How AI Created the Fastest Product Cycle in History

Recently, a16z General Partner Anish Acharya joined Ollie Forsyth on NEW ECONOMIES. They talked about why consumer tech is surging again, how AI is enabling 100M-user products at unprecedented speed, and what founders need to understand heading into 2026 — from distribution shifts to founder mindset to the mechanics behind the fastest product cycle in tech history.

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

• 0:01Speaker 00

  Anish Acharya is A16Z's general partner for consumer tech and AI. He recently joined Ali Forsyth on New Economies for a wide-ranging conversation on where the next wave of breakout products will come from, how AI is reshaping distribution, and why consumer tech is re-accelerating as we head into 2026. They also dig into founder psychology, market timing, and the traps early builders should avoid in the current cycle. We share that discussion here.

• 0:30Speaker 01

  Anish, it's great to see you. Thank you so much for your time. Welcome to the podcast, A16Z. Wow, you guys are on fire right now.

• 0:38Anish Acharya?

  We're working hard. We try to be everywhere, you know? And when there's more opportunity, that means, you know, Ben says there's no such thing as luck. We're not allowed to be lucky. We've just got to cover everything. So when there's more things to cover, we've just got to put in more cycles, you know?

• 0:52Speaker 01

  I kind of feel like A16Z is so well-known in the ecosystem, but I don't think founders know well enough on what actually happens inside Andreessen. Can you just give us like an update? What's Andreessen all about? What are you guys focused on? And what's the lay of the land in startups?

• 1:11Anish Acharya?

  Yeah, you know, it's funny, Ali, because Andreessen is so well-known, but the kind of core thesis of the firm, I think, is less well-known. I didn't know it when I joined in 2019. And the core thesis of the firm, Mark and Ben have written a lovely blog post about this that, you know, we should refer your readers to. But the core thesis has always been that founders make the best long-term CEOs and leaders of their companies. Right? And that sounds like a non-controversial statement. But 10 years ago, when the firm started, 15 years ago, it was actually controversial that common practice at the time was that venture firms would bring in a so-called professional experience CEO. Now, what is the difference between a founder and a CEO? It tends to be two things, right? Knowledge and networks. So the whole structure of the firm is meant to help founders be those CEOs of their companies forever by pulling networks and knowledge around them.

• 1:57Anish Acharya?

  So that's like the core thesis. That's a good sort of foundational building block. And then in terms of the way the firm is composed, it is a big firm, but everybody is a specialist. So the expectation is that we're all very, very deep and kind of obsessed and technical and operational and networked in our areas. And because so many interesting things in software cut across many areas, we're able to kind of come together and bring a better proposition to the founder than you would get from a smaller team of pure generalists. So that's how we work.

• 2:27Speaker 01

  And your team size now is pretty large, right?

• 2:30Anish Acharya?

  The team size is large, but the way to think about the teams, I think the overall firm is maybe 500 people. But the way to think about this is, you know, the original sort of Andreessen, which is all the GPs in one room and all the sort of operating teams around them, we've sort of replicated that. So today, our app fund that I invest out of, you know, looks a lot like Andreessen Horowitz period 10 years ago. The Infra Fund, the American Dynamism Fund, et cetera. So we've really taken the structure of a small number of GPs, operating specialists and other folks, and replicated it because software is just now so much more horizontal than it was 10 or 15 years ago. So that's the kind of ethos, you know, the energy that you get in working with us is no different than 10 years ago. You just have more specialization.

• 3:13Speaker 01

  And it's just becoming so competitive, right? And what I love about you guys is it feels you're always one step ahead of the curve. And every single venture fund out there, you have specialized practices. You've just launched this new media vertical, which I think is really interesting. From the new media vertical, why do you think it's now so important for investors to be thinking about, not just about capital, but also about distribution, customers, marketing and so on?

• 3:40Anish Acharya?

  Yeah, Mark said this recently, and I think it's the right framing, which is the thing you want from your venture firm is power. And the reason for that is, you know, when you're a tiny, you know, baby bunny rabbit startup, you don't necessarily have the types of power that you need. You don't, you're not necessarily able to fill in the Fortune 500, the Fortune 2000. You don't have brand power and presence. So what you really want to do is take the platform that your investor gives you and build on their power. And then over the course of time, if things go well, you of course become more powerful and more significant and more well-known than your venture investors. So distribution is a part of that. But I think broadly, what you want to do is borrow the sort of credibility and the presence that your investor has. And we really try to create the platform that founders can jump off of.

• 4:25Speaker 01

  I like that narrative, you know, I mean, we've only been going a year. We do about a million views a month across our media channel and we're starting to invest in a few companies, especially Y C companies. And actually, like our biggest value add right now is distribution. And I think we're going to see this kind of involvement, right, over the next 12 or 18 months. More VCs are going to try and do this, but I think it's going to be tough. It's super hard to do this well. And I mean, you guys have a big team and quite a lot of capital behind you. But the ones who can do it, I think the ones who are going to make it.

• 4:58Anish Acharya?

  Well, you guys have done it really well. You know, when you have somebody like a Matty on your pod, and then you've got a lesser known founder with a smaller scale company, you know, it's sort of the collective presence that you and Matty and the other guests that you've had really prop up that founder that may be earlier stage. So it exactly mirrors what we're doing. And, you know, it really benefits the ecosystem as a whole. And by the way, I hope more firms do do it. Like, I think we're going to have a lot more software and we need a lot more founder stories to be told.

• 5:24Speaker 01

  Totally. Well, we need to collaborate at some stage. That's the first.

• 5:27Anish Acharya?

  I'd love to. I'd love to. Yes, yes, yes.

• 5:29Speaker 01

  Let's make it happen. But I think also, you know, this whole AI landscape has been changing so quickly. Before we came on the show, we said November 30th this year, it's going to be free years since GPT a thousand, a thousand days. What the hell is happening in AI right now? Can you help us just, you know, break down what all is happening? It just seems to be changing every freaking day.

