, and so like if I mention, oh yeah, we work on XYZ, you know, he's like, okay. Um, but when he discovers something, then then it's cool. Or when his friends tell him about it, it's cool. And so he he he through no inter interference on my part uh discovered Replet about uh about three months ago and discovered vibe coding and is like completely obsessed with vibe coding games and all kinds of all kinds of things and like literally was s do it for hours and so I'm seeing that phenomena 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 party trick at dinner parties now is to pull out uh Grock uh with Bad Rudy, which is if you've seen it's it's the it's a foul mouse raccoon uh avatar on the uh in in the Gro app. So um I think that's super fun. We have this company Sesame that had, you know, they they went viral last year for this, uh, you know, the this just incredibly like, you know, intimate, emotional, you know, kind of voice experiences. Um, so I think the voice stuff is fantastic. I'm also super fascinated by all the voice input stuff. Um, and so um, you know, you know, most recently that company recently sold, but um, you know, the all the I think like the pendants, the wearables, like all that stuff is going to be big. The meta glasses um, I you know, I think there's going to be a whole wearables revolution here. Um, I I love the voice input stuff. Um, I have this app on my there's this app on my phone now called Whisper Flow. Um, which is voice transcription. Um, which works like staggeringly well. Um, uh, it's like incredibly it's like a voice

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 party trick at dinner parties now is to pull out uh Grock uh with Bad Rudy, which is if you've seen it's it's the it's a foul mouse raccoon uh avatar on the uh in in the Gro app. So um I think that's super fun. We have this company Sesame that had, you know, they they went viral last year for this, uh, you know, the this just incredibly like, you know, intimate, emotional, you know, kind of voice experiences. Um, so I think the voice stuff is fantastic. I'm also super fascinated by all the voice input stuff. Um, and so um, you know, you know, most recently that company recently sold, but um, you know, the all the I think like the pendants, the wearables, like all that stuff is going to be big. The meta glasses um, I you know, I think there's going to be a whole wearables revolution here. Um, I I love the voice input stuff. Um, I have this app on my there's this app on my phone now called Whisper Flow. Um, which is voice transcription. Um, which works like staggeringly well. Um, uh, it's like incredibly it's like a voice

transcription function, but you can actually talk to the AM model while you're doing voice transcription. So, you can kind of it kind of understands when you're telling it, no, no, you know, 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 I think the voice mode stuff is going to be is going to be uh is going to be really great. >> Uh subscribers of my newsletter get a year free of Replet and Whisper Flow. So there we go. Uh uh what's the what's the most memorable thing your son built with Replet? >> Oh well so he's gotten super into Star Trek. Um and so so far it's been he's like writing like Star Trek simulators. Um >> so like all the you know all the by next generation they actually had >> Next generation. Okay. I was going to ask which >> Well, he like we actually we like them all. We watched the new Starfleet Academy last night which actually is quite is actually quite good. Um but uh we we watched the original, you know, we

watched we watched them all, but it was in next generation where they actually developed an actual design language for the computers >> because if if you watch the original series, they just had like basically, you know, knobs with lights and they didn't really, you know, they just like were like, you know, around on set trying to pretend they were doing it. But by next generation, they actually had designed, they actually had a UI design language. So, one of the one of the fun things you can do v 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 this I'm a nerd now. They call it LCARS um design language and um it'll you know it'll actually build you like Star Trek Next Generation British um using that design language but you know with your choice of like a Star Trek game for example. Um and so he's he's going crazy for that kind of thing. >> That sounds extremely delightful. You guys should uh open source or release that. Mark, I like I said, I could talk to you for hours. Uh, you got things to do. Uh, anything you want to leave listeners with before we wrap up?

Anything you want to double down on or just leave listeners with? >> Yeah, so a couple things. So, one is we got super lucky last week. Uh, Py McCormack uh wrote the best piece ever written about us actually? Um, which he released um and so it's the best explanation of what we do uh and how we think. And so I I would definitely recommend that. Um, and then you know we're putting a lot we have a you know great team of folks now. We're putting a lot of effort ourselves into video um in you know in content um and so I definitely recommend our YouTube channel which I I think has a lot of great stuff and is going to be very exciting in the next year. >> Awesome. We'll link to that. I think it's just YouTube.com6Z something like that. And you guys have great stuff. >> Mark, thank you so much for being here. >> Awesome. Thank you for having me. I really I really appreciate it. >> Bye everyone. >> Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You

can find all past episodes or learn more about the show at lennispodcast.com. See you in the next episode.