The Top 100 GenAI Products, Ranked and Explained

1. 0:00 – 0:36

   Consumer AI Trends

   1. OMOlivia Moore0:00

      Consumer activity typically lags by 6 to 9 to 12 months what's happening on the research side. I think compared to where we're going to be, we're still incredibly early.

   2. AAAnish Acharya0:10

      So many of these assumptions, um, and that's why they're assumptions, they seem intuitively correct, are gonna turn out to be incorrect.

   3. OMOlivia Moore0:16

      We are finally on the verge of AI video starting to work, to really work.

   4. AAAnish Acharya0:21

      It sort of follows the trend of AI decreasing the cost of creation in every way.

   5. OMOlivia Moore0:26

      95% of YC companies or something are now kind of building using those tools.

   6. AAAnish Acharya0:30

      The App Store is gonna be chaos.

   7. OMOlivia Moore0:32

      Yeah. [laughs]

2. 0:36 – 2:38

   The Gen AI 100 List: Methodology and Insights

   1. OMOlivia Moore0:36

      Yes.

   2. SSSteph Smith0:36

      We're back for the fourth edition of the Gen AI 100 list. You guys have been working hard and tracking the consumer landscape for years now, but specifically for the last two and a half years since we really had that kind of ChatGPT moment. Tell me more about how you're tracking that ecosystem and how that comes through in this list.

   3. OMOlivia Moore0:53

      Yeah. It's super fun. This is one of my favorite reports that we put together a couple times a year. We track the consumer AI landscape through what we do every day, which is, like, meeting with consumer AI startups that come to pitch us, seeing what goes viral on Twitter. But actually, there's a whole separate set of companies and products that might be reaching the true mainstream consumer, that might not even be marketing themselves as AI products, but they're kind of powered by and, and made possible by AI. And so the whole original purpose of this report was to see how much overlap is there between those two categories, and what is the actual everyday person who might not know that they care about AI, uh, using in their day-to-day?

   4. SSSteph Smith1:32

      That's great. And so talk about the methodology, like, what makes it onto this list or not? 'Cause to your point, there's certain household names that you might see on Twitter-

   5. OMOlivia Moore1:40

      Yeah

   6. SSSteph Smith1:40

      ... or have that viral moment, um, but I think some people might be surprised to see what made it onto this list, so let's start with the methodology and what-

   7. OMOlivia Moore1:47

      Yes

   8. SSSteph Smith1:47

      ... it requires.

   9. OMOlivia Moore1:48

      Yeah, so it's entirely based on data. We have two lists here, the top 50 on web and the top 50 on mobile. So the top 50 on web, we use a data provider called Similarweb, which tracks every single website globally, and we essentially go down in descending order of how many visits they get each month. For this report, it was January 2025. And then we go and we pick the first 50 of those that have the most monthly visits that are gen AI-first products. We do something similar on mobile, but a different data set from Sensor Tower. For mobile, we look at monthly active users on the app, and then again, we pick the top 50 that are gen AI products. And then for the first time ever, we actually looked at the top 50 on mobile by revenue-

   10. SSSteph Smith2:33

       Mm

   11. OMOlivia Moore2:33

       ... which we hadn't done before, and it was a really interesting experiment because the lists were pretty non-overlapping.

3. 2:38 – 5:37

   Pivotal Moments in AI Development

   1. SSSteph Smith2:39

      We've been in this AI ecosystem for a few years now. In your eyes, what were the pivotal moments that led up to, you know, this point in time where we have, like you said, 50 on mobile, 50 on desktop, and a whole lot more in the wider ecosystem?

   2. OMOlivia Moore2:53

      You often say, actually, it's usually, like, the papers are written and then the models are developed and then applications are built on top of it, so the consumer activity typically lags by 6 to 9 to 12 months-

   3. SSSteph Smith3:05

      Mm-hmm

   4. OMOlivia Moore3:05

      ... what's happening on the research side. So maybe just from, like, a consumer awareness or behavioral perspective, there's a couple moments for me. Actually, Midjourney and Character.ai both came out before ChatGPT, which I think a lot of people don't know, but there was maybe these early niche communities of early adopters that were using both of those products-

   5. SSSteph Smith3:24

      Mm-hmm

   6. OMOlivia Moore3:24

      ... in the summer and the fall of 2022 leading up to ChatGPT. And then post-ChatGPT, things that just brought AI to consumer consciousness, so even remember Snapchat's My AI with that little bot that appeared at the very top of your feed? And, like, 150 million people used it, and for a lot of kind of younger consumers, that was actually probably their first real chance having a conversation with an LLM. On the image side, I think of the Balenciaga pope-

   7. SSSteph Smith3:53

      Mm

   8. OMOlivia Moore3:53

      ... uh, which was also, I think, spring 2023.

