Marc Andreessen: Why Perfect Products Become Obsolete

Marc Andreessen joins TBPN for an unfiltered conversation spanning everything from ads in LLMs to why Apple’s AI strategy may be risky for anyone not named Apple. Marc breaks down the current state of AI: why open source is resurging, how foundational research is (or isn’t) turning into product, and whether we’ve hit the moment when phones start to fade as dominant platforms. He also shares his candid thoughts on Meta’s wearable wins, Vision Pro’s imperfections, and how humor and deep research are his two favorite use cases for AI today.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Marc Andreessen?

  Are ads purely destructive or negative to the user experience? Or are they actually, if done properly, are they actually either neutral or even positive? You know, if you're not Apple, do you really want to be a company that basically sits there and says, yeah, the world's moving and we're very deliberately not going to lean as hard as we can into it? I think there's a lot of survivorship bias in these kinds of strategy discussions where people look at the one company that's able to pull this off and they don't look at the 50 other companies that are in the graveyard because they didn't adapt.

• 0:26Speaker 01

  Marc Andreessen went live on TBP on this week, and today we're dropping that full conversation here on the pod. Mark gets into it all, what's really happening in AI right now, how Apple is playing its hands, the return of open source, and why perfect products can signal the end, not the peak. He also shares his take on how to break into venture capital in 2025 and what he's actually using AI for day to day. Let's get into it.

• 0:51Speaker 01

  This information is for educational purposes only and is not a recommendation to buy, hold, or sell any investment or financial product. This podcast has been produced by a third party and may include paid promotional advertisements, other company references, and individuals unaffiliated with A16Z. Such advertisements, companies, and individuals are not endorsed by AH Capital Management LLC, A16Z, or any of its affiliates. Information is from sources deemed reliable on the date of publication, but A16Z does not guarantee its accuracy.

• 1:21Speaker 02

  We have Marc Andreessen joining us. He's live from the TBP in Ulster, June. Welcome to the stream. How are you doing, Mark? Hey, what's happening?

• 1:30Speaker 03

  Great to see you.

• 1:31Speaker 02

  Yeah, you too. A lot. It's a little bit of a slow news day, but exciting stuff with GPT, open source.

• 1:39Speaker 03

  It's not a slow August.

• 1:40Speaker 02

  It's not a slow August. We're glad. We were just reflecting that we've taken exactly one day off this summer. That was July 4th, and we're showing the Europeans how American companies work.

• 1:51Speaker 03

  American work ethic.

• 1:52Speaker 02

  We're setting an example, and we have proof of work because we exist on the internet and you can see us live every day. So we're setting an example. How are you doing? How's your summer going?

• 2:03Marc Andreessen?

  Fantastic, going really well. So how long is it going to be until you guys put up avatars that make claims that you're working hard all through the summer, but it turns out you're on the beach?

• 2:11Speaker 03

  You might have caught us.

• 2:12Speaker 02

  I think you'll know better than us as to when the technology gets there. We've been demoing some of the stuff. People have been doing a lot of deep fakes of us and fortunately, all of them have been clockable. So it doesn't feel like a brand risk, but they're getting closer and closer. And I know that there's going to be a moment where we have to say, hey, that's actually using our name and likeness to endorse something that we don't necessarily endorse. Can you please take that down? So we're approaching the touring test, the uncanny valley. We're escaping the uncanny valley.

• 2:40Speaker 03

  I think a question, like looking back over the, you know, maybe 10 or 15 years was, what moments did you feel like there just was not a lot of action happening? Because this summer is just the pace from so many different teams has been absolutely insane. Everybody's like trying to keep up and it didn't used to feel that way, at least from my point of view.

• 3:04Marc Andreessen?

  So my view of it always is there's like these, there's this, these disconnected, you know, kind of patterns or trends. There's sort of the, the sort of day to day phenomenon where like engineers show up every day and they make things a little bit better. And then every once in a while, you know, you get a technical breakthrough or a new platform. And that process kind of this, you know, kind of sawtooth, kind of up to the right kind of process kind of plays out over time, kind of regardless of what else is happening in the world. And so it keeps happening through recessions and depressions and wars and like all kinds of crazy, crazy, crazy stuff that's happening. But basically, you know, the technology keeps getting better. So there's, there's kind of that curve. And then, and then there's the, the sort of enthusiasm curve and then the adoption curve, you know, which is basically like, when do these things actually show up in the world? And then by the way, when are people actually ready?

• 3:48Marc Andreessen?

  You know, for, for the new thing. Like if you talk to the people who worked on, I'm sure you guys have talked to people who work on language models. They will tell you that they were surprised the chat GPT was the breakthrough moment because they thought everybody already knew what these models could do for, you know, three years before that. And so they were, you know, they were shocked that it was the chatbot interface that made, that made the thing go. And so there's somewhat of a sort of arbitrary disconnection between what's actually happening in the substance. And then what, what, what people are, are seeing and feeling. And so it's just, it's, it's really hard to predict when these things pop. But also if you're in this day to day, it's, it's really hard to tell, you know, when things are going to be hot or not. Because it doesn't necessarily map to how much the technology is improving.

