20VC: Is SaaS Dead in a World of AI | Do Margins Matter Anymore | Is Triple, Triple, Double, Double Dead Today? | Who Wins the Dev Market: Cursor or Claude Code | Why We Are Not in an AI Bubble with Anish Acharya @ a16z

23:23It was the shittest question ever. But, you know, after 10 years, I'm not embarrassed to ask shit questions. No way. How does the UI paradigm change in the world of AI? Everyone's like, now we're just all going to be voice. Do you agree with like just, it's all voice? So voice is amazing for enterprise. I think that one, dynamic UIs and two, chat UIs are overstated in consumer. And the best thinker on this is actually Eugenia who founded Replica and now Wabi. She's great on this. And what she would tell you if she was here is that, look, most people don't want to save time. They want to spend time.

23:58Okay. And the products are designed by the most high agency people in the world. Like Sam and Elon are the most high agency people in the world. For them, the optimal UI is a chat box where you say exactly what you want and like voila, there it is. But for many people, they're again looking to waste time, spend time. They want a browse-based interface. They're not quite sure what they want. They can't always articulate it. So I think that in a world where we have intent-based and browse-based, browse-based largely stays the same. And perhaps the future of intent-based is chat. I'm still a little skeptical.

24:28I think people are consistently concerned by, we mentioned it earlier, but defensibility, switching costs, durability. When we think about moats and Alex's statement of hostages, not customers, in a new world of AI, do we just accept that there's no defensibility or are new moats created? I think defensibility still exists and still matters. Like networks are the gold standard and they still are. You know, a network effect product is incredibly powerful. Now, look, you might argue that something like Moldbook is a new type of synthetic network that perhaps means there are certain types of networks that are less defensible than they once were.

25:06But something like an Airbnb, you can have all the vibe coding in the world. Their network effect is incredibly powerful. So one, I think defensibility matters. Traditional moats still do matter. I do think that within moats like systems of record, there will be some who are more or less prone to disruption. So if you're an on-prem database and there's no engagement layer and there's not a lot of human workflows built around the so-called system of record, I think that you actually are at some risk. If you're the core system for a bank, you've got thousands of transactions per second. You've got hundreds of humans that interact with you.

25:39You have this incredible demand for accuracy. I still think that you're sort of as good as gold in terms of defensibility. Is there any forms of defensibility which were very prominent in the prior 10 years which are no longer as prominent? Yeah, I'll give you the opposite. I was always skeptical of the sort of data network effect. You know, that was like this thing that got thrown out a lot when you couldn't think of what mode to say. But today, if you look at companies that have proprietary data sets, and not just proprietary, Open Evidence is a good example of this, but live, proprietary and live is a very, very powerful mode.

26:10When you say live, what do you mean? Like your health data, for example, right? That's our sort of live and ever-changing source of data. Now, there's a question of how proprietary can that be? But once you actually have data like that, or perhaps live data about a product that's running, now you can put a relatively commodity model in front of it and get much better results than the most cutting edge model that does not have access to the proprietary or live data. Okay, so we have relatively the same forms of defensibility that have existed before that we'll continue to make. Many. I'm always trying to understand.

26:42I feel very kind of insecure right now as an investor because I'm trying to understand what holds true from the prior decade and what doesn't, and I need to change my mind on. When the facts change, I change my mind. When we think about a lot of the forms of defensibility remaining true, I was always taught that margins matter. I walk with my mother around London and Portland, and I'm always like, Mom, margins matter. Yes, I can imagine you holding your hand. Yeah, poor mom. Handheld, yes. Jesus, no wonder she wants to finish the walk. My question to you is, do margins matter as much in a world of AI?

27:15And are we entering a new way that we should be thinking about margins? Yeah, so here is actually where I think there's nuance in the margin conversation that's important. So if you look back at any time you've got, and we should talk about the bubble that doesn't exist, or perhaps there is some sort of subsidization and distortions happening in the market. For the record, I don't believe we're in that period. But I do think that any time you have this sort of superheated markets, you have some distortion. If you look at the distortion from 2021, you essentially had this indirect subsidy of Google and Facebook.

27:46So you would invest in a fintech company. You would give them$10 million. They would go spend$8 million on Google ads and Facebook ads. So there's a subsidy that was happening that were sort of these empty calories for the startup. If instead you look at the form of subsidy that happens today, what it typically means is zero margin or negative gross margin credits for the user to try the product. So these things tend to be a drag, but these are actually very healthy calories for the companies because out of that you get conversion into high-paying users, and many of whom are actual power users.

28:16So I do think that the blended margin story for AI-native companies tends to be worse. But if you look at the overall sort of form of distortion that's happening, it's a much better one than we had five years ago. Does that make sense? It does. Jason Lemkin is a very good friend of mine from Sasta, and he said to me, I said a brilliant statement. He said, for the best companies, inference is the new sales and marketing. Yeah, I love that. 100 % correct. Yes. Yes, I also think that power users are so much more powerful than they ever have been. Like Andrew Chen used to say pre-AI, and I love this, like power users are just users.

28:49And it was true. Because even if they got 100x more value, they typically didn't pay 100x more. Like you look at Spotify, great European company, the very best Spotify SKU with the highest bitrate music, totally lossless, all the pods, all the videos, family plan, everything was$20, $25 a month. So there was a belief that the price ceiling for consumer products mass market was$20 to$25 a month. You look at Grok heavy, it's$300 a month. ChatGPT,$200 a month. Gemini Ultra, $250 a month. So we're seeing 10x higher prices paid and you have consumption revenue on top of it. So for the power users, they're paying incredibly high subscription rates plus consumption revenue.

29:27So the S &M costs of acquiring those users are very wisely invested. And I think this is an important point that's changed. But you're telling me then for my team, when I'm looking at margins with the investing team, that we should have the same high bar that we carried or we should have greater elasticity to lower margins? So first of all, it's typically a lot of organic traffic. One, I would look at your M1, your sort of month one as traffic, not truly acquired users because it's organic and it's free to acquire. And then second, I would take the look at the sort of margin cost of those users' free trials and sort of just say, hey, that's CAC and that's okay.

30:06And then look at the margin profile of people who convert and say, that's the sort of durable margin profile of the product and the business. So you're sort of unbundling the CAC oriented margin spend versus the durable margin, which is what's associated with your power and paying users. It totally does. The challenge becomes, if you're trying to work out a CAT2LTV metric that you can kind of oscillate around, it's very difficult to get an accurate sense of LTV in such a changing landscape where you're not sure of the durability. Is the LTV 12 months or is it 48 months? Yeah, well, I think that retention really matters.

