The a16z Show - The State of Consumer Tech in the Age of AI

Episode Date: June 6, 2025

In this episode, a16z General Partner Erik Torenberg is joined by the a16z Consumer team—General Partner Anish Acharya and Partners Olivia Moore, Justine Moore, and Bryan Kim—for a conversation on the current state (and future) of consumer tech.They unpack why it feels like breakout consumer apps have slowed down, how AI is changing the game, and what might define the next era of products. Topics include:The rise of AI-native consumer tools and companion appsWhy users are now spending $200+/month on AI productsThe missing AI-powered social graphWhy speed and iteration may matter more than traditional moatsAnd what it means to build for a world where software touches everythingFrom shifting business models to new behavior patterns, this is your pulse check on where we are—and where consumer is heading next.Timecodes:00:00:00 – Introduction to Consumer AI00:01:00 – The Evolution of Consumer Breakouts00:03:18 – The Shift in Consumer Spending00:08:00 – The Future of Social Networks with AI00:13:00 – Enterprise Adoption of AI00:20:42 – The Rise of Voice Technology00:23:06 – AI's Role in Enterprise Conversations00:25:25 – AI in Education and Personal Development00:26:34 – AI Companions: The New Norm00:31:52 – The Future of AI Companions00:38:50 – Speculating on New AI Platforms00:42:07 – The Social Norms of AI IntegrationResources: Find Anish on X: https://x.com/illscienceFind Olivia on X: https://x.com/omooretweetsFind Justine on X: https://x.com/venturetwinsFind Bryan on X: https://x.com/kirbyman01Stay Updated: Let us know what you think: https://ratethispodcast.com/a16zFind a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

I think in the future you're going to see consumer spam to be like food, rent, software. All of the aspects of our lives are going to be intermediated by the models, and we're going to pay for that. The definition of what a companion is has evolved so quickly from either a friend or a girlfriend to like anything, any sort of advice or wisdom or entertainment or counsel you could have gotten from a human before. Maybe you just need to feel connected to something. It doesn't need to be human. I think it's been a puzzle to me what the first AI social network is going to look like. To work, a social network has to have like real emotional stakes. We're living in this early era of AI where velocity is demote.

For decades, consumer tech followed a similar beat. New platforms, new behaviors, new breakouts. Facebook, Twitter, Instagram, Snap, TikTok. But lately, that rhythm has changed. and so as the nature of what we mean by consumer. In this conversation, we bring together A16Z's Consumer and AI investing minds to ask, what is the state of consumer in the AI era? You'll hear how creative tools like Mid Journey and VO are reshaping expression,

how voice is becoming the new interface, and how companions, AI ones, are filling in social white spaces. We talk about retention and revenue curves, defensibility beyond network effects, and why velocity might be the new mode. We also get speculative. What happens when AI knows you better than your friends do? What does the next social platform look like? And are we heading towards a world where software, not shoes, not handbags, is the new luxury good?

This episode is about new form factors, new business models, and a new definition of connection. Let's get into it. As a reminder, the content here is for informational purposes only. Should not be taken as legal business, tax, or investment advice, or be used to evaluate any investment or security and is not directed at any investors or potential investors in any A16 Z-4. Fund. Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. For more details, including a link to our investments, please see A16Z.com forward slash disclosures. It seems like every few years there was a breakout,

starting from Facebook, Twitter, Instagram, Snap, WhatsApp, Tinder, TikTok. Every few years, there was this sort of new paradigm's new breakout. And it feels like at some point a few years ago that just stopped. Why did it stop or did it stop? Would you reframe how we should think about that? And where do we go from here? I would argue probably Chachybt was a huge consumer outcome and winner in the past few years. And we've also seen a bunch of other ones in various other like modalities of AI in like image and video and audio companies like Mid Journey and 11 labs and Black Force labs. Now things like Kling and VEO. Weirdly though, a lot of them don't have the same like social or traditional consumer dynamics that you mention. I think because AI is still relatively early and so much of the new products and innovation

has been driven by research teams who are like so good at training models, but historically have not been amazing at creating the consumer product layer around them. So I think the optimistic view is that the models are now mature enough and many are available either open source or via API for people to build great, more traditional consumer products on top of them. It's interesting that you asked that question because I was thinking about the past, what, 15 years, 20 years, where, as you said, like Google, Facebook, Uber, all the names. And it's interesting because when you think about internet, mobile, cloud, everything together, there were all these amazing names, and you asked has that slowed down. I think the cloud, mobile, all that had a lot of maturity

baked in. Like the platform was around for like 10, 15 years, every little nukes and cranny that has been explored to some extent. The changes that people had to adopt was Apple coming out with new features, as opposed to changes that people need to adopt now is the underlying relentless model updates. So I think that's one different. But the other thing is, again, just you touched on this,

but if I think about the past historical winners, there's like information area like Google of the world, and now I think chat GPT is certainly doing that. And they're the utility we messed out like box and drop box of the world. They are more consumer, prosumery that people use where we also see a lot of the companies

attracting and going after that use case. Expression, creativity, same thing. The creative tools are endless and that's happening. What I think is missing potentially is connection. Like this social graph, this thing hasn't rebuilt on AI yet. And that may be just a white space or something that we just continue to see what develops there. It's interesting because Facebook's almost 20 years ago at this point, like the companies that you mentioned justine aside from Cheshivin and Open AI, are they going to be around 1020?