• 4:24Speaker 02

  Yeah, we were just talking about that in the context of of Google's new world model. It's this like generative video game that you can kind of move around in. And it feels like DeepMind is just absolutely crushing at the AI research frontier. They have the best world model simulator that you can walk around in. The question is like, if they let another lab do the ChatGPT thing and just get it out into the consumer three months earlier, they might wind up kind of chasing and trying to catch up if somebody actually figures out how to make it like a dominant consumer product. Now, in the enterprise, it's more oligopolistic, but consumer seems to be winner take all. I guess the question is like, how much value do you place right now in the AI race to

• 5:06Speaker 02

  just like moving fast, breaking things, you know, dealing, having like the thick skin to deal with like the safety constraints and all of the different stuff, obviously not being irresponsible, but just speeding up the organization as much as possible. It feels like now is the time to really push on that.

• 5:23Marc Andreessen?

  Yeah, well, first of all, I need to correct you. It's moving fast and making things.

• 5:27Speaker 02

  Making things, that's right.

• 5:28Marc Andreessen?

  I don't even know where that came from. I have no idea. Never heard, never heard of it.

• 5:34Speaker 02

  I mean, ChatGPT didn't really break anything. I think that's a good point. It really did just move fast and make things. The first things it made were weird, but that was fine. And it failed and it hallucinated a ton, but it didn't really break anything. I don't know.

• 5:45Marc Andreessen?

  Yeah, I believe that I believe in this case, total deaths attributable to ChatGPT are still zero.

• 5:50Speaker 02

  Zero.

• 5:52Marc Andreessen?

  So notwithstanding all of it, notwithstanding all of the caterwauling. But yeah, so look, I think the AI industry in particular has a very acute version of the of the of the sort of challenge that you identified with. And, you know, and I don't say this negatively, just an observation, which is that they're, you know, like in sort of a normal technology company, you've kind of got engineers who make products and then you've got, you know, kind of salespeople or marketing people who sell them. You know, in the in the ad companies, you have this third tier of, you know, the quote unquote researchers.

• 6:17Speaker 02

  Yeah.

• 6:18Marc Andreessen?

  Right? Um, and so, you know, which is which has worked out incredibly well. I mean, the researchers have done, you know, they've just done like amazing breakthroughs at these companies. But, you know, the the the handoff, you know, there's not necessarily clean handoff from the researchers to the to the market. Um, and so it kind of raises this question of like, OK, like, is there is, are these companies there for kind of three, you know, kind of three segment companies where they have research and then they have product development, um, and then and then they have go to market? Um, and I think that's a really open issue. I mean, if you, you know, Google's kind of a case study of this, you know, you alluded to DeepMind, but even more broadly, Google, you know, Google developed a transformer in 2017. Um, and then they basically let it sit on the shelf, right? Because it was a research project, they they didn't productize it. They were very worried about, you know, from people I've talked to, they were very worried about the, you know, brand issues and safety issue, you know, kind of all these, all these, they had all these reasons to not productize it.

• 7:03Marc Andreessen?

  Uh, I talked to somebody senior who was there at the time, but then I I asked them, you know, when when when could you have had chat GPT with GPT four level output? Um, if you had just got, you know, gone gone flat out, starting in 2017? And they said by 2019.

• 7:15Speaker 02

  Yeah.

• 7:16Marc Andreessen?

  You know, they're they already knew how to do it. And then, you know, they've now caught up, but it took it took an extra five years, five years to catch up. Um, and so I I think a lot of these companies kind of have that challenge. Elon, as usual, of course, is provoking this question, as I'm sure you guys talked about, but, you know, he he has now, you know, with an XAI, he's now collapsed, you know, he's eliminated the distinction between research and product.

• 7:36Speaker 02

  Yeah.

• 7:37Marc Andreessen?

  Um, and so, you know, of course, he, you know, he's pushing this as hard as he can. And I I think it's a it's a good question for a lot of the other companies, kind of how hard they want to push on actually getting these things in fully productized form out to the market.

• 7:46Speaker 02

  Yeah, yeah. On on Elon's like distinction, it feels like there is more research to be done, but it feels like we're we're entering like a new cycle of, you know, just focus on the engineering, focus on the deployment, the applications, let's get all this technology out into the world, let's reap all that benefit. And yes, there will be a a different track of fundamental research that's happening somewhere, but it's really, really hard to predict. And so if you have something that's working, just double down and just go really aggressive on it. Um, I'm I'm wondering, uh, more on on that, but also on Apple's strategy. It feels like Apple's been Kind of like, you know, people have been maligning them for not for missing the AI

• 8:28Speaker 02

  opportunity and Tim Cook's just there on the earnings call being like, look, we acquired a couple of small companies and

• 8:34Speaker 03

  Seven this year.

• 8:35Speaker 02

  Seven companies, but then it seems like they're taking more of like an American dynamism approach. Like there was news today in the Journal that they that they're investing $100 million in American manufacturing. They're certainly doing stuff. They're just not chasing the, you know, the shiny tennis ball.

• 8:51Speaker 03

  Headline $100 billion CapEx.

• 8:53Speaker 02

  Um, so I'm wondering about your thoughts on on when you have a, you know, when you have a platform, how hard is it to resist chasing the new shiny object? Is that the right move? Or are there any other things that you think Apple should be, you know, changing their strategy on?