• 5:51Anish Acharya?

  I know. I mean, I think it is objectively the fastest sort of developing product cycle we've ever seen. There's a lot of reasons for that. You know, one of it is just the size of tech is so much larger than it ever was before. You know, we, I think for a long time, tech was the dog chasing the car and now we are the car or something. We've really fulfilled our ambitions. We're no longer these kind of, you know, weirdo hippie kids out in San Francisco or Palo Alto or whatever else. So like, one, the scale of tech is a lot bigger. Also, I think the nature of this product cycle is different. Like, if you think back to the mobile product cycle, it sort of was all downstream of Apple. So Apple did the iPhone in 2008. They did the App Store in 2009. This was a surprising fact to me, but when the App Store came out in 2009.

• 6:35Anish Acharya?

  Nine, there was only six million iPhones in distribution, right? So one year post iPhone, your cam as a mobile app developer was six million customers. Today, if you build into the apps SDK, which is the new AI app store that the chat GPT is going to be releasing, you've got an audience of eight hundred fifty million people. So just like the scale is enormous. But the other interesting thing is when we were building an app in the App Store in two thousand nine, two thousand ten, what happened was Apple sort of decided what APIs they would expose. And all of the developers would organize around those APIs. Whereas it feels like with large models, it's more of a process of sort of biology than systems design in that

• 7:15Anish Acharya?

  the the models are being trained, we're discovering what the models can do, and they have all of these emergent properties. So I think for that reason, there's just this much wider diffusion of things that are being built, things that can be built, because no central decider is, you know, upstream of the entire innovation ecosystem. It's it's really, really crazy.

• 7:34Speaker 01

  It's so exciting as well with, you know, you've probably seen a few more AI tech bubbles, sorry, than I have. But it feels just in the last three years, since generative AI was launched, then we've had AI agents, now it's vibe coding, or it was vibe coding, still vibe coding, now it's voice. These trends just keep emerging, emerging, emerging. Is it tough to be a founder right now in this highly competitive AI landscape? If you're raising ten, fifteen million dollar pre seed rounds?

• 8:03Anish Acharya?

  I mean, I think that the the whole trick of being a founder, much of the trick is an exercise in psychology, personal psychology. I think there are just so many places that you can get stuck. You know, and I'll tell you about some of the traps. One of the traps is, oh, my God, I'm too late, you know? And every founder has that feeling like, oh, I should have started my company a year ago, a month ago. You know, and if I had, I'd be where XYZ is. So I think that's a very common trap. Another common one is, you know, nobody is funding anyone, you know, we're in that, we're in a winter. Oh, my God, like even if I build something, nobody will pay attention. When I was building my first startup in two thousand and nine, I remember the TechCrunch article well. The sort of headline was the end of venture capital. And I sent it to my co-founder and I said, oh, it's over, you know, like venture capital is over.

• 8:46Anish Acharya?

  TechCrunch has said so, and you know, it doesn't matter what we build because no one will fund it. Looking at competition is another sort of mind trap where you can look around and feel like, oh, my God, look at how much everyone else is raising from all these credible folks. But if you're able to put the blinders on and just turn that noise down for a moment and look at where we are from first principles, what you'll see is actually we're in kind of the best time to build a startup we've ever been in, that I've ever seen for sure, which is let's say you're building in consumer. What is the nature of consumer product today? Consumers are incredibly excited about AI, despite what you read in the newspaper. Millions and millions of users are downloading consumer AI products organically. So there's no paid acquisition necessary. With these large models, you can do these incredible extraordinary things that would have sounded like

• 9:31Anish Acharya?

  science fiction five years ago. And then, you know, the the model companies are beating each other's brains out to kind of spend more to improve the models that really benefit all of the founders and builders. We just saw that with Gemini three, which looks extraordinary, was released yesterday. So just it feels like from a first principles perspective, there's never been more opportunity, even though to your point, there's never been more noise.

• 9:53Speaker 01

  So many founders are saying, you know, oh, I'm too late, you know, they want to do a legal tech platform or vibe coding platform. When you see lovable just turned one year old yesterday, $200 million in annual income revenue.

• 10:05Anish Acharya?

  Good for them.

• 10:06Speaker 01

  You know, incredible, right? But then do we, you know, how many vibe coding tools do we need? Are we going to be, are we going to go down the route of these founders are going to create really interesting products, but they're highly specialized and highly verticalized? Is that the route we're going to kind of go down?

• 10:23Anish Acharya?

  Well, I'll tell you, Oliver, the mistake that I have consistently made, and I feel like I continue to make it in this AI ecosystem, is underestimating how big these markets are. And that's why the way I describe it is like, these are not markets, they're industries. Okay, so AI code is not a market with a single winner or even a half dozen winners. It's going to be an industry with, you know, 30, 40, 50 winners. Legal, AI legal is going to be as significant as simply legal. You know, it's like we used to say e-business, but it's really just business. When we say AI legal, we really just mean legal. And I think it's going to be enormous. Yes, there's going to be specialization, but the size of those specialized markets are going to be as big as entire software markets were previously. It's definitely not too late.

• 11:08Anish Acharya?

  And I think the one mistake I'd encourage folks not to make is underestimating the size and significance of the opportunity.

• 11:15Speaker 01

  Totally. There's so much noise out there. But like, I think, you know, just what's happened in the last thousand days is incredible, right? I mentioned before, uh, before we came on the show, we had Emmett, the former co-founder of Stability AI. And he's got this whole thesis around this is what's happened in the last thousand days, but the next thousand days is going to be the most crucial and the most critical. Potentially, AI is going to start replacing jobs. Potentially, we're going to start using it on a, you know, global basis with no, for those people who don't have any internet connection. I think one of the big questions is who actually owns these AI models? I think this is a slightly wider question, kind of like long term. But the next, you know, thousand days, what do you think is going to happen?

• 11:59Anish Acharya?

