Anish Acharya: Is SaaS Dead in a World of AI?

In this episode from 20VC, Harry Stebbings talks with Anish Acharya, general partner at a16z, about the future of SaaS in an AI world. Anish argues that software is completely oversold and that the general story about vibe coding everything is flat wrong. They discuss why SaaS switching costs are actually going down thanks to coding agents, where startups versus incumbents will win, and whether the apps layer or foundation models will capture more value. They also cover agent overhype, the changing UI paradigm, what defensibility looks like now, and why boring wins versus weird wins in this product cycle.

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

• 0:00Anish Acharya?

  You have this innovation bazooka with these models. Why would you point it at rebuilding payroll or ERP or CRM? The general story that we're going to vibe code everything is flat wrong and the whole market is oversold software. Now, an interesting topic that's not discussed is the cost of transitioning from one SaaS provider to another going dramatically down. So, systems integration. I don't think we're allowed to believe in luck at Andreessen. We have to see 100% of the deals in our domain and that we win 100% of the deals that we go after.

• 0:29Erik Torenberg?

  There's a popular narrative right now that SaaS is dead. AI is going to vibe code everything. The incumbents are toast. Anish Acharya thinks that framing misses the bigger picture. If you look at IT spend, it's 8 to 12% of enterprise budgets. You have this innovation bazooka with AI models. Why would you point it at rebuilding payroll or ERP when you could use it to extend your core advantage or go after the other 90% of spend? What is changing? Switching costs. Coding agents are making it dramatically easier to move from one provider to another. That's a positive incentive for the entire ecosystem. More competition, better products, more innovation. In this episode from 20 VC, Harry Stebbings talks with Anish Acharya, general partner at a 16Z,

• 1:12Erik Torenberg?

  about the future of SaaS, where startups versus incumbents will win and why the apps layer is underhyped.

• 1:21Speaker 02

  Anish, dude, I've wanted to do this for a while. We've been going back and forth.

• 1:23Anish Acharya?

  Yes, we have.

• 1:24Speaker 02

  And so I'm so glad that we can do this in person. Thank you for joining me.

• 1:27Anish Acharya?

  Of course. Thank you for having me.

• 1:28Speaker 02

  I'm diving right in. We were just chatting now and I was saying, I think it's better to build in London than in SF. Where in other places other than SF, talent is cheaper, it retains for longer. You don't have the promiscuity of people jumping from role to role.

• 1:42Anish Acharya?

  Yes.

• 1:43Speaker 02

  And you've built a company now, both in Canada and in SF.

• 1:47Anish Acharya?

  Uh huh.

• 1:48Speaker 02

  How do you reflect on what I just said?

• 1:51Anish Acharya?

  I disagree with you. I wish it was true. I simply wish it was true and I want it to be true and maybe it will be true that it will be, you know, the whole thing that we always love to say to ourselves around sort of talent and opportunity not being, you know, talent is equally distributed, opportunity is not. The truth is that cities are the original network effect. And for technology, there is a network effect for builders in SF and for this moment in technology, right? Where so many of the secrets are these sort of things whispered down shadowy hallways, the benefit of being in SF is enormous. There's also, we just talked about this, there's a selection bias question. Do you care enough to make it happen in SF? You can make it happen anywhere, New York, London, Toronto, Tel Aviv, you name it. But there's something different about saying, I'm going to give

• 2:34Anish Acharya?

  everything else up and be singular in my focus and move everything to SF to make it happen.

• 2:38Speaker 02

  Are there any other locations where you think there is actually positivity associated with there being located there?

• 2:46Anish Acharya?

  Tel Aviv. I think Tel Aviv, you can be incredibly ambitious and uncompromising on that ambition and have a really, really good reason to be there. I think the other nice thing about the Tel Aviv ecosystem is that the country's so small, it's 10 million people, that you can't possibly fool yourself into thinking that the domestic market is going to be big enough for whatever you're doing. So you immediately go outside. Whereas if you're in London, there's 60 million people here. Okay. And you might say, well, that's actually a lot of people. And you know what? There are parts of the market like fintech where the LTVs are so high that perhaps 60 million is sufficient. But for most mass market products, it's just not sufficient. And if you end up starting focused on the domestic market, it's often hard to actually move on to a bigger market. So there are all of these reasons that it's just, it's not that it can't be done. And there are

• 3:30Anish Acharya?

  incredible counter examples like 11. But I do think that it's just that much easier in SF and that's why that's where I focus.

• 3:37Speaker 02

  You said the word sufficient there. Yes, you can build a sufficient sized business, say in the UK, a three to five billion dollar business, say, is an example. Respectfully, when we look at companies being created today, three to five billion dollars just doesn't seem like it's interesting enough. Has the world of venture changed so significantly on what is sufficient for a venture outcome?

• 4:00Anish Acharya?

  I mean, three to five billion is an extraordinary outcome. Don't get me wrong. So in no way, no way am I minimizing that. And look, I do think that those types of venture outcomes stack to create really meaningful funds. So this is not about working backwards from venture economics. But the biggest companies in the world today are trillion dollar companies. If you want to build a trillion dollar company, if that's your intention, you've sort of got to start with a set of assumptions that can lead to that. If your intention is to build an extraordinary enterprise and you build a three to five billion dollar enterprise, like you are one of the few people in the world.

• 4:33Speaker 02

  When we say about those three to five billion dollar companies,

• 4:36Anish Acharya?

  Yes.

• 4:36Speaker 02

  Yeah, I mean, I heard a brilliant statement, which is the SaaSica, the massacre of SaaS companies that's going on in kind of the public markets today. And when we look at it, essentially investors are no longer confident that traditional enterprise revenue is sticky or durable. Are they right to question whether traditional enterprise revenue is sticky and durable?

• 4:59Anish Acharya?

  I think software is completely oversold. I think it's a silly story. I heard it called SaaSocalypse today. It's very funny. Bloomberg is trying to get that to stick. Look, if you look at SaaS spend today, if you look at IT spend overall, it's eight to 12% of enterprise spend. Okay. So even if you vibe coded your ERP and your payroll with all the kind of risks and dangers that that entails, you're going to save eight to 12%. You have this innovation bazooka with these models. Why would you point it at rebuilding payroll or ERP or CRM? Right, you're going to take it and use it to extend your core advantage as a business or are you going to take it to optimize the other 90% that you're not spending on software today? So I just think that of course there will be secular losers. There are like specific business models that are now going to be disadvantaged.

• 5:44Anish Acharya?

  But I think the general story that we're going to vibe code everything is flat wrong and the whole market is oversold software.

• 5:50Speaker 02

  Okay, and so we are actually overly negative and we are being too critical on these companies. How do we think about then the continuing negative growth that we've seen in a lot of these companies? The continuing seat contractions in a lot of your, say, CRM providers or Mondays of the world?

• 6:06Anish Acharya?

