What’s Next for Consumer AI? | Josh Elman Joins a16z

16:36But yet the world should be so much richer because of AI and so much more open-ended.

16:40Anish Acharya:So does that mean that the sort of Gen Alpha that's coming up, the Roblox Minecraft generation, will they expect to be able to kind of fork and remix all their utility apps? I mean, what does that mean in practice? I mean, honestly, I think so. Yeah. I think that's actually a huge opportunity is every piece of software, you know, it's still going to have to do a lot of its core functionality. And not every Gen Alpha is going to go, I need to start my accounting software from zero. I need to start my travel planner from zero. But once they've got the thing that does most of those functions, they're going to want to tinker with it.

17:10They're going to want that flexibility. And the apps that will win in the next generation will give people that sense of ownership at the end. Yeah, yeah.

17:17Anish Acharya:Really, really interesting. I mean, it leads to a natural question, which is when it's trivial to create anything, how do you discover things? How scarce is attention? So maybe just talk about distribution broadly. Yeah. I mean, I think this has been this really interesting wave of the internet of how much, so much of it's powered brand new distribution methods. We both grew up through the social era. Yes. Where most of it was virality. And it was a lot of techniques and tactics and testing and learning of how to drive more virality. How to get one person so excited about something, they would share it.

17:50And sometimes some people overhack this with how to get one person to inadvertently invite their whole address. Right. But that never worked. It was always the intentional viral sharing. this is so great, I want you to join me. And then we got so many of those that everybody got a little bit jaded. And you're like, why are you inviting me to another thing in each? And like, all of a sudden, you're going to stop doing that. And so we had to move into this world. You know, search was the other big way of search. And, you know, being able to be search optimized for Google was a massive thing. What we've seen the past five or 10 years that are really the working methods now are the trust we have now in these new creator relationships.

18:22Sometimes they're true social relationships. Sometimes they're somewhat parasocial, but the creators are able to talk about the things that they're doing and exploring and figuring out. And you learn to trust that this person isn't just doing it to make money or an endorsement. They're doing it because they're passionate about what they're tinkering with. And if I like what they're doing, whether it's in beauty or, you know, health or restaurants or technology, I follow some really cool Apple creators. They'll go and tinker with these things and talk about them to the world. That's the new path of discovery is you have to be so good that you're getting those people to talk about it.

18:58And sometimes you can even pay for those endorsements and try to get that started. But honestly, everything only ultimately works if it's true organic, word of mouth. I love this so much. I'm telling you about it at some level. And everything then you do is you feed a lot into the engine to get to that point where your product's so good at spreading itself.

19:15Anish Acharya:So, okay. So let me challenge you on this a little bit because there's something intellectually dissatisfying about creators being the next-gen channel versus the traditional networks. You know, in the old days, the old days, I mean, the value of the Insta network or the Facebook network or the X network is so powerful. And you could argue that the ones who own those networks have sort of maybe abused their powers or used them in ways that benefited them more than the ecosystem. Creators just feels like a weaker form of that. I find that they're the biggest form of that because actually most creators have earned their reputation based on trust and based on a trusted relationship.

19:52Now, I remember in the olden days, you know, it'd be a very famous athlete that would then get up and go, I endorse this cereal. And you're like, there's no way that that athlete is eating that cereal every day. Like, they're just getting paid to endorse it. Right. In the commercial. But now when a creator says, here's my health routine or here's my travel routine. And I went here, here, here. And these two I liked and this one wasn't as good. Yeah. Like, you're actually, if you learn to trust them and build that relationship and follow them along. Yeah. You actually believe it much more. And yet, it scales all the way down.

20:20there are influencers in college, the ones who actually influence their college could be the ones in high school, and there were always that. And so it is still about community. It is still about influencing your friends. But it is in there. I mean, Discord, for example, is another good example. Yeah. All through influence, all through this kind of influence, but it wasn't like these mass influencers. Sometimes it was streamers going, hey, we're playing on Discord now. But most of it was the person who gathers everybody for games would go, hey, I'm trying this new tool. It's way better than what we've been using before.