• 9:12Marc Andreessen?

  Yeah. So look, Apple's always had this, you know, very clearly defined strategy that, you know, Steve and Tim, you know, working together, figured out a long time ago, which is, you know, they, I forget the exact term, but it's something like basically they, they invest deeply into the core of what they do. You know, they'll basically work internally on things for many years. They only actually release things when they feel like they're kind of fully baked.

• 9:30Speaker 02

  Yeah.

• 9:31Marc Andreessen?

  Right. And so as a consequence, they have this thing where, and Tim says this, right? You know, they're rarely first to market with new technologies. You know, they're more often in the category of what, you know, Peter, Peter Thiel calls last to market. You know, they're, you know, they'll, they'll, they'll come out whatever, three years later, whatever, five years later. You know, there, you know, there were tablets for years before the iPad. There were, you know, smartphones for years before the iPhone.

• 9:51Speaker 02

  Folding phones. They're about to do a folding phone. It's like 10 years into that technology. But I'm sure if they do it, they'll hit it.

• 9:56Speaker 03

  Last mover, the last mover.

• 9:58Speaker 02

  Yeah, yeah, yeah. Sorry.

• 9:59Marc Andreessen?

  The last mover. And I guess, yeah, what I would say is like, look, that clearly works if you're Apple, right? And so it clearly works if you're Apple. But I would say there's a fine line between that strategy and just and simply becoming obsolete, right? And so the, the problem is like, if you're not Apple, and you don't have all the other kind of super strengths and, you know, kind of now the market position that Apple has, you know, do you really want to be a company? You know, if you're not Apple, do you really want to be a company that basically sits there and says, yeah, the world's moving and we're very deliberately not going to lean as far as we can into it? And so I think there's a lot of survivorship bias in these kinds of strategy discussions where people look at the one company that's able to pull this off and they don't look at the 50 other companies that are in the graveyard, you know, because they, you know, because, because they didn't adapt. I mean, you know, all the other smartphone companies, when the iPhone came out, they were like, oh yeah, well, we could do touch too, right? You know, we'll just,

• 10:43Marc Andreessen?

  you know, we'll get to it, right? And, you know, you know, they're gone. What do you think?

• 10:49Speaker 02

  BlackBerry Bold, I remember it was like an iPhone knockoff.

• 10:52Speaker 03

  What do you think, you know, right now, people are, variety of, you know, shareholders are annoyed at Apple around their reaction to AI, LLMs, John's annoyed around just like transcription generally, just like super basic stuff. But it doesn't feel like the, the core business is immediately threatened today. It feels like it's still on the horizon around these sort of like, you know, eyewear based computing, you know, potentially net new devices that we're, that, that we'll see from, you know, companies like OpenAI over time. But where do you like, like, how, how real is the threat, you know, this year versus 10 years from today? And kind of what's your framework?

• 11:35Marc Andreessen?

  Yeah, well, look, I mean, I think the biggest ultimate danger, I mean, the biggest ultimate danger is very clear, which is just like, at what point do you not carry around a pane of glass in your hand, you know, called a phone, you know, because other things have superseded it. And, you know, like, everything, you know, everything becomes obsolete at that point. So there will, there will come some time, if you're when we're not, you know, carrying phones around, and we'll, we'll watch movies where people have phones and we'll be like, yeah, look at that, look at how primitive they were, right? Because, because we'll have moved on to other things. And whether those things are I based, or, you know, you know, the other kinds of wearables, or whether it's just kind of, you know, computing happening in the environment, or just, you know, entirely voice based, or, you know, who knows what it is. But, you know, there will come a time when that happens, you know, is that time, three years from now, because there's like some, you know, huge breakthrough, you know, from, from some company that figures out the, the product that obsolescence the phone right away? Or is that 20 years from

• 12:20Marc Andreessen?

  now, because the phone is just, you know, such a standard platform for everything that we do in our lives and everything else, you know, kind of remains a peripheral of the phone? I mean, that, you know, that's, you know, that, that's the game of elephants that's playing out there. You know, obviously, I think, you know, I think it's highly likely that we'll have a phone for a very long time. Having said that, it is, it is exciting that there are companies that are going directly at that challenge. And, you know, whoever cracks the code on that will be, that will be the next Apple. And by the way, that, that may in the fullness of time be Apple itself, you know, they, they may be the company that figures that

• 12:49Speaker 02

  Yeah, I remember being at a board meeting at Andreessen Horowitz, maybe a decade ago or something, and Chris Dixon showed me the HoloLens. And I was like, OK, we're one year away from this being everywhere. And I feel like today I'm still in the like, yeah, VR, it's definitely one year away. The next Quest, I'm going to be wearing daily. And it feels like we're always there, but it does feel like Apple did a lot of work on the fundamental, you know, pixel density of the resolution of the display. And then Meta has been doing a ton of work on just getting it light and affordable. Like, it feels closer than ever, but you know, you always got to wait until you see the churn numbers until you really call the game, right?

• 13:28Marc Andreessen?

  Well, you're saying the same, but you know, I think that's true. But you'd also say, you know, I'm on the Meta board, so I kind of have a dog on this one. But like, the Meta Ray-Ban glasses are a big hit.

• 13:38Speaker 02

  Oh, totally.