30:38And if you take a look at the best AI products, even if you look at M2 as the new M1, because again, you're getting a lot of tourists who come in at M1, you're not paying anything for them. And so M1 means month one for those that don't know. If you look at M2 sort of as your first month for some of these products that are acquiring a ton of top of funnel traffic, then you apply the same high retention bar you ever applied to them. What's an M12 that would make you very excited? I mean, like the bigger the better, but certainly 50 % is solid, right? And if you're 60, 70%, I mean, we're very, very happy.

31:12So we have that in terms of margins. I do want to touch on, you said bubble, no, I'm not in that camp. I like to attack things while I'm there. Why are you not in that camp? Well, there's a little quip that I like to use, which is like, it's not a bubble and it's good that it is. And I'll tell you why. Look, this is not my area of focus or expertise, but one, you look at OpenAI's recent announcement, which is that there are 20 billion of top line. And the way that they got there is they 3x capacity and they 3x top line. So every time they bring on capacity, all of that supply, that inference supply is 100 % spoken for.

31:48And we're seeing that story happen over and over again. Whereas in previous, you know, sort of so-called bubble periods, you saw this incredible build out of supply far ahead of demand. So, so far, we're not seeing that, right? Two, if you actually look at the prices that customers are paying, they're going up. So, you're not seeing the sort of price compression that you would get from a typical overbuild of supply, right? And then three, as I said previously, even if there is subsidization, There's always going to be some distortion subsidization. It's a sort of intelligence subsidization that's mostly being paid for by big tech and the labs.

32:18And it benefits consumers and startups. Like, God bless. I'm all for that. I do a show with Jason Lemkin and Rory O'Driscoll. And Rory said something brilliant, I think, which is like, this will all work out if we see the transition of spend from the 12 % SaaS budgets that we operate in today transition from that budget to the human labor budget. Do you think we will see that transition? I mean, we're already seeing it. I think DG was on the show talking about C.H. Robinson, right? Like we're seeing a lot of companies start to see the productivity improvement from this new technology. I mean, how can they not, right?

32:53It's not just coding agents in which this is showing up. You talked about voice. Voice is the wedge into the enterprise. Voice agents are so powerful. And by the way, I think that the near-term story of a lot of voice, I know we talked about support. You talked about sort of customer support. That's interesting. But the more interesting thing is why is support an isolated function? And let's go through it. You typically have had sales, support, operations, and collections. Who is the person that's really good at customer support? Empathetic. They're a listener. They really understand the product well.

33:20Who is really good at sales? They're more of a yapper. They're a talker. They're high energy. They're very charismatic. They're sort of good at the upsell. They're always in a good mood. You've got these two different human archetypes for these two different roles. We've typically organized the enterprise around these two archetypes, right? But now the models can be either of those people at any time. So the most sophisticated companies are starting to take support, sales, collections, operations, bundle them all together with one broad goal like CAC improvement. And I think that is going to be the 10x on productivity more than saying, hey, we're just going to take cost out of customer support.

33:54How do you think about competition within markets? I'm jumping around so much. I'm just fascinated. You brought up customer support. I tweeted it the other day and I tweeted it before. I just can't get my head around this market. There are like 50 providers with over$50 million in funding, 10 with over$100 million. I'm very much of the Peter Thiel school of thought that competition is for losers, and we want to have monopoly markets. With your Decagons and your Sierras and your Intercoms and your Poloas, and I can go on and on. I don't know. Well, the question is, how do you define market? Okay, that is an important point, right?

34:26So I would argue that in many cases, what you're calling a market is actually an industry. Let's look at legal. Many great companies have been funded, and there's still room for another dozen. And I think the reason for that is legal is a$500 million. It's sort of infrastructure for capitalism, broadly. Is there going to be one company that wins the entire market of infrastructure for capitalism? Of course not. That is an industry, not a market. And you're going to have dozens of winners that all specialize. Just as in legal today, you've got dozens of specializations. So I think in many of these markets, we are talking about it as if it is one market, when it is much, much bigger and all the companies will specialize in their own directions.

35:01Well, it's a$500 billion market if you assume that we eat their market, not we're an attach to it, correct? Correct, yeah. And we are an attach to it. I mean, that's an open question. I don't think that we're in the 8 % to 12 % anymore, right? $50 billion legal software traditionally. I think we're going to be somewhere between the$50 and the$500, and I think closer to the$500 than the$50. What does that look like? That means AI native law firms? Possibly. I think it means dramatic productivity increases for lawyers, dramatic productivity increases for programmers and engineers. I think that the difficulty of doing 100 % of a job is really, really high.

35:37It's this thing of pretty easy to get to 60%, 70%, 80%. So I do think that's why a 20 % productivity increase, so far we're seeing it show up more as a four-day work week than 20 % less jobs. Because jobs as bundles of tasks don't set themselves up to be 100 % automated so far. You can do all the customer support you want, but sometimes you've got to take the customer out for a steak dinner. And so far, the models are not doing that. They're not. We mentioned the$500 billion TAM. Do you do TAM analysis work when investing? Here's what I think. I think we tend to consistently underestimate how big the markets are and consistently overestimate how easy it is to go from zero to one.

36:17I think when you squint, you can take something that's not working and say, I can see how it will work. And that is why, in my mind, seed investing is its own sort of art. I focus very much on the Series A because I believe that having shipped something and having sold something is such a dramatic signal. To me, that is actually the optimal point in terms of information provided slash entry ownership and price. Whereas at the seed, it could be anything, very, very difficult to get something working. Once you do get something working, I believe these companies tend to be even greater and greater versions of themselves for a long time to come.

36:52And then I think the mistake that many venture capitalists have made is just not estimating the market to be as big as it is. I'm enjoying this so much. I have really three things I want to dig into there. You said about markets and underestimating size. Our dear friend Alex at Deal, I met him at the seed round and he told me about Deal. And I was like, dude, you're brilliant. The payroll. I'm sorry, brother. Deal and 11. I'm sorry. Fuck off. I didn't tell you about it. What's your next pass, please? Granola. Pre-seed. Go get my church. Granola, pre-seed. Okay. Well, yeah. Okay. Just keep them coming.

37:25Chris knows this. I sent a voice note to my partner saying, will someone please set up a JustGiving page for Chris because no one's going to invest. I will send you my next pass. Please. You know most investors when they send you the pass, you're like, wow. I look forward to your downturn traffic. Mine you should do. Yeah, 100%. Yeah. You said about market underestimation. I underestimated the payroll market. I thought Alex, I didn't underestimate him, but the market I did. What market did you underestimate, which you later realized you were wrong on, and what did you learn? It's such a good question about which market did we underestimate.