20:50Or everybody jump on it, and that one person would bring everybody in their group that they played games with. And then a few people would go, that was really cool, and I also played games with this group. I'm going to get this group on, and then I'll do that. So that's even, you know, it's not a micro-influencer. It's a dumb word for it. That's pure word of mouth. But I think it scales all the way down to that.

21:08Anish Acharya:Yeah, that's interesting. So do you think then that that's the channel sort of for the AI-native consumer products? Or is it going to be something like ChatGPT apps directory or Codex? Or is there some other thing that's going to happen? I mean, I kind of brushed over this, but we always talk about virality and search and search was sort of the single purpose tool. I think we're going to be back in the same world where people are going to need this sort of spread this word of mouth, whether that's accelerated through creators or just through individuals being so excited. At the same time, you're going to need to figure out how to do, you know, what they call GEO, generative optimization, where the agents talk about you.

21:43And when someone's trying to solve a problem, the agents will actually do that. And I think there's both huge opportunity for whether it's the directories or whether it's just getting into the content for the model training or the rag, or ultimately, whether these products become really smart and they realize that referring things out makes them better. And right now, I don't think any of the core assistants kind of have that mentality that referring people out makes them actually stronger. But I think that's the biggest opportunity. What do you mean referring people out? When I start trying to solve a problem with Chachapiti or Cod, it does everything it can to solve my problem.

22:20Hey, I want to plan a trip. Hey, I want to figure out a good bottle of wine. I want to do this. But what would be really cool is if it said, hey, I know you're trying to plan a trip. Here's a bunch of things. By the way, here's the resources to go deeper. Yeah. And maybe they'll want to own a few of those verticals, but they can't own them all. And actually being even smarter about knowing when it's good to hand you off, I think will be great. And then it'll create a lot of opportunity for those tools.

22:43Anish Acharya:And perhaps those tools are apps. Yeah, I think a lot of them will become apps in their own services. They'll have some chat experience, but a lot more. You know, when you're trying to plan a trip, chat is great to get some lists of stuff, but then like - It's not awesome. You got to turn it into bookings and lots of other stuff. And, you know, when you're trying to deal with some financial plan, look, it's great to like work through some problems. You still need to turn it into like a lot of actual details. Yeah. And I think those artifacts and managing those are going to be actually better in other services.

23:13Anish Acharya:Yeah, that's really interesting. So then would you say that creators are sufficient for the AI consumer products to get to scale and we don't need an AI native distribution channel? Or do you think there's still something on the come? I think this is what we've got to figure out over the next couple of years. Yeah. I think the short answer is there's a lot of ways to get to scale today. People can get to 10 million, 50 million users in ways you never could before. And all that really matters is if you get to them, do they actually use you? Do you stick? Do you become part of their lives? So I'm less worried about finding just the distribution methods for awareness as much as like what are the products that are actually going to move our habits and change us?

23:54And part of being an AI product today is it has to be so much better than the products that were before. Chat2PT was amazing for a whole bunch of searches that we thought were totally solved through Google. And all of a sudden you start putting those searches into Chat2PT, you're like, this answer is more than 10 times better. This experience is more than 10 times better than Google links back and forth. And I think that's why Chat2PT blew up. And I think for every experience consumers have today, with this new possibilities of building things differently, of presenting things differently, of experiencing them differently, one of those things that the moment you use it, you're like, oh my God, I can never go back to the old way.

24:29Anish Acharya:Yeah. Yeah. Really interesting. So it sounds like you're saying retention is still the most important metric. Is that true? I mean, I think it's always been this idea of, do you really use the product? Yeah. You know, and if you can get me to try something and the willingness to try, what's really cool about this era, willingness to try is bigger than it's always been. That's true. And that's part of what got me so excited to come back to the startup side and the venture side was we can actually get people to try new things. Yes. But trying new things only matters if people stick and bring it into their lives and it becomes part of their lives in a way that they're so excited to tell about the next people.

25:05And everybody is like, how do you get to this many users so fast? And the answer is don't. Get to a smaller number who have moved their lives over to your product. Yeah. Who have truly found something new that they are doing that they will not want to go back from. That's right. Once you find that, then it becomes how do we repeat that? And everything I've gotten to work on in my career has been really fortunate to have found its way to that and then build and compound and set the company up to really scale from that.