• 13:39Marc Andreessen?

  Right? Like, they're a big, you know, so I think we now have a form factor that we know works, you know, for eye-based wearables. You know, there's not VR, and then VR, you know, on top of that. But, you know, just the, you know, the glasses, and you know, and then the glasses of camera, you know, sort of integrated camera, integrated microphone, integrated speaker.

• 13:54Speaker 02

  Yep.

• 13:55Marc Andreessen?

  You know, that's a very interesting platform. You know, the watch clearly works, by the way, which Apple, of course, you know, has played a significant role in making happen. You know, that now sells in huge volume. You know, so that's the second data point. And then, you know, like, I think these, you know, these, I think some form of AI pin is going to work.

• 14:09Speaker 02

  Yep.

• 14:10Marc Andreessen?

  Also, the headphones are going to get a lot more sophisticated, which is already happening. And so, you know, you do have these, you know, kind of data points coming out. And then, yeah, look, the trillion-dollar question ultimately is, are these peripherals to the phone? You know, which is what they are today, or are these replacements for the phone? And, you know, we, yeah, I would say, you know, we have, I think we have a lot of invention coming, both from new companies and from incumbents who are going to try to figure that out.

• 14:32Speaker 02

  Yeah, I always think about the value of like narrowing the aperture on these new technologies. Like, with the Meta Ray-Bans, I feel like the fact that they aren't also trying to be a screen is actually a feature, not a bug. And I always go back to the iPhone, like, it was first and foremost a phone. And people bought it because it could make calls, and then it could make text messages, and then it was an iPod. But I, do you disagree with that? Please?

• 14:56Marc Andreessen?

  Well, you guys, I don't know, you guys might be too young. The first iPhone actually was a bad phone.

• 15:01Speaker 02

  How so?

• 15:02Marc Andreessen?

  For the first two years, it couldn't reliably make phone calls.

• 15:06Speaker 02

  I had like the third one and a friend had one, but I feel like it was still like people were carrying cell phones and that was the least of the expectation. But yeah, I mean, I guess you're right.

• 15:16Marc Andreessen?

  For the first two, it was a classic Apple strike because the first, for the first two years, the thing couldn't reliably make phone calls. And then it turned out, there was an issue with the antenna and with how you held it. And there was a famous email.

• 15:26Speaker 02

  Yeah, and you would disconnect it.

• 15:28Speaker 03

  You could basically brick the device.

• 15:30Speaker 02

  Yeah.

• 15:31Marc Andreessen?

  Based on how you held it. And somebody emailed, this is when Steve would respond to emails from random people. And somebody emailed Steve saying, if I hold the phone this way, it doesn't make phone calls. And he's like, well, don't hold it that way.

• 15:40Speaker 02

  Yeah.

• 15:41Marc Andreessen?

  Right?

• 15:41Speaker 02

  Yeah.

• 15:42Marc Andreessen?

  So even there, it was like, yeah, and people, you know, people forget, it took like five years for the iPhone to find its footing. It took like two years to get the thing. I remember also, the original iPhone didn't have, it didn't have broadband data. It was on, it was on the old 2G. It was called the AT&T Edge Network. So it didn't have broadband data. And then of course, it didn't have an App Store. Right? It was completely locked out.

• 16:00Speaker 03

  So the challenges, the challenges for Apple now is that people are so used to perfection with the device that launching a product that isn't perfect, like is embarrassing. Right? Like you look at the Vision Pro and it's like, well, the battery's big. Steve would have hated this. Right? Like how he never would have shipped this. And that being constrained and not being able to innovate because you're tied to this like impossible standard of being on whatever generation 17 of the iPhone and perfecting every element is a real challenge.

• 16:32Marc Andreessen?

  So I would say there's a corollary to that. One of the things I've observed over the years is I think technology products become obsolete at the precise moment they become perfect. And did you find what I mean by perfect? Basically is like, yeah, it's like the perfect, idealized, complete product. Like it does everything you could possibly ever imagine. Everything a customer could imagine, everything you as the technology developer can imagine, it's absolutely perfect. And there's, there's been tons of examples of this over the last 50 years, where it's like the absolute perfect, it seems to be the permanent version of that product. And then it just turns out, that's actually the point of obsolescence. Because it means creativity is no longer being applied right into that platform. You're just like, there's just nothing else to do. You're just like, you're done, right? The product has been realized. And then, and then the cycle is what happens to your point.

• 17:14Marc Andreessen?

  The cycle is other people come in with completely different approaches, completely different kinds of products that are broken and weird in all kinds of ways, you know, but are fundamentally different. And so, you know, that is one of the time honored traditions. And, you know, one of the, you know, one of the, you know, things you could say about, you know, Tim is, you know, his willingness to kind of break the mold of Apple only ships perfect products, but, you know, be willing, being willing to ship the, you know, the Vision Pro, you know, you know, shows a level of determination to kind of stay in the innovation game, which I think is very positive.

• 17:40Speaker 02

  Yeah, yeah, yeah, yeah, that's great.

• 17:42Speaker 03

  Updated thinking on open source. Since we last talked, there's, there's a lot that's been.

• 17:49Speaker 02

  Open AI is an open source company again.

• 17:51Speaker 03

  Yes, Open AI is open again.