  Well, I don't know if that's what we're seeing across the board. Like, I looked at the data this morning, and if you look at SaaS, public market SaaS companies, seventy-five percent have raised prices since ChatGPT was released, seventy-five percent. And they've raised prices meaningfully. The mean is eight to twelve percent, but there's a large group that have raised it twenty-five percent or more.

• 6:25Speaker 02

  Is that not because they have to, because they're not growing seat count, and so they have to grow revenue count?

• 6:29Anish Acharya?

  Price is a measure of product market fit, right? And if you have enormous competitive pressure, you are not raising prices, you're typically cutting prices. So I think, one, you've got this sort of, you know, this dissonant fact that prices are going up, right? Two, if you look at the incumbents today, like ServiceNow is not IBM. They're a highly capable incumbent. They just went public and they raised guidance. So I think it's very easy to look at these things and say incumbents, incumbents, incumbents. Like, again, like, they're not seers. They're very, very capable, and I think they actually have a right to win and deploy technology in the context of these workflows. Now, will there be disruption? Of course, we've talked a bunch about, you know, companies that can now, that were once priced on seats,

• 7:11Anish Acharya?

  which are now going to be priced on outcomes, and like, that is going to be a big drag. But I think for the majority of SaaS, it has so little upside in being rewritten and vibe-coded and so much downside. Why would you do it? Now, an interesting topic that's not discussed is the, uh, the cost of transitioning from one SaaS provider to another going dramatically down. So systems integration. If you and Alex said this funny thing, and I know you laughed and I laughed too, which is that, like, some companies have hostages, not customers.

• 7:38Speaker 02

  Yeah, I love this statement.

• 7:39Anish Acharya?

  I love it too. And if you actually have, you know, an SAP system, you are a hostage of SAP, and they need to do nothing after they win you as a customer, except the bare minimum. If you want to switch to Oracle, oh my God, that's like a multi-year high risk. It's probably going to fail and you're probably going to get fired. It doesn't happen. But now with coding agents, the complexity of transitioning from SAP to Oracle is dramatically lower, the speed, the risk. So that is how I think coding agents shows up in enterprise software, especially amongst public names. Decreased switching costs, more customers, less hostages, which is a positive incentive for the entire ecosystem.

• 8:13Speaker 02

  You mentioned it's from PEL. I actually. Sounds super weird. I actually think about Alex every day.

• 8:20Anish Acharya?

  I do too.

• 8:20Speaker 02

  Yeah, well, there we go. Because he says the most brilliant thing, which is, and I'm going to butcher it slightly, but you know, will the incumbent incumbent acquire innovation before the startup acquires distribution?

• 8:31Anish Acharya?

  That's right, yeah.

• 8:32Speaker 02

  How do you think about who wins in this world? The public SaaS company who has distribution, be it a HubSpot or a Salesforce who has millions of customers?

• 8:41Anish Acharya?

  Yeah.

• 8:42Speaker 02

  Or is it actually the startup who has speed, agility and incredible engineers?

• 8:48Anish Acharya?

  So if history is any guide, and you know, to reference Alex, he would say that it often is, you know, those who have actually studied history tend to do better than those who have not. And what I would say is that when you have this product cycle and you have a capable incumbent, what happens is they usually make their product better for their existing categories. So Microsoft will make a better word processor than they've ever made. Google will make a better search engine than they've ever made. And we're actually starting to see that, some of that anyway. What you instead see is the native categories that did not exist before the product cycle being owned by startups. So I think that's a little bit of what we're going to see. You know, if you said something like, yeah, you know, software movies or AI movie making, or a sort of AI assisted movies, that's just not a category in which there is an incumbent.

• 9:32Anish Acharya?

  And I'm betting that a native company will actually win that. It probably won't be Adobe. Will Adobe make a better sort of Photoshop and Illustrator than ever before? Probably, right?

• 9:41Speaker 02

  You said there about kind of native being an opportunity. In terms of like kind of where opportunity sits in the stack, why do you think the application layer will create more value than the foundation models?

• 9:51Anish Acharya?

  I don't know if it'll create more value, but I think that it is under discussed how much value it's going to create. Right? If you think of what the models are, so if we lived in a world and, you know, we were actually thinking about this a lot in 2022 and late, early 2023, which is if you had a single foundation model company, which at the time was OpenAI, which was a whole generation ahead, right? Then they essentially were this unique supplier to everybody downstream in the innovation ecosystem. And they could do what you would do if you, for example, you know, controlled the Beatles and you're the only record label that had the Beatles. Like, it's like, do you want the Beatles or not? You can charge 99% of your customers. Gross margin and you do and you actually tend to charge a hundred or a hundred and ten percent. So that actually was a big risk to the ecosystem. What has instead happened is we have all these foundation model providers.

• 10:36Anish Acharya?

  They're all innovating roughly in lockstep. Eighty percent of what they do, I think that they're actually substitutes for. And then there's the open source models, which also do the same things. And then in the twenty percent, which arguably is where a lot of the value is, they are all specialists. So because you live in this world of multi-model where for some use cases are substitutes, for some use cases, they're actually specialists. There's a lot of value in having an aggregation layer and that is the apps company. So let me tell you two categories specifically. One is coding. I think that if you actually look at coding, you might know that Gemini is great for front end. Codex is great for backend, right? If you're vibe coding your project, you probably want to use both and you don't want to switch between two CLI's all the time. It's just a pain. So being able to use cursor as a single way to orchestrate all the models is valuable.

• 11:21Anish Acharya?

  Similarly, for creative tools, right? We're seeing this specialization, fragmentation, specialization. Midjourney and Crea with their Crea one model, these are the most aesthetically opinionated models, right? They create this credible, beautiful imagery. Conversely, if you look at Ideogram, Ideogram is often used by graphic designers. It is intentionally not opinionated from an aesthetic perspective. If you're somebody who's working as a creative at a big company, sometimes you're doing graphic design and sometimes you're just doing beautiful photography for print ads. You want to actually have access to both and to do that, you use an apps company.

• 11:53Speaker 02

  So I think we massively overestimate the durability of revenue of AI companies more broadly as well. I think there's a chance that Curse loses half of their revenue this year with the cannibalization of them by Claw Code. I don't know anyone who's not moved to Claw Code. When I hear that someone's still on Curse, I'm like, wow.

• 12:10Anish Acharya?

  Yeah, I think the thing that we are underappreciating is that we assume, you know, efficiency is increasing, but ambition and number of customers is staying fixed. I think this is one of the. Incorrect assumptions that keeps getting made around AI. It's like, well, what are all the people going to do? Where will all the jobs be? You know, it's like our ability to be ambitious for wanting more things always grows so much faster than our means. And in the same way, if you look at software, the desire and demand for software, both to make it and to consume it, is dramatically more than the supply that we have today. And I think there is a developer and developer adjacent archetype for whom Cursor is going to be perfect, Codex as an app, Codex as a CLI, Quadcode, like all of these products are going to find market fit and all grow.

