The a16z Show - Where Does Consumer AI Stand at the End of 2025?

Episode Date: December 29, 2025

As 2025 comes to a close, consumer AI is entering a new phase. A small number of products now dominate everyday use, multimodal models have unlocked entirely new creative workflows, and the big labs have pushed aggressively into consumer experiences. At the same time, it is becoming clearer which ideas actually changed user behavior and which ones did not.In this episode, a16z consumer investors Anish Acharya, Olivia Moore, Justine Moore, and Bryan Kim look back at the biggest product and model shifts of 2025 and then look ahead to what 2026 may bring. They discuss why consumer AI appears to be trending toward winner-take-most, how subtle product design choices can matter more than raw model quality, and why templates, multimodality, and distribution are shaping the next wave of consumer products.Where do startups still have room to win? How will the role of the big labs continue to change? And what will it actually take for consumer AI apps to break out at scale in 2026? Resources:Follow Anish: https://x.com/illscienceFollow Olivia: https://x.com/omooretweetsFollow Justine: https://x.com/venturetwinsFollow Bryan: https://x.com/kirbyman01 Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow 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.

For most of the year, less than 10% of chatchipt users even visited another one of the big LLM providers. When you open Gemini, it has a pop-up, says, we got a nanobanana. Would you like to do something with it? A little pain where you have to type something. I don't know what to do. Eat our product nuances that I think makes people actually take the first thing. The models have gotten to the level of quality that you can build a real scalable app on top of them. And so the hope is 2026 will be a huge year for consumer builders.

As 2025 comes to a close, consumer AI is starting to look very different than it did at the beginning of the year. A small number of products now dominate everyday usage. New multimodal models have gone viral and the big labs have pushed harder than ever into consumer experiences. To take stock of the year, the A16Z team, Anisha Charya, Olivia Moore, Drishtine Moore, and Brian Kim break down what actually worked in 2025 and what didn't. They discuss which model launches and interfaces change user behavior, why small product details matter more than raw model quality and whether the consumer AI market is trending toward win or take most.

The conversation also looks ahead to 2026, where there is still room for startups, how templates and multi-modality are reshaping creation, and why this may finally be the moment when scalable consumer AI apps break out. Today we're talking about who won consumer AI in 2025. This was arguably the year that we saw the big model providers, OpenAI and Google, most out of everyone, make a major push of their own into consumer,

both in terms of new models they release, but also in terms of new products, features, and interfaces that target the mainstream user. You might wonder, why does it matter who is in the lead here? There are some early signs that the general LLM assistant space might be trending towards winner-take-all or at least winner-take most. So only 9% of consumers are paying for more than one out of the group of chat chippy-tie-tee, Gemini, Claude, and Cursor. And for most of the year, less than 10% of ChatchipT users even visited another one of the big

LLM providers like Gemini. If we had to call it now, Chatchibati is currently in the lead, by far, at 800 to 900 million weekly active users. Gemini's at an estimated 35% of their scale on web and about 40% on mobile. And everyone else significantly trails this. So Claude, Grock, Perplexity are all about 8 to 10% of it. of the usage. But especially in the last three to six months, things are changing very quickly. With the launch of new viral models like nanobanana, Gemini is now growing desktop users

155% year over year, which is actually accelerating even as they reach more scale, which is pretty crazy to see. And Chatsy BT is only growing 23% year over year. And we're starting to see players like Anthropic almost specialize within consumer owning different verticals like the hyper-technical user. So today we've brought together the A16Z consumer team to recap what we saw this year from the big model companies in consumer and also to predict what might be ahead of us in 2026. Cool. Well, thank you, Olivia. It's been a super fun year. If we kind of wind the timeline back to last January, maybe we should start with what we saw launches, products, what worked, what didn't. So Justine, tell us what you saw this year, opening eye at Google. What are you paying attention to?

What have you changed your mind on? Yeah, those two in particular had a ton of consumer launches, like Olivia mentioned. From a model perspective, I would argue their most viral models this year, at least among consumers, were in image and video. So for OpenAI, it was the ChachyBT4O image,

the Givley moment, which is crazy that that was this year. It seems like this is a year. It feels like it was years ago. And then SORA, obviously, SOR2. And then for Google, it's VO, VO3, and VO3.1. And then Nanobanana and Nanobanana Pro

