--:-- Host: Are ads purely destructive or negative to the user experience, or are they actually, if done properly, neutral or even positive?
--:-- Marc Andreessen: 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.
--:-- Host: Marc Andreessen went live on TBP this week, and today we're dropping that full conversation here on the pod. Marc gets into it all: what's really happening in AI right now, how Apple is playing its hand, 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.
--:-- [Disclaimer read by host]
--:-- Host: 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.
--:-- Host: We have Marc Andreessen joining us. He's live from the TBPN UltraJump. Welcome to the stream. How are you doing, Marc?
--:-- Marc Andreessen: Hey, what's happening? Great to see you.
--:-- Host: Yeah, you too. A lot. It's a little bit of a slow news day, but exciting stuff with GPT, open source. It's not a slow August.
--:-- Marc Andreessen: 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. American work. 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?
--:-- Host: Fantastic. Going really well.
--:-- Marc Andreessen: 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 when it turns out you're on the beach?
--:-- Host: You might have caught us. 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 Turing test, the Uncanny Valley.
--:-- Host: I think a question looking back over the maybe 10 or 15 years was: what moments did you feel like there just was not a lot of action happening? Because this summer, the pace from so many different teams has been absolutely insane. Everybody's trying to keep up, and it didn't used to feel that way, at least from my point of view.
--:-- Marc Andreessen: My view of it always is there are these disconnected patterns or trends. There's the day-to-day phenomenon where engineers show up every day and they make things a little bit better. And then every once in a while, you get a technical breakthrough or a new platform. That process kind of sawtooths up to the right over time, regardless of what else is happening in the world. It keeps happening through recessions and depressions and wars and all kinds of crazy stuff. But basically, the technology keeps getting better. So there's that curve.
--:-- Marc Andreessen: And then there's the enthusiasm curve and the adoption curve, which is basically when do these things actually show up in the world? And when are people actually ready for the new thing? If you talk to people who work on language models, they will tell you they were surprised that ChatGPT was the breakthrough moment because they thought everybody already knew what these models could do for three years before that. They were shocked that it was the chatbot interface that made the thing go. There's somewhat of an arbitrary disconnection between what's actually happening in the substance and what people are seeing and feeling. It's really hard to predict when these things pop. But if you're in it day to day, it's really hard to tell when things are going to be hot or not, because it doesn't necessarily map to how much the technology is improving.
--:-- Host: Yeah, we were just talking about that in the context of Google's new world model. It's this generative video game that you can kind of move around in. 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: if they let another lab do the ChatGPT thing and just get it out into the consumer three months earlier, they might wind up chasing and trying to catch up if somebody actually figures out how to make it a dominant consumer product. In the enterprise, it's more oligopolistic, but consumer seems to be winner take all. I guess the question is: how much value do you place right now in the AI race on moving fast, breaking things, dealing with safety constraints and all 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.
--:-- Marc Andreessen: Well, first of all, I need to correct you. It's moving fast and making things.
--:-- Host: Making things, that's right. I don't even know where that is from. I have no idea. Never heard of it.
--:-- Marc Andreessen: 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 believe in this case, total deaths attributable to ChatGPT are still zero. Zero. So notwithstanding all of the caterwauling.
--:-- Marc Andreessen: Look, I think the AI industry in particular has a very acute version of the challenge you identified. I don't say this negatively, just as an observation. In a normal technology company, you've got engineers who make products and salespeople or marketing people who sell them. In the AI companies, you have this third tier of the so-called researchers. That has worked out incredibly well. The researchers have done amazing breakthroughs at these companies. But the handoff from the researchers to the market is not necessarily clean. So it raises the question: are these companies three-segment companies where they have research, product development, and go-to-market? I think that's a really open issue.
--:-- Marc Andreessen: Google is kind of a case study of this. You alluded to DeepMind, but even more broadly, Google developed the transformer in 2017. And then they basically let it sit on the shelf because it was a research project. They didn't productize it. From people I've talked to, they were very worried about the brand issues and safety issues. They had all these reasons not to productize it. I talked to somebody senior who was there at the time, and I asked them, "When could you have had ChatGPT with GPT-4 level output if you had just gone flat out starting in 2017?" And they said by 2019. They already knew how to do it. And then they've now caught up, but it took an extra five years.