25:31Anish Acharya:Yeah, there's some like non-intuitive wisdom in that, you know, like Paul Graham's whole thing about monopolizing a really small market being much better than, you know, sort of having being diffuse across a big market. Similarly, Andrew talks a bunch about the way to build a big network is to build a bunch of small networks, which makes total sense. But, you know, we're so overtrained on this, like, go big, billion users. It's hard to do things on small scale. I mean, the problem is you have to be able to think in both at the same time. Right. Like the best founders I've gotten to work with figured out how to both have that vision of what is billion user scale and why is the world different when we're actually everybody's using it.

26:07But then go, but I'm not going to get there today. Today, I've just got to get to this. and I have to win, you know, this area and convince this group to become passionate. Robinhood's an incredible example where they had a vision to democratize finance for everybody. You can imagine anybody in the world who didn't formally have access to the stock market, to the type of investing products that other people were able to do, to be able to give that to everybody. But that certainly didn't mean overnight you need to be getting every single person to be able to do it, you know, in your retirement account and everything else.

26:38It was like, no, it started very small with, hey, if you are, actively thinking about wanting to invest or actively already trading, we should be a better product for you. And then, hey, for those people who aren't there, who might not even ever want to be investing in single stocks, how can we over time get the right to expand the platform to everybody else? Right. But not, let's go out with 30 products today because that would have confused everybody and landed no one.

27:01Anish Acharya:I'm glad you actually mentioned Robinhood because there's two companies we sort of talk about as the exceptions and the consumer lore from a distribution perspective. One is Robinhood and one is TikTok. Yeah. You've obviously been involved in both. So the way we tell the story, you should tell me if this is correct or not for Robinhood, is that they did do paid acquisition, significant paid acquisition. But because it was this very brilliant mechanic of give a stock, get a stock, you sort of had this non-inflationary customer acquisition cost versus being in an auction on Facebook and Google, et cetera.

27:28Anish Acharya:So, you know, they were able to scale it and it worked even though it was paid. And historically, we sort of say, well, paid is a problem at scale. Yeah. You know, I think what's interesting with Robinhood is they didn't start paid. They started with a product that they thought was just a better way to invest in the stock market. Let's remove the cost of commission. I mean, back then, it cost five bucks or more a trade with any of the other big platforms. And so they said, we're going to figure out how to give it away for free. We know there's going to be other ways that we can monetize, including, you know, they found several, you know, mechanisms through the ecosystem that still were better trading costs.

27:59Sure, yeah, P5. But the key was, it was all word of mouth at the beginning. And they figured out how they were on Reddit. There were Reddit communities that were really excited about it. Anybody just word of mouth on mobile was saying, I kind of want to invest in the software market. This app is great. And by the way, it also had beautiful design. Like one of the things that you needed when you were dealing with people's money was trust. And so beautiful design, an app that showed that people cared and put a lot into it. That's interesting. You know, really helped Robinhood have that initial credibility.

28:26Over time, as you're figuring out, okay, how do we grow from here? Tried a lot of things. Definitely tried some paid ads. And you know what? They worked free. free trading was a message that worked for people who were already kind of in a trading mindset. But if you weren't, it wasn't. But the referral program was really magic. And the secret to the referral program was it was there's a lot of referral programs that were big in the time. Airbnb, Uber had ones like give 10, get 10. You'll get 10 bucks for getting somebody. You'll give 10 bucks. The 10 bucks are the starter for the person who does it.

28:55And like those are nice because you have a little bit of a discount, but it's a dollar amount. You're like, is it worth 10 bucks? Am I trading off my friend for 10 bucks. Robin, here's 10 bucks to invest. What are you going to invest in for 10 bucks? You know, you couldn't even buy a share. So the team came up with this mechanic to figure out how to make it give and get a share, an actual share, and then was able to use the fact that that share was a lottery. Sometimes it would be a$2 stock. Sometimes it would be a$100 stock. And enough people got the$100 stock that they raved about it, and that made them very, very excited.