in image models, which went insanely. viral, probably comparable to if not beyond the Ghibli moment for OpenAI. I think in terms of the product layer, what we saw was Open AI tended to keep more things in the ChatGBT GBT interface. So like Pulse, group chats, shopping, research, tasks, all of these features launched inside ChapGBT as the core. The exception there is obviously SORA as a standalone video app, whereas Google tended to launch more things as standalone products. So they did ship a lot through like Google AI Studio and Google Labs and Gemini and the plethora of Google surfaces

there are to launch a product. But they would also ship things as standalone websites that you could go to and visit, which basically allowed for a more custom interface for each type of product, not just the kind of chat entry, chat exit or image video exit. So just you have a question for you on that. So it felt like 18 months ago we were talking about Mid Journey and most of the multimodal models were defined by ascetics and realism. Is that still true? What changed this year? Yeah, I think there's definitely different styles still. And I think Mid Journey, when you talk to people really deep in image and video,

it still kind of stands apart for this like aesthetic sensibility that a lot of the models don't have if you don't know how to prompt for it. But I would say this year in particular, we made a lot more strides on realism and also on reasoning within both image and video. Like all of the little details that make an image where a video actually seem real. For example, if you have a person walking and talking, the people in the cars in the background, if they're on a street, should be moving in the correct direction, like they shouldn't be morphing and looking strange. An image, we were able to have multiple input images and text and sort of reason across all of those uploads to create like a cohesive design or something like that, which was not something we saw happening last year for sure.

Yeah, I remember when we were excited about having a letter show up correctly in images. And now we have insane infographics. Yes. We can just put up amazing YouTube video and say, give me an image that explains us. Yeah. That's incredibly different. Nano Banana Pro can even generate like market maps. Like I have a telemarked a market map.

It's incredible. And it either has or we'll go do the web research within the image model, which is crazy to get the correct list of companies and then pull their correct. Which is insane. I know. There's one benchmark left that the reasoning image models have not cracked. I tested GPT image 1.5 yesterday. They sometimes struggle with both reasoning and multi-step reason. So what I've been testing is you upload a picture of a monopoly board and you say,

remove the names of all the properties and replace them with names of AI labs and startups. And GPT image 1.5 is actually the closest, but it's very hard for them to do all of those steps, remove it, come up with the new names, put all of the new names in the correct places, make sure there's not overlaps or one thing you mentioned three times and another big player you never mentioned. So there's still some room to go on the first. image evils. It's interesting that, especially from the image model from chat GPT, where you can actually see perseverance of like it carries a character over into multiple image generation,

the same style. And I thought that was like, oh, like this is actually very interesting. We're storyboarding. Totally. Makes you want to generate more. Yeah. You know, for me, it felt like the most underhyped aspect of nanobanana was the integration with search because it feels like there's realism, which is physics and sort of other things that feel like we're on. Canney Valley, there is reasoning, which is apply modifications that are adherent to what the user asked for. But then there's also sort of accuracy. And for me, a good example of this is product photography. If you say, hey, generate a photo of this album cover or a historically accurate photo of this moment in time, you have to actually have the search integration. And that was sort of

non-intuitive, but it is actually very useful. Totally. Yeah. It's kind of like the V-O-3 moment when I don't think it was intuitive to people that video would be cracked necessarily by bringing audio together with video in the same place, and that ended up being the thing that made AI video go viral. Like, since V-O-3, and now SORA maybe dominates, but, like, since V-O-3, my social feeds have been, like, full of really realistic. I counted. About one-fifth of my feeds are AI-generated. Amazing, yeah. What do you guys do? There's so many launches this year, and many of them went well, like VO and Nano. What do you think is underhyped or products that you think didn't get enough attention?

Brian? It's a good question. I think underhyped pulse of the world is probably still underhyped. And we're talking about Open AI, Google, which to me fall under productivity category. So if you actually think about, if you go to App Store today, five out of top 10, productivity apps are all Google. It's insane. And Chatsyby is number one.

So we're talking about a productivity category where it helps you do things. And I feel like a lot of people are trying this from a different angle. Like how do I actually ingest your data or your source? schedule your email to make it more helpful and give more proactive and notification to you. I think a lot of people are working on it. Given the frequency of people using chat GPT, which I think is what 25 times a week, pretty good, pretty good, three to four times a day. It feels like it's a really good position to actually give you proactive nudges and summary

and help your life in general. So I feel like the everything app was always this myth in the Western world. I think Open AI is trying to move in that direction where it's ingesting enough. People are going there enough to start giving really useful proactive nudges. And I think that's a space that I'm excited about. It's interesting. But are you a DAU? I am not a DAU.