37:57I mean, I've made this mistake a couple of times. For example, I remember when we were acquired by Google, and I remember looking at the stock price and telling my co-founder, well, maybe this can go up 10 % or 15 % or 20 % or 30%. How much bigger can it possibly get? So if you look at a company like that, which was so capable but seemed dominant in their core market, it was very hard to squint and see what they would become. And they're so much more valuable than they once were. I think another interesting example of this is credit karma. You know, free credit scores for Americans. And I know the credit score is a much bigger concept in America than it is where I grew up in Canada or even here.

38:33I think you'd sort of ask yourself, if you did the back of the envelope, you would say, well, most people tend to use their credit score once or twice a year, right? And most people don't even actually need it that often. It's only when you're applying for a new financial product. And then for most people, you either have exceptional credit and you don't really need to look at it because you already know that, or you have terrible credit and you just don't want to look at it and you kind of already know that. So now you've got this torso of people who infrequently need access to their credit score.

39:00Is that really a big company? And if you then look at Credit Karma, you know, it's like over 100 million Americans use it. You've got 50 million quarterly actives. You've got people logging in on average four times a month. And the reason that it works is that the credit score is actually this sort of mirror that people like to look in and see how they're doing objectively as an adult. Whether you're doing great, whether you're doing poorly, whether you're doing just okay, people really find a lot of sort of satisfaction in the feedback loop of looking at their credit score. Not something that I ever would have predicted.

39:33And as a result, Credit Karma has many opportunities to sort of inform and sell their customers' products. And it really, really works. So how do you reflect on that, like missing that? I think when you have a formidable founder and they're showing a lot of early momentum in a market, inertia is the best mental model. In my mind, inertia is the most powerful force in the universe. So everything that is happening today is going to default happen forever. And when you have a formidable founder making tremendous nonlinear progress, you have to tiebreak in the direction of them doing it forever. That has to be your underwrite.

40:05So funny. Roy, you're just going to mention earlier. He says, when I found a continuously hits target, you should bet on them continuing to continuously hit target. Don't overthink this shit. It's hard to hit target. Well, this is, you know, I'll tell you a funny thing. So when I first started, I remember sitting, I spent a bunch of time with Mark and Dixon and everyone. So I remember sitting down with Mark and saying, all right, Mark, what's the process? Like, tell me exactly what the process is. You know, and Mark said this maddening thing, which is just be right a lot. And I was like, Mark, what is, of course be right a lot.

40:35But what else? What is, and of course, you know, there's a bunch of things that we talked about. talked about. But ultimately, having reflected on that, I think his view is like your process doesn't matter as long as you're consistently winning. When I started my career at Amazon as an engineer in 2003, they had a very similar thing. I think it's still a part of their kind of leadership principles, which is that you're consistently right. And I remember being 23 or 24 years old and just finding it to be maddening because like, well, why are you right? How are you right? But this quality of being right sort of supersedes the why or the how or all of our very intellectual mental models of how long I can sustain.

41:08And you said, like, just win and the importance of winning. What we said downstairs, I lost to a wonderful colleague of yours, Seema, in a company, Ask Leo, in Germany at the Series A. And I reflect on this a lot, a lot. I can tell it's on your mind. When you reflect, what was your most painful loss? And how do you reflect on that? I haven't lost a deal. You've never lost a deal? I've never lost a deal. How long have you been in Andreessen? Six and a half years. Huh. Yeah, yeah. Do you worry about that? I mean this in the nicest way. Like, you know, I asked Ram Pal about this because, you know, he lost the A of Rillit and then did the B, which is great and fantastic.

41:46Well done, him. But yeah, perhaps risk aperture is not high enough if you're never losing deals. Maybe. I don't know. Like, I think that there is a process by which you can be a part of most important companies that you want to be a part of. I think that there are some very difficult pre-existing conditions to overcome. Like somebody has a very healthy, successful relationship with a past investor. You're just never going to overcome that, right? And by the way, like having been that, I think, healthy and supportive past investor for many people, I would never expect those founders to go work with someone else.

42:15What do you do in those situations when they're like this? I love you, but I've known these guys for 10 years. They backed me before. Do you joke, hey, we're going to be the collaborative partner and try and nestle in now? or like we'll just peace out and not take part for this round? I think that there are no games to be played. And I think this is the magic of being in this business and being at Andreessen Horowitz. You know, when I started, I had this nervousness around like maybe it's a sales job. But I realized if you just sort of show up with the right intentions and like, you know, you have to assume that they know everything you know.

42:45Of course they do. We live in this era of very, very sophisticated individuals and founders. And you respect that and say like, look, I want to like respect the relationship that you have. With that said, our mission is to be a part of every important technology story that happens. If there's a way to be a part of it now, great. If not, let us get to know each other and earn the right to be your lead investor at the next round. And sometimes that's the right thing. How elastic will you be on ownership in order to win deals? Not very elastic. I try to explain what our model is, but I'm very elastic on price.

43:14I should probably be careful about saying that. My mental model is that below a certain threshold, the price doesn't matter. You just have to be a part. I want to learn from you. Yeah, yeah, well. Well, I mean, this is my mental model. No, no, no, it works. I've learned in venture, simply copy often works. Yeah, yeah. So, like, very elastic on price, and below a certain price, it doesn't really matter. What is that price? I mean, look, I think price starts to really matter once you're into the hundreds of millions. You know, and certainly at the stage that DG does, price does really matter. But I think at the early stage, let's say sub$100 million, like$50,$70,$100, even$120, The main way that price shows up is it may impair your ability to raise the next round because you price something so high.

43:57And we're very transparent about that. I'll tell a founder, look, you've got great metrics. We can do this Series A as 12 on 60, 15 on 75. 12 to 15, it's a little bit of a wash for us in terms of the check size that we're writing. And it's more about what expectations you want to sign up for at the next round. And look, the one thing that we typically don't flex a lot on is ownership because that is our whole model. And like the model of, hey, we're going to put all the chips in behind you doesn't work if we're not real partners. 200 versus 300. Yeah, I mean, it's in the margins. Again, I think a lot more at that sort of price threshold.

44:33I start to think a lot more about the next round than the absolute dollars in, right? The absolute dollars, again, for a sufficiently large fund probably aren't going to make or break the fund, but your ability to raise the next round, especially once you're in that growth territory, right? The$500 million round is a hard round. The difference between having to raise at 300, 500, and 700 is pretty significant. Do you think we're skipping that round? And what I mean by that is if you think about the companies that are raising at 100 to 200 with 1 to 3 million in revenue, say early signs of PMF, and then they're growing so fast that they're hitting 30 to 50 within 12 to 24 months.