• 12:55Anish Acharya?

  And if you look at any of the other markets like Creative Tools, they're going to specialize and fragment in their own directions.

• 13:01Speaker 02

  So when you think about market composition for that market and that kind of developer tooling space, does that look more like cloud? Or does that look more like Uber and Lyft?

• 13:13Anish Acharya?

  I don't think it looks like Uber and Lyft. I think Uber and Lyft are, to my mind, the most extreme examples of pure substitutes. And a lot of the sort of price has been competed away. You look at cloud, you sort of have this oligopoly where they all actually have pretty reasonable margins, right? And you can squint and say, of course, they have their specializations, but they're roughly substitutes and yet they've all done well. I think the foundation model companies look a little bit like that. And I think in the app layer, you're just going to have people that want to consume the code they generate through a rich IDE and those that want to be closer to the metal. And that's probably closer to AWS, Google Cloud than it is Uber Lyft.

• 13:49Speaker 02

  So when we think about that, I think,

• 13:54Speaker 02

  how do you think about competitive investing? Like, it seems to me like it doesn't matter anymore. But when I started, it was a big problem. You didn't invest in competitors. Now everyone is investing in competitors.

• 14:06Anish Acharya?

  Yeah.

• 14:07Speaker 02

  Are we in a world where that no longer matters?

• 14:09Anish Acharya?

  I mean, when you think about a firm that's organized the way we are, which is we actually do stuff for our companies, it becomes very difficult to invest in directly competing companies because then you've got, you know, the same resources, the same sort of Fortune 500 buyer, the same engineer that both companies want to hire. And I just like, I don't think we can run our business by investing in directly competing companies. Now, with that said, I think we're in a part of the market where companies are diverging very rapidly. So even companies that appear to be directly competing today. Tend to be not competing in 12 months, 18 months.

• 14:44Speaker 02

  Going back just before to you said about the opportunity in the apps layer. When we think about that, one threat that's often posed to the apps layer is the models themselves providing products. Whether it's OpenAI focusing on health now a lot, or whether it's Claude Code. Or I saw Anthropic do some Claude attachment to legal yesterday. To what extent is models invading the apps layer a credible threat to the verticalization of apps?

• 15:10Anish Acharya?

  Yeah, so this is such an interesting topic. So Granola, which we're not investors in, but I admire them a great deal. It's a great company. They've built a really interesting thing and they're first, of course, to live meeting recording and transcription, which is awesome. They have been copied to the moon, right? Now, everybody has a meeting transcription feature. OpenAI released one within ChatGPT. Very cool. The thing about Granola, and I assume this is true, is that their vision is not to be a meeting transcription product. I assume it's to be a productivity suite, right? They're going to build Word and Docs and spreadsheet and all of these other products around that core primitive. Does OpenAI have the sort of prioritization, the resources and the ambition in that direction? To build all the feature surface around the primitive?

• 15:52Anish Acharya?

  So I think the models will often actually recreate the primitive and even do product marketing, which I think the Claude legal stuff was. But if you have a market that demands a lot of feature surface, I just think the model companies are less set up to prioritize it.

• 16:06Speaker 02

  Do you not think if bundled into an existing solution with 80% of the features, the majority of people just go, ah, fuck it?

• 16:13Anish Acharya?

  Perhaps, I just think that the model companies have ambitions in so many directions. It is hard for them to prioritize building opinionated UIs for the legal community. I also think in many of these categories, again, being multimodal is important. And OpenAI is only going to ever give you OpenAI models, right? Anthropic is only going to give you their models, same with Google. So if you are multimodal, rich feature surface, I think being an apps company is better.

• 16:36Speaker 02

  Boring wins is a statement that you said to me before when we were talking about kind of apps layers and where value will accrue.

• 16:43Anish Acharya?

  Huh.

• 16:43Speaker 02

  What do you mean by boring wins? And how does that translate to the next generation of iconic companies?

• 16:48Anish Acharya?

  Oh, did I say boring wins?

• 16:49Speaker 02

  Yeah.

• 16:50Anish Acharya?

  Oh, well, let me make the sort of exact opposite case. I think weird wins.

• 16:53Speaker 02

  Huh.

• 16:54Anish Acharya?

  Yeah, so I mean, here is something that's actually very interesting, which is the nature of these models is very different than the nature of any technology we've had before. I'd say a lot of the technology we've had before, it's quantitative, it's sort of clinical, it can do incredible things, but it's sort of bounded in the range of, you know, feelings that it can sort of capture. Now we have this wild, non-predictable, emotional, very human technology, and sometimes it gets pointed in these directions that are very human, but perhaps uncomfortable to a big corporation, right? What is the human experience? It often involves disagreement, persuasion, sexuality, and we see that mirrored in some of these AI products.

• 17:37Anish Acharya?

  Yet if you're Google or Apple, you have a thousand committees that are explicitly designed to ensure there is never any persuasion, disagreement, or sexuality expressed in your products. So I think that there is a pocket that startups can really thrive in, which is building these weird products that really touch on many core aspects of humanity that the models can reflect, but the big corporations are uncomfortable.

• 17:59Speaker 02

  What's an example?

• 18:00Anish Acharya?

  To release. I mean, everything in companionship, right? Every product in companionship has been, you know, both well-received by customers and a little uncomfortable for the labs to build, perhaps modular.

• 18:12Speaker 02

  I'm sorry, when you say companionship, you're saying like?

• 18:14Anish Acharya?

  Character, but also janitor, right? There's a ton of products that are there for, you know, replica, which is probably the, you know, one of the most like healthy and nourishing forms of companionship. But all of these products are there, and they're there to facilitate friendships between people and technology. And a lot of that stuff is just uncomfortable for big tech to do.

• 18:33Speaker 02

  Would you encourage your children to use them?

• 18:36Anish Acharya?

  Absolutely. In fact, one of the products that I would love to exist, my request for startup, is what I call a contextual companion for my son who plays Minecraft. My son plays Minecraft, he plays it online, he absolutely loves it. You know, the like, the other kids playing Minecraft may or may not be the best influence, often not the best influence. I'd love to actually have an AI companion play Minecraft with them. So there's this context in which they interact. And I don't know, just sort of models pro-social behaviors and is still cool and chill. I think there's a lot of room for teaching through these types of relationships and technology can help provide that.

• 19:09Speaker 02

  Do you not think that it engenders or removes the ability to interact with other humans and makes people even more withdrawn or used to building a relationship with technology?

• 19:20Anish Acharya?

  Yeah.

• 19:21Speaker 02

  Than we already have?

• 19:22Anish Acharya?