A pulse? Well, not a false. Similarly, I tried Pulse for a while and have kind of largely turned off of it. But I would agree with you that I feel like Pulse and a couple other examples that Open A.I. launched this year are kind of new primitives or ideas that feel under- typed, but because the execution is a little off. I think it's execution.

The usage is off. Another example that I would give, which is similarly like personal contacts would be their connectors. So now you can, and you can do this on Cloud as well. You can connect your calendar, your email, your documents. And so hypothetically, you could say to chat, GBT, you know, read all of my memos over the past six months and like summarize what's most interesting least interesting. I think when that works, it's really exciting.

I have found it to be a little bit unreliable so far, but I think as the models get better, they have a real chance to kind of own the prosumer workspace if they get that right. Pro sumers perfect category because we talk about it sometimes, but 99% of people don't run their lives on calendar. Yeah. We do. Right. So that's what I'm thinking about the actual average frequency of using chat GPT. And look, if it's 24 times a week, that's pretty good place to start. Yeah. Olivia, I feel like you're the ultimate power user. What are you still using? What's your stack? It's a great question. From my. All of the larger model companies, actually, I would have to say the thing that I'm still using the most and was maybe the most impressed by this year was the perplexity Comet browser.

And I don't and was not using perplexity as my core general LLM assistant. I use Chachibit and Claude much more. But I think they really executed on it in a first class way in terms of both the agentic model within the browser, but also perhaps more importantly, all the workflows that you can set up that allow you to basically run the same task. over and over, either at a preset time or when you trigger it on a certain web page. So that to me was a really exciting launch. And if you look at the data, like the spike at launch and the sustained traffic for a comment was actually much higher than for Chat Chachibit's own browser launch, Atlas, which is kind of crazy given how much more distribution Chatsubit has than Proplexity.

But I think they also launched an email assistant this year. Proplexity did. And they made a couple acquisitions of really strong agentic startups. And so what I would love to see from them next year is more of these dedicated prosumer interfaces. I feel like that would be an awesome direction for them to kind of double down in. They do feel like the startup that has the biggest breadth of ambition

alongside the labs and sort of big tech. It's very, very impressive, just the number of things they've shipped this year. Yes, definitely. One thing I wanted to ask you, Justine, was sort of Gemini feels like it's having a real moment because of all the image and video models. Do you think it can overtake chat GPT?

is there truly that much demand for these types of models? I think yet. So what I've seen basically is there is always nearly infinite demand for like the best in class image or a video model because then you have a mix of tons of different people seeing it and wanting to use it. You have, like if you're using it professionally, if you're marketing or an entertainment or storyboarding or whatever,

you always want to be using what's at the forefront of the field. And so you're totally fine to go somewhere other than chat. APT and SORA to get access to VO. Even if you're an everyday consumer, so many new viral trends are created around new capabilities of the best in class image and video models. And so that ends up driving users into different products that they may have never tried before.

Like you might be downloading the Gemini app or accidentally ending up on Google AI Studio, which I know they're trying to make me more for developers to use Nanobanana Pro, which a lot of users, I think, experienced in the past, couple of months. Yeah. The interesting thing about Gemini to me is, like, hypothetically, they benefit from the massive Google distribution advantage. Like, if you look at Android, Gemini is at, like, 50% of chat GPT scale on mobile, whereas on iOS, it's like 17%. So, like,

clearly something is working there. They launched a little Gemini widget within Chrome recently that encourages you to use it. They're launching it within Google Docs and Gmail and other things. Yeah. But I think that most, the average person is still just using one AI product. And Chatsybt is like the Kleenex of AI. Like it is the brand that has become. Exactly. Yes, yes. And so I think the Gemini still has a pretty big hurdle to overcome just in terms of that. Yeah. But if they keep doing what they're doing on these amazing viral consumer creative tool launches and model launches, like they could get there next year. I'm thinking about this. It's really interesting when you look at Gemini, which is everywhere. Yeah. Yeah.

but yet nowhere to some extent, right? You don't like, you know, when you look at the actual usage, people still think of the Kleenex. Yep. And they go to chat GPT. But the interesting thing also is on the product sensibility. So this morning I had like two panes open, open AIS image model and Google's Gemini.

And basically use an image functionality. When you open Gemini, it's a blank screen. It has a pop-up, says, we got nano-banana. Would you like to do something with it? and a little pain where you have to type something. Yeah. I don't know what to do. Yeah.

Chat-T-P-T, you go in, and it has a very TikTok-like style of, like, here's a trending themes that you might want to generate. And you click on, I want a sketch pen or whatever. And then it just, like, use one other picture, and it creates something amazing. And then it says, would you like a holiday car? Would you like a blah, blah, blah, blah. These are product nuances that I think makes people actually take the first step to generate it. And then once you have it, you have character consistency. Yeah.