  Yeah, and I have to sort of quibble with the framing of AI is going to start replacing jobs because we're out in the frontline, talking to all of these AI companies that are selling enterprise software. And what we don't hear very often is it fully replaces a job. What we do hear is it fully automates a task, but tasks are not jobs. So what we've typically seen with these enterprise software plays, even ones that when you squint at from afar and say, oh, wow, the AI is answering the phone and doing a lot of negotiation. Like, maybe that's going to replace a job. What we actually see is that it gives the people that are doing the job a lot of leverage. They no longer have to do the sort of administrative rote parts of the job. They're able to specialize.

• 12:36Anish Acharya?

  And, you know, perhaps those folks are, you know, spending less time than they previously spent overall working, but we're not seeing role elimination broadly. So I would kind of quibble with the narrative of AI is replacing jobs. I think AI is automating tasks. As for the next thousand days, you know, if you look back at December of 2022. You know, just, you know, D thirty after ChatGPT launched. I think there was a very valid concern that if a single company was an entire generation ahead in terms of model quality, then there was all kinds of economic implications of that, including that they could take a lot of the margin from the entire AI ecosystem, that they would sort of decide what everybody would build, what constraints, what opportunities, et cetera.

• 13:21Anish Acharya?

  But it's just not what we've seen over the thousand days. Instead, we see, you know, a half dozen really significant cutting-edge models that are all improving neck and neck. We see a bunch of open source efforts, you know, some from China, some from the US, all of them very interesting, all of them pointed in different directions. So it feels like there's been this diffusion of models, cutting-edge models in particular, that mean the kind of dystopian predictions about what would happen if one company controlled all of the AI so far haven't played out. So I think the next thousand days will be extraordinary in terms of model capability improvement. But I don't know that we're going to suddenly see, you know, some sort of runaway dystopian effects from the models. I think we're just going to see more of what we've already seen.

• 14:04Speaker 01

  Totally. I think that's a good way of putting it. And also, you know, if you look at customer service roles, you know, I think that's one of probably the biggest use cases, right? Where AI has been a superpower to these people. Instead of paying them, you know, a hundred, a hundred and fifty thousand dollars a year to basically set their own obstacles, they could be doing so much more and AI can do it for a fraction of a price. And that's going to probably be replicated across multiple roles, right?

• 14:31Anish Acharya?

  A hundred percent like what we've actually seen in one of our best companies called Happy Robot does this where they sell voice AI to freight brokers. You may be familiar with them. And what they've actually seen is for a lot of the folks that were previously doing, you know, just low-level customer support work. They're now moved into customer relationship management. We're looking like the AI is never going to take a key customer account for a steak, out for a steak dinner. Somebody's still got to do that. But if people are too busy handling kind of the day-to-day minutia, they have less time for relationships. So instead, we're seeing, you know, humans get to be more human than ever and AI takes away a lot of the work that really didn't get leverage from, you know, human, human skills anyways.

• 15:10Speaker 01

  Totally. Happy Robot. Great company. Spanish-based company, right? Only a few years old.

• 15:15Anish Acharya?

  Based here, but Spanish founders. Yeah, they're tremendous.

• 15:18Speaker 01

  Awesome. I think this is maybe a good way to segue into some of the trends that's kind of happening in the ecosystem. And I feel it'd be helpful for this episode to really lay out four or five trends, which are really exciting for founders to start ideating, find ideas to go and build companies, right? So I feel it'd be really helpful to understand what's happening around consumer tech, the future of voice. This is really interesting. The creator economy, I think this is kind of intersecting consumer tech and AI. Social media platforms, we haven't seen really any new social media platforms in the last few years. Is AI going to change that? These AI rappers, before we came on the show, we were talking around these AI models who are allowing APIs to startups.

• 16:03Speaker 01

  Are these AI models just watching these companies and then going to start copying them? I think that's TBC. And then let's jump into just what's happening more on the fundraising landscape. How's that sound?

• 16:13Anish Acharya?

  Sounds excellent. Let's do it. Where should we start?

• 16:15Speaker 01

  Cool. Let's start with the consumer tech. So consumer tech, right? I'm sure you get this all the time as a consumer investor. People thought nothing's happened in consumer tech for the last five or 10 years. It's boring. But now it kind of feels consumer tech is coming back, but it's AI focused. What's happening?

• 16:32Anish Acharya?

  Yes. Yeah, that's exactly right. So consumer is hyper cyclical. So for long, long periods of time, nothing happens and it's a very tough time to kind of invest or build in the consumer ecosystem. And then you have these magical moments where the window opens up and all of a sudden you can build consumer tech. And all of a sudden the consumers change, something is in the water, new products are being launched, the sort of boundary of imagination is being pushed. And born from those moments in time are some of the biggest companies in the world. You know, if you look at Meg Seven, the majority of those companies are consumer companies or have a significant consumer offering. If you look at what happened post iPhone, it's 2011, 2012, we suddenly had this explosion of Lyft, Uber, WhatsApp, Airbnb.

• 17:15Anish Acharya?

  It was just extraordinary what happened. We're in that moment again. And there's three things that really unlock. Lock consumer markets. You know, the first is a new technology, which we of course have in AI. The second is new consumer behaviors, which is connected to new technology, but people just making different choices. You know, in the mobile era, I remember people saying, oh, location is too sensitive. No one will ever share their location. And now every Gen Z shares their location with all their friends and their exes. And it's it's very strange behavior. But, you know, the consumer choices and preferences just change very quickly. And then the third is a new distribution channel. If there was a critique of consumer tech at this moment, it's that we don't really have an AI native distribution channel. I think that's about to change in 2026, and we can talk about that. But we sort of have the ingredients of really magical

• 17:59Anish Acharya?

  sort of consumer growth and consumer startup building right now. In terms of the exact trends we're seeing, I think the most important trend, the one I'm personally most excited about is, you know, consumers building software. If you think about the internet, the internet has been this sort of driving force for participation. You know, everything from written content, which transformed into social media, to video content, which transformed from shaky home camera films into what we now see in YouTube. I think I read that YouTube's a $550 billion enterprise. Like, that's pretty crazy, built off the backs of, you know, Mr. Beast and, you know, unboxing videos and things that were entirely non predictable 20 years ago. It feels like the software ecosystem is headed to a similar place.