--:-- Marc Andreessen: Elon, as usual, is provoking this question. Within xAI, he's now collapsed the distinction between research and product. He's pushing this as hard as he can. I think it's a good question for a lot of these other companies: how hard they want to push on actually getting these things in fully productized form out to the market.
--:-- Host: On Elon's distinction, it feels like there is more research to be done, but it feels like we're entering a new cycle of 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 different track of fundamental research happening somewhere, but it's really hard to predict. So if you have something that's working, just double down and go really aggressive on it.
--:-- Host: I'm wondering more on that, but also on Apple's strategy. It feels like Apple has been kind of maligned for missing the AI opportunity. And Tim Cook is just there on the earnings call being like, "Look, we acquired a couple small companies." But then it seems like they're taking more of an American dynamism approach. There was news today in the Journal that they're investing $100 million in American manufacturing. They're certainly doing stuff. They're just not chasing the shiny tennis ball. The headline $100 billion CapEx. So I'm wondering about your thoughts on 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 changing their strategy on?
--:-- Marc Andreessen: Apple always had this very clearly defined strategy that Steve and Tim working together figured out a long time ago. They invest deeply into the core of what they do. 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. As a consequence, they have this thing where, and Tim says this, they're rarely first to market with new technologies. They're more often in the category of what Peter Thiel calls "last to market." They'll come out three years later, five years later. There were tablets for years before the iPad. There were smartphones for years before the iPhone. Folding phones — they're about to do a folding phone, it's like 10 years into that technology. I'm sure if they do it, they'll hit it.
--:-- Host: The last mover.
--:-- Marc Andreessen: The last mover. Look, that clearly works if you're Apple. But I would say there's a fine line between that strategy and simply becoming obsolete. The problem is, if you're not Apple and you don't have all the other super strengths and market position that Apple has, 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. All the other smartphone companies, when the iPhone came out, they were like, "Oh yeah, we could do touch too. We'll get to it." And they're gone.
--:-- Host: What do you think? The BlackBerry Bold, I remember, was like an iPhone knockoff.
--:-- Marc Andreessen: Yeah.
--:-- Host: Right now, a variety of shareholders are annoyed at Apple around their reaction to AI, LLMs. John's annoyed around just transcription generally, just super basic stuff. But it doesn't feel like the core business is immediately threatened today. It feels like it's still on the horizon around eyewear-based computing, potentially net new devices from companies like OpenAI over time. How real is the threat this year versus 10 years from today? What's your framework?
--:-- Marc Andreessen: Look, I think the biggest ultimate danger is very clear. At what point do you not carry around a pane of glass in your hand called a phone because other things have superseded it? Everything becomes obsolete at this point. There will come a time when we're not carrying phones around and we'll watch movies where people have phones and we'll be like, "Look at how primitive they were," because we'll have moved on to other things. Whether those things are eye-based, other kinds of wearables, computing happening in the environment, entirely voice-based, who knows what it is. But there will come a time when that happens.
--:-- Marc Andreessen: Is that time three years from now because there's some huge breakthrough from some company that figures out the product that obsolesces the phone right away? Or is it 20 years from now because the phone is such a standard platform for everything we do in our lives and everything else remains a peripheral to the phone? That's the game of elephants playing out. Obviously, I think it's highly likely that we'll have a phone for a very long time. Having said that, it is exciting that there are companies going directly at that challenge. Whoever cracks the code on that will be the next Apple. And by the way, that may in the fullness of time be Apple itself. They may be the company that figures that out.
--:-- Host: I remember being at a board meeting at Andreessen Horowitz maybe a decade ago. Chris Dixon showed me the HoloLens, and I was like, "Okay, we're one year away from this being everywhere." And I feel like today I'm still in the, "Yeah, VR, it's definitely one year away. The next Quest I'm going to be wearing daily." It feels like we're always there, but it does feel like Apple did a lot of work on the fundamental pixel density of the resolution of the display. And Meta has been doing a ton of work on just getting it light and affordable. It feels closer than ever, but you always have to wait until you see the churn numbers to really call the game.