So you keep going. Right. So that's interesting in that I think OpenAI and Chatchip team has proven that there is deeper product sensibility. Yeah. But then this is a funny thing. Maybe a little non-coacher thing to say. But, you know, I worked at Snap. So when you look at Meta versus Snap, famously, Evan Spiegel was chief product officer of meta.

Yeah. Yeah. I wonder if there's a world where the chat GPT team at Instagram. innovates on the product front again and again, Google was distribution, looks at them like, that's cool. Let's just integrate it and keep going and actually play that game. The interesting thing there is that images pain just launched yesterday when we're filming this. In chat chisb-t.

In chat, Gvt. Brand new. And it took them, like, they had image models for years and it took them that long to come up with a separate, relatively basic interface for generating images. I would almost argue the application layer companies, like the, the, the CREAs, the Hedras, the Higgs field of the world, popularized that template format and did it first and did it better. And they are chat TVT's product people and then maybe the chat Chb2 product people.

So it's a supply chain of product ideas. Always. Yeah. Well, maybe going in a slightly different direction, BK, I'm very curious for your take on opening eye social features. Because it does feel like that's something that you really have to get product execution right on, but also network design. You know, there's some efforts around SOR2. We should talk about that.

There's also group chats within. chat, GPT, you're our sort of social guy or having historically, bullish, bearish. Where's your head up? Barish for now. Okay. And the reason to me is twofold. Historically, we look at sort of, it's funny. I look at products based on what I call it inception theory.

You go like three to four layers down to figure out what the one liner is, which is like, I want my dad to love me. And so, you know, when they think about products, that's up for you or for the world. That's for me as well as for a walk. Okay. Yes, yes. And so I look at some of the products like chaty pt. Ultimately, when you peel the onion five times, I think essentially is it helped me be better.

Like, help me get that information. Help me be more productive. Help me be more efficient. And then when I think about social features, meta, Instagram, what have you, or even TikTok, the two layers of information or the emotion that is trying to address to me is for TikTok, entertain me. I want my clown. Entertain me.

Yeah. And then the other layer is. I'm lonely, I want to be seen, I want to connect with people. And to me, these are pretty two different parallels in the product direction. And Open AI's product is incredible. It's magic. It's amazing. But it's ultimately a see-me or help me category, which essentially is why it's the number

one in productivity category. Yeah. Now we're trying to take this and shove it in people's life and say, guys, connect, connect better, and like actually feel like you're being. being seen. And even the group chat function, which I love, it'll be so good to plan a trip and they actually have that common pain. But I think it still stops at probably end count of two to three people planning something in a help me way versus, oh, I feel like I understand a niche so much better because I've sort of done that. So largely over time, I think that's the reason of that

division, but that is not to say you can build a separate product that completely sort of addresses that. I think Sora, so we talked about group chat, SORA 2 was the other big, I think social push this year from all the consumer AI giant. Which was basically like a TikTok feed, but all AI generated video and you can make cameos at your friends. The cameos was a very good bet. Yeah.

It was a strong bet. Yeah. But I think what we've seen is like in the retention data and how we're seeing it used is it was massively successful as a creator. tool. Like now my feed is probably two-thirds A-I-SLP, if not more. And over 50% of it is now SORA, whereas before it was like all V-O and some cling. But it has not been as successful as like a social app. Consumption. Yeah. People are like a small number of creators are creating a ton of content and then bringing it out to like TikTok, Instagram, X, Reddit, where it's going massively

viral. But it doesn't seem like there's a as much consumption happening in the the app. Yeah. As much remixing, as much commenting, especially as there was initially. You know, in a funny way, the way I think about it is like Sora's competition or analogy isn't actually TikTok. Mm-hmm. It's actually Kepka.

Hmm. It's like a funny way. Is it almost like a creative tool? Yeah. Interesting. Yes. Olivia, what's real thing? Well, I was going to say, like, I think it goes back to your earlier point, which is like the

kind of motion that drives social apps is both these like positive and negative feelings of like. oh, I'm publishing this thing of myself that's kind of sensitive or that I want people to think it's this or that or this other thing. And so that's kind of what drives participation on the app. The status game. Yeah. It's exactly the status game. And when it's AI generated content and people know it's not real, like a real representation of you as a human being, the status game is lost a little bit.