45:09Well, then they raised a billion, and that 500 million tweener round is now gone. Yeah, look, I think that happens. And I think in the case where it's because core metrics are super healthy, like good for them. God bless, you know. I have a lot of enterprise SaaS companies that do double, double or triple, triple, double, double. Is the world of triple, triple, double, double dead? And do we all have to be lovable or up within 11 labs to get funded? I don't think so. I mean, I think that a lot of it is dependent. It's calibrated to your part of the market. So product velocity plus business velocity.

45:40I do think that you have to be top quartile compared to your peer set. I think there are some markets that are consumer lad or bottoms up where you can just see this explosive growth. And that is awesome. It's extraordinary to see. But look, if you're selling an ERP, you've got a much more cautious customer. It's a much more high stakes sale. If you're selling payroll now, granted in the case of payroll, Alex and team have done a tremendous job of what should be like a slow boil sale and turning it into a fast boil sale. And they've got some very specific ways that they do that. But typically, that is an industry that moves on slower cycles.

46:12So I think that there is just physics to some of these markets that mean triple, triple, double, double is phenomenal. But there are other markets in which, especially with these new primitives, you can go like 10 to 100 or 10 to 200. So you bring in triple, triple, double, double to partnership and they won't shit on it? Absolutely not. No, no. Again, I think that these are all heuristics that we use and we throw it around. First of all, I want to say like, I respect the difficulty of getting to a million in revenue, dude. It is so hard. Like getting anyone to pay you anything that's not a family member or a friend is hard.

46:43And then going from one to five or 10 is super hard. And 10 to 100 is tremendously hard. So one, I think that it's, I hate it when investors are very flip about this. And then two, no, look, I think it's all about the sort of assumptions that the founder is making, the data as a way to validate those assumptions and the kind of direction, the what if it works. What is the sort of direction of the curve? What's the area underneath it, right? Totally get you. And by the way, sorry to interrupt, there are companies that are area under the curve companies where it may be a much more complex sort of slower growth story, but the area under the curve is much more significant than companies that have very high slope, but potentially have challenges with defensibility.

47:22Super interesting. So you're saying that like the length of the start line, as Des Treynor at Intercom says, like it takes a very long time to build, like in Figma. And Figma for like three or four years was kind of in the build process. Yeah, area under the curve. And what do you have today with Figma? you have an end of one network effects product that, by the way, is sort of ahead of where I think the market is going in terms of moving from products focused on execution, which today are being subsumed by coding agents, to markets focused on thinking. And I think a lot of the thinking work is going to be done in products like Figma.

47:53I'm not sure that Dylan and team saw that 10 years ago, but I think they're well positioned today. Area under the curve, companies. How does the world change for them today? And do they still hold inherent value of fundraising early? How How does that change? Because it's difficult to sell. Yeah, I mean, I think the challenge for area under the curve companies is that, you know, you've got to have enough momentum that you can continue to fundraise. You've got to have enough substantiality that your customer loves you. They're willing to, like, pay you up front. They're willing to expand with you.

48:22So it has its own idiosyncrasies and difficulties. But I think often some of the most significant companies are these area under the curve companies. And they're, look, they're these, like, 20-year overnight success stories. And I think that those are underestimated in venture lore. The like one to 100 companies are extraordinary and we all love to be a part of them. But we may talk about those and lionize those perhaps sometimes at the expense of the area under the curve company. You said you very much focus on the Series A. We mentioned some of the pricing kind of differences there. I get in trouble with my team constantly for tweeting things and like, oh, Harry, you make my life so much harder.

48:56And I'm like, it's too easy otherwise. And I say that Series A is the hardest place to be investing right now because essentially you have a million in revenue, very little signs of product market fit, honestly, at a million in revenue. You're paying 100 to 200 XAR. It's incredibly competitive. Price to progress ratio is incredibly mismatched between a 25 million seed. Why am I wrong? Yeah. Well, OK. So first of all, I think as an investor, you have to decide what kind of risk you want to take. OK. So that is what we're paid to do. So let's talk through what are the different types of risk. So the first risk is one that you mentioned.

49:30That is competitive risk. Can I win this process or not? Okay. The second risk, and this is maybe a slightly less good risk to take, but I think still a fine one is pricing risk. Did I overpay? And again, I think the way that shows up is the difficulty of the next round based on your entry price, right? Maybe the third risk is team risk. Can this team actually go the distance? You know, can the company be, can they be big enough to fulfill the company's ambitions? because I think the founder themselves can attenuate or amplify a company's destiny, right? The company can't be bigger than their ability for it to be big, okay?

50:02The fourth one, I think, is a little bit of geographic risk. And maybe this is less true today, but like, is a Silicon Valley team going to do this? And the fifth is fundraising risk. This is a non-consensus deal that actually has no other investor interest around it. That is not to say that you need investor interest, but if the team has a difficult time fundraising, no matter how good they are at product and technology, they're not going to get the opportunity to see their vision through. So I think taking competitive risk, can I win, and pricing risk. When did you say, sorry, can I win? You were saying can I win as an investor winning the deal?

50:34Yes, against the other VCs. That is what we should do. That is the number one most important thing that we do, win the deals by building trust with the founders, being smart on the markets, being first to conviction, all of these things. And that's why I think the Series A being hard, it's supposed to be hard, and you should be winning anyway. A couple of questions on the back of that. We're seeing teams fall apart quicker than ever. They're leaving their startups fast than ever, having just raised big rounds to do new things. Are we seeing this increased promiscuity from founders, do you think?

51:02I mean, I think we've always had to assess how sort of authentic their connection is to the problem at hand, right? Because as it is, doing these startups is a little bit irrational. And Alex said this on the pod, and I think he's exactly right, which you have to be a little bit irrationally optimistic to do it. I think you also have to be irrationally interested in the domain in which you're working because these things get hot and cold all the time. And I think that that authenticity, which is not like a comment on intent, sometimes really well-intentioned people, I've been this person, have a reason that they're building their company other than authentic connection to the problem.

51:35I just don't think that's a good setup. That's a setup for promiscuity. Do you mind when someone comes in and says, listen, I don't have any particular interest in, I don't know, sales for car dealerships, but I saw it as a ripe area for innovation. and where models can be transformative. Do you mind that? I think there has to be some sort of irrational direction in which they're pointed. Maybe it's pure capitalism, you know? And they're like, look, I've studied the living shit of this market and it is a means to an end for me, but like I'm, you know, I'm going to get there or die trying. You need to see a little bit of that outlier sort of emotion and commitment.