29:27People get the$2 stock, and they're like, oh, I have a whole share of stock. I can sell that. I have$2 in my account that I didn't have before. And problem and disability balanced that, made it a very, very cost-effective mechanism. So look, when you're doing paid ads to bring people in who are already susceptible to the message, when you're bringing in this referral program to then have people share it and advocate it, and again, referral is not quite as pure as word of mouth, but it's pretty close. I'm only going to bother somebody if I at least believe in it. Or the incentive for me is so good, which they know the incentives, they're getting the same one.

29:59And so it really became this powerful mechanism. And then the brand just kept building and building and building. And people started to trust it more. And the design got even better. And all of a sudden, one day you're like, whoa, this is no longer this little upstart financial thing. But every other company is dropping commissions because they now see the threat. Schwab did it. Ameritrade did it. Schwab then went and bought Ameritrade. Like it transformed, you know, the brokerages all from this little plucky, let's try to democratize finance, but get the people who we can early.

30:32Anish Acharya:Well, it really demonstrates the power of a founder-led company even being post-public. Because now you see what Vlad is doing, sort of agentic trading stuff. I mean, it seems like he's leaned the most into it out of everyone. I mean, I'm just blown away by what they've done with the company, you know, since I've been gone. I left at the end of 2019, and it's turned into this incredible, realizing the vision, multi-platform. It's no longer just trading. It's retirement. It's credit card. It's got some banking components. And all these products that bring in the same care, design, trust for the user, truly trying to bring value.

31:09And Vlad has just done an incredible job navigating the seas. It went through some real bumpy times, too. I mean, so many great companies have had these existential crisis moments. and Robinhood has had a few, but both between some crazy downtimes that happened at critical moments in the stock market, what happened around GameStop that felt like that almost might be existential for the brand, but they came back to their core values. Great design, great product, trust for the user, something people are proud to talk about and share. And they've really been able to win people back and grow a ton from there.

31:39It's amazing.

31:39Anish Acharya:They've done so well. Okay, so we've established that Robinhood was a referral program. So now talk about, maybe just teed up, So talk about Musical.ly TikTok, not everybody may know the connection. And then how they grew, because they are the other great exception, which is anytime we say, well, paid doesn't really work at scale, people say, but TikTok. Yeah, well, and this is a crazy kind of multi-part story. You know, Musical.ly was a group of a small team in China that was trying to build for the Western markets. That was actually their initial vision. They started trying to build an education app, hadn't really worked.

32:11They had seen some fun things happening around lip syncing. and so they decided that they were going to build a little lip sync app. And they built this and they put it on the app store and it said lip sync. And they were seeing spikes every week because Alex, who was the founder of Musical.ly and actually went and ran a lot of TikTok was telling me this, that they were so confused and they found out finally that like the spikes on Thursday night, I think it was Thursday, was because of when Lip Sync Battle appeared on like MTV. So Lip Sync Battle would run and then people would go type lip sync into the app store and they'd download Musical.ly and they'd start creating lip syncs.

32:43Interesting. And... musically they'll design their product in two really smart ways the first was it was really easy to take your video and still go post it elsewhere so you could create this great lip sync video and post it elsewhere but the second thing was they also curated a feed of the great lip sync videos so when you'd open the app you'd swipe through you'd add some friends and you'd create your video and you might go post it on instagram yep and so that loop was create something you couldn't create anywhere else at the level of quality then be able to post it out to instagram and your friends, you'd start following your friends.

33:15So you'd see what your friends had posted alongside some other really cool stuff they were curating. So they really created this loop. And then they found out that there were a bunch of, I'd call them like B plus stars on Instagram who weren't quite getting enough credibility and were only posting pictures. And Instagram video was just coming out at the time. And they were like, let me use Musical.ly to create some cool content for my Instagram feed. Got it. And then on Musical.ly, they'd become the number one stars. They'd become the A-listers, the ones with the most followers because they were getting featured in the feed.

33:43So now you have this loop where the influencers were posting a ton of stuff on Instagram. So you're starting to see Musical.ly on Instagram. You're starting to have a better experience in the feed and people were talking about it with their friends and it all started to compound. And the other secret was there was always a little Musical.ly bug at the bottom of the Instagram video. Right, right, of course. And you could actually download the video. It was like unheard of at the time. You'd create the video in Musical.ly, download it, upload it to Instagram, and it would keep the Musical.ly bug.