  I think it does the exact opposite. I think people are able to be more self-reflective and explore aspects of themselves and human relationships that they often just don't have another person to explore these things with. And I think, you know, if you're wealthy and perhaps educated, you know, maybe you're interested in therapy and that's like an outlet for it. Or if you are like you and I and you've got this embarrassment of social riches and you have all these people that want to hang out with you and you go to these dinners where you stay up late, having all these philosophical conversations. Or perhaps if you're one of the relative minority today that is spiritual or religious in some way and it's very, you know, emotionally nourishing to you. Like, there are directions in which we can explore these things, but I think for the majority of our society today, they just don't have an outlet. And I do think technology can be that outlet.

• 20:09Speaker 02

  I like the idea. I also like it, especially when you think about the amount of old people who are alone. And you think about the companionship there.

• 20:15Anish Acharya?

  Yes, and by the way, I think the whole thing is that there's got to be a level of indirection. This is why I think contextual companions are very powerful. Because I think for a senior citizen, like, you know, it's important they have a big sense of self-respect. So if an AI calls them every night to like, check in on them, well, they're gonna be like, well, hold on, I don't need that, you know, I don't need to be babysat. But if instead the AI called to, you know, check to see if they'd taken their medicine, ask them how their day was, maybe lightly flirt with them, talk about World War II, I don't know. Like, suddenly they've got a context in which they're interacting. There's a level of indirection, but the thing that's actually delivering is sort of spiritual nourishment.

• 20:50Speaker 02

  How the shittest question ever, but you know, after 10 years, I'm not embarrassed to ask shit questions.

• 20:56Anish Acharya?

  Go for it.

• 20:57Speaker 02

  How does the UI paradigm change in a world of AI?

• 21:01Anish Acharya?

  Yeah.

• 21:01Speaker 02

  Everyone's like, now we're just all going to be voice. Do you agree with like, just all voice?

• 21:08Anish Acharya?

  I think 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, 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. Okay. 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 are 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.

• 21:53Anish Acharya?

  And perhaps the future of intent based is chat. I'm still a little skeptical.

• 21:57Speaker 02

  I 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 a new moats created?

• 22:16Anish Acharya?

  I, 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 Moltbook is a new type of synthetic network. That perhaps means there are certain types of networks that are less defensible than they were, you know, once were. But something like an Airbnb, you know, you can have all the vibe coding in the world. Like 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.

• 23:01Anish Acharya?

  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. You have this incredible demand for accuracy. I still think that you're sort of as good as gold in terms of defensibility.

• 23:16Speaker 02

  Is there any forms of defensibility which were very prominent in the prior ten years which are no longer as prominent?

• 23:23Anish Acharya?

  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 where you can put-

• 23:42Speaker 02

  When you say live, what do you mean?

• 23:43Anish Acharya?

  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.

• 24:07Speaker 02

  Okay, so we have actually relatively the same forms of defensibility that have existed before that we'll continue to make.

• 24:14Anish Acharya?

  Many.

• 24:15Speaker 02

  I'm always trying to understand. I 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. You know, 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, poor woman, and I'm always like, Mom, margins matter.

• 24:39Anish Acharya?

  Yes, I can imagine you holding your hand-

• 24:41Speaker 02

  Yeah, yeah, poor mom.

• 24:42Anish Acharya?

  Handheld, yes.

• 24:42Speaker 02

  Jesus, no wonder she wants to finish the walk.

• 24:47Speaker 02

  My question to you is, do margins matter as much in a world of AI? And are we entering a new way that we should be thinking about margins?

• 24:55Anish Acharya?

  Yeah, so here is actually where I think there's nuance in the margin conversation that's important, okay? So if you look back at any time you've gotten, we should talk about, you know, the bubble that doesn't exist, or perhaps there is some sort of subsidization and distortion that's 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, okay? If you look at the distortion from 2021, you essentially had this indirect subsidy of Google and Facebook. So 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

• 25:37Anish Acharya?

  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. So 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?

• 26:05Speaker 02

  It does. Jason Lampkin is a very good friend of mine from SAST and he said to me, I say a brilliant statement. He said, for the best companies, inference is the new sales and marketing.

• 26:14Anish Acharya?

  Yeah, I love that. A hundred percent 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. And it was true because even if they got a hundred X more value, they typically didn't pay a hundred X 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 twenty, twenty-five dollars a month. So there is a belief that the price ceiling for consumer products mass market was twenty to twenty-five a month. You look at Grok heavy, it's three hundred a month. ChatGPT, two hundred a month, Gemini Ultra, two fifty a month.

• 26:56Anish Acharya?

  So we're seeing ten X 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. So the S and M costs of acquiring those users are very wisely invested. And I think this is an important point that's changed.

• 27:12Speaker 02

  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?

• 27:22Anish Acharya?

  So first of all, it's typically a lot of organic traffic. One, I would look at your M one, you know, 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. And 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. Does that make sense? So you're sort of unbundling the CAC-oriented margin spend versus the durable margin, which is what's associated with your power in paying users.

• 27:58Speaker 02

  It totally does. The challenge becomes if you're trying to work out a CAC to LTV metric that you can kind of oscillate around.

• 28:05Anish Acharya?

  Yeah.

• 28:06Speaker 02

  It's very difficult to get an accurate sense of LTV in such a changing landscape where you're not sure of the durability.

• 28:12Anish Acharya?

  Yeah.

• 28:12Speaker 02

  Is the LTV 12 months or is it 48 months?

• 28:16Anish Acharya?

  Yeah, well, I think that retention really matters. And if you take a look at the best AI products, you know, even if you look at M2 as the new M1, right? Because again, you're getting a lot of sort of tourists who come in at M1, you're not paying anything for them.

• 28:30Speaker 02

  And so M1 means month one.

• 28:31Anish Acharya?

  Month one, that's correct. 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, you know?

• 28:42Speaker 02

  What's an M12 that would make you very excited?

• 28:45Anish Acharya?

  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.

• 28:53Speaker 02

  Okay, so 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?

• 29:03Anish Acharya?

  Well, and 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 investment announcement, sorry, which is that they're at 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. And 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

• 29:48Anish Acharya?

  overbuild of supply, right? And then three, as I said previously, even if there is subsidization, there's always going to be some distortion in subsidization. It's a sort of intelligent subsidization that's mostly being paid for by big tech and the labs, and it benefits consumers and startups. Like, God bless. I'm all for that.

• 30:05Speaker 02

  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?

• 30:25Anish Acharya?

  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? This is 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? Why is it? And let's go through it. It's you typically have had sales, support, operations, and collections. Now, who is the person that's really good at customer support? Empathetic, they're a listener, they really understand the product well. Who is really good at sales?

• 31:08Anish Acharya?

  They're more of a yap or they're a talker, they're high energy, they're very charismatic, you know, 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.

• 31:39Speaker 02

  How do you think about competition within markets? I'm jumping around so much. I'm fascinated you brought up customer support.

• 31:45Anish Acharya?

  Yeah.

• 31:46Speaker 02

  I tweeted it the other day, I tweeted it before, and you can't get my head around this market. There are like 50 providers with over 50 million in funding, 10 with over 100 million. And I'm very much of the Peter Thiel school of thought that, you know, competition is for losers and we want to have monopoly markets with your Dakagons and your Sierras and your Intercoms and your Polloas and that can go on and on. Fuck, I didn't know.