• 17:53Speaker 02

  Yes.

• 17:53Marc Andreessen?

  Yeah, yeah, it looked very encouraging. You know, a year ago, I was very, you know, I was getting very distressed about open, you know, whether open source AI was going to be allowed, right? It was even going to be legal. And so, and I think, you know, we're basically through that at this point. What I was going to say, we're through that in the US. You know, we'll, we'll see about, we'll see about the rest of the world. And then, look, you know, the US-China thing is obviously a big deal, but you know, I think it's been net positive for the world that China has been, been so enthusiastic about open source AI coming out of China, which has been great. And then, yeah, look, Open AI leaning hard into this, you know, and releasing what, you know, what they did is, I think, fantastic, both because of what they released, which is great, but also just the fact that they are now, you know, willing to do that. And then Elon reconfirmed overnight that he's going to, you know, open source, you know, start open sourcing previous versions of Grok.

• 18:35Marc Andreessen?

  And so, yeah, so we, you know, we, we, we seem to be, we seem to be in a timeline where open source AI is going to happen. You know, right now, you know, what you, I think what you would say is it kind of lags the leading edge proprietary implementations by, you know, six months or something like that. But, but I think that, you know, that's a good, if that's the status quo that continues, I think that would be a very good status quo.

• 18:54Speaker 02

  What are the rough edges that we need to kind of sand down when we're thinking about Chinese open source models specifically? Is it, we need to do some fine tuning on top of them to add back free speech? Or do we need to watch for backdoors, say it's phone in home if it runs into this specific thing? The Chinese open source thing, it was remarkable because I feel. Like it really does accelerate the pace of innovation because everyone gets to see, oh, this is how reasoning works. I think that's great. At the same time, it made me very, it made me much more appreciative of AI safety research and capability research and actually being able to interpret what's going on and say definitively, this model is going to behave weird in this weird way. Like the Manchurian candidate problem, we haven't found any of that, but it certainly seems like something we'd want to keep an eye on. But from your perspective,

• 19:39Speaker 02

  like what, what are the, what are the risks that we need to be aware of going into a world where China is really pushing hard into open source?

• 19:46Marc Andreessen?

  Yeah, there's two, there's two, and you identified them, but let's, let's, let's talk about both of them. So the phone, so the phone home thing is the, is the easy one, which is you can put up, you know, you can packet sniff, you know, a network and you can tell when the thing is doing that. And you, and plus you can go and you can go in the code and you can see what is doing that. And so you, you can validate, you can validate that that's either happening or not happening. And I think that, you know, that's important. But I, you know, I think people are gonna, people are gonna, are gonna figure that out. You, you can kind of get that problem practically. The, the, the bigger issue is we, we have this term in the field right now called open weights. And open weights is a loaded term. It, it uses the open term from open source, but of course with open source, the thing is you, you can actually read the code.

• 20:28Marc Andreessen?

  You know, with open weights, you have, you know, just a giant file full of numbers, as you said, that you, you can't really interpret. And then what you don't, what you don't have, what, what most, what most of the open source, open weights models don't have, including, you know, deep sea specifically. What they don't have is they don't have open data, right? Or open corpus, right? So you, you can't actually see the training data that went, went into them. And of course, you know, most of the people building models are kind of obscuring what that, you know, what that training data is in various ways. And, and so when you get an open weight model, you know, the good news is the, the, the software source is open. The good news is you can run it on your machine. You can verify that it doesn't phone home, but you don't actually know what's happening inside the weights. And so I, I think that, that is going to be a bigger and bigger issue, which is like, okay, how the thing behaves, like, yeah, what, what has it actually been trained to do?

• 21:13Marc Andreessen?

  And what restrictions or directives has it been given in the training, you know, that are embedded in the weights that, that you need to be able to see? You know, this is, I would say this is coming up as sort of, I would say a global issue. You know, which, you know, we worry about when these models come from China. Other countries worry when these models come from the US. Which is, right? So one of the, one of the phrases you'll hear when you talk to people kind of outside the US is kind of this, this phrase people are kicking around, which is not my weights, not my culture.

• 21:36Speaker 02

  Okay.

• 21:36Marc Andreessen?

  Right, right. Or by the way, for that matter, not by waste, not by laws.

• 21:40Speaker 02

  Yeah.

• 21:40Marc Andreessen?

  Right. Which is like, okay, like, what actually is this thing going to do? Right? And to your point, the Chinese models, for example, might, you know, never criticize, you know, communism or something. I can tell you, the American models have all kinds of constraints also.

• 21:54Speaker 02

  Yeah.

• 21:55Marc Andreessen?

  Right? Implemented, you know, usually by a very specific kind of person at a very specific location in the US.

• 21:59Speaker 02

  Yep, yep.

• 22:00Marc Andreessen?

  And so, you know, I think that this is, this is a general issue and we're going to have to see basically people's tolerance levels. Being willing to run open weights models where they don't fundamentally have access to the data. And then correspondingly, I think what we'll see is more open source developers also doing open corpus, open data. So you can see what's actually in them.