34:08People were cutting that out. And it created this great loop. And the company got really big. We got tens and tens of millions of users daily. Hundreds had tried it, and it was in incredible shape. And then they started thinking about whether or not to keep going independently, raise a lot more money, sell, and got this incredible offer from ByteDance to go and join ByteDance. And ByteDance had had a product, Douyin, that was very, very large in China. And so they had kind of both modeled some after Musical.ly, had had their own invention, and had this great AI team. And they were like, we can help Musical.ly scale even more worldwide.

34:44And so they bought Musical.ly, and the team that was already in China became part of that high-tensing. And then they spent about six months or so kind of tinkering, rebuilding the product, moving Musical.ly, and doing it into a shared code base. And then they relaunched it with ads, with dollars. because what they figured out was to get from here to where we want to go, we need to pour a lot more into it. Okay. They got, they spent, they were probably one of the biggest spenders on Facebook, Twitter, kind of every social media to get people to download TikTok at that time. But the product loop was so good that everybody retained because you would sign up for it and all of a sudden with a couple of swipes, you were deeply personalized.

35:24Your friends who were already there on Musical.ly were coming back and trying new things. You were seeing that and it was really energizing and the whole loop worked. And it still took them pouring a lot of money in to get that distribution, but the retention really worked. And I joke at the same time, Quibi was pouring similar amounts of money to get people to download Quibi, which didn't totally work. Didn't work as well.

35:43Anish Acharya:Yeah, yeah, yeah. Okay, so is the lesson from that then that if you have a highly retained working loop, you can do paid and it's okay? I have no problem with people doing paid if they understand it. Yeah. Like paid to both get people in who will become very good retained users and who will spread the word for you can be a great catalyst. What you can't do is spend a lot of money to burn 10 people to find the one who actually stuck with your product and think that that's going to scale because that only gets more and more expensive. That's right. It's interesting. It's sort of adjacent to this is a debate we've had, which is, on one hand, it's amazing that consumers are willing to pay for software, and in a big way.

36:21Anish Acharya:If you look at the top Chachi VT SKU, it's$250 a month. The top Grok SKU is$300 a month. Gemini Ultra, I think, is$300 a month. So, wow, consumers are paying for software. On the other hand, because there's no zero marginal cost of distribution, inference costs money, you can't really build a mass market-free product without a massive balance sheet. Is it better or worse? Is it just changing the shape of startups? I mean, what's your view? I mean, I think there's a willingness to pay and necessity to pay is definitely shifting. You know, we had this period, you know, 15, 20 years ago where everything was shifting to the cloud and all of a sudden the startup cost for our company became much less than ever before.

36:59You didn't have to buy a bunch of servers, rack them, and sure, serving costs a little bit of money in bandwidth and compute use, but it was actually relatively low for what you thought you were getting as a startup. Obviously now, if you're running a ton of inference, you need your customers to be willing to pay for it, but I think they are, and the ability to pay in apps is so much easier than it's ever been. Getting payments is easy if you're providing value, and I think you have to. I think it hearts companies that need massive network effects. Because part of the benefit of these massive network effects was free distribution to everybody helps you get there.

37:35And so I haven't totally figured out what that balance is, but I think that's what I'm excited to go work through over the next few years, various startups.

37:42Anish Acharya:Yeah, it seems like one of the things that could really change that is if iPhones get really powerful GPUs. That's right. It would seem crazy for that to not happen at some point in the future. But I think we're going to be figuring out with the models even that you can run on iPhones or on laptops how to push more and more of the less complex inference that needs to be done onto device to lower the cost. I mean, there's no reason that everything you're ever trying to do, whether it's refining a title or just, you know, rewriting a paragraph or answering some basic questions, those can actually use models that are incredibly powerful that can run on the devices now.

38:14And then you only send the more complex stuff up. And I think, you know, both from the enterprise side, you're going to see a ton of that. And I think from the consumer side, I think really smart founders are going to optimize that too.

38:23Anish Acharya:Yeah, it'll be interesting. I know that Karpathy has done a bunch of work. A few folks have showing that you can actually train and run models on 386s and 486s. Incredible. So I'm sure there's also just a lot of good old-fashioned engineering that will make the models push more and more to the edge. That's right. Okay, so one topic that we discuss a lot is, are the labs just going to win it all? Should we all just go home? And I know it feels like we have a version of this conversation every time there's a new product cycle. What's your view? So I think a funny way to think about this is, 20 years, everybody was like, oh, well, won't Google just do it?