52:11And I think it's best expressed when it's in the direction of the problem, but it doesn't have to be. I think if somebody comes in and they're like, I did a case study on it and it looks great. Like not a great setup. Do you find with the founders that you work with, the best founders are the best fundraisers? Or actually, can they be a bit quirky? Like are the best founders generally great fundraisers? I mean, look, I don't think they all have to show up the same stylistically. You know, the sort of like polished, you know, go to market oriented, whatever, like the type of founder we saw more often five years ago.

52:43I mean, the Kriya guys to me are a great example. They come into our first pitch, first meeting with everyone in the room, Thanksgiving holiday. And I think they're both wearing matching kimonos. They're both drinking Celsius. Victor's got his long skate hair. He's just this total badass who looks exactly the opposite of every MBA founder that we had been meeting five years ago. And he's got a quiet presence, and a lot of it comes from his command of the technology and the domain. It's a totally different style. It works really well for fundraising. So I think you do need to be able to fundraise and you can be very authentic in the way that you do it.

53:17In terms of having a command of technology, and you said earlier about the challenge of shipping products and getting from zero to one, showing that you've had a success building in the past is a great way to prove that you can do it moving forwards. Do you have an unreasonable or an unwavering leaning towards serial founders who've proven that they can do it because of their track? Yeah, I'll give you a nuanced take on this. So I think that repeat founders working in their domain of expertise are formidable. Like the Clutch guys sold a company to Carvana. You know, they weren't super happy with the way that the whole thing, you know, ended up in terms of their startup achieving their ambitions.

53:54They went and then started another company out of that also in the auto space called Clutch. It's going extraordinarily well. And they know, you know, they're taking all the shortcuts because they know the market. So I do think particularly in enterprise, working in the same domain and, you know, being a repeat entrepreneur is a huge source of alpha. But I actually think conversely in consumer, having a beginner's mind and a high willingness to be embarrassed is a competitive advantage. Because so many consumer products feel embarrassing. And, you know, they're immediately dismissed as embarrassing or impossible or a silly, non-serious thing to be working on.

54:27When you're 25 and, like, the stakes are low, you just want to make something happen in the world. That is a perfect setup. Once you've sold a company, all of a sudden it's like your venture friends are like, what are you working on? You know, like your girlfriend or your boyfriend is like, what are you working on? You want to sound cool at dinner parties or at the bar. And that slight hesitation to be embarrassed can sometimes hold you back from the most ambitious, interesting consumer ideas. I said earlier, you know, when the facts change, I change my mind. What about the way that you used to invest has changed most significantly?

54:57Well, I think the number one thing, and here's my free advice to other investors, but also founders, it's just like you have to use the products today more than ever. You know, and I think the investing landscape of five or seven years ago when there was a ton of fintech. And I'm a fintech guy. I love fintech. But it was harder to build intuition for a small business factoring solution. Like I'm not really, I don't know, maybe I should start a small business. There's too many steps to actually try the product. But today being native in this product cycle just means waking up every day and being like, if there's three new models today, I'm going to try three new models.

55:30I'm actually going to make something. So holding yourself to an incredibly high standard of trying everything just gives you so much information and intuition. I think it's non-negotiable for founders, and I think it's incredibly important for investors as well. Yet most don't do it. We say about trying product. I mean, 90 % of the companies that I get pitched today, especially on the application side, are agent-led or agent-first. You said before there might be agent overhype. Can you talk to me about this? Why do you feel there's agent overhype today, and what does that mean? Here's what I think.

56:00I think that the extremist view that we are going to have autonomous agents that simply do everything over incredibly long time horizons, like maybe we'll get there someday. But I do think that at a minimum, you need humans in the loop for exception handling. And then these models are only as good as the instructions that we give them. And our instructions, I mean, think about the way you manage your team. Your instructions are often frustratingly vague. So I do think that we need people in a tight loop with the models to actually achieve our objectives. And I think that the sort of agent maximalist view, which is, you know, you just like chill out for the day and your AI does everything you need to do is probably a little bit ahead of where we actually are.

56:39Do you take the view that agents won't remove tasks from what you do, but they'll enable you to do tasks that you didn't have time for? I think it's both. I think that they will do tasks. They'll do the low-end PS work that you don't want to do, right? Do the work that you want to do, not the work that you have to do. I think the second thing is, yes, like the surface area, the sort of circumference of ambition is going to go dramatically up for us as individuals, but also for us as a species. Harry, how can this be the peak expression of our ambition as a species? You know, you've read enough sci-fi books to like know, even have a glimmer of what that looks like.

57:11And I think that's a world that we're going to actually live in, which is if you are ambitious in a direction, you should be able to like fully chase it down and express and fulfill it. And the only question is like, who are the ones that are ambitious to go do things? Because I don't think execution or expertise is any longer a constraint. When we think about kind of those best place to win an agent first game, I had Eric from Podium on the show. We had a fascinating story of like a kind of traditional SaaS provider that's now got a hundred million dollar plus agent business. And he said that fundamentally, if you want to win in an agentic world, you have to own the tools, the workflow and the data.

57:45And so you have to kind of own the full stack, a la, of course, him and Salesforce. Do you agree that you have to own the stack to really be a big player? Or can you be a meta layer on top of a core provider? Yeah, I mean, I think that you can use a core provider via tool use. I mean, to me, the big question is just sort of ambiguity as one of the big sort of questions for how much leverage you get out of agents. So if you look at BPOs, business process outsourcing, they're the areas in which there's the least ambiguity, where the job is literally a series of tasks, where people in offshore call centers take a task off the queue.

58:21Those things are very well set up for sort of automation and agent replacement because you've got incredibly well-defined tasks and you've got jobs that are bundles of these well-defined tasks. I think there are many jobs in which there's just such a high degree of ambiguity. I mean, even in software development, like arguably the coding is the easy part. The tough thing is like, what are we coding today? And how do we adjust and how do we sort of adapt to what the customers are saying, what the market is saying, what our own epiphanies were overnight. The models are incredible at getting us into these local maximas.

58:52And sometimes the local maxima is the global maxima, but I think often it takes human intuition to break from the local to the global. And that is something I think the agent's just not going to do. You mentioned BPOs there. How do you think about the future of UiPath? They've had a tumultuous journey in the public markets. Is that one that's sadly suffering from this or actually are they well positioned to take advantage of distribution that they have? I wish I knew more about UiPath. I just don't know enough about the company to comment. I mean, I think RPA is super interesting, but vision models haven't nearly kept up with the sort of, you know, the way that we've talked about them.

59:24One thing that we haven't discussed, which I want to, is kind of open versus closed. It's a big question. A lot more use open than actually they say publicly, I find. And there's a lot more willingness than ever to use open. Open source? Yeah. How do you think about the distribution in terms of open versus closed and how that looks in the next kind of 24 months? That's a good question. So I don't think we're at a point in the cycle where companies are focused primarily on cost optimization. And I think that is one of the reasons to choose Open, you know, which is like get an open source model, host it, and then have a cost benefit as a result.