Like, what is the defensibility of the companies we're talking about? And also the use cases of all the companies I mentioned, are they going to be disrupted by these new players? Or in 10 years from now, will they continue to be sort of the mainstream application for all those use cases that they serve? I mean, you could argue that chat GPT has got way higher business model quality than the analogous consumer companies from the last product cycles, right? Their top skews $200 a month.

At the top, Google, consumer skew is $250 a month. So, sure, there's a question of defensibility, networks, all these other things. but that might have been a response to the poor business model quality that would have occurred if you didn't have those things. Now you can just charge people a lot of money and perhaps we'd been overthinking it previously. Yeah. There was poor business model quality,

maybe stronger, sort of retention or product market, or durability. Yeah. Like you had to have a story for how this, it was like compounding enterprise value in the absence of just making money right away. And now these models and these companies are just making money right away. Yeah.

I think the other thing is, Justine, you talked about this. Like all the foundation models are kind of pointy in different ways. So you could say, look, Claude and the Chachybth horizontal model and the Gemini model, aren't they interchangeable and doesn't that mean price pressure? But different people use them for different things. And it seems like they're raising prices, not lowering them. So I think when you like zoom in a little closer, you see that there are like some interesting defensibility dynamics that are already there.

The increasing price, not decreasing in an interesting point because monetization is clearly a different thing from previous era to AI era, especially for consumer companies. They're making money right away. One thing that's always on my mind and Olivia tell me if you think that's not correct, but like the retention, when we talked about retention on the consumer subscription model before AI, I don't know if we actually try to make a differentiation between unique user retention and revenue retention because they're like kind of the same. Like you don't get to change pricing that often. You don't get to upgrade. Like it's the same thing. As opposed to now, we make a very clear differentiation between unique user retention and.

revenue retention because people actually upgrade, they actually have all these like credits and points they need to actually overages that they actually end the spending. So you actually see revenue retention being meaningfully higher than unique user retention, which again, like I haven't seen that before. Yeah. Yeah. I think before the average consumer subscription was maybe $50 a year, if that, that was kind of a lot. Like the best in class consumer products would charge that. And now we have people very happily paying $200 a month. And even saying in some cases that they feel like they're being under charge for that or they would pay more. How do we explain that?

What value are they getting such that they're paying? I think it's doing work for them. Like consumer subscriptions in the past were around things like, I don't know, personal finance, fitness, wellness, like things that. Entertainment? Yeah. But there were things that ostensibly would help you, help yourself, entertain yourself. But you would have to invest a lot of time to get the value from them. And now with products like deep research, for example, that could replace 10 hours of generating a market report by yourself.

And so that kind of thing is easily worth, I think, for many people, $200 a month, even on one or two generations. I mean, I think things to, like, V-O-3, like, people are paying $250 a month. Unfortunately, I've since, it's a limited, the $250 for plan. You're the wail, Justine. You're the $1,000 a month. I've since charged several more of the $50 credit packs. So I probably spent, if I had a guess, like over. $500 in the first few weeks of 9-8-3.

It's why revenue retention is higher. Yeah, exactly. And I'm happy to pay that because it's like you have this suddenly, it feels like a magical mystery box that you can open in and get whatever video you want, only for eight seconds. But it's incredible and the characters can talk and you can make amazing things that you can share with friends, make like personal memes of someone delivering a message to your friend with their name in it.

Create full stories that people are posting on Twitter and Reddit and all of these different places. It's sort of like nothing we've seen before in terms of what consumer products can actually do for people. It seems like every part of consumer discretionary spend is going to be overtaken by software. And I think in the future, you're going to see consumer spend to be like food rent software. And that's kind of where we're going, which is Dean speaking to.

And can you give some examples of that? Well, a lot of it is what Olivia said, right? So I think all the entertainment is being subsumed by it. A lot of the sort of creative expression work that you would do outside of software is now being subsumed by it. A lot of the sort of relationship intermediation, which might have been a place for dispositions, income spend is being subsumed by it. So all of the aspects of our lives are going to be intermediated by the models,

and we're going to pay for that. Brian, you're saying what we're still missing is connection from this new paradigm, and people are still relying on sort of Instagram, Twitter, some of the other social networks of the past. What's going to get us to something new here in the realm of connection? Or is that just been one data network effects? No, it's funny. When I think about social, which is a category that I get so excited about,

At the end of the day, a lot of it was status update, right? Facebook, Twitter, Snap. It's just like, here's what I'm doing. And through status update, you feel connected to that person. And that status update showed up in different modality. You used to be, here's what I am, here's what I'm doing, to actual photos of where you are and what you're doing to videos and short-form videos now. So now people feel connected to others through reels and what have you.