--:-- Marc Andreessen: Well, you're saying that, but I think it's true. I'm on the Meta board, so I'm kind of a dog hunting this one, but the Meta Ray-Ban glasses are a big hit.
--:-- Marc Andreessen: They're a big hit. So I think we now have a form factor that we know works for eye-based wearables. Not VR, and then VR on top of that, but just the glasses with integrated camera, integrated microphone, integrated speaker. That's a very interesting platform. The watch clearly works, by the way, which Apple has played a significant role in making happen. That now sells in huge volume. So that's the second data point. And then look, I think some form of AI pin is going to work. Also, headphones are going to get a lot more sophisticated, which is already happening. So you have these data points coming out. And then the trillion-dollar question ultimately is: are these peripherals to the phone, which is what they are today? Or are these replacements for the phone? I think we have a lot of invention coming both from new companies and from the incumbents who are going to try to figure that out.
--:-- Host: I always think about the value of narrowing the aperture on these new technologies. 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. I always go back to the iPhone. 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 do you disagree with that?
--:-- Marc Andreessen: Well, you guys might be too young. The first iPhone actually was a bad phone.
--:-- Marc Andreessen: For the first two years, it couldn't reliably make phone calls.
--:-- Host: I had the third one and a friend had one, but I feel like it was still people were carrying cell phones and that was the expectation.
--:-- Marc Andreessen: 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. There was a famous Steve Jobs email. You could basically brick the device based on how you held it. Somebody emailed Steve — this was when Steve would respond to emails from random people — and said, "If I hold the phone this way, it doesn't make phone calls." And he said, "Well, don't hold it that way."
--:-- Marc Andreessen: Even there, it was like that. And people forget, it took like five years for the iPhone to find its footing. It took like two years to get the thing. The original iPhone didn't have broadband data. It was on the old 2G AT&T Edge Network. So it didn't have broadband data. And then it didn't have an app store. It was completely locked out.
--:-- Marc Andreessen: The challenge for Apple now is that people are so used to perfection with the device that launching a product that isn't perfect is embarrassing. You look at the Vision Pro and it's like, "Well, the battery's big. Steve would have hated this. He never would have shipped this." Being constrained and not being able to innovate because you're tied to this impossible standard of being on generation 17 of the iPhone and perfecting every element is a real challenge.
--:-- Marc Andreessen: I would say there's a corollary to that. One of the things I've observed over the years is that legacy products become obsolete at the precise moment they become perfect. By "perfect," I mean the perfect idealized complete product. 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. There have been tons of examples over the last 50 years where it seems like the permanent version of that product. And then it turns out that's actually the point of obsolescence because it means creativity is no longer being applied to that platform. You're just done. The product has been realized. And then the cycle is that other people come in with completely different approaches, completely different kinds of products that are broken and weird in all kinds of ways but are fundamentally different. That is one of the time-honored traditions. One of the things you could say about Tim is his willingness to break the mold of Apple only shipping perfect products. Being willing to ship the Vision Pro shows a level of determination to stay in the innovation game, which I think is very positive.
--:-- Host: That's great. Updated thinking on open source since we last talked. There's a lot that's been happening. Yesterday, OpenAI is an open source company again.
--:-- Marc Andreessen: Yes, OpenAI is open again.
--:-- Marc Andreessen: Very encouraging. A year ago, I was getting very distressed about whether open source AI was going to be allowed, whether it was even going to be legal. I think we're basically through that at this point in the U.S. We'll see about the rest of the world. The U.S.-China thing is obviously a big deal, but I think it's been net positive for the world that China has been so enthusiastic about open source AI coming out of China, which has been great. And then OpenAI leaning hard into this and releasing what they did is fantastic, both because of what they released, which is great, but also just the fact that they are now willing to do that. And then Elon reconfirmed overnight that he's going to start open sourcing previous versions of Grok. So we seem to be in a timeline where open source AI is going to happen.
--:-- Marc Andreessen: Right now, I think what you would say is it lags the leading edge proprietary implementations by about six months or something like that. But if that's the status quo that continues, I think that would be a very good status quo.