• 32:10Anish Acharya?

  Well, the question is, how do you define market? Okay, now this is an important point, right? So 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. You're going to have dozens of winners that all specialize, just as in legal today. You've got dozens, 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.

• 32:49Speaker 02

  Well, it's a $500 billion market if you assume that we eat their market, not we're an attached to it, correct?

• 32:57Anish Acharya?

  Correct, yeah.

• 32:57Speaker 02

  And we aren't attached to it.

• 32:59Anish Acharya?

  I mean, that's, that's an open question. I don't think that we're in the eight 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.

• 33:11Speaker 02

  What does that look like? That means like AI native law firms?

• 33:15Anish Acharya?

  Possibly. I think it means dramatic productivity increases for lawyers, dramatic productivity increases for programmers and engineers. Like, I think that the, the difficulty of doing 100% of a job is really, really high. It's this thing of like, 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, you know, a four day work week than 20% less jobs. Because jobs is bundles of tasks, don't set themselves up to be 100% automated so far. Right? You can do all the customer support you want, but sometimes you gotta take the customer out for a steak dinner. And so far, the models are not doing that.

• 33:51Speaker 02

  They're not. We, we mentioned like the $500 billion TAM. Do you do TAM analysis work when investing?

• 33:57Anish Acharya?

  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. Right? I 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, you know, it's its own sort of art. I focus very much on the Series A, because I believe that the, having shipped something and having sold something is such a dramatic signal.

• 34:26Anish Acharya?

  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. And then I think the mistake that many venture capitalists have made is just not estimating the market to be as big as it is.

• 34:51Speaker 02

  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, but payroll, like, come on.

• 35:06Anish Acharya?

  I'm sorry, brother. Deal and 11. I'm sorry.

• 35:08Speaker 02

  Fuck off. I didn't tell you earlier.

• 35:11Anish Acharya?

  What's your next pass, please?

• 35:12Speaker 02

  Granola, pre-seed.

• 35:15Anish Acharya?

  Okay, well, great.

• 35:16Speaker 02

  Yeah, Chris knows this. Chris knows this. I sent a voicemail 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. You know, most investors, when they send you the pass, you're like, wow.

• 35:32Anish Acharya?

  I look forward to your downturn.

• 35:33Speaker 02

  Mine you should do.

• 35:34Anish Acharya?

  Yeah, 100% yes.

• 35:36Speaker 02

  So you said about market underestimation. I underestimated the payroll market specifically. I thought Alex was right. 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?

• 35:48Anish Acharya?

  It's such a good question about which market did we underestimate. I mean, I've made this mistake a couple of times. You know, like, for example, I remember when we were acquired by Google, and I remember looking at the sort of the stock price and telling my co-founder like, 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. Right? 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. I think you'd sort of ask yourself, if you did the back

• 36:32Anish Acharya?

  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. Is 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

• 37:15Anish Acharya?

  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. And as a result, Credit Karma has many opportunities to sort of inform and sell their company, their customers' products. And it really, really works.

• 37:38Speaker 02

  So how do you reflect on that? Like, missing that?

• 37:41Anish Acharya?

  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.

• 38:03Speaker 02

  So funny, Roy just mentioned early. He says, "When a founder continuously hits target, you should bet on them continuing to continuously hit target."

• 38:11Anish Acharya?

  Yes, yes.

• 38:12Speaker 02

  I don't overthink that shit. It's hard to hit target.

• 38:14Anish Acharya?

  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." And, 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, but what else? What is like?" And of course, you know, there's a bunch of things that we 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?

• 38:59Anish Acharya?

  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.

• 39:08Speaker 02

  And 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.

• 39:22Anish Acharya?

  I can tell it's on mine.

• 39:25Speaker 02

  Yeah. When you reflect, what was your most painful loss and how do you reflect on that?

• 39:33Anish Acharya?

  I haven't lost a deal.

• 39:35Speaker 02

  You've never lost a deal?

• 39:36Anish Acharya?

  Never lost a deal.

• 39:37Speaker 02

  How long have you been at Andreessen?

• 39:38Anish Acharya?

  Six and a half years.

• 39:39Speaker 02

  Huh.

• 39:40Anish Acharya?

  Yeah, yeah.

• 39:42Speaker 02

  Do you, do you worry about that? I mean this in the nicest way, like, you know, I asked, I asked Ram Pel about this because, you know, he lost the A of Riddit.

• 39:49Anish Acharya?

  Yeah.

• 39:50Speaker 02

  And then did the B, which is great and fantastic. Well done him.

• 39:52Anish Acharya?

  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.

• 40:13Speaker 02

  Fucking impossible.

• 40:14Anish Acharya?

  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.

• 40:23Speaker 02

  What do you do in those situations when they're like this, I love you, but like, yeah, I've known these guys for 10 years, they backed me before. Do you try, hey, we're going to be the collaborative partner and try and nestle in now?

• 40:32Anish Acharya?

  Yeah.

• 40:33Speaker 02

  Or like, we'll just peace out and not take part in this?

• 40:35Anish Acharya?

  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? And I started, I had this nervousness around like, maybe it's a sales job, but I've 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. Of 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, like, 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, like, 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.

• 41:13Speaker 02

  How elastic will you be on ownership in order to win deals?

• 41:17Anish Acharya?

  Not very elastic. I try to explain what our model is, but I'm very elastic on price. I should probably be careful about saying that. I mean, my mental model is that below a certain threshold, the price doesn't matter. You just have to be a part-

• 41:28Speaker 02

  I want to learn from you.

• 41:30Anish Acharya?

  Yeah, yeah, well, this is my mental model.

• 41:33Speaker 02

  No, no, it was. I've learned in venture, simply copy often works.

• 41:37Anish Acharya?

  Yeah, yeah.

• 41:38Speaker 02

  So like very elastic on price and below a certain price, it doesn't really matter. What is that price?

• 41:44Anish Acharya?

  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. And like, we're very transparent about that. I'll have to tell a founder like, look, you've got great metrics. We can do this series A as, you know, 12 on 60, 15 on 75, like 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 do 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

• 42:29Anish Acharya?

  of, hey, we're going to put all the chips in behind you doesn't work if we're not real partners.

• 42:35Speaker 02

  200 versus 300?

• 42:37Anish Acharya?

  Yeah, I mean, it's, it's, it's in the margins. Again, I think a lot more at that sort of price threshold, I 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.

• 43:01Speaker 02

  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-

• 43:08Anish Acharya?

  Yeah.

• 43:08Speaker 02

  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-

• 43:16Anish Acharya?

  Yeah.

• 43:16Speaker 02

  Within, I don't know, 12 to 24 months.

• 43:18Anish Acharya?

  Yeah, yeah.