So I think that has been. one era of feeling connected with others. Now the question is how can AI help that? How can AI feel like you're connected to other human beings and know what's going on in your friend's life? The truth is if I just think about modality of photo, video, audio type things, I think a lot of it has been explored. Different versions and mutations of that have been explored quite extensively,

especially on mobile. I think where we could get to is, it's funny, I don't know about you guys, but I pour my heart and soul into chat GPT and knows more about me than probably Google potentially, which is an insane thing to say. Like Google, I've using Google for a decade plus and chat GPT may know more about me than Google because I type more, I tell it more, I give more context. What my connection feel like when that essence of me is shareable with others? And I don't know if that's the next version of feeling connected, but I can certainly see a world where that is that resonates with a lot of folks nowadays, younger generation, et cetera, that are tired of just looking at the surface of stuff.

I mean, we already see some examples of exactly that where, like, there's all these viral trends where people are like, I ask my chat, GPT, based on everything you know about me, write my five strengths or weaknesses, or, like, make an image of who you think the essence of me is or make a comic, like, about my life. and people are sharing those everywhere. I posted one the other day, and within minutes,

I had dozens of people responding with their own and sharing stuff people I didn't even know. I think the interesting thing, though, is so far, the social behavior that has come from the AI creative tools largely, but also things like chat GPTE, is still happening on the existing social platforms and not in the new AI platforms. Like Facebook now is like a lot of AI content.

Potentially unbeknownstice on with audience. Facebook is like the boom. For AI swap and then like Reddit and reels are like the younger people's AI content. tragic. Yeah. I agree. I think it's been a puzzle to me what the first AI social network is going to look like. Because we've seen attempts at, for example, like a feed of pictures of you that are AI generated.

And I think the problem there is that to work, a social network has to have like real emotional stakes. And if you can generate the content in a way that you like it and you always look amazing and you always look. and you always look happy and you're always in a cool background, like it doesn't have the same sense of stakes. And so I don't think we've seen the version of what a ground-up AI social network would be. You use the word skeuomorphic. A lot of the AI social products that mimics Instagram feed or Twitter feed was bots and AI. That feels skemorphic.

That feels like this is what it used to look like. We're going to do it, but with AI. And maybe that's not really the form factor. And, you know, there's an additional hurdle in my mind. that a true consumer product probably needs to leave it mobile. And for AI products to work really, really well, I think there's still a little bit of work where the cutting edge models can do

to live on edge, live on the device side of things, to really enable that. So I'm also excited to see what happens there. It seems like people recommendation is the obvious use case at some point, like who would be good for me to start a business with, who would be good for me to be friends with, who would be good for me to date.

These platforms get all this information about us, connect the dots. I mean, I think an interesting area that's maybe informed like where this all goes is if you look at the AI native LinkedIn efforts, the observation is that LinkedIn is a pointer to what you know instead of actually containing what you know. And with this tech, we can create a profile that actually contains what you know so I can talk to synthetic ET and get all of your wisdom. Perhaps that's what future social looks like as well. That's what you're talking about, Justine, right? If the models already know who you are, then is there like a synthetic you you can deploy? in an interesting way to interact with people.

I don't know. One thing I heard you guys say is that when surprised that you guys sort of realized was that enterprises are sometimes adopting these products first before consumers, which feels different from previous error, or maybe not what we expected. What can we say there? Yeah, that has been fascinating.

And BK and I saw that a lot with 11 labs, which we were relatively early. I think we did the series A a month or so after the initial launch. And I think what we saw was first the early adopter consumers got on board and they were making memes. they were making fun video and audio, they were cloning their own voices, they were doing game

mods. But then I would argue it hasn't even gone in many cases to the true mainstream consumer. Like it's not yet every single person in America or most have 11 labs on their phone or have a subscription. But the company has these massive enterprise contracts and a ton of huge customers across like conversational AI, entertainment, tons of different use cases are using 11. And I think we've seen this across a bunch of AI products, which is like, there's an initial consumer virality moment, and then that actually leads to lead generation in enterprise sales in a way that we did not see with the last generation of products. Like enterprise buyers, there's so much of a mandate to have AI now, an AI strategy and use AI

tools, that they're watching places like Twitter and Reddit and all of the AI newsletters. And they're saying like, hey, this looks like a random consumer meme product, but I can actually think of a really cool application of that in my business and become the hero for having our AI strategy. I've also heard of like similar in that vein, really exciting use cases of AI where you start with consumer virality. So, you know, from a company side, you get all these stripe payment data. You look at all the stripe cells and you basically put it in an AI tool to go try to find

where they work. And then when you find out more than X number of people working in that company, you reach out and say, hey, by the way, looks like 40 plus people are using a product. what's up? I think the fact that they can do it was one person on an hour was like really what really struck me. It was a chief of staff guy who was like, yeah, what I do is do this. And like it all does it in like a couple minutes.

And then I send a mass email out and that's Jesus. Okay. That's like a go to market at extreme speed. Yeah. Justine, you rattled off a list of products and companies in the beginning of this conversation. What I'm curious is do you think just as examples, are they sort of the Myspace or Friendster? Are we in sort of that era? Or are they the list of companies?

I rattled off that are still relevant 20 years later, like, where are we right now? I mean, I think our hope always is that every big consumer AI company now that we see in love and use all of the products, which we all do, sticks around. I think, unfortunately, that's not always going to be the case. I think maybe the interesting differentiation in AI versus the last era of consumer products or even two eras before is like the model layer and the capabilities are still improving. Like we have really not even, I think in many cases, scratch the surface of what these models can do.