38:56And then all of a sudden, Google could do everything. And certainly, there's a bunch of categories that Google has absolutely expanded on and done great. 20 years ago, there's a ton of startups that have grown and become massive companies since then. 15 years ago, 2010 era, everybody was like, well, isn't Apple just going to do it all? It's going to be everything's going to be their own mobile apps. They have this great world of mobile-enabled apps that we could have never imagined before in these social apps. But about 10 years ago, I kind of started thinking that too. I kind of started thinking about, I'm not sure if there's a world in these networks that are now 1 billion plus users.

39:33If you can truly build another consumer startup from scratch, it's part of why I actually left Venture to go and I said, I just want to build again. And I went to Robinhood, that led me over to Apple, and said, gosh, I'm not sure if you can actually build something big enough in kind of pure consumer areas. Yeah. And I'm not sure if I was wrong. I mean, ChatDBT is obviously a massive. What about Discord? Well, I had invested in Discord and we had just sold Musical.ly. Yeah. And I was like, those are going to make it through. I joined Robinhood, which I said that one's going to make it through.

40:04But starting from scratch, you have to get enough momentum to get to that billion user scale. I was like, I'm not so sure. Yeah. And this is part of my own, like, if I didn't really believe that I could find that path and venture, I was going to go and work on them instead. Yeah. And, you know, part of why I went to Apple was to go learn and work at the biggest scale you can and try to deliver that value to everybody's pocket. But I think right now, I think the world is so open again. Yeah. I think that the main chatbots, the main assistants are going to do a lot for us. Yeah. We're going to rely on them for a lot of things, but I think we're going to expect everything to work like them.

40:39And we're going to rewire so much else of what we do in life and our services and the way we get things done that the opportunities to fill all of those areas of our lives and help us connect and help us get information that we want and help us explore things are not just going to go to like, there's only two products we ever use. Yes. Yeah.

40:57Anish Acharya:Yeah, no, no. Look, I totally agree. And I also think there are ways that startups can play that incumbents can't and labs can't. You know, to me, Companion is such a great example of this because I feel like Companion touches on everything that every committee at a big tech company doesn't want you to do. You know, there's disagreement. There is probabilistic behavior. There's sexuality. There's, you know, there's just all of these ways that you can interact with a product that are very human. And as you know, when you're at really big scale, it's hard to ship things like that. But, you know, I think it is, although having been part of, you know, one of the biggest companies, learning to ship things that matter and make the world better is kind of the fundamental value of what we do and the fundamental value of what you can do when you get to work at that scale.

41:38But when I think about things like the companion products and entertainment and how AI can sort of take us on these journeys, I think it's incredible how much different it can be than everything we've had in the past. We've never had an experience like that. On the other hand, I think it's also a high level of responsibility. We have to be very, very careful with kids, with safety, with, you know, sexuality, with letting people who might be going through any mental challenges to feel like they're getting something served through a product that isn't bringing them back to the community or helping them get the help they need.

42:09So I think we have to very much find that balance. But then once you accept that that's just the baseline, there's so much to explore that not every product wants to be. You know, lots of products don't want to be your best friend. I mean, if you've used any of Siri, it's incredible. It's very much trying to help you get things done. It's designed to help you get things done. It's incredible helping you get things done with the experiences and the content that you already have and what it knows about you and what it can go access in the world. But it doesn't need to be sycophantic. and it doesn't need to be like, you look great today and create that personality.

42:42But there are other experiences where you actually might want opinions on a wardrobe and how you dress and give you tips and treat you a little bit more in that human relationship. I think it's a very different product.

42:54Anish Acharya:Yeah, it's interesting because if you almost unbundle the two, there's a product that's just about getting things done, which sort of almost has no soul by design. Yeah. And that's great and we need that. But then there's also these products that might mirror things that we do, in the rest of the world, which is I might join a volleyball team because I'm looking for friends. And volleyball is like a level of indirection to building new adult male friendships. So I think there will also be companion products that look like that. I agree 100%. I think there's so many that can help us do more of that and explore the world and use, you know, in the background, do things with other people and try to figure out what makes sense for you.