   9. SSSteph Smith3:57

      Such a cultural moment.

   10. OMOlivia Moore3:58

       It was, and I think it made a lot of people realize for the first time that they should even be interested in AI images, um, because they could be that good and that convincing. The first big AI music moment for me was, well, the BBL Drizzy song, which I think was spring of 2024. Um, and that also went, like, mega viral. I think one of the moments where creative AI really shifted into almost enterprise consciousness was the end of last year when Coke did their Christmas ad-

   11. SSSteph Smith4:27

       Mm

   12. OMOlivia Moore4:27

       ... and a lot of that was generated by AI. And then of course, the DeepSeek launch earlier this year.

   13. AAAnish Acharya4:32

       DeepSeek was so interesting because I think it, it sort of had become settled wisdom that it would be very hard for a horizontal model to get to mass consumer scale quickly again. Like, ChatGPT had kind of done it, and ChatGPT had become a verb, and-

   14. OMOlivia Moore4:46

       Mm-hmm

   15. AAAnish Acharya4:46

       ... that opportunity, you know, had already been explored. And now we see DeepSeek growing as quickly as it did. And, and there's actually a couple of interesting nuances to DeepSeek. So one I think important nuance is the fact that they released their reasoning model for free, um, at scale. So previously you had to use o1 Pro and you had to pay, um, ChatGPT's premium subscription to get access to it. The other thing was just the product execution around chain of thought, which we've talked about a lot, and I think is pretty well understood, but the fact that it showed you its thought process in real time-

   16. OMOlivia Moore5:18

       Mm-hmm

   17. AAAnish Acharya5:18

       ... was just super captivating, and now something that's become a step that every model takes. So I think it just really illustrates how early we are. You know, we as sophisticated users and investors are looking for further and further refinements, and once in a while, something like DeepSeek comes out of the clear blue sky and just blows away all assumptions.

4. 5:37 – 8:48

   Assumptions and Realities in AI

   1. SSSteph Smith5:37

      That word specifically, assumptions, I think is so key when you talk about these pivotal moments. I feel like you could actually match each pivotal moment with an assumption, like an assumption being, oh, well, like, AI could never trick me into thinking a picture-

   2. OMOlivia Moore5:49

      Yes

   3. SSSteph Smith5:50

      ... is real when it's not, right? Or I would never actually listen to a top 100 song that's generated by AI, or, you know, ChatGPT has cornered the market. No one else can penetrate it, right? All of these assumptions that people are like, "Okay, sure, I was wrong about that prior one-

   4. OMOlivia Moore6:03

      Yeah. [laughs]

   5. SSSteph Smith6:04

      "... but this one I'm pretty sure about."

   6. AAAnish Acharya6:05

      Mm-hmm. Mm-hmm.

   7. SSSteph Smith6:05

      We're seeing just, like, months-

   8. OMOlivia Moore6:07

      Yes

   9. SSSteph Smith6:07

      You know, being the delta between assumptions being broken.

   10. OMOlivia Moore6:11

       Yeah.

   11. SSSteph Smith6:11

       And so to your point on, like, the arc of the, of the market or the industry, I could see an argument where people are like, "Oh, you know, we're actually pretty far along because we've already, like, slashed all of those assumptions." But then on the other hand, I'm hearing, you know, we still have a long way to go. So kind of maybe, um, put us along that arc if we were to compare to, you know, the mobile era or the cloud era or previous technology eras and, you know, do you- are we in that early innovator stage still, or are we somewhere else?

   12. OMOlivia Moore6:37

       Yeah. I think we're still very much in the early adopter phase. In many of these categories, we're kind of just, I mean, arguably still in, like, the infrastructure-building era and kind of moving into the application-building era. Uh, it, it depends on the modality. Like, now LLMs are ... Maybe people thought that was a solved problem, but then again, DeepSeek came in [laughs] and upended all of that. There's a lot of things that are definitely not, you know, fully solved, like AI video right now can generate great three or five or six-second clips, but hopefully years from now we have AI video that can generate minutes long or, you know, even hours long movies. And so I think compared to where we're going to be, we're still incredibly early.