--:-- Host: What are the rough edges that we need to sand down when we're thinking about Chinese open source models specifically? Is it that we need to do some fine tuning on top of them to add back free speech? Or do we need to watch for back doors, phone home, if it runs into this specific thing? The Chinese open source thing was remarkable because I feel like it really does accelerate the pace of innovation. Everyone gets to see, "Oh, this is how reasoning works." I think that's great. At the same time, 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. From your perspective, what are the risks that we need to be aware of going into a world where China is really pushing hard into open source?
--:-- Marc Andreessen: There are two, and you identified them. Let's talk about both. The phone home thing is the easy one. You can packet sniff a network and you can tell when the thing is doing that. Plus you can go in the code and you can see what is doing that. You can validate that it's either happening or not happening. I think that's important, and people are going to figure that out. You can kind of gate that problem practically.
--:-- Marc Andreessen: The bigger issue is we have this term in the field right now called "open weights." It uses the "open" term from open source, but with open source, you can actually read the code. With open weights, you have a giant file full of numbers that you can't really interpret. What most of the open weights models don't have, including DeepSeek specifically, is open data or open corpus. You can't actually see the training data that went into them. Most of the people building models are obscuring what that training data is in various ways. So when you get an open weights model, the good news is the software source is open, you can run it on your machine, you can verify it doesn't phone home. But you don't actually know what's happening inside the weights.
--:-- Marc Andreessen: I think that is going to be a bigger and bigger issue. How does the thing behave? What has it actually been trained to do? What restrictions or directives has it been given in the training that are embedded in the weights that you need to be able to see? This is coming up as a global issue. We worry about it when these models come from China. Other countries worry when these models come from the U.S. One of the phrases you'll hear when you talk to people outside the U.S. is "not my weights, not my culture." Or for that matter, "not my weights, not my laws." What actually is this thing going to do? The Chinese models might never criticize communism or something. I can tell you, the American models have all kinds of constraints also, usually implemented by a very specific kind of person at a very specific location in the U.S. So I think this is a general issue. We're going to have to see people's tolerance levels for running open weights models where they don't fundamentally have access to the data. Correspondingly, I think we'll see more open source developers also doing open corpus, open data, so you can see what's actually in them.
--:-- Host: Obviously, open source is very important in terms of 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 in most of the labs right now. There's also this specter on the horizon of potentially putting ads in LLMs and what that would do to the world. Jordi 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?
--:-- Marc Andreessen: My point broadly was that ads have been an incredible way to make a variety of products and services online free. Just saying default, no ads, would potentially be incredibly destructive.
--:-- Host: But yeah, curious, your framework.
--:-- Marc Andreessen: Yeah, so I should start by saying whenever I personally use an internet service, I always try to buy the premium version of it that doesn't have ads.
--:-- Marc Andreessen: And so if I can live personally inside an ad-free universe and pay for it, that's great. And I'll freely admit whatever level of hypocrisy or incongruence results from that.
--:-- Host: No, the point is choice.
--:-- Marc Andreessen: The point is choice. Well, the point is exactly what you said, it's affordability. So the problem is if you really want to get to a billion and then 5 billion people, you can't do that with a paid offering. At any reasonable price point, it's just not possible. 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 the Google search engine, or the Facebook social app, or the frontier AI model to be available to 5 billion people for free, you need to have a business model. You need to have an indirect business model, and ads is the obvious one. So if you take some principled stand against ads, I think you unfortunately are also taking a stand against broad access, just in the way the world works today.
--:-- Then the other really salient question is the same one that companies like Google and Facebook have been dealing with for a long time: Are ads purely destructive or negative to the user experience? Or are they actually, if done properly, either neutral or even positive? This was something that Google, I think to their credit, figured out very early: a well-targeted ad at a specifically relevant point in time is actually content. It actually enhances the experience. The obvious case is 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.
--:-- So can you have ads or other things that are like ads—different kinds of referrals, mechanisms—in such a way that they're actually additive to the product experience? Just like with search and with social networking, you can imagine lots of examples of that. People will whine in lots of different ways, but I think that hasn't been a bad outcome overall. And I think it's entirely possible that's what happens with these models as well.