I think we've seen that in things like the VO3 launch where it's like you can suddenly have multiple characters talking, you can have native audio, you can do all of these things. Like all of these modalities, I don't know, maybe we could argue about this with the text people. The LLMs are more mature, but have the opportunity to just keep improving capabilities as they scale. And I think what we've seen is as long as a company stays at

what we say is sort of like the technology, or the quality frontier. So as long as they sort of have a state-of-the-art model or are integrating one or something like that, they won't become like the Myspace or Friends or whatever. Like they just keep, you fall a little bit behind, you ship the new update, suddenly you're number one again and you keep moving.

The interesting thing now, though, too, is we're starting to see even segmentation in that. So like an image, for example, there's not just one best image model. There's like best image for designers. There's best image for photographers. there's best image for people who can only pay $10 a month versus the people who can pay $50 or $100 a month.

And so I think there can be, just because Ganesh mentioned, people are spending so much, there can be multiple winners that persist over time as long as they keep shipping. I absolutely agree. I mean, even in video, it's like different video, but ad video. And then even in ad video, I saw a post yesterday.

I'm like, this is best for product shots and this is what best with people. And it goes on and on. And each ad though I think is a very large market. Yeah. See more about how we, I know we talk a lot about defensibility and moats and how that is changing this error, how we've changed how we consider that topic. I've gone through a little bit of a come to Jesus woman on that, especially recently.

I think moats always been very important, right? The goal standard is this network effect being part of the workflow, being system of record and these are all very, very important moats. And I will posit that that's still very important. But funny enough, like I would say the companies or investments, that I've reviewed with this moat first theory has not really been the winners. And the winners in the category that we look at

has always been the ones that break the mold, move really fast, have these incredible model launches, have these incredible product generation speeds. And I've sort of come around that in that, we're living in this early era of AI where velocity is the mode. And whether that's in distribution, which is incredibly important, hard to break through noises these days, but also followed with product velocity, that's what

wins the game because that what leads to Mineshare. And frankly, right now, mine share and users and traffic, that actually converts to real revenue that gives you more ability to continue that journey. It's interesting. Ben Thompson, I think a decade ago at this point, had this blog post called Snapchat's gingerbread strategy where he was basically saying, hey, anything Snap can do, Facebook can do better, But Snap is just going to keep sort of coming up with the next sort of innovation. And if they could just keep doing that, maybe that's their mode.

And he called it the gingerbread. It's a good. It's a good theory. I think you just keep going to. Keep adding candy to it. Yeah, that's funny. And at some point it'll be such a beautiful gingerbread house. You know, I think that worked to some extent.

Yeah. And famously, I think Evan joked that he's the chief product officer about it. I think distribution and network effect ultimately kicks in, right? And Snap has that too when I saw. where it sort of has the corner of Gen Z and the younger users as like a core messaging platform. How do we think about network effects for these new products? I think it'll, we're not there yet where I think it's because it's mostly creation efforts right now. There isn't really a close linked, close loop with creation, consumption, network effects, social network.

So I think we're still a little early before a network effect kicks in. But I think we see that in, we see a different type of remote form in the likes of a level. Like I said, because it moves so fast, because the product is very good, it gets to go into enterprise and gets to get locked in into the workflow. So I think that version of moat we're starting to see, I think the true network effect we're still looking out for. I think 11 is an interesting example. I was making an AI generated video the other day that I needed a voiceover for.

And 11 now, because they had a head start, they had the best models, which then more people were using the product, they could make the models better, all of these compounding advantages. they now have a library of people who have uploaded their own voices and their own characters. And so for me, when I was looking across a bunch of voice providers, if I needed a very specific, like, old wizard mystical voice, like 11 had 25 options for that fit what I need where another platform might have, I don't know, two or three. And so I do think it's early.

Yeah, that's interesting. But we're starting to see signs of that. But they're more like traditional network effects that we saw with old marketplaces. They're not necessarily something like completely new. I want to go deeper on voice as we talk about sort of new paradigms and form factors. We got excited about voice pretty early on, or we're the first friend that I saw a thesis around it. Anish, why don't you talk about what got you so excited about voice in this new paradigm and what's sort of played out and what hasn't yet? Where do you think is going?

I mean, the original observation, and Olivia really is our voice experts, so we should hear from her. But the original observation that got us started was that voice has intermediated human interaction since the beginning of time. And yet it's been not a substrate on which technology has been applied because we just, the never worked. And there's all these previous efforts, voice XML and voice apps, and it just, it simply didn't work. The technology wasn't ready yet. And even then, there was these pockets of Dragon Naturally Speaking and all these products from the 90s. So there was always interest in voice, but it never made sense as a technology substrate. And now with the generative models, you can just use voice as a primitive. So it's sort of unexplored, yet so critical to our

