The State of Consumer Tech in the Age of AI

0:00I think in the future you're going to see consumers spend to be like food rent software. All of the aspects of our lives are going to be intermediate 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 that 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.

0:38We're living in this early era of AI where velocity is the most. 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 has 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? Go here how creative tools like Mid -Journey and VO are reshaping expression, how voices becoming the new interface, and how companions, AI ones, are filling in social white spaces.

1:18We 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 A16Z fund.

1:58Please note that A16Z and its affiliates may also maintain investments in the company's discussed in this podcast. For more details, including a link to our investments, please see A16Z .com forward slash disclosures.

2:14It 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, new breakout and it feels like at some point a few years ago they just stopped. Why did it stop or did it stop? Would you reframe how would you think about that and where do we go from here? I would argue probably Chatchy B. T 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 modalities of AI, in image and video and audio companies like Mid -Journey and 11 Labs and Black Force Labs.

2:53Now things like clang and VO, weirdly though a lot of them don't have the same social or traditional consumer dynamics that you mentioned, 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 VAAPI 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, to what 15 years, 20 years, where, as you said, like Google, Facebook, Uber, all the names.

3:35And it's interesting because when you think about internet, mobile, cloud, everything together, there were all these amazing names and you ask, 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 or 15 years, every little nukes and crannies that have been explored to some extent, the changes that people had to adopt was Apple coming out with new features. As opposed to the changes that people need to adopt now is the underlying relentless model updates. I think that's one different, but the other thing is, again, just in Utah, I shouldn't just say this, but if I think about the past historical winners, there's like information, area like Google of the world, and now I think ChatGPT is certainly doing that.

4:18And there's the utility we messed out, like box and drop box of the world, and are more consumer, consumer, 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 or 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 just seen aside from Genshin, Genshin Open AI, are they going to be around 10, 20, like what is the and the defense ability of the companies we're talking about.

4:57And 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 Chad GPT has got way higher business model quality than analogous consumer companies from the last product cycles, right? Their top skew is $200 a month, at the top Google consumer skew is $250 a month. So sure, there's a question of defense ability, networks, all these other things, but that might have been a response to the poor business model quality that would have occurred.

5:28If you didn't have those things, now you can just charge people a lot of money and perhaps we've been overthinking it previously. Yeah, there was poor business model quality maybe stronger sort of retention or product marketability. Yeah, like you had to have a story for how this 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 just you talked about this, like all the foundation models are kind of pointy in different ways. So you could say, look, Claude and the Chatsubitih horizontal model and the Gemini model aren't they interchangeable and doesn't that mean price pressure?

6:03But different people use them for different things and it seems like their raising price is not lowering them. So I think when you zoom in a little closer, you see that there are some interesting defense ability dynamics that are already there. The increasing price not decreasing at an interesting point because is 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 I'll tell you 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.

6:44Like you don't get the change pricing that often, and you don't get to upgrade, 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 credits and points and need to actually overage it as they actually end up spending. So you actually see revenue retention being meaningfully hired and unique user retention, which, again, I haven't seen that before. So yeah, I think before the average consumer subscription was maybe $50 a year, if that, that was kind of a lot.

7:18Like 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 undercharge 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 on 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.

7:49And 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, VO3, like people are paying $250 a month. Unfortunately, I have since it's a limited, the $250 plan. Yeah, I still just need you to charge you. I've since turned several more of the $50 credit tax to probably spend if I had to guess like over $500 in the first few weeks. I'm going to rebe in a retention of time. Yeah, exactly.

8:22And 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.

8:56And 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 Steve speaking to. I can give you some examples of that. Well, a lot of it is what Olivia said, right? So I think all of 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 disposable income spend is being subsumed by it. So all of the aspects of our lives are going to be intermediate by the models and we're going to pay for that.

9:27Brian, you're saying we're still missing as a connection from this new paradigm and people are still relying on sort of Instagram, Twitter, some of the other sort of social networks of the past, what's going to get us to something new here in the realm of connection, or has that just been one data network effect? 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.

10:01It used to be, here's what I am, here is what I'm doing to actual photos of where you are and what you're doing to video than 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? If the truth is, if I just think about the 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.

10:43I 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 it knows more about me than probably Google potentially, which is an insane thing to say. Like Google, I've been using Google for a decade plus, and chat you be doing me no 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.