• 18:41Anish Acharya?

  And, you know, you asked a question of like, will there be a new sort of social network? Maybe there will be, but I think it'll be more focused on things like software versus content. And we're seeing the beginnings of that now. You know, we announced an investment in a really cool company called Wabi a few weeks ago, W A B I, which is a platform where consumers can create and consume personal software, mini apps. It feels exactly like YouTube in 2006. And it's easy to look at it and say, well, hey, do people want to make software? What kind of software will they make? Can they make really serious software? I think that's the same thing as looking in 2006 and saying, hey, how big and how important can consumer video be? So the idea that people will make software for themselves, for their friends, the idea that you've got 20 million people who are programmers today and 6 billion people that use software,

• 19:27Anish Acharya?

  like, let's change that ratio, you know? Why can't there be 500? Billion or a billion people making software. And it just feels like, you know, lovable, replit, codex, Claude code, Wabi, like emergent. I mean, you can vibe code, Rorik, you can just name the companies. And the amazing thing is they're all working. And the reason they're all working, I think, is that there's just this huge sucking sound of demand from the market that no matter how many new startups cross a hundred billion of revenue, there's like room for another dozen.

• 19:56Speaker 01

  Totally. And there's so many calls out, you mentioned Wabi. This is the replica of former founder, right?

• 20:01Anish Acharya?

  Eugenia. Yeah, Eugenia. Yes, yeah.

• 20:03Speaker 01

  Eugenia, there you go. There's like, I mean, there's just so much core innovation happening, but also it feels, why do you think now consumer is so exciting? And what's, what are some of those learnings we can look back on over the next, over the last, you know, five or 10 years where maybe it was just kind of boring for founders?

• 20:21Anish Acharya?

  Yeah. Yeah. Well, I think it's two things. I think, you know, top down, business model quality is really high. So you could just, as a consumer founder, you have to ask yourself, like, how am I going to spend every day? And I think as a consumer founder from 2014 to 2023, the way you probably spent your day with marketing, you know? And that's just very few of us are people that get joy from consumer product sort of marketing and customer acquisition. Whereas if you look at how you spend your day today as a consumer founder, you're spending it building product. I would argue that there are no marketing problems today for consumer companies. There are only product problems. And if you're not getting distribution, you probably haven't been ambitious enough in product. So I just think that this is a really fun and magical time. You know, business model quality is high.

• 21:06Anish Acharya?

  Consumers are willing to pay. They want to try new things. And then you have so much to work with as a consumer founder. You know, you're able to build products that are emotional and sort of capture and understand emotional experiences, products like poke, you know? You're able to do things with new sort of primitives like voice. I mean, voice is the original form of human communication, and yet there's really been zero tech built around it ever. Like, what will the future of voices and interface look like? I don't know, but you can kind of invent it and imagine it today. So it just feels like the amount of fun you're having and like the really exciting consequences of being successful and having that fun are something that we haven't seen since 2010.

• 21:46Speaker 01

  Also, you know what's really interesting? Consumers are willing to pay for these products. Before, it may have been $10, $20 for Spotify and Netflix, or very, you know, specific subscriptions. Oh, I'm not sure I want to pay for it. $25 now for Lovable is like, sure, I'll sign up tomorrow.

• 22:01Anish Acharya?

  Well, yeah, and I actually think $200 is like, sure, I'll sign up tomorrow for many people. And those are the price points. If you look at, you know, Gemini Ultra, Google Ultra, that's 250 a month. ChatGPT's top skew is 200. Grok Heavy is 300. People are paying it, you know? I mean, if you look at the spend on Cursor, I'd love to see what hobbyist spend is on Cursor. I bet it's really significant. I think it's easy to look at their revenue scale and say, hey, it's enterprise. And I know, I'm sure a significant part of it is enterprise, but I'm sure a lot of it is also hobbyist. The other cool thing is for the first time ever, you've got consumption revenue for consumers, right? So typically in the past, a consumer could subscribe to a product, but you know, you're never going to pay Spotify $100. If you pay 20 a month in subscription, there wasn't a way, if you listen to 5X more music,

• 22:46Anish Acharya?

  for you to pay them $100 in a given month. Whereas now, if you're using a creative tool like Creia, a coding tool like Cursor, you can conceptually pay that company a lot more than the fixed subscription rate. And again, that's kind of a new business model improvement for consumer founders.

• 23:02Speaker 01

  You mentioned earlier around this new distribution type of model. What does that look like for new consumer AI companies coming out to market?

• 23:11Anish Acharya?

  Yeah, this is such a great topic. And I think this is the one thing we've all looked for. You know, it was in 2005, 2006, it was the Facebook sort of social APIs plus access to Facebook notifications as a channel. If you look at 2009, it was the App Store. And now we actually have this moment, I think in 2026, where we're going to see something similar. So the first thing I'm paying attention to is the Apps SDK, which was announced, I don't know, 30 or 45 days ago by OpenAI, where you can embed experiences within ChatGPT and get distribution. They're going to have Discovery and an App Store, some sort of an App Store. The second thing I'm paying attention to is mini apps. And this is, it's cool because Wabi was ahead on the mini apps. And I didn't expect Apple to fully embrace it, but they have. They announced that they're going to support a mini apps ecosystem.

• 23:55Anish Acharya?

  Importantly, they've reduced their take rate for mini apps from thirty percent to fifteen percent. So that's a pretty cool economic benefit to the platforms and the mini app creators. You know, and then finally, we saw a bunch of hubbub around group chat in ChatGPT. They're launching it initially in New Zealand and a bunch of other countries. It's of course going to come to North America. I suspect what that means is that OpenAI will have app discovery and consumption within group chats. And then met at others will be forced to replicate that. So as a consumer founder, you know, you've got these three channels, AI, apps, SDK, mini app and group chats, which could be really, really big, which means twenty twenty six is going to be a footrace, you know?