1:00:00I do think there has been some interesting properties of Open models like Kimi K2. You know, I believe that they didn't post-train it to sort of restrain what it could say. As a result, it was just a lot more interesting in terms of text generation in many directions. So it had this sort of interesting product characteristic that a bunch of companies built around, a bunch of companion companies in particular. So I think there are these idiosyncratic reasons we choose the open models for product quality. But in most cases, I think companies are thinking about maximizing the sort of direction of ambition and their ability to fulfill it versus taking cost out.

1:00:33And closed is still a bit advantaged there. Now, the nice thing about Closed is they, too, have been cutting their costs, right? So, granted, Closed is more expensive than Open in many cases, but the cost of actually a token on GPT-40 has gone down 100x since the model was released. You said that we're not in the period of cost optimization, which I agree and think is a very interesting point. Jason Lamkin said to me, he's a real builder with one of your tools, actually, with RapLit. I think he's literally at one of their top users. It's insane what an incredible power user he is. Amazing. But he uses 11 Labs as part of the voice for one of his games.

1:01:10Yeah. And he said, this will be the year where we see the true substitution of AI products based on price. He's at 11 Labs. I love it. It's amazing. Yeah. It's too expensive. It's too expensive. This is the year where we've moved from trying things to shit. It works. Yeah. But it's too expensive. No comment on 11 Labs. But do you agree that we're going to see this transition in mindset from shit at worst to shit it's expensive? I don't think so. Because I think what we keep seeing is as the models get better, downstream players' ability to take those capabilities, productize them, and raise prices has outstripped the raising costs.

1:01:47Right? So the incremental cost increase potentially, and in many cases not a cost increase, but it's not a cost decrease, is so far outweighed by what the new capability unlocks. Like coding agents, right? What you can do with coding agents, Cloud Code came out last February, is dramatically better. Is anybody here saying, well, I should go back and use Sonnet 3.7 because it's cheaper? Or I should use something other than Opus 4.5 or Codex 5.2? Nobody is saying that because the capability is so much more powerful. It really sparks your imagination in the other direction. What more can we do rather than how do we make the existing thing cheaper?

1:02:22It is interesting. I remember when he said he's got a startup game and he's like, dude, I'm terrified that people are going to use it because I'm going to go bankrupt. Okay, so this is actually a fun topic, which is that the fact that these products have costs are a very good thing. But what it means then is Jason's going to have to figure out his business model early. So this field of dreams investing where a company builds a free product and they're like, someday we'll figure out a business model. That's not viable. It's like, no, you have costs today the way that every small business in the history of small businesses has had pre-software.

1:02:55So the fact that these companies have costs actually forces a business model hygiene that I don't think existed across the board 10 years ago, and that's a good thing. If you were 11 Labs, would you not just say, fuck, subsidize, cut prices, own market, this is a land grab. Don't risk churn by price for the next year or two. They would just raise 500 million. They could have raised 5 billion more. I think there's so much more to be done at the frontier, and there's so many more categories and capabilities that those things unlock. It's just a better use of time. Today, again, we talked about 8 % to 12 % of enterprise spend is on SaaS.

1:03:30How much of consumer disposable income is spent on software today? A few hundred dollars a month, maybe? We're going to asymptote to 80 % to 90%, I believe, for consumer spend and enterprise spend. The way we do that is by pushing the frontier, not by... So 80 % to 90 % of consumer spend. The sort of discretionary spend. Of course, there's going to be rent and food. But yes, dude, I think that software is going to eclipse many parts of our discretionary spend. And we just talked about companionship and friendship. We talked about entertainment. We talked about potentially therapy, potentially health care, potentially professional, right?

1:04:04A lot of the spend that I do on things that help me be better at my profession, education. So there's a tremendous sort of area for software to expand into. Let's forget about taking costs out of things for now. I don't know if you're including food in that. Yeah. If you're including a door dash, then I can get on board with that. Discretionary. Non-discretionary spend is fair. And you're clearly not European because you missed one crucial one, which is fashion. Yeah, fashion. Which would not be that easy. I thought you were going to say wine. Dude, no one buys wine. No one drinks anymore. Okay.

1:04:34Tough to be in the wine industry. Not even the Europeans? No, not at all. It's super interesting. Do you agree with kingmaking today in terms of the belief that, you know, as I think you know, but like an anointed winner can be made. Do you think kingmaking is real? Let me comment in two ways. One, I think an example of where there is a very positive sort of catalyst in their investor base for enterprise companies is YC. YC is an awesome place to start an enterprise startup that sells to other enterprise startups. And they've got these sort of like good vibes within the community that makes it easier to sell into even much bigger, more established YC companies.

1:05:07So I think that's a good example in which picking the right investor is actually a big benefit. You know, a lot of what we do is connect companies that are small but have really important product and technology to the Fortune 500 and 2000. But we can't force them to buy that technology, right? And again, you have to assume that the buyers, especially these days, have perfect information. So I think that the right investor can be a catalyst. But I don't think that you can take a product that would not otherwise be the winner and anoint them the winner. Do you agree that the best founders you work with don't need their VCs?

1:05:38I think the best founders that I work with know how to maximally leverage their VCs. And look, I think there is a set of founders who perhaps would never need their investors. But I do think that the best founders know how to sort of extend their success and increase their momentum by leveraging the right investors. Like Alex does, right, dude? I mean, I basically have a sales quota with Alex, you know? And DG would say the same thing. And Ben, he's even calling Ben saying, hey, Ben, can you help make this introduction to XYZ? Like, he knows how to get the best out of Andreessen Horowitz. and all of the, it's not just the investors, the entire team shows up for him that way.

1:06:10Could he do it without us? Of course he could. What advice would you give then? We have so many founders that listen. What advice would you give to founders on how to have maximum value extraction from an investor base? Yeah, well, first pick an investor that does stuff, I think, number one. I think number two is - How do you know everyone says they do? Well, the best way is talk to other founders, right? You should talk to other founders. I think the second thing is, again, the VC can't distort the market, right? All they can do is make all the introductions. And I think the best thing, Mark talked about this, is when you're small, the VC sort of gives you power.

1:06:42That's what you want. The VC basically takes your brand, which is not big, and they lend you their brand. So you're not XYZ company. You're an Andreessen Horowitz company. Now, over time, your brand becomes much bigger than Andreessen Horowitz, and that is great. But they can help bootstrap you and create credibility in conversations. But you still have to have the best product technology go to market to go win the customer. Totally agree with that in terms of I think the list. lending of brands, I think is how you've described it before. It is phenomenally valuable. Can I ask you, when we think about kind of the lending of brands, who's the single best founder you work with?