11:23I mean, we already see some examples of exactly that where like, there's all these viral trends where people are like, I asked my chat GBT 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 dozens of people responding like 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 GPT 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 Tenshri unbenosis some without you Facebook is like the boomer AI swap and then like reddit and reals They're like the younger people AI content.

12:15Yeah, 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 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. When you use a worse Q more fake a lot of the AI social products that mimics Instagram feed or Twitter feed Was bots and AI's that that feels Q more fake that feels like this is what do you see look like we're gonna do it What was AI and maybe that's not really the form factor and you know, there's additional hurdle in my mind that And the true consumer product probably needs to leave it mobile.

13:13And 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 you synthetic ET and get all of your wisdom.

13:59perhaps 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. What thing are you guys saying 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 era or maybe not what we expected, what can we say there? Yeah, that has been fascinating. And we can, I saw that a lot with 11 labs, which we were relatively early.

14:27I think we did the series 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.

15:04And I think we've seen this across a bunch of AI products, which is like, there's an initial consumer viability 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 from 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, 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.

15:38I've also heard of similar end up being 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 striped 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 with 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.

16:22Okay, that's like a go -to -market at extreme speed. Just seeing you rattled off a list of products and companies in the beginning of this conversation. When I'm curious, 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 I can be now that we see and 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.

16:51I think maybe the interesting differentiation in AI versus the last era of consumer products, or even two errors before, is like the model layer and the capabilities are still improving. Like we have really not even, I think in many cases, scratched 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 LLM's are momature, but have the opportunity to just keep improving capabilities as they scale.

17:27And 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 Fencer or whatever. like they just keep you fall a little bit behind, you ship the new update, suddenly your 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, in Image, for example, there's not just one best image model. There's like best image for designers.

18:00There'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 videos, 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 was best for people. And it goes on and on. And each of those, I think, is a very large market. See more about how we, I know we talk a lot about defensibility and motes and how that is changing this error, how we've changed how we consider that topic.

18:41I've gone through a little bit of a come to Jesus woman on that, especially recently. I think MOTE's always been very important, right? The goal is standard, this network effect, being part of the workflow, being system of record, and indeed, they're all very, very important MOTE. And I go positive that that's still very important. But funny enough, like I would say, the company, their investments that I've reviewed with this MOTE 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.

19:18And I've sort of come around that in that we're living in this early era of AI where velocity is the mold. And whether that's in distribution, which is incredibly important and hard to break through noises, these days, but also followed with product velocity. That's what wins a game because that what leads to mind share and frankly right now mind share and users and traffic. That actually converts to real revenue that gives you more ability to continue that journey. If there's a Ben Thompson, I think a decade ago at this point had this blog post called snap chats gingerbread strategy where he was basically saying, hey, anything snap can do Facebook and do better, but snap is just going to keep sort of coming up with the next sort of innovation.

20:04And if they could just keep doing that, maybe that's their mode. And he called it the gingerbread. You know, it's a good, it's a good, I think you just keep going. Yeah. Yeah. Yeah. That's right. And at some point, it'll be such a beautiful gingerbread house. You know, I think that worked to some extent. Yeah. And it's famous I think Evan joke that he's a chief product officer. Yeah. I think distribution and network Work Effect ultimately kicks in, right? And Snap has that too when I saw him, where it sort of has a cornerable Gen Z and the younger users as like a core messaging platform. How do we think about network effects for these new products?

20:39I 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 closed linked, closed 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, And we see a different type of mode form in the likes of a level knob, like it said. Because it moves so fast because the product is very good, it gets to go into enterprise and get to get locked in into workflow. So I think that version of mode we're starting to see, I think the true network effect we're still looking at for.

21:13I 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 can 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 like 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.

21:48And so I do think it's early, but we're starting to see signs of that. But there are 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 over the first time. That is sort of a thesis around it. And these, what do you talk about? What got you so excited about voicing this new paradigm and what sort of played out and what hasn't yet? What do you think is going? I mean, the original observation in Olivia really is our voice expert.

22:17So we should hear from her. But the original observation that got us started was that voice has intermediate and 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 tech 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 drag and 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.

22:44And 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 and 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.

23:37And 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 GBT 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.

24:11For 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 the 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 intermediate 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?