day-to-day lives. It feels like a perfect area where you'll see a lot of AI-native efforts. Yeah. I think we first got excited about voice from more of a consumer perspective, like the idea of an always-on, like, coach or therapist or companion in your pocket that you can talk to. And that has started to play out, I would say. There's lots of products where that's working. I think what surprised me, at least, is as the models got better, like real enterprises have picked up voice so quickly to replace human beings on the phone or to augment what human beings are doing on the phone, even in really sensitive and critical categories like, financial services because previously they were using offshore call centers that also had lots of compliance issues and had 300 percent annual turnover and were really difficult to manage. And so I think we're still waiting to see in many ways what the first great, truly net new consumer voice experience will look like. There's some early examples. I think people are pulling chat GPT, advanced voice mode into fascinating directions. We've seen products like granola blow up because they allow people to finally, for the first time,

do something valuable with all of the things that they're saying all day. But the great thing about consumer is it's completely unpredictable. And the best products emerged out of nowhere. Otherwise, they would have been built already. So I'm excited to see what happens in consumer voice in the next year. For sure. I mean, it feels like voice is the AI insertion point for the enterprise period. And I think the thing that everybody is missing right now is that this sort of mental model many folks have is that the low stakes conversations will be AI voice, the customer support, etc.

But what we've talked about is like the most important conversation that happens in a business in a given day, week year is going to be intermediated by AI because AI will just do a better job with the negotiation or the sales pitch or the persuasion or the friendship. What's going to be sort of the first use case where people are going to be talking to synthetic versions of ourselves, like in a sort of consistent, relevant way? Like, why are they going to be talking to sort of AI justine for AI, Anish or AI me? We've seen a little bit of that. There's companies like Delphi that sort of create AI. clones of people who have a big knowledge base that they can go and reference and you can get advised or get feedback or things like that. And Brian sort of alluded to this earlier, there's this really interesting question of what if you allow not just like thought leaders or experts to have

this AI clone that you can talk to via text, voice, maybe even video one day, but what if you unlock that for everybody? One of the things we think a lot about in consumer is there's a lot of people who basically have had some sort of skill or insight or knowledge, whether it's your first, you're friend from high school that's like insanely funny and you always thought they should have a comedy cooking show, but they just never were able to break through or get it or your guidance counselor who had incredible advice. Like how can we enable those people to essentially scale themselves in a way that they never could before having an AI clone or an AI persona? What we've seen as far is a lot of that has been either thought leaders or experts or on the other, like total

other end of the spectrum, like characters that people already know and like. We saw early versions of that with character AI, which added a voice mode, where there's this poll, especially when you're trying out a new technology to have some sort of familiarity of I'm talking to this character from my favorite anime series that I already know and love. But I think we'll start filling in everything in the middle that's not just like a character, a fictional character, not just a human thought leader, but like all of the real people in between. I mean, I think people learn in different ways and AI voice products play really well to that. Masterclass launched kind of an interesting beta where they take people who have already recorded courses on the platform and turn them into voice agents,

where then you can ask questions that are really specific to you. And for my understanding, it basically does rag on everything they've said in the course. And so returns a fairly customized and accurate result. And that for me is interesting because I'm a fan of them as a company, but I've never had the attention span or the time to sit down and watch like a 12-hour masterclass. But I've had some really interesting conversations with the masterclass voice agents where I can talk to them for two or three or five minutes. And so I think that's an example of where we'll see real people turn into AI clones in ways that are useful.

Drawing on that one of the things that we said earlier, which is enterprise they're pulling these type of things faster even than customers. Like we actually talked to a company that from its inception recorded every single interaction of every single employee. So when the employee's gone, the ghost lives there. And you can still get all the whizom. Terrifying. Terrifying. But also, I'd love to continue to get wisdom in. thoughts from the greats, you know.

Echoes the idea that everyone's replaceable. And it's interesting. By yourself. By yourself. Yeah. We only need you for five hours. But I thought that was fascinating, like crazy. Like everyone's sort of ghost version that lives on like Harry Potter.

It's also like, do you want to talk to a synthetic version of a person that you find interesting? Or is there an entirely synthetic person that doesn't exist in the real world that is a perfect match for your interests? And maybe that's a more interesting question. What does that person look like? they might even exist in the world, but if you don't meet them, you don't meet them. And now they can be sort of brought to life with this technology. Yeah, it's interesting to think about what are the set of use cases for which we're going to want to have a human or someone we think is a human sort of doing the activity versus where are we going to be more open to that.

Like I think Olivia's point is with the master class thing, there's already this parissocial relationship. So there's value in feeling like you're talking to a specific instance of a person versus talking to the abstract most interesting person you may ever meet where you don't need to have that. pre-wired. Which may be chat GPT. Wasn't there like a viral tweet that someone recorded in a New York subway? Like this person was fully talking to chat GPT as if they were talking to girlfriend.

Yeah. Yeah. And there was another one where this parent posted, they had lived through 45 minutes of their son asking questions about Thomas the Tank Engine. And they couldn't do it anymore. So they gave him the phone. They put voice mode up and forgot about it

and went to do something else and came back two hours later. And the kid was still talking to chat GPT about Thomas. the tank engine. In that case, like, the kid has no idea who the character on the other end is. They just know it's a person who wants to go super deep on their interests. Right. And there is no human that can talk about a tank job for that many hours. For two hours and 45 minutes straight. That's right. I mean, if we go to chat, GPT, or Claude right now for therapy or coaching, I'd prefer to go to my sort of AI clone therapist or coach and maybe in the future we record

our session so that they have the data or the therapist or coach has like so much content online that we could just recreate them. But yeah, to your point of like five, 10 years from now, will the top artists be sort of new versions of Lil Mikaela, you sort of AI generated people, or will they be sort of Taylor Swift and her just army of AI? Or a duet. Yeah. A little bit of both.