Absolutely lost. Yeah. I think the status game comes then with can you prompt something very cool. Yeah. But that's a different type of product. And that's why I think it goes viral on, like, Twitter and all these other existing platforms. I mean, my sort of counterpoint or bullcase for Sora 2

is actually think the status game was about humor more than anything else. And humor is the intersection of knowing how to prompt and sort of being culturally aware. Yeah. So I think that if they iterated on that, that's like a direction that nobody has captured before. Yeah. Yes.

But if you can export those videos, isn't it true that, like, TikTok with Sora videos on it is strictly better? than sort. We talked about it so much where like the ultimate social product is where consumption and creation both live together and that the output of it is not native to other platforms like TikTok, like YouTube shorts. So what do folks think of the challengers? You know, we're talking about sort of to, I mean, meta, it's crazy to talk about meta as a

challenger. I guess in this context they are, but I think Claude, perplexity, Grock are the more obvious names for challengers. Olivia, what's your take? I love Claude. I talk to Claude all the time. Claude is somewhat replaced Chashi-B-T for me as my general L-LM. I think Claude is opinionated in an interesting way. I also love Claude because I'm willing to invest time into building out AI workflows. I think Claude actually launched a lot of really powerful things this year around like artifacts and skills where you can essentially set up tasks or workflows to run over time. I do think the reason it hasn't hit the mainstream yet is even the way they built those things is, geared towards a technical user or an engineer. I think they tried to make skills as easy as they could to create, and it still was not anywhere near easy enough for the mainstream consumer.

Another example would be they were actually the first of the big players to kind of launch file creation, slide deck creation, editing, and they branded it as like file generation and analysis or something, and it was like a toggle feature within a setting bar of a setting bar of a set, setting bar or something. So like very few people used it. Yeah. And yet to me, it's still the best product across all of them and doing that kind of complex work. So I love Claude, but I think if they want to be a true mainstream consumer product, they need to dumb it down even more in terms of accessibility. There was that survey you found recently of U.S. teens. Yeah, there's, I think it was

three times more U.S. teens have ever used character AI than have used Claude. Yeah. So I think that shows It's like the key. It's a pretty broad thing. Clod is beloved amongst tech people, but outside of tech people, I think they are maybe struggling to pick up relevance. It is interesting, though. Like if you look at the sort of aesthetics, the product design, the craft, like three things that Anthropic did were MCP skills and command line interface, Claude Code.

Yeah. Like those are three surprising bets, especially Claude code. I would have said command line interface, really? Like, is this the way that people want to interact with? I thought you were going to talk about taking over air mail and the thinking cap. Yeah, that too. They're a consumer. Yeah.

So three, you're thinking like, where is a thinking cap? Yeah. But it's sort of very high-minded design. Yeah. It's sort of like versus mass market or maybe that's apologetic on their behalf. But I think it is it is that it's opinionated and it's great.

Yeah. Yeah. I do need to hear Jocene's take on both meta and grok as I feel like they both had fascinating years. Okay. Yes. So meta, I hired all those researchers. I think their strongest models

are actually not consumer-facing models. It's their SAM-3 series. So like the segment anything for video, for image, and for audio. And basically, like, for video, for example, you can upload a video and you can describe a natural language, like find the kid in the red T-shirt.

And it will find and track that person across the entire video, even if they're coming in and out of the frame. It will let you apply effects, like blurring them out, or removing them or whatever. And you can imagine a similar thing with audio with different stems and then with image with different objects in an image.

I think we're going to see next year, hopefully some incredible consumer products built on top of those models. But today they're more of a playground for developers than they are a consumer-based product. Which is surprising given just like the DNA of the company. Yeah. So the one good consumer feature I think they've launched this year with AI is the Instagram AI translations.

where when you're uploading a reel now, you can opt in to enable translations and it will clone your voice, translate it into five different languages, apply the translation with your voice, and then re-dub with the lip sync. Wow. And so it basically makes it seem like

you're a native speaker in whatever language. So I would love to see more of that stuff come to the meta-products. Grog I think has had, so Grock had a crazy year with like the companions, with all of the LLM progress and the coding progress. I think their image and video progress

is probably the steepest slope I've seen of any of the companies. Like, it was probably like six months ago they didn't even have image and video models, and they're shipping so fast to launch new features. Like it was initially just image to video. They added text to video. They added audio. Then they added lip sync with speech.