--:-- Host: So a similar kind of question: what should be legal? Trying to create legal frameworks on a number of issues with AI. There have been a number of IP cases working their way through the courts. What can labs use to train models, et cetera. There have been some good outcomes recently. Sam was also talking about how a lot of people are using AI as a confidant, like a friend. 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 legal system in the U.S. can get some of these issues right, where maybe it can't just be total free markets, lawless, whatever goes?
--:-- Marc Andreessen: In the case of training data, there are a bunch of these copyright lawsuits happening right now. The big New York Times one and a bunch of others. My guess is that problem ultimately has to be solved through legislation. It's ultimately a legislative question because it goes to the nature of copyright law itself, which is legislation. The content industry is already claiming that using copyrighted data to train without permission and without paying is illegal on its face, a violation of copyright law. The counter argument, which we believe, is that it's not copying. There's a distinction between training and copying, just like in the real world there's a distinction between reading a book and copying the book as a person.
--:-- The courts are trying to grapple with that. There are jurisdictional questions. Probably ultimately, Congress is going to have to figure out an answer on that. By the way, the president kind of threw down that gauntlet in his speech last week or two weeks ago, where he said Washington probably needs to deal with that as an issue.
--:-- On the privacy thing, that one feels like it's a Supreme Court thing to me. Whether, for example, your transcripts are considered your property and whether they're protected against warrantless search and seizure. If you look at the march of technology over time, the Constitution has very clear Fourth and Fifth Amendments, very specific rights around the things that are yours—your home, the thoughts in your head. The government can't just come in and take them, can't search your house without a warrant, can't put you in a jail cell and beat you until you fess up. We have constitutional protections against the government taking information or possessions.
--:-- Every time there's a new technology that creates a new kind of thing that you own, that's yours, that you would consider private, law enforcement agencies naturally go try to get those things because there are ways to solve crimes. Then the courts come in later and rule one way or the other, saying that actually is also protected against warrantless search or warrantless wiretapping. This is the latest of probably 20 of those over the last hundred years. I don't know which way it'll go, but it's going to be a key thing because people are already telling these models lots of things that are very personal.
--:-- Host: 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 terrible at others. Where are you actually getting value out of AI right now? Where is it falling down for you? How are you using AI day to day?
--:-- Marc Andreessen: I have a barbell approach. One is for serious stuff. I love the deep research capabilities. I'm doing this in a bunch of models. The ability to say, "I'm interested in this topic, write me a book," and I'm hoping for the longest book I can get. I always say go longer, go longer, more sophisticated. The leading edge models now are getting up to 30-page PDFs that are completely well-formulated, long-form essays. Incredible richness and depth. If it's 30 pages today, I'm crossing my fingers that it'll get to 300 pages in the next few years. I'm able to have the thing generate enormous amounts of reading material with incredible richness and depth and complexity.
--:-- On the other side of the barbell is humor. I've posted some of these to my X feed over the last couple of years. I think these models are already much funnier than people give them credit for.
--:-- Marc Andreessen: Yeah, I think they're actually quite highly entertaining.
--:-- Host: Is it specific formats? Like prompts, or is it just chatting back and forth?
--:-- Marc Andreessen: They're really good at greentext. That works really well. But the ones I find hysterical are the screenplays for TV shows or plays or movies. I posted one where I had it write a new season of the HBO show *Silicon Valley* set 10 years later. I had it write 10 scripts for a complete season. I said, "Make it like *Silicon Valley* except it's happening in 2021, kind of peak woke." I thought it was just—I'll sit there at two in the morning laughing my ass off at how funny this thing is. I think these things are already extremely funny, extremely entertaining when used that way. I generate a lot of those that I don't post.
--:-- Host: Stay in the group chats.
--:-- Marc Andreessen: It's probably good.
--:-- Host: They're your property.
--:-- Marc Andreessen: Yeah.
--:-- Host: Hopefully the Fourth Amendment holds on these.
--:-- Marc Andreessen: Yeah.
--:-- Host: That's great. I have one last question.
--:-- Marc Andreessen: Go for it.
--:-- Host: How do you get a job as a venture capitalist in 2025?