• 22:17Speaker 02

  Yeah. Obviously, open source is very important in terms of just distributing intelligence broadly. Giving people the ability to run their own models and really fine tune them and have control. There's also the big push just to make frontier models and high capability models free. One model is you charge for the premium, you give the free away. It's a freemium model. That's what we're seeing at most of the labs right now. There's also this kind of specter on the horizon of potentially putting ads in LLMs. And what that would do to the world, Jordy got in a little dust up with Mark Cuban on the timeline. Deciding whether or not it would be a net good to put advertising in LLMs. What might happen that might be bad there? What do you have to take?

• 23:01Speaker 03

  Yeah, my, my point broadly was that ads have been an incredible way to make a variety of products and services online free. And just saying like default, just no ads would potentially, you know, be incredibly destructive. But yeah, curious your framework.

• 23:22Marc Andreessen?

  Yeah. So I should start by saying like, whenever I personally use an internet service, I always try to buy the premium version of it that doesn't have ads. Right? And so if I can like live personally inside an ad free universe and pay for it, like, that's great. And I'll freely admit, you know, whatever level of, you know, hypocrisy or incongruence, you know, kind of, kind of, kind of results from that.

• 23:39Speaker 03

  But the point is choice. The point is choice.

• 23:42Marc Andreessen?

  Well, the point is exactly what you said, affordability. So the problem is, if you really want to get to, if you want to get to a billion and then five billion people, you can't do that with a paid offering. Like it just, at any sort of reasonable price point, it's just not possible. The, you know, global per capita GDP is not high enough for that. People don't have enough income for that, at least today. And so if you want to get to, you know, if you want the Google, if you want the Google search engine, or the Facebook social app, or the whatever AI, you know, frontier AI model to be available to five billion people for free, you need to have a business model, you need to have an indirect business model, and as is the obvious one. And so I do think if, you know, if you take some principled stand against ads, I think you unfortunately are also taking a stand against, against, against broad access, just

• 24:27Marc Andreessen?

  in the way the world works today. And then, look, the other, the other really salient question is, you know, the same question that the companies like Google and Facebook have been dealing with for a long time, which is, are ads purely destructive or negative to the user experience? Or are they actually, if done properly, are they actually either neutral or even positive? Right? And this was something that, you know, Google, I think to their credit, figured out very early, which is, you know, a well-targeted ad at a specifically relevant point in time is actually content. Like, it actually enhances the experience, right? Because it is the obvious case. You're searching on a product, there's an ad, you can buy the product, you click to buy the product, that was actually a useful piece of functionality. And so, you know, can you, can you have ads or other things that are like ads or look like ads, you know, different kinds of referrals, you know, mechanisms or whatever?

• 25:09Marc Andreessen?

  Can you have them in such a way that they're actually additive to, to the product experience? And you can imagine, just like with searching, with social networking, you can imagine lots of examples of that. People will, you know, the people will, you know, they'll whine or howl in lots of different ways, but I think, you know, I think that hasn't been a bad outcome overall. And I think that, I think it's entirely possible that that's what, what happens with, with these models as well. Yeah.

• 25:33Speaker 03

  Kind of similar kind of question, what should be legal, kind of trying to create legal frameworks on a number of issues with AI. There's been a number of IP cases that have been working their way through the courts. What can labs use to train models, et cetera? There's been some good outcomes recently. Sam also was talking about how a lot of people are using AI as like a confidant, like a, you know, a friend, things like that. And he mentioned that currently your chats are not privileged. They can be used in a lawsuit or other situations. How optimistic are you that our sort of legal system in the US can get some of these issues

• 26:16Speaker 03

  right, where maybe it can't just be, you know, total free markets, kind of lawless, whatever goes?

• 26:23Marc Andreessen?

  Yeah. So in the case of training data, I think that there, I mean, there's a bunch of these copyright, you know, kind of lawsuits happening right now. There's, you know, the big New York Times OpenAI one, and there's, you know, been a bunch of others. Yeah, I think in that, for that particular problem, my guess is that problem ultimately has to be solved through legislation. It's ultimately a legislative question. The reason is because it goes to the nature of copyright law itself, you know, which is legislation. And of course, you know, the content industry is already claiming that, of course, you know, using copyrighted data to train, you know, without permission or without paying is sort of, you know, they believe illegal on its face, you know, due to violation of copyright law. The counterargument to that, which, you know, which we believe is, well, it's not copying, right? There's a distinction between training and copying, just like in the real world, there's

• 27:06Marc Andreessen?

  a distinction between reading a book and copying the book, you know, as a person. And so there's going to need, I think, you know, the courts are trying to grapple with that. There's a whole bunch of cases, there's jurisdictional questions, you know, probably ultimately Congress is going to have to figure out a, you know, figure out an answer on that. And by the way, the president is kind of, you know, throwing down that gauntlet in his, I think, the speech he gave last week or two weeks ago, you know, where he said, you know, Washington probably needs to deal with that as an issue. So that's one on the on the on the on the on the privacy thing. I think that that one feels like it's a Supreme Court thing to me. It feels like that's the kind of issues that is Supreme Court. And in other words, like whether, for example, your transcripts are considered your property and whether they're protected against, you know, warrantless search and seizure. And

• 27:49Marc Andreessen?

  the observation I would make there is if you look at the march of technology over time. So the Constitution has like very clear, you know, Fourth, Fifth Amendments, you know, very specific rights around the, you know, the things that are yours, you know, such as, you know, your home, you know, being in your home, you know, by the way, the thoughts in your head, right?