• 24:36Anish Acharya?

  It's not going to be for the faint of heart, but the consequences should be multiple consumer companies with a hundred million users when we have this conversation next year.

• 24:45Speaker 01

  Let's make it happen. Well, I think another really interesting consumer trend, also trend happening is like this whole future of voice. Voice is now becoming, you know, potentially the new interface and productivity and, you know, making us, you know, just better at our jobs.

• 25:02Speaker 01

  What's happening in voice and why is now so exciting?

• 25:06Anish Acharya?

  Voice is cool. You know, we've been obsessed with voice and covering it really closely for the last few years. I think part of it started from a little bit of a dreamy vision of, I don't know if you've read Ender's Game, but they've got a voice assistant named Jane in that. And, you know, of course, her has been discussed to death. But we've had these sort of fantastical imaginations of a voice interface to technology. We've just never had the technology to make it happen. So we were sort of dreaming those dreams in twenty twenty three and making some predictions. And as I, as I said, for AI-coded legal tech, we underpredicted how important, how big it was going to be. Like voice is not a market, voice is not a primitive, voice is an industry change. What's happening with voice is that it's turning out to be the insertion point for AI into the enterprise.

• 25:48Anish Acharya?

  Because it's something that the enterprise already does. Every enterprise in the world has phone calls and voice. There's two parts of voice. There's sort of scribes, which is note taking broadly. And then there's phone calls and what we call agents. It's turned out so far that the agents have worked, you know, better and are at higher scale than the scribes. Those scribes are also very interesting and important. And it's just, it's turning out to be a lot bigger than any of us expected. So I think there's going to be hundreds of companies that get to scale and verticals with voice as their wedge.

• 26:19Speaker 01

  And what's so interesting about voice now is it used to be very robotic, right? Now it's more humanish, the ums, ahs, mms, I kind of like that. Maybe the personal connection is not quite there yet, but we're still so early.

• 26:35Anish Acharya?

  I think the personal connection is there, you know? And I think that there's a few interesting things about voice. So one is we've all been so scarred by phone trees that whenever we hear voice AI, we're like, oh, my God, it's going to be another press two, press three, press four. It's not that at all. I think the second is that the voice AI companies and sort of primitives, they're not trying to trick the person on the other side. Like they tell the other person, hey, I'm an AI. The third is that the relationships are being formed despite point two, that people know they're talking to an AI. Because we're so, our sort of primitive brain is so trained to react and start to form an emotional connection once it hears something that mimics a human voice on the other side. But despite knowing that it's an AI and it's a machine, you start to warm up to it.

• 27:19Anish Acharya?

  And that's why the AI has been so effective in negotiations, persuasion, building friendships. This is not just low level, unimportant, you know, information gathering phone calls. I think the most important phone call that happens in a business in a given year should be and will be handled by AI.

• 27:36Speaker 01

  Totally, and we're seeing this more and more, right? I spoke to a founder a few weeks ago who's building Gmail for voice. So if you're on a run or you're in the car, you can actually respond to emails by voice. I think that's quite interesting, dealing with like medical appointments, dentist, trying to get a refund from an airline, which we all hate, we've all been there. Doing voice, I think, could be really interesting. Where do you think the opportunities are? Is this more going to be a consumer product and enterprise product? Who wins in this space?

• 28:08Anish Acharya?

  I don't think there's one winner. I think it's a primitive, you know, it's something that everybody's going to productize in different ways. So far, it's been more of an enterprise story than a consumer story. But, you know, there's no reason it can't reach into the consumer as well. I do this thing where I'll sometimes go for walks and talk to ChatGPT, just have a voice conversation where I want to explore topics or ask questions or learn about the history of something. I do it in the car as well. So I think we're starting to see voice as the second interface to the models for consumers after text. And there's no reason it won't get to a lot more scale than it is today. I love the Gmail idea, by the way. I think that's a great idea.

• 28:44Speaker 01

  Yeah, it's a pretty interesting company. It's going to be interesting to see if voice goes to the enterprise side and we're all using voice within teams. Can you imagine going into an office and everyone's talking to these voice agents for ideas or responding to emails? I don't think that's going to work, is it?

• 29:00Speaker 01

  Can you imagine?

• 29:02Anish Acharya?

  I think it would, you know, try to imagine the way that we work today, you know, remixed by these capabilities does feel a little bit strange, but I also just think that we've designed the enterprise to build around the ways that humans like to work, the way that humans like to learn, the way that humans like to specialize. So for example, if you have a call center, you might have a set of people that handle support and a set of people that handle sales. And maybe being great at support means you're very empathetic, you're very patient, you really know the products, you're a user, passionate user yourself. Maybe being great at sales is you're more of a killer, you're a hunter, you're good at persuasion, you've got a really bright personality, you're more of a talker than a listener. Like, these are just two different human archetypes, which is why we have two different

• 29:46Anish Acharya?

  job functions for them. But is there a world in which support and sales is handled by the same agent? Or is there a world where you do some support while you're doing sales, some sales while you do support? So I think this is why the kind of configuration in the enterprise is going to dramatically change. We're no longer constrained to the ways that humans need to work and we can sort of build these things from first principles around what the models can do.

• 30:08Speaker 01

  I think what was really interesting for voice as well is around the creator economy. You know, we mentioned 11 labs earlier, right? Before the show and as, you know, creators before COVID or before these AI models could only, you know, publish content in a spoken language, native language. Now there are tools available where you as a creator, us as a creator, we can have our content translate into every language globally.

• 30:30Anish Acharya?

  Amazing.

• 30:31Speaker 01

  Which is amazing, right? You know, we mentioned we do around a million views a reason month now across all of our channels. If we start translating our content to Chinese, Indian, Japanese, we can get like five, 10 million, nine quickly.