• 43:20Speaker 02

  Well, then they raised a billion and that 500 million tween around is now gone.

• 43:23Anish Acharya?

  Yeah, that's right. Yeah, look, I think that happens. And I think in a case where it's because core metrics are super healthy, like, good for them. God bless, you know?

• 43:33Speaker 02

  I have a lot of enterprise SaaS companies

• 43:36Anish Acharya?

  Yes.

• 43:36Speaker 02

  that do double, double, or triple, triple, double, double.

• 43:39Anish Acharya?

  Yeah.

• 43:40Speaker 02

  Is the world of triple, triple, double, double dead? And do we all have to be lovable or uplit in 11 labs to get funded?

• 43:46Anish Acharya?

  I don't think so. I mean, I think that a lot of it is depend, it's calibrated to your part of the market. So product velocity plus business velocity. I do think that you have to be top quartile compared to your peer set. Right? I think there are some markets that are consumer led or bottoms up, or 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 stake 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. So I think that there is just physics to some of these markets

• 44:30Anish Acharya?

  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.

• 44:39Speaker 02

  So you bring in triple, triple, double, double to partnership and they won't shit on it?

• 44:43Anish Acharya?

  Absolutely not. No, no. Yeah, look, 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 of revenue, dude. It is so hard, like getting anyone to pay you anything that's not, you know, a family member or friend is hard. And 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, you know, very flip about this. And then two, no, look, I think it's all about the sort of assumption 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?

• 45:24Speaker 02

  Totally get you.

• 45:25Anish Acharya?

  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.

• 45:41Speaker 02

  Super interesting. So you're saying that like the length of the start line, as Des Trainer 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.

• 45:51Anish Acharya?

  Absolutely. Yeah, area under the curve. And what do you have today with Figma? You have an N of one network effects product. Right? 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, right? And I think a lot of the thinking work is going to be done in products like Figma. I'm not sure that Dylan and team saw that 10 years ago, but I think they're well positioned today.

• 46:17Speaker 02

  Area under the curve companies, how does the world change for them today? And do they still hold inherent value of fundraising early? How does that change? Because it's difficult to sell.

• 46:28Anish Acharya?

  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 upfront. They're willing to expand with you. So 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 those are, 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 companies.

• 47:07Speaker 02

  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 like, oh, Harry, you make my life so much harder. And I'm like, it's too easy otherwise. And I say that Series A is the hardest place to be investing right now.

• 47:24Anish Acharya?

  Yeah.

• 47:24Speaker 02

  Because essentially, you have a million in revenue, very little signs of product market fail, honestly, at a million in revenue.

• 47:30Anish Acharya?

  Yeah, I disagree.

• 47:31Speaker 02

  You're paying 100 to 200 x ARR, and it's incredibly competitive. The price to progress ratio is incredibly mismatched between a 25 million seat. Why am I wrong?

• 47:45Anish Acharya?

  Yeah, well, okay. So first of all, I think as an investor, you have to decide what kind of risk you want to take. Okay? 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, that 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? And try like, 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.

• 48:30Anish Acharya?

  The 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 as a product and technology, they're not going to get the opportunity to sort of see their vision through. So I think taking competitive risk, can I win? And pricing risk.

• 48:59Speaker 02

  When you say, sorry, can I win? You're saying, can I win as an investor?

• 49:02Anish Acharya?

  Yes, against the other VCs.

• 49:03Speaker 02

  Okay.

• 49:04Anish Acharya?

  That is what we should do. That is like the number one most important thing that we do, win the deals by building trust with the founders, being smart on the markets, you know, being first to conviction, like 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.

• 49:19Speaker 02

  Couple of questions on the back of that. They're leaving their startups faster than ever, having just raised big rounds to do new things. Are we seeing this increased promiscuity from founders, do you think?

• 49:29Anish Acharya?

  I 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, you know? 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. I just don't think that's a good setup. That's a setup for promiscuity.

• 50:06Speaker 02

  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 was a ripe area for innovation and where models can be transformative. Do you mind that?

• 50:21Anish Acharya?

  I think there has to be some, some sort of irrational direction which they're pointed. Maybe it's pure capitalism, you know? And they're like, look, I've studied the living shit out 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. And 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.

• 50:49Speaker 02

  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?

• 51:00Anish Acharya?

  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. I mean, the Crea guys to me are a great example. You know, they come into our first pitch, first meeting with everyone in the room, Thanksgiving holiday. And, you know, I think they're both wearing matching kimonos. They're both drinking Celsius's, you know? Victor's got his like long skate hair. He's just this total badass who looks exactly the opposite of every MBA founder that we'd been meeting five years ago. And, you know, 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.

• 51:42Anish Acharya?

  So I think you do need to be able to fundraise and you can be very authentic in the way that you do it.

• 51:46Speaker 02

  In terms of like 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?

• 52:10Anish Acharya?

  Yeah, I'll, 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. They 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. 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.

• 52:52Anish Acharya?

  And, you know, they're immediately dismissed as embarrassing or impossible or a silly, non-serious thing to be working on. When 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's 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.

• 53:20Speaker 02

  What if you, 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?

• 53:30Anish Acharya?

  Well, I think the number one thing, and here's my, my free advice to other investors, but also founders, is 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, you know, like a small business factoring solution. Like, I'm not really, I don't know, like, maybe I should start a small business. Like, 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. I'm actually going to make something. So holding yourself to incredibly high standard of trying everything just gives you so much information and intuition.

• 54:12Anish Acharya?

  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.

• 54:19Speaker 02

  We say about going to try and product. I mean, 90% of the companies that I get pitched say, especially on the application side, that 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?

• 54:35Anish Acharya?

  Here's what I think. I 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.

• 55:15Speaker 02

  Do 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?

• 55:22Anish Acharya?

  I think it's both. I think that they will do tasks, they'll do the low NPS 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. Like, 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. And 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.

• 56:05Speaker 02

  When we think about kind of those best place to win an agent first game, I had Eric from Podium on the show. We did a fascinating story of like a kind of traditional SaaS provider that's now got an $100 million plus agent led 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. And so you have to kind of own the full stack, à 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 matter layer on top of a core provider?

• 56:37Anish Acharya?

  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, you know, business process outsourcing, they are 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. Those 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?

• 57:21Anish Acharya?

  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, right? The models are incredible at getting us into these local maximas. And 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.

• 57:41Speaker 02

  You mentioned BPOs there.

• 57:43Anish Acharya?

  Yeah.

• 57:43Speaker 02

  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?

• 57:55Anish Acharya?

  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.

• 58:06Speaker 02

  Can I ask you, one 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.

• 58:19Anish Acharya?

  Open source?

• 58:19Speaker 02

  Yeah.

• 58:20Anish Acharya?

  Yeah.

• 58:20Speaker 02

  How do you think about the distribution in terms of open versus closed? And how that looks in the next kind of 24 months?

• 58:27Anish Acharya?