   13. AAAnish Acharya7:17

       You know, here are two assumptions that I think are interesting because it may turn out the reality is the exact opposite. One is that AI will be very good at transactional interactions, but humans will still be the ones to build relationships and connection.

   14. OMOlivia Moore7:30

       Mm-hmm.

   15. AAAnish Acharya7:30

       So an example of that would be, you know, what kind of phone calls are AI gonna be best at? And I think the assumption was, well, they'll be great at sort of scheduling and logistics and the exchanging of information and facts. But we've heard over and over that in many cases, the AIs are more human than humans.

   16. OMOlivia Moore7:46

       Mm-hmm.

   17. AAAnish Acharya7:47

       They just have more patience, more nuance. They're never having a bad day. They're never hungover. Um, so that's an interesting area of exploration. You know, the other one, um, that I think is interesting is the idea that humans will delegate work to the AIs, and the AIs will do it. Like, what if the AIs are the ones delegating the work to us?

   18. OMOlivia Moore8:05

       Hmm.

   19. AAAnish Acharya8:05

       Perhaps AI is really good at organizing work, and we're really good and also get a lot of joy out of doing it. So I think so many of these assumptions, um, and that's why they're assumptions, they seem intuitively correct, are gonna turn out to be incorrect.

   20. SSSteph Smith8:18

       Totally. And if we think about the report, maybe one, one important data point is the fact that we see so many newcomers still, right? If we were in that later part of the innovation curve, you might expect more stagnancy, you might expect to see the same players, but every time you guys build out this report, we're seeing all of these newcomers. In this particular time, the fourth report, we saw 17 new companies on the web rankings in particular. And you actually have this quote where you say, "A few unexpected players rewrote the leaderboard overnight." So can you just speak to

5. 8:48 – 11:53

   Emerging Trends and Newcomers

   1. SSSteph Smith8:48

      that and the movement that we're seeing?

   2. OMOlivia Moore8:50

      One of the biggest trends among the newcomers is we are finally on the verge of AI video starting to work, to really work. So we had three new video models on the list this time, um, Hailuo and Kling, which are both Chinese models, and then Sora, which was OpenAI's model that was announced, I guess, more than a year ago at this point and finally was released. I think we'll see even more of a shakeup here because Veo 2 is the new Google model that is even next level beyond that from what we've seen in testing, and that is probably finally gonna hopefully come out in the next, you know, three or six months. The other big category of newcomers were these vibe coding products.

   3. SSSteph Smith9:29

      Mm-hmm.

   4. OMOlivia Moore9:30

      Cursor made the list, so it's more of like an agentic ID for a technical audience. And then Bolt made the list, which is for a non-technical audience, where you basically go from a text prompt to a fully functioning web app. Even though they made the list, I think we've still seen there's a really significant portion of their users that are people who are in tech and are actually technical, but they might be using something like a Bolt or a Lovable, which made our, our Brink List, which we can talk about, to maybe prototype something easier and then export the code and go and play with it themselves. So I think we haven't quite seen the vibe coding products hit the true mainstream user in terms of someone who's never worked in tech or developed an app.

   5. AAAnish Acharya10:14

      I love this category. It's so fun, and it's so satisfying to actually see your ideas come to life. I mean, in the case of Bolt and Lovable, sometimes they are just sort of compelling interactive prototypes more than they are full-fledged products, but that's usually enough to get a feel for whether this is something you wanna invest deeper in.

   6. OMOlivia Moore10:32

      Mm-hmm.

   7. AAAnish Acharya10:33

      I mean, it sort of follows the trend of AI decreasing the cost of creation in every way and-

   8. OMOlivia Moore10:38

      Yeah

   9. AAAnish Acharya10:38

      ... people just trying more ideas.

   10. SSSteph Smith10:39

       Just think about what that says about the untapped market of people who wanted to build things-

   11. OMOlivia Moore10:44

       Yes

   12. SSSteph Smith10:44

       ... with code that this is on, you know, the top 50 list, right?

   13. OMOlivia Moore10:48

       Totally. And, and I think honestly, both of them haven't had many apps built on them yet that have gone super viral.