And similarly on Twitter, the social characters that we follow the next Kim Kardashian, is that a real person or is that AI generated? Do you have a hypothesis on it? I have been thinking about this a lot for a couple of years because I think we all followed little Michaela closely. Then we followed some of the, like, K-pop bands that I think were the first to start introducing, like, AI, hologram-based type characters. I thought you were going to say they were AI generated. I was like, that would make sense to me.

No, one or they went to the military, so they, like, replaced them with an AI. Something like that. And then I think we've also really closely followed, like, this is sort of tied really closely into photo, realistic image and video, because we're now seeing people create these, like, influencers who get a ton of attention and followers, largely because they now look realistic enough. that you don't know if they're AI or not, and there's a lot of debate around that. My take is probably there will be fragmentation into two types of creators or celebrities. One type is like a Taylor Swift type

where like the human experience of it, I think, matters in some ways. Like a lot of people not only love her song, but resonate with the things that have happened to her in her life and her stories and her live performances and like all of those things that AI cannot yet replicate. There's another type of celebrity or creator who is more like interested. space. What we were talking about with ChatGBTDB talking about, like, Thomas the Tank Engine,

it sort of doesn't matter if that person has lived the real human experience or not. It just matters if, like, they can be interesting talking about or sharing content around a certain topic. And so if I had to guess, it will still have both. Yeah. This kind of gets back to the great, like, AI art debate that always reaches on. Yeah. Which is like, yes, anyone can generate art now easier than never before, but it still takes an enormous amount of time to make great AI art. We hosted an event with a bunch of AI artists last summer. And many of these people, when they walked you through their workflow of making an AI movie, it actually probably takes just as much time as it would have to film that. But maybe they didn't have the skill set. So they'd never be

able to do that before. And so I think we've seen, yes, an explosion of like influencers that are AI, but still very few of them have risen to the top and become the little Michaela's. There's only been a couple. So I think we're going to see something similar happen where we're going have pools of AI talent and pools of human talent and the very best of each is going to rise to the top. And it's going to be a really low conversion rate on both, which is probably how it should be. Or non-human talent. Like I think like AI unlocks. One of the interesting things we've seen in V-O-3 is like that street interview format, but like the person being interviewed is like an elf or like a wizard or like a ghost or these furry blob characters that Gen Z loves talking to. Like those could all

be AI. Like that sort of thing is very interesting. I mean, I think we see this in music too. I think a lot of music, the problem is that the music that the AI generates is it just feels very mid. And definitionally, these things are averaging machines and culture is supposed to be at the edge. So I think it's more of a problem with bad art versus bad artists. And we're conflating those two things and saying it's AI. It's not the AI that's the problem. It's the bad art that's the problem. So if the art was at the same level, you don't think that there's necessarily any, that people

would just want to hear from humans. Well, potentially. And then I also think this is where we start to get a more philosophical. topic debate, which is if you train a model with all the music up until but just prior to hip hop, would it like in for hip hop? I don't think so because music is the intersection of past music and culture is critical to it. So you sort of need something that is at the edge and outside of the training data to create new interesting music. And that sort of definitionally doesn't exist in the models. Fascinating. So some of my closest friends who are some of the most talented

people I know are working on a gay AI companion app, which the 2015 version of myself, upon hearing that statement would have been like, what? That's the thing. But one of the things they were saying is that on our lists, 11 of the top 50 apps were companion apps. So let's reflect on, are we just at the beginning of that trend? Is there going to be all these different vertical companion app? What is the future of this? How do we think about that? Everyone's looking at me? Yeah. Well, you've done the most work here. Yeah, we've done an enormous amount of time in every facet of companionship from the like therapy, coaching, friends, all the way to the like not safe for work, AI girlfriends. Like, we've looked at basically everything. And interestingly, I think

like it was probably the first mainstream use case of LLMs. We like to joke that like literally any chat bot, whether it's like your car dealers, customer support or whatever, people try to turn into their therapist or their girlfriend. Like you talk to these companies and you look at the logs of the chats and it's like a ton of people just want someone

or something to talk to. And the fact that you can now have a computer be talking back in a way that's like immediate, always available and feels human, is just like a massive unlock for so many people who could never get that before or felt like they were just yelling or talking into the void.