• 28:06Marc Andreessen?

  You know, that the government can't just like come in and take, they can't, you know, they can't just come in and search your house without a warrant. You know, they can't like, you know, put you in a jail cell and beat you until you fess up. Like, you know, there are, you know, we have constitutional protections against the government being able to basically, you know, take information, you know, fundamentally, you know, as well as possessions. And then basically, what happens is every time there's a new technology that creates a new kind of sort of, you know, thing that you own, you know, thing that's yours, thing that you would consider to be private, thing that you wouldn't want the government to be able to take without a warrant, you know, out of the gate, law enforcement agencies just naturally go try to get those things because there are ways to assault crimes. And, you know, it feels like that that's a legal thing to do. And then basically, the courts come in later, and they, you know, rule one way or the other. And basically, they say, no, that that actually

• 28:51Marc Andreessen?

  is also a thing that is protected against, you know, warrantless, for example, warrantless search, you know, or warrantless wiretapping. And so I feel like, you know, this is the latest of probably, I don't know, 20 of those over the last 100 years. And, you know, I don't know which way it'll go, but I think it's going to be a key thing. Because as you know, people are already telling these models, you know, lots, lots of things that they're, you know, that are very personal.

• 29:13Speaker 02

  Okay, lightning round, quick questions. We're letting you get out of here in a couple of minutes. We're in this age of spiky intelligence. Models are great at some things and then terrible at others. Where are you actually getting value out of AI right now? Where is it falling down for you? Where are you? How are you using AI day to day?

• 29:30Marc Andreessen?

  Yeah, so I have two kind of, I don't know, barbell approach. One is for serious stuff. I love the deep research capabilities. And so, and I'm doing this in a bunch of models, but like the ability to basically say, I'm interested in this topic. And I just felt like, write me a book. And I, you know, I kept kind of hoping for the longest book I can get. I was telling like, go longer, go longer, more sophisticated. You know, but the leading edge models, now they're getting up to like 30 page PDFs. You know, that are like completely well formulated, you know, basically long form, long form essays. You know, it's just like incredible richness and depth. And, you know, if it's 30 pages today, I'm sort of crossing my fingers it'll get to, you know, 300 pages coming up here in the next few years. And so I, you know, I'm able to basically have the thing generate enormous amounts of reading material with just like, I think incredible richness and depth and complexity.

• 30:14Marc Andreessen?

  And then on the other side of the barbell is humor. And I've posted some of these to my X feed over the last couple of years, but I think these models are already much funnier than people give them credit for.

• 30:24Speaker 02

  Really?

• 30:25Marc Andreessen?

  Yeah, I think they're actually quite highly entertaining. A while ago, I posted.

• 30:31Speaker 03

  Specific, specific formats like.

• 30:33Speaker 02

  Like prompts or is it just chatting back and forth?

• 30:35Speaker 03

  Be Marc Andreessen, you know, that, that format.

• 30:38Speaker 02

  Take a dip in my pool in my office.

• 30:41Marc Andreessen?

  They're really good. So they're really good at green text. That works really well, but the, for some reason, the ones I find hysterical are the, I have it right, screenplays. You know, for like TV shows or plays or movies. And I posted, I had it right, a new season of the HBO Silicon Valley, you know, set 10 years later. And I had it right, like an entire, I had it right, like 10, 10 scripts for a complete season. And of course I just said, you know, make it like Silicon Valley, except, you know, it's happening in 2021, it kind of peak woke.

• 31:09Marc Andreessen?

  And I thought it was just, I think it's just, you know, I'll sit there at 2:00 in the morning and just like laughing my ass off at how funny this thing is.

• 31:15Marc Andreessen?

  And so I think these things are actually, are actually already like extremely funny. They're extremely entertaining when they're, when they're, you know, when they're used to that way. And I do, I do enjoy that a lot and I generate a lot of those that I don't post.

• 31:27Speaker 02

  Stay in the group chats.

• 31:29Marc Andreessen?

  It's probably good.

• 31:30Speaker 03

  They're your property.

• 31:31Speaker 02

  Yeah, hopefully the fourth amendment holds on these.

• 31:34Speaker 03

  Yeah.

• 31:35Speaker 02

  I have one last question.

• 31:36Speaker 03

  Go for it. And then I've got one more.

• 31:38Speaker 02

  How do you get a job as a venture capitalist in 2025?

• 31:41Marc Andreessen?

  So I mean, look, the best way, the best way to do it is to have a track record early as somebody who is like in the loop specifically on new product development. And so somebody who, you know, be like deeply in the trenches at one of these new companies in one of these spaces, you know, participate in the creation of a great new product and a great new company and, you know, really demonstrate that you know how to do that. You know, there's there, you know, there are great VCs who have not done that. But, you know, I think that is sort of a foundational skill set, you know, for working with the kinds of founders that you want to work with, who are going to, who, you know, are going to want you to have, you know, kind of very interesting things to say on that. As I think, you know, still the best way to do it.

• 32:16Speaker 02

  Yeah, like feel the growth, be immerse yourself in the growth, the aggressive growth environment, and then you'll be able to identify it when you see it from afar.