• 30:46Anish Acharya?

  Well, this is what I mean. I mean, the multilingual capabilities of the voice models are so amazing. It also just means, one, that the big implication for the world is just more information diffusion, which is great. You know, we need more of this knowledge. The knowledge was so specialized. Twenty years ago, you had to be in one room in Silicon Valley to get the knowledge of like, how to build a, you know, come for the tools, stay for the network, for example, you know, Chris's famous essay. And that was this sort of lore that maybe five, seven, 10, 20 people understood. And then over time, you know, Chris wrote the blog post, but the blog post is in English and you had to know to look for it. And, you know, hundreds or thousands and eventually millions of people became trained on that framework. But there are hundreds of millions or billions of aspiring founders in the future that have not been trained on it. And one of the things that

• 31:30Anish Acharya?

  holds them back is the multilingual necessity. So I just think that all of these things are pushing to information diffusion, which is a very, very powerful thing. It also means that products are more compelling. You know, if you look at some of these enterprise voice use cases like collections, when you're able to call somebody and speak to them in their native language, you're just able to be a lot more effective, you'll be able to be a lot more empathetic. So I think for folks who grew up in a household like I did, where my parents spoke English, but also other languages, for them to be able to connect in their native language is, it kind of can't be overstated how important it is.

• 32:03Speaker 01

  Totally. We're gonna see a big change in this. And, you know, this is a good segue talking about creators, now the creator economy. It kind of feels, you know, the creator economy, this was a big thing during COVID, right? We publish these creator reports every year. And it kind of feels the creator economy is, is super exciting, but we haven't seen any outlier companies really at the scale versus AI yet.

• 32:27Anish Acharya?

  Yes, yes.

• 32:28Speaker 01

  Is the creator economy still exciting? And what do you think AI's impact is going to have on creators more generally, but also creativity?

• 32:37Anish Acharya?

  Creators are some of the most tremendous people, I think, in our entire society. And I really hate the conversation around like, oh, the kids used to want to be astronauts. Now they want to be YouTubers. Like, yes, they do. And what is met by that, I think the underlying desire is they want to be entrepreneurs. And if you're an individual who's not technical, and not that many people are technical, right? Again, 20 million programmers in the world. The best path to being a digital entrepreneur was probably being a streamer. So I think that is the kind of heart of what people say when they say they want to be a creator or a content creator, but the only thing they've ever been able to create is content. And what they've done with it is tremendous. YouTube, $550 billion enterprise, shows like yours, which get incredible reach and help so many people.

• 33:21Anish Acharya?

  Now creators have two other tools in the toolbox. Okay, so one is in addition to content, they can create software. So creators using platforms like Wabi now have a place to create sort of software. And a software is very different from content in that the value compounds over time, where the value of content can tend to plateau or decay. So you've got this new thing that creators can make, and they will be wildly creative with this canvas that they've been given. The other interesting thing that creators can make is models. And we've seen this a lot in the creative tool space, where you've got all these folks on sites like Civit, who have fine tuned these specialized models to point in a specific artistic direction. And these are individuals doing it. There are non's a lot of the time, they're hobbyists, they're charging money for it.

• 34:06Anish Acharya?

  So I think now creators, giving them more tools, software, models, plus content, is going to make them more compelling than ever. And I expect we'll invest in more companies like Wabi that sort of provide a platform for them.

• 34:17Speaker 01

  Yeah, also, you know, we're seeing this trend now where fully AI-generated movies. Is this really going to be a thing?

• 34:25Anish Acharya?

  Yeah. You know, it's funny. So if you look at the history of film and movies, so the movies that came out soon after the sort of film camera was invented, they looked like plays. Okay, so they'd have set pieces and people would act the way they act in stage plays. And then, of course, what happened was film developed its own grammar. So things like method acting, right? Method acting is a relatively, an innovation that came later. After the invention of the medium, which is of course film and film cameras, it's the same thing I think is going to happen with AI. So today we say things like AI movies, but what does that really mean? I think it means two things. I think, one, you're going to have people that make movies today.

• 35:08Anish Acharya?

  They're able to like do much more ambitious things, be wildly creative and not have to go through the Hollywood gauntlet of getting permission from a financier to execute on your creative vision. But I think the other thing is we're going to see new formats that are native to AI, things like microfilms that might even be disposable. Like you would never make a disposable film five years ago. It's just too expensive, but now you can make a five, seven, 10, 15 minute film at a very, very cheap price with, you know, without the same consequences. So, so yeah, I don't know if AI movies is like a concept we're talking about in 10 years. I think we talk about movies that are assisted by AI plus AI native formats like microfilms.

• 35:47Speaker 01

  I think that's a good take. I've seen a couple of YouTube channels now, which literally started 12 months ago. They have five or four, four, five million subscribers and it's AI generated content with amazing storytelling. I think those types of channels, you know, potentially have really interesting opportunities if they focus on a particular niche.

• 36:05Anish Acharya?

  It's amazing. I mean, I think that the creative vision for this is what if every story was told? You know, how many stories are just left untold? How many of them are, you know, where they're left in a script? Or the movie's even made, but it's not published? Or the movie's made, but it's not sufficiently ambitious? Or the person has the idea, but they don't write the script? Like, we're going to live in a world where all stories are told. And I just, it feels like that'll be a world of creative abundance that we're excited about, not in dread of.

• 36:31Speaker 01

  So many opportunities, right?

• 36:35Speaker 01

  Let's maybe jump on to AI wrappers. We talked about this earlier and it's around, okay, a lot of these AI models provide APIs to startups. And I was talking to someone called PJ, he's a partner at a VC fund called North Zone in Europe. And if these, if these AI models in simple terms provide APIs to startups, they have full visibility on what these startups are doing, how well they're doing. And all of a sudden, two months later, they launched their own version. It wipes out all the companies. Are we going to see more of this? And is it fair?

• 37:12Anish Acharya?