I would argue we're just at the beginning, especially because the products that have existed were largely very horizontal and came from or were exclusively from the base model providers. Like people were using chat TPT for all of these things it wasn't designed for. We've already seen a bunch of cases where like an individual company can create a personality for a character

and embody it in some like digital avatar and prompt it and, create a game or a world around it that gets a ton of engagement. Companies like Tolan that are doing this for teenagers and college kids, whereas a totally different company, which I would also call a companion, is like allowing you to take a photo every time you eat something. It pulls out and analyzes all of the data. And then it gives you all this information about how you're doing nutrition-wise and

allows you to talk to it and get emotional support. Because for a lot of people, like food and eating issues are tied into kind of emotional issues or things they would traditionally go to therapy about. And so I think what's really exciting to us is, like, the definition of what a companion is has evolved so quickly from either a friend or a girlfriend to, like, anything, any sort of advice or wisdom or entertainment or counsel you could have gotten from a human before. And we're going to see even more vertical companions moving forward. One thing I thought about is having worked at a social company, there is a very clear trend

of average number of friends that you can talk to over time going down. I think the youngest generation is something above one. So I think the need for companion as a use case will absolutely be there. It'll be an enduring use case. It'll be something critical for actually a lot of people. So I think I'm very excited about the companion use case. And as just seen said, I think it branches out into different things. But the need for having a close connection to talk to will endure.

And perhaps we talked about how maybe connection is a missing area, white space, But maybe this is filling that in, right? Like, as we say, maybe you just need to feel connected to something. It doesn't need to be human. That average number of one will go down to zero. That's a sad part of it. One AI friend. Yeah, that's the same optimistic.

Tell the story about the senior citizen that they set up with the AI. Oh, I love that story. Oh, my gosh. Yeah. So this woman set up her dad. He was having some memory issues. Her mom had passed away. Her dad, I think, went into like a camera.

home. And she posted on Reddit. And this was like when AI companion didn't exist as a term. So she posted on some subreddit. I think it was like a not safe for work, AI one being like, I don't really want something not safe for work, but I want like an AI girlfriend or an AI friend to talk to my dad and keep him company all day because like I can't spend hours on the phone with him all day every day. And then when she actually reviewed what he was doing and what he wanted to talk about, he wanted to like mostly talk about World War II stories and like random and like occasionally feel like someone was like flirting with him and found him interesting. And that sort of thing, it's like chat GPT is not great at, just the way it speaks, the voices, like, Open AI does not want to build the AI girlfriend for seniors who mostly want to talk about World War II.

But that might end up being a massive market. In a flirty way. In a flirty way. It's interesting. I tend to look at like Korea sometimes or Japan as like an indication of what the societal changes can be. And there's a bunch of elderly there. And the ratio is completely. off. So that need for beings that need to talk to the elderly people and keep them company

about World War II and so on and so forth. I think that's actually a really interesting use case too. It's phenomenal. I'm imagining, just seeing you trying all these companions that are getting immersed in it and Olivia being like, what are you doing? And just being like, it's for work. What has been your impression of all of it? I think it's been really fascinating the companion thing because there is a huge category of people who have been willing to type into a text box and treat it as a friend. And then there's probably a much bigger category people who don't want to think of themselves that way. And so I think that we have yet to unlock the next modality of companions where maybe it's like a voice in your ear or maybe it's sitting

on your computer screen where it's not obvious that you're turning to it for friendship, but it provides the same emotional value. Yeah. And I think that is what is just now emerging in companions as the models become more multimodal essentially. Always on companion. Yeah. Yeah. And that's what's really exciting. Like some people would use an AI assistant.

Yes. But not an AI friend. Yes, exactly. Even if the assistant is like a friend that's also an agent that can send emails for you. So a lot of people upon hearing this conversation of companions just think, oh man, people are going to have less friends, people aren't going to date anymore and depression is going to go up. Suicide's going to go up. Fertility is going to continue to go down. Mark and Dr.

Someone said this famous quote of, I'm not saying you're going to be happy. but you're going to be unhappy and new and exciting ways. Are you kind of like, yep, that is what it is. That's technology. Or are you like, no? I don't think so. This reminds me my favorite post of all time on the Character AI subreddit, which I've spent in a immense amount of time, which is, okay, and to set the scene.

So there's all of these, like, high school or college kids who had their formative years during COVID, and they weren't really in person with other kids or teenagers or learning how to talk to people. And I think it really ended up impacting a lot of them. And one of those kids, I think he's in college now, had been post. posting on the character AI subreddit about his AI girlfriend for a while. And then one day he posted that he found a 3DGF, so a real-life girlfriend's, and that he wouldn't be returning to the subreddit for a while.

And he actually credited character for teaching him how to talk to other people, especially teaching him out to talk to girls, like how to flirt, how to ask people questions, how to engage with them about their interests. And I think that, like, in some ways, that's sort of like the peak value of AI. It's like enabling better human connection. Just less weird. Yeah. Were people happy for him or do they call him a traitor?

People were extremely happy. I mean, there were a few, I think, jealous souls in there who had not found their 3DGF yet, but I have hoped for them. I think that's real, though, because we've even seen studies, like, I think of the replica product where actual studies were showing depression and anxiety and kind of suicidal ideation were going down in users. I do think there's this trend of a lot of people don't feel understood and don't feel safe. And so then it's hard for them to be in the real world doing real things. And so if AI can help them, and maybe they don't have the money or the time to go to therapy and make all of these changes in their lives. And so if AI can do that for them, they can emerge a transformed person that's then more able to do things in the 3D world. As I'm a techno optimist too.