Then they added 15-second videos. Like, they're just not. slowing down the speed of progress. And Elon has made a bunch of statements about, like, wanting more interactive video game type content out of GROC and wanting movies out of GROC by the end of next year. So let's hope it continues to go at that pace. Do you feel like it's a pinster movement where, like, on one hand,

there's, like, a very infrastructural model layer of, like, let's get to the, let's top the LMA Rina charts. And then the other one is, like, let's go, Annie. It's like a little bit of, like, bifurcated move. Right. Like the entertainment and the like smart. Absolutely.

But entertainment in a way that like we're talking about, you know, anthropic and chatty. He's general population. But you just said character AI is way more popular. Yes. So then like how do we think about that? And I think, you know, it's a very interesting strategy in my mind. And Grok like in the image and video app,

since pretty early on they've had templates of popular things. Like you're standing somewhere and suddenly like a thing drops, a rope drops from the ceiling. you grab onto it and it like swings you out of the scene, like some really good ones that go viral regularly on TikTok and other places. Yeah, really, really interesting. Well, so maybe switching gears from 25 to 26, what are some of all your predictions for next year?

What do you think we'll see hardware, models, commerce we haven't spoken about yet? So what do we think we'll play out? I think I know this is we're talking about consumer, but one of the things that's been really maybe underrated for me about chat, Chabit, that we might see more of next year is they've really made a push into the enterprise,

both with the traditional enterprise licenses and then working with specific companies to even train models for them. And I think when we think about the fact that most consumers only use one general LLM product, chat Chabit enterprise usage, they publish a big study,

but it's up somewhat like 8 or 9x year over year. Yeah. And so if we're entering a world now where people have to use chat Chubit for their company or as part of their work, that could really translate into consumer usage.

Or maybe they become the workspace with the connectors and some of the other things that they're investing in and someone else owns the consumer consumer use cases. I think to that, and we have to talk about their push into apps, and I think whether or not that works is going to be kind of the defining question for them next year. Yeah, and I think that we've all discussed the importance of the apps SDK and the apps directories they're calling it,

and it's going to be a huge new channel for consumer. I think what's less discussed is it's hyper-relevant to enterprise. So I think where chat GPT shines is where it's able to operate across a number of tools for one workflow. And if you think about the number of things you do in your sort of business day-to-day that operates across many tools, it's most of those things. Yeah. So I think that will have very interesting implications for the SaaS ecosystem, and it's a part of the app store we're not talking about as much. Yeah. Yeah, maybe less of a prediction, but thinking through 2025, and we talked about all the big moves.

from Big Labs. And from the startup point, I think one of the biggest trend we've seen is app generation. And I think there's a real world where we see the big labs with the distribution and the frequency of usage of people coming in to start saying, look, like maybe there's a common type of product and apps that we could actually help you generate within the confines of the big lab products. Yeah, yeah.

I think that's like one of the interesting thing, which, you know, again, going back to the supply chain of ideas and research, maybe that's one thing. And again, nothing groundbreaking. But as we know, the Ghibli broke the internet. My cousin who knows nothing about tech sent me a Ghibli photo. Well, let's not send this to your cousin then. Yeah. And I think that goes to show that templates matter.

Yeah. That style matters. Yeah. And I think of a video and like it's pretty, freaking good. Yeah. And it's possible that we're already

at a point that it's not necessarily just about the capability of models of the big labs, but the stylistic things, a template, think of TikTok.

The large capability, largely still the same. Music, trend, dance, go. Except the trend and format keeps on changing. It keeps it extremely fresh. So I feel like there's a real world

where the repurpose or our team, or what have you, can start thinking about ways to actually really build in video first products into these lab models. And I think the cost will go down and off for people to try it out. And I'm excited to see that.

Yeah, I think what I'm most excited about is sort of along those lines, basically everything becoming multimodal. Like I call it like anything in to anything out, which is basically initially, especially with these image and video models, it was you put in a text prompt and you get an image out or a video out. You couldn't really do much with it. And now we started to see this with the image edit models with like nanobanana and with Flux and with the new Open AI model where you can put an image in now and get another image out.

You can put an image in with a text pair in a direction or put an image with a template and another reference image and get another image out. What happens when you can put a video in and get images out that are related to or the next iteration of the video, or you can put a video in and a text prompt about what you want to edit and get the edited video out. From my conversations with the labs, a lot of them are trying to basically combine all these largely separate efforts they've had across, like, text reasoning and intelligence, the LLM space and image and video into like, what if we can put, merge those all into like a mega

model that can take a lot different forms of content and produce much more. I think it's also going to have huge implications for like design. Yeah. Because if you think about it, a lot of design is combining images with text, with video, with different elements in kind of interesting ways. Yeah. I guess if I think about like a macro level prediction, I think it's actually going to be more of the same in that when we talk about what all

of the labs have launched in consumer, they've done a great job with models and they've done a great job with incremental things that improve the core experience of using like a chaty BT or Gemini. Yeah. In my opinion, we've gone through dozens of things that they've launched or tried as new consumer products or new consumer interfaces like group chat, like Pulse, like Atlas, like Sora. Google has had a long tail like Stitch, gems, Opel, Dopple, tons. Yeah.