  Yeah, this is a fun topic. So I don't worry at all about the AI wrapper conversation. And let me give you a couple of reasons why. So I think first of all, there are parts of the market where you're very advantaged being a startup. And an important part of the market is any category where the customer gets a better experience when they use multi-model instead of a single model. So if you're at OpenAI, you're only ever going to be able to ship products with OpenAI models. If you're at Google, you only ship with Google models, etc. But if you look at a product like a Cursor or a Kria, these are products where you really want access to every model and every model provider. And sort of definitionally, the labs in big tech are not going to be able to do that.

• 37:55Anish Acharya?

  So multi-model is one really interesting area. I think the second is if you look at models not being products, that's an important distinction, right? So models can do things that start to hint at products, but even if OpenAI replicates Granola's meeting recorder feature, which they have replicated, I think what Granola is going to build, we're not an investor, is an entire AI-native productivity suite with spreadsheets and documents and presentations. And it's just so much feature service for an OpenAI to replicate all of that and think it all through. It's just a really hard prioritization problem for them. I think the last counterpoint to the AI wrapper concern is that you now have

• 38:36Anish Acharya?

  fine tuning of models with feedback, either reinforcement learning through data or reinforcement learning through human feedback, which means that as some of these startups start to get to scale, they're able to deliver a better offering because the data they're collecting is feeding back into a specialized version of the model that is only available to them. So I don't think the wrapper concern is a big one. I think that if you're building a product that is directly overlapping with something the labs do today, then sure, maybe there's some risk. Maybe it's difficult to out Claude code. But if you look at something like Cursor, they've had tremendous success despite from afar saying, hey, that's something that an Anthropic or an OpenAI might replicate.

• 39:17Speaker 01

  True. It's kind of one of those things where I mean, it's going to happen to some solos, but solos should be focused on what they really go at and just execute.

• 39:25Anish Acharya?

  Totally, totally, man. Dude, I also just think that there are some, some of these products are really weird. You know, and I always joke that the, you know, the company's priorities get sent in promo committee for big tech. So if you're at Google, you know, you're thinking as a PM there like, hey, how do I get promoted? And the way you get promoted is not by launching some wildly creative sort of risque new product. You know, you don't say, hey, I'm going to create this like sort of grumpy, personality driven interface to email. Like that is not a good way to get promoted. That sounds very risky. You say, oh, no, no, I'm going to add, you know, AI generated email drafts to Gmail. That feels good and safe and I can go talk to my, my manager about getting promoted based on that. So I just think that for a direction of ambition, you're incentivized to have at big tech is really different.

• 40:09Anish Acharya?

  Whereas when you're a founder, you're like, look, I need to distinguish myself. I want to do something crazy. Nobody is here to tell me no. That's how you end up with a product like Poke, not being a PM at Google or Facebook or wherever else.

• 40:22Speaker 01

  Exactly. You probably have some great lessons from being, you know, in all of these companies. So if you're, if you're a founder, just focus on what you're good at. Why don't we focus on the last trend, which is around social media platforms? You know, I think this has been talked about a little bit, but we haven't seen any new social media platforms really. Substack is probably one. I mean, I know you guys in the best, we're very happy on, on Substack and

• 40:52Speaker 01

  you know, are we going to see more of those types of platforms? Why haven't we seen the new social media platform emerge in the last five, six years?

• 41:00Anish Acharya?

  Yeah. It's a great topic. I mean, I, again, I think we're so trained to look at the last cycle and assume that what success will look like in the next cycle will be similar to the last cycle. So everybody is looking for, you know, the next gen Instagram will look like the last gen Instagram, and I think it'll be totally different. So when I look at a product like a Wabi and I say, look, you know, maybe that's what the next AI native network looks like. Something where the status game is focused on people making the coolest, most interesting software instead of the coolest, most interesting content. I think another question is just around, you know, what is a media format that's native to the new technology? So, you know, video, photograph, all this other stuff, that's

• 41:43Anish Acharya?

  all native to mobile and that's great. But I just don't know that the AI native social network will be based around media from the last generation. The media of the new generation is things like models, things like software. So I do think there's space for a new social product or a new network broadly. I just think it's going to look so different. It's not going to be Instagram plus plus. It just sort of definitionally can't be because Insta is going to build that. I think the critique of a lot of AI so far has been, hey, there's been a lot of, a lot of tools, not a lot of networks. But again, to your point about a thousand days, like where are we if we overlay where we are today in comparison to mobile? You know, we're 2011. 2011 was really before Airbnb, Uber, WhatsApp, everything

• 42:27Anish Acharya?

  got to scale. So it's still very, very early days and it's, it's hard to predict what it's going to look like.

• 42:33Speaker 01

  Where do you think the new social media platforms focus? Are these going to be highly focused type of, you know, vocalized types of platforms? Are they going to be completely open to everyone? You know, when I think about a couple, which have emerged, there are a couple of, you know, very good health and wellness type of platforms. You look at the, you look at some of the likes of Time Left, which is not really a social platform, but it's more around kind of like solving loneliness. I don't know if you know Time Left, but you go and have dinner with strangers. These guys started two years ago. I interviewed the founder a few months ago. $16 million in net revenue they make in just two years by connecting strangers together. That's something quite interesting. But when are

• 43:18Speaker 01

  we going to, we're probably not going to see another Instagram, Facebook, possibly emerge. I don't know.

• 43:24Anish Acharya?

  I mean, Sora was an interesting effort, right? And maybe Sora will work. Like, the cool thing about Sora, what I paid attention to was, one, the status game was very different. I think the status game on X is be the smartest, or maybe shitposting, something like that. The status game on Instagram is like, be the hottest, I guess. The status game on Sora seemed like it was focused on comedy, be the funniest, like, who can generate the funniest, strangest things. My friend Kevin Rose did some hilarious videos that did really well. So, one, it was a different status game. Two, the number of people creating, it wasn't a typical 90-10, 99-1. I think actually, the majority of people were creating at least one video, which is super different from most social products today.