• 32:25Marc Andreessen?

  Yeah, that's right.

• 32:26Speaker 03

  Last question for me. State of M and A in your mind. How are you advising, you know, companies where you're on the board or just the portfolio broadly around what they should expect now and in the near future?

• 32:41Marc Andreessen?

  You mean in terms of whether you can get things approved?

• 32:43Speaker 03

  Basically, yeah.

• 32:45Marc Andreessen?

  Yeah, yes. So look, approval still, approval is not a slam dunk. There was, you know, there was a, I just saw there was a medical device company this morning, you know, where the acquisition was not allowed by the FTC. So, you know, there is still scrutiny. It's, you know, it's obviously a very different political regime in Washington, but, you know, this is, this is not, you know, by their own statements, this is not an administration that believes in total laissez faire. M and A, and it definitely wants to, you know, in their view, maintain a very healthy level of market competition.

• 33:10Speaker 03

  Yeah. How many, do you expect, do you expect certain companies to be negatively impacted by the Figma story, right? You have this deal gets blocked, successful, you know, IPO, Lina Khan is taking a victory lap. You know, many people are responding and joking, saying, you know, someone, Lina cuts off the arm of a pianist and they endure and can create a masterpiece and then. And so I expect, and then you look at the example with, you know, Roomba, I think it was where Roomba had a deal with Amazon, it was blocked and and the company has just been in shambles ever since. So my concern is that people look at Figma and say, you should be independent, you just figure it out.

• 33:53Speaker 02

  Nothing can go wrong.

• 33:54Speaker 03

  Yes.

• 33:55Marc Andreessen?

  Yeah, and it's kind of taking a victory lap was very disconcerting. And for exactly the reason you said, which is survivorship bias. Right, which is you, you, you picked the one that worked out. And then, you know, it's the, it's the airplane, the red dots, the airplane. You know, you, you, you ignore the 50 that are in the ground that you've never heard of. And so that was very disconcerting because that, you know, it's sort of the central planning fallacy, which is like, we make centrally planned economic decisions. We have one example. You know, it's like in Europe, it's like, yeah, well, the, the bottle caps actually don't fall off the bottle. Right, like, you know, it works.

• 34:27Marc Andreessen?

  Right? It's like, okay, but, but do you want to live, you want to live in an economic regime in which that, you know, the government has dictated bottle cap design? The answer is clearly no. Because the downside consequences.

• 34:37Speaker 03

  Or even looking at that, you know, the Chinese model, which is, you know, people can say they're picking winners, but to get to maybe picking a winner, you have this intense bloodbath of competition where, you know, teams need to rise to the top and sort of prove themselves before they get any of that real, like, you know, meaningful state benefit.

• 34:59Marc Andreessen?

  Yeah, that's right. And so you just, you just, yeah, you just, you just have this adverse selection survivorship bias thing where you just, you don't pay attention to all the collateral damage. So I, I, I do think that mentality is like super, super dangerous. And so, yeah, look, I think companies just have to be very thoughtful about this, both acquirers and acquirers. You know, and the big thing is if you're selling a company, like, you just need to anticipate that you might, you might not get it through. And if you don't, they're sort of like, okay, number one, is there like a big enough breakup fee? Right, are you going to get, you know, paid for the, you know, paid for the, you know, the damage that you're going through? You know, and how is that structured on the one hand? And then two is, yeah, look, do you have the kind of company culture that's going to be able to withstand that? And is your business, you know, strong, strong enough to be able, to be able to get through that? And it's, it is a real risk and something worth, you know, taken very seriously.

• 35:42Speaker 03

  Yeah, and that's, that's why it felt emotional. We were at NICI last week. It felt emotional this, that, that the, the Figma team was, was able to like effectively just like restart the business and say, like, we're, we're, we're taking this all the way. So.

• 35:57Marc Andreessen?

  If you talk, I don't know what you think about it. If you talk to any really successful company, what they'll tell you is, yeah, over the years, we have these like crucible moments in which like we almost died. Right, but we like pulled together and we pulled it off. And then that became like, you know, one of these central kind of mythical events in the history of the company that we always refer to. And of like, my God, we got through that and we're so strong and tough. And we've been forged in fire and now we can do anything. And it's like, yeah, that's great. And then there are 50 other companies that have those crucible moments, blew up and died.

• 36:24Marc Andreessen?

  So yeah, it's all of the lessons learned on this stuff. They're all conditional on my survival. And so they, these things need to be taken incredibly seriously. You know, which, which the great CEOs do.

• 36:36Speaker 02

  Yeah. Well, thanks so much for joining. We'll let you get back to your day. We are five minutes over. Next time we have to book five hours because this is fantastic. I got 10% of the way through.

• 36:44Speaker 03

  Twenty four hour TV.

• 36:45Speaker 02

  Yeah, we would love to have you again. It's a lot of fun. Enjoy the rest of your day. We'll talk to you soon, Mark. Have a good day.

• 36:51Marc Andreessen?

  Bye. Thank you, guys.

• 36:52Speaker 02

  Thank you.

• 36:55Speaker 01

  Thanks for listening to the A16Z podcast. If you enjoyed the episode, let us know by leaving a review at ratethispodcast.com/a16z. We've got more great conversations coming your way. See you next time.