None of those are really working. And I think it's because it's not the core competency of these companies anymore to build opinionated standalone consumer UI. Out of all of those, I think the product that's working the most is like Notebook LM. And that's one of like maybe 20 things that Google has tried or experimented with. So I think it's actually very positive for startups in that consumer startups and that the models will keep getting better, which the startups can use. And they'll keep, you know, they'll make Chat Chabit better and better.

But I don't necessarily think that Chat Chabit, like, verticalizes into all of these other amazing use cases or products. And there's still room for startups to be building there. I have a yes and to that. where absolutely. However, when the input and the output is text, where Chatsy, PT and Gem and I of the world shine the most, no matter how deeper you go,

no matter how specific you think your text output is going to be, essentially given the frequency of the usage of the main Big Lab products, I think it's going to be really hard to stitch that and get that away from that usage if your product is mainly text and text out. So I do think you have to be creative around what is the angle that you can go steal people away from. You know, I love that you use the word opinionated because I think that for labs, certainly for big tech and perhaps increasingly for labs, their priorities get set in their promo committee, always. And if you're a PM, and it's always the sort of mid-career PMs, and I've been one of these.

And the incentives are always to get promoted. And the way to get promoted is to build something safe that extends a core metric and a core feature. So building opinionated products is a very risky way to manage your career, you know, because they're probably not going to work. They're probably going to have a bunch of implications for legal and compliance, and the CEO might yell at you. So I just think that they are so structured to do incremental things. The more founders do opinionated things, the more advantage they are. I think, honestly, the big thing we haven't discussed here, too, is compute, which is the labs have this inherent tension between there's a limited amount of compute, and they either spend it on, like, training models or they spend it on inference. And even with inference, there's this split between, like, the entertainment Ghibli use cases and the, like, coding intelligence use cases.

I think XAI is probably the only model company that is not bottlenecked on compute, from my understanding. Whereas the others have to make really, like, serious and significant calls of, like, if we let, if we release nanobanana and go super viral, like, it may slow down the next, like, big LLM we're trying to push forward. Whereas startups who focus on the app layer don't have that problem because there's no tension there. Absolutely. Yeah. Look, we've talked about this before. I also think that there are categories in which being multi-model just allows you to deliver a better proposition to the customer.

And the labs in big tech are always going to be sort of definitionally first-party model only. So I think as all the models get better, perhaps 80% of what you need can be received from a single model. But for the power users, and so much of AI is a power user story. You know, you always said that like, well, power users are just power users. And I think that's true in a pre-AI world. But now the kind of depth of value. you and the depth of monetization is so much higher that maybe all of AI is actually a power user story, you know, and everyone else is just traffic. Yes.

Yeah. Which is why we're also seeing, like, consumer products for the first time ever have more than 100% revenue retention. Yes. And that's separating the good from the great, from the exceptional in consumer AI. And to be clear, how that happens is they charge for usage often in addition to a subscription. So you can use beyond whatever your quota is for the month, given your subscription and pay more. It's either upgrade of the tier. Or actually buying tokens or more usage.

Yeah. It's, that's what differentiates it. Like, you know, if you told me pre-AI, we see a consumer company with 100 plus retention and money. I'm like, that doesn't make any sense. Doesn't that compute? Yeah. Yeah.

No pun intended. Exactly. Exactly. Well, guys, okay, maybe let's talk about start with specific recommendations. Like after this pod, what are the products people should download or the features or the models? What should folks be using today? I guess on the multimodal. point, I think one really under-hyped product that people should check out, not because they'll

use it every day, but because it shows sort of what is possible when you combine like an agent with image with text is Pameli. So this is like the Google Labs product where you put in the URL of your business and it has an agent, go to the website, pull all of the product and brand photos, summarize what it thinks your brand's aesthetic is, what it stands for, what kind of customers it's targeting, and then it will generate three different ad campaigns for you. And it will generate not only the text, but it will generate like the Instagram posts. It will generate the flyer. It will generate like the photo of your product and this, you know, whatever, wherever it

thinks it should be based on your customer. And very cool product would be hard to become a giant standalone product within Google, I think, but shows sort of the future of what happens if we combine agents with generate. models that have sort of really deep understanding of context that an image model or a video model normally wouldn't have. Startup products, though. Do you have a favorite startup product? Oh, so start a product.