1:07:15Alex is just such a beast in terms of his go-to-market instincts, his product creativity, and just his responsiveness. The guy's nuts, you know? Alex is 100 % working all the time. It's just incredible. I've got a fun story. We have Project Europe, which is like the Teal Fellowship for Europe, basically back 18-year-olds with a big dream and technical capability. Oh, yeah. Jane was telling me about this. Yeah, it's cool. It's amazing. Anyway, I pinged Alex on a Sunday morning, 7 a.m., saying, hey, they want an intro to a sales rep on your team. Who's the best person? He's like, intro to me, please.

1:07:47I'm like, dude, it's like a$1 ,000 deal. He's not worth your time. He's like, no, no, to alexatdeal.com. That's what I mean. Yeah. Yeah. He's so impressive. But look, there are other founders who have specialists in their domain, like the Clutch guys I mentioned, who are deep technologists and know how to apply to product like CREA or the Happy Robot team. So there's just so much to learn from all these individuals. And I know it sounds trite, but I'm privileged to work with them. No, the Happy Robot guys, I wish I was invested in that too. They're amazing, man. Please don't tell me you passed on that at the seed too.

1:08:18No, no, I didn't. I never met them. Thank God. Okay, good, good, good. No, no. That's one of those ones where it's one like I wish I was in it, but I never had the chance to be here. They're wonderful. Yeah. Incredible technologists, really earnest people, and they're seeing a ton of success. When you reflect on companies or investments that you've made that were not good, what did you not see? If there's a mistake that I've made, it's been being a bit too casual about product market fit. And this was more of a 2021 mistake, which is assuming something had product market fit, and perhaps it didn't.

1:08:50And perhaps the founder had a super credible theory, which, by the way, matched my theory for why it would get to product market fit. But as I said, it's easy to overestimate the sort of path from zero to one. And I'd say if there was a sort of mistake I made, it was not being intellectually honest about, is this actually working? Or do I think it will work in the near future? Now, look, I've done a bunch of seed investing, and I've made the bet. And I think if you're intellectually honest and sort of clear-sighted about a belief that it will work, then that's a fine way to invest. But investing with a sort of self-deception of like, well, let's just assume it's working when it's not quite working is a mistake.

1:09:24I think you know a good investment or a bad investment in the first three months. Do you agree? There are moments when you win a deal and you are just, you're like, you know, the feeling is like sheer relief. And I'm sure that there are moments, I haven't experienced this thankfully, when you win a deal and you're like, wow, I won it. And you're sort of faced with uncertainty. And I think the sort of psychology of that latter moment is very telling. Have you ever felt that the Andreessen brand holds you back in any way? Like maybe with a, no? No, not one bit. It's a massive tailwind in a lot. There's never been one where there's like been a political question.

1:10:03Not at all, no. And Mark and Ben are so special and authentic. And look, what Ben has said many times is that they sort of, you know, feel like it's their responsibility to kind of extend the surface area of the entire industry. And like I see them do that every single day. So no, I'd like, there's never been even a moment at which it held me back. In fact, it's been just the opposite. I could talk to you all day. I do want to do a quick fire round with you. Okay, are you ready for this? Okay. What's the most memorable first founder meeting that you had? It doesn't have to be like the best founder, but the most memorable first founder meeting you had and why?

1:10:36I mean, yeah, so it's probably the guys at CREA. Just because, you know, they'd been so mysterious. We'd been unable to get a hold of them for nine months. They'd been making all this noise on X with their sort of creative tools and their models. And, you know, there's so much anticipation meeting them. It was Thanksgiving week. We all sort of flew in. Mark was there. And just to see these two guys walk in, total badasses, with their matching kimonos, with their Celsius drinks, and just hold the room by being these deep, authentic technologists and product people, it's just not something that I'd seen before.

1:11:08And there was so much of a setup to the meeting that it's what I'll never forget. Mark, Ben, DG, who's the best investor? I mean, they're all extraordinary. Yeah, let me tell you the strengths. So like Mark is the guy that can just tell you, one, he'll paint a picture of the future, but two, he knows everything about everything else outside of technology. He's read every book. He's memorized them all. He's got these incredible stories. Of course, he invented the consumer internet. So he is just, his storytelling ability is extraordinary. Then, like, to me, I mean, Hard Things was the first honest business book.

1:11:42Okay, and I always say about business books, like, the business model of business books is selling business books. It's not making you better. Most business books are full of shit, and Hard Things is the first one that was, like, authentic. And if you've read it as a founder, you're like, oh, my God, somebody finally sees me. So just his sort of stories of wartime and navigating these inflection points and his ability to contextualize that for whatever you're going through, totally unmatched. The thing about DG that's so special is a lot of us are sort of these founder investors. We are like learning how to be investors through the lens of being a founder.

1:12:15DG is a pure and highly, highly seasoned investor. he has this sort of pure play investor clarity that I tend to learn a ton from. He, to me, is so, so interesting at the growth stage in the same way that Dixon is interesting at the early stage. So much of our best thinking is Dixon and also DG. What's been the hardest decision that you've had to make in the last two to three years? I mean, to me, a big decision was coming into investing and not being a sort of hands-on builder anymore. I wasn't sure because I'd, you know, I've had some incredible investors. I've had some investors that, you know, just weren't the best.

1:12:52And sometimes through no fault of their own, sometimes they're sort of early career. And sometimes, you know, they just were disengaged in a way that I never wanted to be. So I was uncertain about whether I wanted to move into investing. And I remember sitting down with Ben, you know, who was I to ask Ben questions? But I'm like, well, I guess like I'm not sure anyway. So let me just be direct with Ben. I'm like, well, Ben, how do you prevent bad behavior? You know, investor bad, but how do you prevent the sort of high anxiety? How do you prevent, you know, the person that's disengaged? And he's like, well, in the near term, we don't measure you based on returns.

1:13:24We measure you by going and talking to every one of your founders every two years, doing a 360 on you. And if your founders say you're telling them the truth, you're showing up, you're doing the work, you're being responsive, regardless of how those companies are performing, then you're doing a great job. If your founders say anything other than that, regardless of how the companies are performing, like you're looking for a job elsewhere. And by the way, we do those. We do these GP360s every two years. It's always a little terrifying, but the incentives are all structured in the right way. And that moment in the answer to that question was at which I knew like, hey, this is not a VC like every other VC I've seen out there.