--:-- Marc Andreessen: The best way to do it is to have a track record early as somebody who is in the loop specifically on product development. Be deeply in the trenches at one of these new companies in one of these spaces. Participate in the creation of a great new product and a great new company and really demonstrate that you know how to do that. There are great VCs who have not done that, but I think that is sort of a foundational skill set for working with the kinds of founders you want to work with. They're going to want you to have very interesting things to say on that. I think it's still the best way to do it.
--:-- Host: Yeah, feel the growth, immerse yourself in the aggressive growth environment, and then you'll be able to identify it when you see it from afar.
--:-- Marc Andreessen: That's right.
--:-- Host: Last question for me. State of M&A in your mind. How are you advising companies where you're on the board, or the portfolio broadly, around what they should expect now and in the near future?
--:-- Marc Andreessen: You mean in terms of whether you can get things approved?
--:-- Host: Basically, yeah.
--:-- Marc Andreessen: Approval is not a slam dunk. I just saw there was a medical device company this morning where the acquisition was not allowed by the FTC. So there is still scrutiny. It's obviously a very different political regime in Washington, but by their own statements, this is not an administration that believes in total laissez-faire. They definitely want to maintain a very healthy level of market competition.
--:-- Host: Do you expect certain companies to be negatively impacted by the Figma story? You have this deal gets blocked, successful IPO. Lina Khan is taking a victory lap. Many people are responding and joking, saying Lina cuts off the arm of a pianist and they endure and can create a masterpiece. Then you look at the example with Roomba, where it had to deal with Amazon, it was blocked, and the company has been in shambles ever since. My concern is that people look at Figma and say, "You should be independent. You just figure it out. Nothing can go wrong."
--:-- Marc Andreessen: It's kind of taking a victory lap. It was very disconcerting. For exactly the reason you said: survivorship bias. You pick the one that worked out. It's the airplane, the red dots, the airplane name. You ignore the 50 that are in the ground that you've never heard of. That was very disconcerting because it's the central planning fallacy: we make centrally planned economic decisions based on one example. It's like in Europe, "The bottle caps actually don't fall off the bottle. It works." But do you want to live in an economic regime where the government has dictated bottle cap design? The answer is clearly no, because the downside consequences are thousands of times worse.
--:-- Or even looking at the Chinese model. People can say they're picking winners, but to get to maybe picking a winner, you have this intense bloodbath of competition where teams need to rise to the top and prove themselves before they get any meaningful state benefit.
--:-- Host: Yeah, that's right.
--:-- Marc Andreessen: You have this adverse selection, survivorship bias thing where you don't pay attention to all the collateral damage. That mentality is super dangerous. Companies just have to be very thoughtful about this, both acquirers and the acquirees. The big thing is if you're selling a company, you need to anticipate that you might not get it through. Number one, is there a big enough breakup fee? Are you going to get paid for the damage you're going through? And two, do you have the kind of company culture that's going to be able to withstand that? Is your business strong enough to get through that? It is a real risk and worth taking very seriously.
--:-- Host: And that's why it felt emotional. We were at NYSE last week. It felt emotional that the Figma team was able to effectively just restart the business and say, "We're taking this all the way."
--:-- Marc Andreessen: If you talk to any really successful company, what they'll tell you is over the years they have these crucible moments where they almost died. But they pulled together and pulled it off. That became one of the central mythical events in the history of the company. "My God, we got through that. We're so strong and tough. We've been forged in fire. Now we can do anything." That's great. And then there are 50 other companies that hit those crucible moments, blew up, and died. All the lessons learned on this stuff are conditional on survival. These things need to be taken incredibly seriously, which the great CEOs do.
--:-- Host: Well, thanks so much for joining. We'll let you get back to your day. We already gave you five minutes over. Next time we have to book five hours because this is fantastic. I got 10% of the way through.
--:-- Marc Andreessen: Let's do the first 24-hour marathon.
--:-- Host: We would love to have you again. Enjoy the rest of your day. We'll talk to you soon, Marc. Have a good day. Bye.
--:-- Marc Andreessen: Thank you, guys. Thank you.
--:-- Host: Thanks for listening to the a16z podcast. If you enjoyed the episode, let us know by leaving a review at ratethispodcast.com slash a16z. We've got more great conversations coming your way. See you next time.