• 44:06Anish Acharya?

  So, these efforts are very, very interesting, and the kind of nature of them, when they work, look really different from the past social products. So, who knows what will happen? But I think we'll have a conversation a year. I think we'll see the beginnings of some new native networks.

• 44:19Speaker 01

  Awesome. Kevin Rose is another awesome entrepreneur. I think you guys go way back, no?

• 44:24Anish Acharya?

  Yes, yeah, yeah, yeah. We've known each other since our days at Google. Yeah, and he's a tremendous person as well. He's very open-minded. So much of his ability to predict what comes next is that he doesn't have preconceived notions that he's trying to back the world into. He's just got the beginner's mind, and he's been early in writing a few times.

• 44:43Speaker 01

  Yeah, see, we try and come well-prepared for all of these shows.

• 44:46Anish Acharya?

  I love it, I love it, Ali. You've done your work.

• 44:49Speaker 01

  There you go, right? A few minutes left, let's talk about fundraising for founders. I think a lot of founders will be, some founders will be freaking out, I have to raise as much as I can, as quickly as I can. Some will be very chilled and quite relaxed about it. How should founders be thinking about fundraising today? Should they be focused on raising as much as they can? Or just be really focused on raising realistic rounds?

• 45:14Anish Acharya?

  Yeah, it's such a complicated question. So, if you think back to First Principles, why is it not optimal for founders to raise all the money they need in the lifetime of a company on day zero? So, if you're a founder, you're going to raise five, and then 20, and then 50, et cetera, why don't you just raise 125 on day zero? The reason that that doesn't work well is actually interesting. It's not because you can't get 125 million, it's because what happens when founders have too much money, and I've been through this myself, is you typically take your scarce resource, which is not money, which is talent, and you spread it across too many efforts. So what you really need is concentration of talent and focus on just one thing at a

• 45:55Anish Acharya?

  given time. And raising the right amount of money sort of drives that concentration. And everybody thinks, I thought it myself when I was a founder, like, hey, I won't get distracted, I'll prioritize. But you just don't. It's hard to like, not, not do many things at once. So I think raising the right amount is really important because it forces a discipline you wouldn't otherwise have. And I think for, for markets that are highly competed, raising a little bit more always makes sense because you want to sort of keep up. I think for markets that are less competed, like, I think Shopify is a great example of just something that was built in relative obscurity and compounded to enormous scale, you don't have to raise as much. But I think that the magic right now is that you can lead with product instead of marketing dollars. So the world we were

• 46:40Anish Acharya?

  in in 2021, which is, look, I have to raise 100 million to spend 100 million on Google and Facebook, that world doesn't exist anymore. It's like, if you have to spend, raise 100 million to train a better model or build a better product, great. Because that's exactly, I think, the kind of, you know, risk capital that investors want to invest in, founders want to raise, as opposed to where we were three or four years ago. So I know that's not a perfect answer. But I think, you know, maybe the brass tacks is raised for 24 months at the best terms you can, but not, you know, such a high price that it makes the next round difficult.

• 47:09Speaker 01

  Totally right. And also, you know, when founders are thinking about how to run a super smooth fundraising process, what have you found is the best approach? Is it just to focus two weeks, go meet as many investors as you can, and get as many term sheets? Or is it a scatty end over a month?

• 47:29Anish Acharya?

  I think it's two things. I think, you know, over the course of time, building relationships. Because I always say, when you need trust, it's too late to build it. So I think having met people that you might want to raise from at least once, maybe having had a coffee, you know, once a quarter over the course of a year is not a bad idea. And then, yeah, when you're ready to fundraise, you should plan to get nothing else done for two weeks. Just put your head down. Let's go do the work. Let's go talk to all the folks that we already have relationships with. And then, like, I think that if you're getting lukewarm reception in the first two or three meetings, you, that's like a very, very important signal. I think that the sort of narrative around investors being more circularly dependent is an unhealthy one for founders. I would just start from first principles. You have a great product, you have metrics to support your assumptions, and then is the investor

• 48:14Anish Acharya?

  conversation, you know, are the vibes good or are they lukewarm? And if they're lukewarm, there might be some more work to do. I think the most useful thing an investor can do other than giving you money is just giving you the real talk. So I think sometimes you've got to torture the investors a little bit, especially if they haven't been a founder themselves. If they have, then they often know that like, look, like, I can't give you the money, but like, let me tell you what's up. Let me tell you like that you've got gum on your shoe, so you can go take that off and let's have another conversation in three months.

• 48:42Speaker 01

  I love it. So, you know, you've seen and met many founders and you've probably got so many cool ideas. You would like to start maybe one day. If you weren't investing today, what company would you build right now?

• 48:53Anish Acharya?

  Yeah, I don't know. I mean, the one thing I would not do is is sort of go work at big tech or scale, you know, because it just feels like right now is the moment to be at the edge. So and maybe there are teams within big tech that are really exciting that are at the edge, and that's the exception. But I just feel like you kind of want to be working on the most important thing, the thing that you can contribute the most to. And I think for me, that would be being a founder or sort of working at the edge, either within big tech or one of the most important labs. The area that I'm personally spending the most energy on is AI code. I just like, I'm so fired up, mostly because I've always been a, I'm an engineer, but a mediocre one. And now I'm a less mediocre one, thanks to the tools and the models. So I'd probably be dreaming of building in something like that.

• 49:38Speaker 01

  Awesome. Well, hey, this has been so much fun, packed with insights, so much information. Thank you so much for your time. And let's come back in 12 months and see just how far AI has progressed.

• 49:49Anish Acharya?

  It's not 12 months. It's another 365, right, Ollie?

• 49:53Speaker 01

  There you go, right?

• 49:54Anish Acharya?

  That's our plan. Thank you for having me. Thanks for providing the platform and I'm excited for our next conversation.

• 49:59Speaker 01

  Let's do it.

• 50:02Speaker 00

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

• 50:17Speaker 00

  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.