1:13:59This is like a company. I remember someone from Andreessen telling me, and I'll keep, I can't actually remember who it is. I'm not actually being deliberately coined. It might've been Brian. It might've been DG. It might've been Alex. I really can't remember. But they said like, hey, I'm sorry. And as they said, in Andreessen, it's totally unacceptable to lose a deal, but it's very acceptable to not have seen it and it'd be great. Is that fair? To not have seen it? Like, random company does very well. We never met them. We never had the chance to meet them. I don't think so. I don't think we're allowed to believe in luck at Andreessen.

1:14:32We have to see 100 % of the deals in our domain. I think it is acceptable to make a decision based on the information you have and have the decision be wrong. Like you invest in a company, it doesn't always work. And that's okay. That's the business. But the expectation is we see 100 % of the deals in our sector and that we win 100 % of the deals that we go after. That was very clear. There was no... No, I love it, Dave. Okay, good. Good, right. That conversation. Sorry to scare you, Dave. Hey, look, some things are ambiguous, but that part is not. No, no nuance. Good. I hate nuance. It depends.

1:15:07It's the worst answer. But you can invest in one seed firm. Which seed firm do you invest in? All right. I think Brompton is pretty special at what he does, actually, at Abstract. I agree. Why? Yeah. I mean, one, he's a cold-blooded capitalist, which is awesome. He just has great instincts. And I think to me, the seed stage is the hardest stage at which to invest. Because it's easy to make one great seed investment. But it's hard to have a system, I think, for doing great seed investing. because there is, even when the people are amazing, there just isn't anything there yet. There is no product, the true seed.

1:15:43There's no product and there's no go to market yet. A post-product pretraction, that gets easier. Post-product, post-subtraction, that gets a lot easier. And I call that a series A. But at the true seed, it's just hard to be right a lot. And he has consistently been right a lot. So when I sort of look at a seed manager I respect, I don't know exactly what his witchcraft is, but it's working. He's right a lot. What have you changed your mind on most in the last 12 months? I think the thing that surprised me about this product cycle, you know, I was building my first company in the mobile product cycle.

1:16:14And in the mobile product cycle, the sort of like the anointed winners in 2008, 2009 were not the eventual winners. So we had the cycle where you sort of had the friendsters and then two or three years later you had the Facebooks, right? In this product cycle, what's actually interesting is a bunch of the early leaders from 23 and 24 have maintained their lead. We talked about Harvey. That's a really impressive company. Gamma is a really impressive company. Cursor is a really impressive company. The companies that were early have so far continued to actually be dominant. And that's something that I've sort of changed my mind on.

1:16:48I think in 26, we're going to see a whole new set of categories. Can I share my view on where we are on the market? I think that late 22, November 22 is ChatGPT. 23, a lot of the kind of obviously good ideas, and that's not to denigrate them, they were obviously good were started in some of 24. In the end of 24, reasoning models started working. So even the ideas that were obviously good but not working, suddenly many of them suddenly started working with the advent of 01 and DeepSeek. 25, those companies scaled. So now we are starting to see for existing markets, which is like customer support and the evolution of that, chat, creative tools, code.

1:17:22we have these early leaders. Those markets are somewhat established. It's going to be very hard to be like another customer support or coding tool today. Conversely, we're going to see a set of AI native categories, I think emerge in 2026. Knowing what we all know now, what company would you build? That is the operative question. And OpenClaw and Moldbook are just the beginning of that. Like those are ideas that were inconceivable two years ago. So I think that the thing that I learned over the last 18 months is like, hey, maybe the early leaders will just be the leaders. And over the next 12 months, I'm going to pay a lot of attention to who the early leaders are in the sort of new native categories.

1:17:57How significant is Maltbook? Everyone's very excited by it. You're a lot more product-centric than me. How significant is this? I mean, it's just so damn cool. Just to talk about it, to observe it, it's shallow. And, you know, Balaji called it robot dogs barking at each other. And I think that there's an element of truth to that, right? any humanity they have is just the sort of sparks of the humanity that it's taken from the context of its owners. I think, though, what is very interesting is the idea that we can have these digital twins, you know, these echoes of ourselves going and interacting with other people.

1:18:31I mean, you could, we were talking about dating downstairs, right, and sort of how the dating apps are a mess and probably not durable in their model. Like, you could imagine a world in which I train, I'm married, but, you know, if I was not, I'd train a little digital twin of myself, and other people would do the same and they would go have, you know, pseudo dates. And then they would come back and match make us and say like, hey, we had this like virtual date and it went kind of well and maybe you guys should hang in person. So now we're able to kind of replicate and scale ourselves in a way that was totally science fiction five years ago, one year ago.

1:19:02I don't know if you've seen match.com today, but the stock price is down like a huge amount because someone basically did this UGC. Oh, yeah. Yes. Yeah. Yeah. Yeah. The hinge thing. Yeah. That's tough. Yeah, so I think that, like, you know, Karpathy said that people are looking at the point and they say that we're overhyping it, but they're not looking at the slope, which is being underhyped. And I think that's correct, right? The point, Moldbook as an individual data point is probably overhyped right now, but what it points at directionally is underhyped. Next 10 years, final one. What excites you most?

1:19:34I like optimism. What are you most optimistic for and excited about? Oh, my God, dude. I mean, where do I start, right? Like robots, pet robots. So specifically like actually medical, I think we'll have amazing breakthroughs in treatments like multiple cirrhosis, which my mom has, which has previously been like, oh, like bad luck. I think we'll have real breakthroughs there, which is super exciting for me. Yeah. Okay. Well, let me tell you something personal to myself, which is I'm a longtime transcendental meditation person. I've been meditating since I was a little kid, 25, 30 years. And it like brings me this, you know, this peace and joy that maybe you see a little bit of my personality.

1:20:12and I think that the idea that everybody could have a little slice of that peace and joy is something that is now becoming more and more possible because I think that with the technology we have, it's going to take away a lot of the rote parts of life. It's going to give people access to more of these types of relationships that they find so fulfilling. So I think just the kind of the NPS of the human experience, for lack of a better phrase, is on the way up and like I love that for my fellow person. That's what I'm excited about. Dude, it's such a pleasure to do this in person. Thank you so much for sitting down with me.

1:20:42I really enjoyed it. Sorry I'm a little loopy. I can't tell if it's 3 a.m. or 3 p.m. But before we leave you today, over 80 % of Fortune 100 companies are running their businesses with Airtable. Airtable combines AI with the scale of an award-winning, infinitely flexible no-code system, a platform where you can see all of your data in one place and use it to make really big picture decisions. Think of it like mission control for your company. Airtable goes beyond organization and automating repetitive tasks. It lets you use your data to inform strategy, monitor progress, and take action. Every cell is capable of performing hundreds of AI-powered tasks like web research or localization and using those results to inform and update hundreds or thousands of other cells and workflows in real time.

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