43:32And by the way, I would argue that even the Get Things Done has a soul, but it has a very different soul. It's not trying to replace any human relationships, and none of this really is trying to, it's all trying to augment relationships. It's not even trying to make you perceive it in some sort of human way. It's trying to really be a tool. That's what we are as technologists. We're tool makers. We make things, and they can be net neutral, and it's our job to infuse humanity into them, no matter what we do.

44:00Anish Acharya:I love that, man. Yeah, it does feel like this is a technology to explore our humanity, and we've never had that before, actually. You know, we've had a lot of technology to extend our intellect. Yeah. And that's let us do incredible things. I mean, SpaceX this week is the best example of it. But we really haven't had any technology that sort of, I don't know, helped us be a little more self-reflective. Yeah. You know, social products are fascinating, but sort of exploring us as groups instead of us as individuals. I think that that's a really profound way to think about what we can do with this new technology.

44:31And so much of it is helping you be better. I mean, I've seen these great little apps that are like helping people learn to date by practicing first date conversation. Right, right, totally. And like, it's one of those things that it sounds funny and we're probably both, you know, older and not in that lifestyle right now. But like, if you're nervous about something, being able to like practice is incredible. I mean, I haven't done one of these in a long time. I have to admit, I did use a little bit of going back and forth to ChatGPT to just practice talking and getting back into this kind of mindset because that's how these things help us be better.

45:09Anish Acharya:You know, it would just be so funny and ironic if the result of all this technology is that Gen Alpha, they're just like the most incredible social apex predators. Like the art of conversation is back. You know, it's like the 1950s. I think that would be amazing. And I think we always forget, but that's the generation they've grown up with. They've grown up fully online, fully mobile. And we've seen some of the downsides of this. I mean, I think there's a lot of things happening right now to even like prevent social media from people under certain ages. Mostly because we haven't all done the work to make these as safe and as additive as possible.

45:44But on the other hand, this generation is going to know how to adapt and get the most out of this technology and use it hopefully in better service of others. and hopefully look at some of the examples of what's gone right in the world that they can live up to and hopefully what's gone wrong in the world that they can say, it's our turn to go face.

45:59Anish Acharya:Yeah, it's fascinating. So this class who's graduating right now is the first class that grew up, had ChachiBT for all of college. Yeah, yeah. Which is really, really interesting, you know? And actually what I think that ChachiBT lets you do or the sort of broad AI is actually, you know, what they call the greats in college, which is studying an ancient Roman, ancient Greek sort of everything related to it. It's a sort of individualistic, very abstract, intellectual exploration of things just for the sake of it. And it's a lot of what the technology lets you do. So I hope they are as enthusiastic about it as we are.

46:34I mean, I really hope so. And one of the things that's really heartwarming for me whenever I talk to kids is when they tell me, hey, I don't use it to do my work. Because honestly, I just know that like, that's not what I'm going to get graded on. I might get caught, something else. But what I use it is to help me make my work better. And the fact that you can turn to something like a ChatGPT when you've done some writing and go, how do I improve this? It's such a powerful tool to have in your arsenal. I mean, that's one of the things that I've been using with new Siri on my Mac is, you know, you write something and they just go, how's this sound?

47:09How could I spice this up? How could I make this feel, you know, get my point across a little bit better? and the tips and the things it comes back with really help you go, okay, that's actually a really good tip. I'm going to put that into what I'm writing. And when you're using it that way, these tools are very additive as opposed to replacement. I totally agree.

47:27Anish Acharya:Yeah, it's fun. Somebody that we both know, Eugenia, who you might have actually introduced me to her or at least whispered a good word in her ear on my behalf. Thank you for doing that. We're so proud to work with her. She just said this thing that was so profound and I keep repeating it, which is, look, people are not trying to save time. They're trying to spend time. I love that. And the entire sort of original sin mistake we're all making in assessing these companies is that the average consumer doesn't know what to do with the blinking cursor. They actually need to have things pushed to them so that they actually can explore and not have to be so high agency.