Yeah. The thing that really got me sort of aware of how big these companion apps are when we did the first interview with the founder of Replicos amazing after she turned off there at W. FW stuff. And the subreddit for Replica and the comments in our video were basically a lot of people being like, hey, this is like my wife when we stopped having sex, you know, like I already have this sort of neutered. And like so many people were just like my life is open. And I'm like, oh my God, I didn't realize how big of a role this app was playing in people's

lives. I feel like that is bringing out an activity that people have done for a long time. Like people have had these like internet, chat room, discord relationships, like the use, the zoomers. have like Discord girlfriends and boyfriends. In our day, there was like this anonymous postcard website where you would go and send anonymous postcards back and forth and develop these like really deep relationships with like people you would never meet

or you didn't know if they were the person they were pretending to be. And I think AI just makes that deeper, more engaging experience. Well, so this is where I think an important point, though, is that the AI not be too agreeable because people in real life, I mean, there's a given to take to human relationship and like highly agreeable AI does not set you up well for that. So I think there's a fine balance between being just agreeable enough to help you, like, engage and get better at this versus being so agreeable that you're actually worse at this.

And that's also important on the therapist's use case. Yeah. You just can't just say, you're absolutely right on everything. Totally. Right. And say, actually, let's actually review your behavior. That weekend when 4-0 was, like, telling everyone that they were like the king of the world. It turns out everyone hated it because you don't believe it when it just tells you

that you're amazing all the time. When it comes to like therapist's use cases, they're the actual real world where the disagreeableness and matters a lot. I want to close with what's possible going forward. Let's speculate on new platforms or form factors that could be game changing. Open AI just acquired Johnny Ives company. You know, Brian, I've heard you talk a bit about glasses and why you're still excited about that form factor. Maybe we can start there, but I want to hear from the group on what they could imagine as something that's additive or even disrupting some of the mobile use cases. It's funny.

I'm just thinking about glasses and all that. but there are 7 billion of mobile phones out there. There aren't that many devices at all that actually gets to that level. So my thought process is either it will live in mobile. And for that, there's many different ways to think about the future where there's a privacy wall around it or is a local LLM or local model that helps you sort of really contain all the things that you want to contain in your device level. So I think I'm still very much excited about the model development.

to get to that. And I think that's what I'm actually most excited about. And then if you think about always on, as Olivia, you said, like mobile, we have always on. But there are other things we also have always on. And what does that look like when there are net new devices or what have you or appendages, if you will, that like actually attach to things that you always have that actually can enable that.

Any speculation from you guys? Is there a piece of hardware or something that we're going to be wearing or carrying around or using that's either attached to the phone or separate from the phone that could enable the use. Yeah. I think AI has scaled for consumers tremendously well given it's mostly been text box in some output in a web browser out. And so I love the idea of AI kind of actually being with you and seeing what you see. It's funny. Now when I go to tech parties, like a lot of the under 20s are wearing pins that record what they're saying and doing and they find like real value from them. That's one example. We've seen a new wave of products that can see what's happening on your screen.

and take action for you, help you, coach you, other things like that that I also find really, really exciting. And I think also the agenic models get even better. It goes beyond just like suggestions to actually doing work for you, sending emails for you, which is very exciting for me, I think. I think, yeah, the human insight layer of that is big too. Like often we have no way of measuring ourselves compared to other people or sort of where we exist in the world. So if an AI can hear all of your conversations and see everything you're doing online and say, hey, look, like, if you spent five more hours a week doing this, you would actually be a world expert in this topic. And based on this vast network of other people, like, you should connect with these three other people. And this person could be an amazing co-founder. You should, like, date this person, like that sort of thing. That, to me, is the ultimate, like, sci-fi vision of like what? Which comes from AI being with you all the time and something that's not just like a chat, chabit text box. Totally.

The device that has been most widely adopted post phone is the AirPods. So that feels like the thing that's hiding in plain sight. And there's a whole bunch of like social protocol questions around it because it's weird to have your AirPods in at dinner. No one does that. Right. But there may be a way that you can integrate AI and also fit the current social protocols around AirPods.

It would be interesting. Yeah. You said something that we glossed over, but young people at parties are recording their conversation. Yes. In the future, is everything going to be recorded? You think that generation is already growing up with the way? that norm to some degree?

Yeah. I think there'll be new social norms developed around this behavior because I think it's like real and it's valuable. And so it's like scary, I think, for a lot of people that this is happening. But I think it's a wave that started and it's not going to stop in my opinion. And I think the context matters too. Like I think a lot of what you're talking about is like the SF networking parties where like work and personal stuff like really blurs.

Yeah. We talked about this. You can do that in SF. If you do that, did that party on brought up in New York. canceled. Yeah. But I think that's why there'll be like a new social. set of call to normal. It's like when the cell phone was introduced, like there's places

where it's rude to take a loud call. Like this, the same set of things will emerge around these recording devices. Yeah. Let's end on this idea that we're very early. Guys, it's been a great conversation. Thanks so much for coming on. Thanks, thank you. Thank you. Thanks for listening to the A16Z. If you enjoy the episode, let us know by leaving a review at rate thispodcast.com slash A16Z. We've got more great conversations coming your way. See you next time.