  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. I 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, you know, 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 for product quality.

• 59:10Anish Acharya?

  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. And 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-4O has, you know, gone down 100x since the model was released.

• 59:34Speaker 02

  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 Raplace.

• 59:45Anish Acharya?

  Yeah.

• 59:46Speaker 02

  I think he's literally like one of their top users. It's insane what an incredible power he is.

• 59:51Anish Acharya?

  Amazing.

• 59:51Speaker 02

  But he uses 11 Labs as part of the voice for one of his games.

• 59:55Anish Acharya?

  Yeah.

• 59:55Speaker 02

  And he said, this will be the year where we see the true substitution of AI products based on price. He's like 11 Labs. I'm, I love it. It's amazing.

• 1:00:04Anish Acharya?

  Yeah.

• 1:00:04Speaker 02

  It's too expensive. It's too expensive. This is the year where we've moved from trying things to shit. It works, but it's too expensive. No comment on 11 Labs.

• 1:00:15Anish Acharya?

  Yeah.

• 1:00:15Speaker 02

  But you agree that we're going to see this transition in mindset from shit. At worst to shit, it's expensive.

• 1:00:22Anish Acharya?

  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 raise in costs, right? 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, Claude 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? You know, or I should use something other than Opus 4.5 or Codex 5.2? Like, nobody is saying that because the capability is so much more powerful. It really sparks your imagination in the other direction.

• 1:01:05Anish Acharya?

  What more can we do rather than how do we make the existing thing cheaper?

• 1:01:09Speaker 02

  It is interesting. I remember when he said he's got like 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.

• 1:01:20Anish Acharya?

  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 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. So 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.

• 1:01:51Speaker 02

  If you were Eleven 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 have raised 500 million, they could have raised 5 billion more.

• 1:02:05Anish Acharya?

  I think the general, 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, right? Today, again, we talked about 8 to 12% of enterprise spend is on SaaS, right? How 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 cutting.

• 1:02:34Speaker 02

  80 to 90% of consumer spend?

• 1:02:37Anish Acharya?

  The sort of discretionary spend. Of course, there's going to be, you know.

• 1:02:39Speaker 02

  On software.

• 1:02:40Anish Acharya?

  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 healthcare, potentially professional, right? A 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.

• 1:03:07Speaker 02

  I don't know if you're including food in that.

• 1:03:10Anish Acharya?

  Yeah.

• 1:03:10Speaker 02

  If you're including a DoorDash, then I can get on board with that.

• 1:03:14Anish Acharya?

  Non-discretionary spend is fixed, right?

• 1:03:16Speaker 02

  And you're clearly not European because you missed one crucial one, which is fashion.

• 1:03:19Anish Acharya?

  Yeah, fashion.

• 1:03:20Speaker 02

  Which would not be.

• 1:03:21Anish Acharya?

  You were going to say wine.

• 1:03:23Speaker 02

  Dude, no one buys wine. No one drinks anymore.

• 1:03:24Anish Acharya?

  Okay.

• 1:03:25Speaker 02

  Tough to be in the wine industry.

• 1:03:26Anish Acharya?

  Not even the Europeans?

• 1:03:27Speaker 02

  No, no, no. No, not at all.

• 1:03:31Speaker 02

  It's super interesting. Do you agree with king making today? In terms of the belief that, as I think you know, but like an anointed winner? Do you think king making is real?

• 1:03:41Anish Acharya?

  One, I think, an example of where there is a very positive sort of catalyst in their investor base for enterprise companies is YC, right? 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. So I think that's a good example in which picking the right investor is actually a big benefit. And 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

• 1:04:26Anish Acharya?

  anoint them the winner.

• 1:04:27Speaker 02

  Do you agree that the best founders you work with don't need their VCs?

• 1:04:33Anish Acharya?

  I 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 XYZ? Like, he knows how to get the best out of Andreessen Horowitz. And it's not just the investors, the entire team shows up for him that way. Could he do it without us? Of course he could.

• 1:05:08Speaker 02

  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?

• 1:05:16Anish Acharya?

  Yeah, well, first, pick an investor that does stuff, I think, number one. I think number two is-

• 1:05:21Speaker 02

  How do you know everyone says they do?

• 1:05:23Anish Acharya?

  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, right? That's what you want. So 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.

• 1:05:59Speaker 02

  Totally agree with that in terms of, I think, the lending of brands, I think is how you've described it before, is phenomenally valuable. Can I ask you, when we think about the lending of brands, who's the single best founder you work with?

• 1:06:11Anish Acharya?

  Alex 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.

• 1:06:25Speaker 02

  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 a technical capability.

• 1:06:34Anish Acharya?

  Oh, yeah, Jayden was telling me about this.

• 1:06:36Speaker 02

  Yeah, it's amazing. Anyway, I pinged Alex on a Sunday morning, 7:00 AM, 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. I'm like, dude, it's like a $1,000 deal.

• 1:06:48Anish Acharya?

  Yeah.

• 1:06:48Speaker 02

  He's not worth your time. He's like, no, no, to [email protected].

• 1:06:51Anish Acharya?

  That's what I mean.

• 1:06:52Speaker 02

  I'm like-

• 1:06:53Anish Acharya?

  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 who know how to apply to product, like Creer 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.

• 1:07:10Speaker 02

  No, the Happy Robot guys, I wish I was invested in that team.

• 1:07:13Anish Acharya?

  They're amazing, man. Please don't tell me you passed on that at the seed too.

• 1:07:16Speaker 02

  No, no, I never met them.

• 1:07:18Anish Acharya?

  Thank God. Okay, good, good, good.

• 1:07:19Speaker 02

  No, no. That's one of those ones where it's one I wish I was in it, but I never had the chance to be a...

• 1:07:24Anish Acharya?

  They're wonderful. Incredible technologists, really earnest people, and they're seeing a ton of success.

• 1:07:29Speaker 02

  When you reflect on companies or investments that you've made that were not good, what did you not see?

• 1:07:38Anish Acharya?

  I mean, I think, again, 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, and 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.

• 1:08:21Anish Acharya?

  But investing with this sort of self deception of like, well, let's just assume it's working when it's not quite working, is a mistake.

• 1:08:28Speaker 02

  I think you know a good investment or a bad investment in the first three months. Do you agree?

• 1:08:34Anish Acharya?

  I don't know. I think the area under the curve companies take time to develop.

• 1:08:38Speaker 02

  I get you. But when you speak to the teams and even if they're...

• 1:08:41Anish Acharya?

  Here's what I'll tell you. I think that 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, you know? And you're sort of faced with uncertainty. And I think the sort of psychology of that latter... Um, moment is very telling.

• 1:09:07Speaker 02

  Have you ever felt that the Andreessen brand holds you back in any way? Like, maybe with a, no?

• 1:09:13Anish Acharya?

  No, not one.

• 1:09:15Speaker 02

  It's a massive tailwind in a lot. There's never been a, there's never been one where there's like been a political question.