48:00Anish Acharya:Yeah. I mean, I think this idea of time well spent is exactly the right method of what consumers want to get. And this is why building for consumers is so different than building for enterprises is you can't just start me with something and I got a problem. I got to solve it. Give me a blank cursor. I'll just dig into it. It's one of the ways that you want to best spend time. And what we've learned is there can always be a lowest common denominator here. A way to spend more time is more scrolling, more anything. just keep going infinitely or just keep pushing this button in this game and see what happens.

48:32Like you can pull people and lull people into that, but the best products can be smarter and can actually take us from idling away time to actually spending it better. And you want to say, hey, to an AI, like, hey, I'm a little bored or I need some ideas of what to do. You want to like spark you and give you motivation and encourage you to go do things. Either it's get out in the world or just do something new or think about something or be entertained. It doesn't always have to be work or learning. It can just be fun, but still things that add value where you reflect on it after that and you're like, I'm really glad I did that.

49:08Totally.

49:09Anish Acharya:Amazing. Okay, well, maybe to bring us home, give us your kind of request for startups. What are the areas that you're personally most interested in? What do you think is underexplored? I mean, coming out of having worked inside of Apple for a long time and at Robinhood and coming back to venture, I'm thinking a lot about what is this next wave of all the ways that we connect as people, spend time well, whether that helps us, you know, things that help us do things like travel better, you know, manage our finances better, manage our health better, get things done, learn how to do our how-tos, you know, and get through that list.

49:44All these ways that we can use all this new technology to help us get through our lives, spend it really well, and connect with other people. Pretty open-ended because so much right now is built for the productivity and the enterprise. and I can make this team more effective and here's 20 workflows and here's 30 prompts that help everybody. And I'm like, what are the things though that make me so happy to go, I'm using this every day and you should too. And you should too. And I can't wait till we all are because it makes it better for everyone.

50:09Anish Acharya:So Josh, take us through what you're going to work on here at Andreessen Horowitz. Look, I am so excited to be back in the startup world and really get this opportunity to help Andreessen Horowitz portfolio companies figure out their way through this consumer landscape, figure out how to grow, figure out how to tell their stories, figure out how to build their products. And then I'm really excited to help all the future Andreessen Horowitz portfolio companies. Let's figure out who they are, what they're doing, how I can help them, how we can help them figure out their paths. And then, you know, when it's the right time, make sure that they come in and we, you know, as an Andreessen team, really fund them.

50:44Anish Acharya:I love that, dude. Talk about maybe for a moment, what are the kind of specific challenges you've worked through with companies? You know, is it about distribution? Is it about M &A? What are some of the ways? I mean, I think the answer is that the stuff I love helping with the most is thinking about the product and the product loop. How do you onboard people to get to that retained experience? What do you need to do to get people all the way up the ladder? How do you let them bring other people into that network? What does a core product do for them every day? And how do you evolve a single-use product into multiple uses and scale that as a product platform?

51:17So helping people right in the heart of what that product and product strategy is, but also happy to help talk about how you organize your product team and growth team. And it's completely changed in this new era. I mean, everything is different. Things are more different for a product management function and an engineering function in the past six to seven months than the past 30 years of my career. It's incredible how much has changed and navigating that, knowing what worked in the past, but translating that to modern times. I'm excited to do that. And then obviously helping companies figure out their own paths, whether that is M &A.

51:50There was a period earlier this year where I had a couple different friends who were going through M &A processes and I was talking to them multiple times a week, helping them just think through the options, how to set up right for every meeting, how to do this. And then lastly is how to tell your story. And one thing I've gotten this incredible masterclass getting to work at Apple is been right in the heart of how do we tell a compelling story to regular people? How do we We take this world of AI and intelligence and distill it into products that we think people would want to use and bring into their lives every day.

52:21And I'm super proud of what the team put together as this most recent WWDC and how we've told the story of Apple Intelligence and Siri AI. And I can't wait to bring more of those lessons to companies as well. Incredible. How can people get a hold of you? They'll be able to email me at jellman at a16z.com. Find me through all the social medias. Find me through a friend. And I'm really excited to help. I love it. Josh, welcome to the team. Thank you. Excited to be here. 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.

53:01For 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.

53:41disclosures.