Yes. In creative tool? Yes. I mean, we're investors in Korea, so this is biased. But I think they've really done an exceptional job of being the best place to use every model or every quality model across every modality and also building more of the interface on top of these models. Like, I now prefer to use Nanobanana Pro on Crea because Crea allows you to save elements, which are essentially characters or styles or objects, that you can like at tag to

reprompt versus having to drag the same image reference into nanobanana over and over again. That's a good one. I suppose it falls under a startup category against shilling companies. But, you know, the one that I use the most is actually a Levin Labs reader. And the reason is, is we've seen an explosion in podcasts, and there's, I think, a reason for that, right? People are a lot more on to go. The reading capability of us for reading, I think it's going down over time.

And so, you know, let's not fight their reality. Let's embrace it. And, okay, so then, like, let's actually find a written material translate into listening and do that. And I used to be a power user of tools like pocket. You know, I didn't have time to read everything that I wanted to read. And it's a saving behavior.

right, you're going around and saving all the things you eventually want to consume. But I think what I do now is similar where I go get all the things I want to read and I just put it, either PDF it or put it on an 11 reader. And just like once in a while when I'm going to walk and I have like three, four minute, you know, 1.5x speed or 2x speed and just listen to one of these and get the gist of it. So I think that's been a good way to use a little bit of time as a sort of semi-normal person. Yeah. Well, first of all, I love this question because I am strongly opinionated that by far the best way to get up to speed on AI is just to try a ton of products.

And you get opinionated really quickly. Justine and I, actually, for the whole month of December, are on Twitter publishing one new consumer product a day for people to check out. So that's one way. I'll name three others that I think are super maybe relevant or interesting that people can plug into their workflows. So one would be gamma for slide deck generations. You can go text prompt to slide deck. You can go document a slide deck. I use it for everything.

Also, the slides are flexible sizes. So you're no longer like editing every little pixel in your Google slides to get it to fit into one, which is great. Granola for no taking. You might not have any meetings over the holidays, but in the new year. And it just gets better and better than more meetings you have on it because it has the context of what you talked about before. And then lastly, I'm still going to plug, try the comment browser. If you want to try kind of an AI native workspace, I think. that's one of the most accessible ones to start with.

I mean, for me, I've spent my whole year obsessed with coding and AI code. It's just been so tremendously fun. I, by the way, Brian, would take the other side of your argument that the big labs or big tech will win an app generation. I think they just lack the focus. Products like Opel have been, you know, released with a whimper, and they're one model only. So I didn't say they will win it. I think we will see them doing it.

Yes, yes, I think that's true. But I think for the pure consumer side, of course, Wabi is really fun and really capable. And I think they are creating the right sort of constraints on app generation so that you can get a really satisfying functional result. And I think so far there's been a lot of overpromising an app generation, which has discouraged the early users. I also think if you haven't tried, you know, GPT-52 in codex or in cursor, it's worth trying. Even for non-technical people, it's just amazing. I think almost being technical is sort of a constraint because you have an pre-existing idea

for what these models can do and they can do a lot more. And I'm hearing increasingly about people doing knowledge work and writing essays in cursor instead of just writing code. Wow. Just one thing I'm going to do at the end, ear end. It's just to plug in like a popular trend I've seen on TikTok where there are people who said, what is the most unhinged thing I said this year.

Okay. And it actually does a review of all the things that you said. But I think similarly it'll be a good thing I'm going to do this at the year end. Tell me how to live a better life next year. Yeah. Give me actual unvarnished opinions and some directions and I think it'll be helpful.

I love that idea. I'm going for a worse life next year. Fantastic. Let's go full D-Gen, guys. Any closing thoughts? That wasn't a lot of things? I mean, the obvious one is we are very actively investing in consumer companies.

And I genuinely, I think a lot of people say this. I genuinely believe that the models have gotten to the level of quality that you can build a real scalable app on top of them. Wabi is a great example of this. And so the hope is 2026 will be a huge year for consumer builders, not just like consumers as, like consumers being consumers of a product. Yes. Well, thank you all for a super fun year in consumer and AI.

We'll be back with more next year. And Merry Christmas. This is a wrap. Happy holidays. Happy holidays. Thanks for listening to this episode of the A16Z podcast. If you like this episode, be sure to like, comment, subscribe, leave us a rating or review, and share it with your friends and family.

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