• 1:09:20Anish Acharya?

  Not at all, no. And Mark and Ben are so special and authentic. And like what Ben said, has said many times is that they sort of, um, you know, feel like there'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, 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.

• 1:09:42Speaker 02

  Dude, I could talk to you all day. I do want to do a quick fire round with you. Okay, are you ready for this?

• 1:09:46Anish Acharya?

  Okay, okay.

• 1:09:47Speaker 02

  What's the most memorable first founder meeting you had? It doesn't have to be like the best founder, but the most memorable first founder meeting you had and why?

• 1:09:55Anish Acharya?

  I mean, yeah, so it's probably the, the guys at Crea. Just because, you know, we, they'd been so mysterious. We'd been unable to get ahold 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. We all, 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. And there was so much of a setup to the meeting that it's, it's one I'll never forget.

• 1:10:30Speaker 02

  Mark, Ben, DG, who's the best investor?

• 1:10:34Anish Acharya?

  I mean, they're all extraordinary. Uh, 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, his storytelling ability is extraordinary. Ben, like to me, I mean, Hard Things was the first honest business book. Okay. 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

• 1:11:16Anish Acharya?

  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. DG 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.

• 1:11:53Speaker 02

  What's been the hardest decision that you've had to make in the last two to three years?

• 1:11:59Anish Acharya?

  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. And sometimes through no fault of their own, sometimes their 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 is I'd 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 behavior? 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

• 1:12:44Anish Acharya?

  term, we don't measure you based on returns. We 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 GP 360s every two years. It's always a little terrifying, but the incentives are all structured in the right way. And that, that moment and the answer to that question is, was at which I knew like, hey, this is, this is not a VC like every other VC I've seen out there. This is like a company.

• 1:13:24Speaker 02

  I remember someone from Andreessen telling me, and I'll keep, I can't, I can't actually remember who it is, so I'm not actually being deliberately coy. It might have been Brian, it might have been DG, it might have been Alex. I really can't remember. But they said like, sorry, as they said, like in Andreessen, it's totally unacceptable to lose a deal.

• 1:13:39Anish Acharya?

  Yeah.

• 1:13:40Speaker 02

  But it's very acceptable to not have seen it and it'd be great. Is that fair?

• 1:13:45Anish Acharya?

  To not have seen it?

• 1:13:46Speaker 02

  Like, random company does very well. We never met them. We never had the chance to meet them.

• 1:13:51Anish Acharya?

  Hmm. I don't think so. I don't think we're allowed to believe in luck at Andreessen. We have to see a hundred percent of the deals in our domain. Now, look, 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 one hundred percent of the deals in our sector and that we win a hundred percent of the deals that we go after.

• 1:14:15Speaker 02

  That was very clear. There was no, uh, no, I love it, dude. Okay, good. Uh, good, right. And that conversation.

• 1:14:25Anish Acharya?

  Sorry to scare you. Hey, look, there's some things are ambiguous, but that part is not.

• 1:14:30Speaker 02

  No, no nuance. Good. I hate nuance. It depends. It's the worst answer. Um, you can invest in one seed firm. Which seed firm do you invest in?

• 1:14:40Anish Acharya?

  All right. Um, I think Rontin is pretty special at what he does, actually at Abstract.

• 1:14:45Speaker 02

  Well, I agree. Why?

• 1:14:46Anish Acharya?

  Yes, yeah. He's, I mean, one, he's a cold-blooded capitalist, you know, which is awesome. He just has great instincts. And I think the seed, to me, the seed stage is the hardest stage at which to invest, because it's, 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, true seed, there's no product and there's no go-to-market yet. Now, post-product, pre-traction, that gets easier. Post-product, post-sumtraction, 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.

• 1:15:27Anish Acharya?

  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.

• 1:15:34Speaker 02

  What have you changed your mind on most in the last 12 months?

• 1:15:38Anish Acharya?

  I think the thing that surprised me about this product cycle, you know, I was building my, my first company in the mobile product cycle and, um, In the mobile product cycle, the sort of like the anointed winners in 2008, 2009 were not the eventual winners. So we had this 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. You know, we talked about Harvey, that's a really impressive company, you know, Gamma is a really impressive company. Cursor is a really impressive company, like 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. I think in 26, we're going to see a whole new set of categories.

• 1:16:23Anish Acharya?

  Cause can I share my view on where we are in 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 O1 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. We 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.

• 1:17:08Anish Acharya?

  Knowing what we all know now, what company would you build? That is the operative question. And OpenClaw and MultBook 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.

• 1:17:31Speaker 02

  How significant is MultBook? Everyone's very excited by it.

• 1:17:34Anish Acharya?

  Yeah.

• 1:17:35Speaker 02

  You're a lot more product centric than me. How significant is this?

• 1:17:39Anish Acharya?

  I mean, it's just so damn cool. Just to talk about it, to observe it, it's shallow. And you know, Bology 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, you know, 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. I 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 train a little digital twin of myself and other people would do the same. And they would go have, you know, pseudo dates.

• 1:18:24Anish Acharya?

  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.

• 1:18:38Speaker 02

  I 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.

• 1:18:46Anish Acharya?

  Oh, yeah, yes, yeah, yeah, yeah, the Hinch thing, yeah.

• 1:18:49Speaker 02

  That's tough.

• 1:18:50Anish Acharya?

  Yeah, so I think that like, you know, 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, well, it book as an individual data point is probably overhyped right now, but what it points at directionally is underhyped.

• 1:19:05Speaker 02

  Next 10 years, final one. What excites you most? What do you like, I like optimism. What are you most optimistic for and excited about?

• 1:19:13Anish Acharya?

  Oh, my God, dude, I mean, where do I start, right? Like, robots, pet robots, space travel.

• 1:19:19Speaker 02

  Specifically, like, actually, medical. I think we'll have amazing breakthroughs in treatments like multiple sclerosis, which my mom has, which is previously she'd been like, oh, like, bad luck.

• 1:19:29Anish Acharya?

  Yeah.

• 1:19:30Speaker 02

  I think we'll have real breakthroughs there, which is super exciting for me.

• 1:19:33Anish Acharya?

  Yeah. Okay, well, let me, 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. And I think that the, 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.

• 1:20:15Speaker 02

  Dude, it's such a pleasure to do this in person. Thank you so much for sitting down with me. I really enjoyed it.

• 1:20:20Anish Acharya?

  Sorry, I'm a little loopy. I can't tell if it's 3 a.m. or 3 p.m.

• 1:20:25Erik Torenberg?

  Thanks for listening to this episode of the A16Z Podcast. If you liked this episode, be sure to like, comment, subscribe, leave us a rating or review, and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts, and Spotify. Follow us on X at A16Z and subscribe to our Substack at A16Z.substack.com. Thanks again for listening, and I'll see you in the next episode.

• 1:20:51Erik Torenberg?

  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.