   14. SSSteph Smith10:54

       Mm-hmm.

   15. OMOlivia Moore10:55

       And though- when that happens, and I'm sure it will, those will become stories of their own, which will then increase awareness-

   16. SSSteph Smith11:00

       Totally

   17. OMOlivia Moore11:00

       ... of the products of the true mainstream audience. I think we're gonna see a really interesting diversity or range of products built on these, which it might just be like, "This is my app that I just used for my very specific [laughs] niche pain point."

   18. SSSteph Smith11:13

       Yeah.

   19. OMOlivia Moore11:13

       Or there might be people who never learned how to code who want to build a venture scale product on something like a Bolt or a Lovable, and so seeing how that plays out will be very cool.

   20. AAAnish Acharya11:24

       Yeah, I think there's two, two phrases I've heard that I like. You know, one is sort of DIY or personal software.

   21. OMOlivia Moore11:29

       Yeah.

   22. AAAnish Acharya11:30

       You know, it never made sense, economic sense to design software for one-

   23. OMOlivia Moore11:33

       Mm-hmm

   24. AAAnish Acharya11:33

       ... really. The other is disposable software.

   25. OMOlivia Moore11:36

       Mm.

   26. AAAnish Acharya11:36

       You know, just as Suno and Udio made it possible to make a song just to capture a, a joke that would be irrelevant the next day, these products make it possible to create a product or an experience that may have an extremely short shelf life, like 20 minutes or a week or, you know, any other time period.

6. 11:53 – 16:08

   The Brink List: Near Misses and Future Contenders

   1. SSSteph Smith11:53

      Let's talk about the Brink List-

   2. OMOlivia Moore11:54

      Yeah

   3. SSSteph Smith11:54

      ... because that's completely new to this year's-

   4. OMOlivia Moore11:56

      Yes

   5. SSSteph Smith11:57

      ... fourth generation. So what is the Brink List, and why add it?

   6. OMOlivia Moore12:01

      Yeah. So the Brink List is essentially the five companies that almost made the list and were right below the cutoff, again, purely based on the data. So we pulled the five websites and the five mobile apps. Um, and I think honestly, we were just curious to see what it would capture. [laughs] We didn't quite know. The takeaway for me, it, it does reflect how fast things are changing because there were a couple companies on the list, like Runway, Otter, Umax, across web and mobile, that have been on the core top 50 ranks in the past.

   7. SSSteph Smith12:30

      Mm-hmm.

   8. OMOlivia Moore12:31

      But maybe they got just edged out by, like, DeepSeek launching this time, and so they-

   9. SSSteph Smith12:35

      Sure

   10. OMOlivia Moore12:35

       ... they lost their spot for this ranking but might be on there the next one, and they still have massive usage. And then the other trend that it caught was a rise in more recent products, like Crea made the list and Lovable made the list, that are very much on the kind of consistent upswing and-

   11. SSSteph Smith12:49

       Mm-hmm

   12. OMOlivia Moore12:49

       ... if it continues, we might see them on the main ranks, and they haven't made the main ranks before.

   13. SSSteph Smith12:54

       What did you- ... predict that you would see on the list that you didn't really see there? Were there any surprises on that end?

   14. AAAnish Acharya13:00

       So one thing I thought would ha- we'd see more of is style transfer as an approach to scalable video, because style transfer is just a much more tractable, tractable problem-

   15. SSSteph Smith13:10

       Mm-hmm

   16. AAAnish Acharya13:10

       ... and has a lot lower cost of inference, um, versus raw text-to-video. But, you know, researchers and product developers seem to be really going for it on text to video, and-

   17. SSSteph Smith13:20

       Right

   18. AAAnish Acharya13:20

       ... we've seen more of that than I would've expected.

   19. SSSteph Smith13:23

       I think the other things that we didn't see on this list that we have seen at the model level, so that means maybe they'll be on the next list, are, like, consumer voice products.

   20. AAAnish Acharya13:31

       Mm-hmm.

   21. SSSteph Smith13:31

       There are a few of them, but, but not a ton of them. Um, some of the new- like, the Gemini Flash model that can see what's going on-

   22. AAAnish Acharya13:39

       Mm-hmm

   23. SSSteph Smith13:39

       ... on your screen and interact with you. Like, I built something to yell at me, like, if I go on Netflix or something. [laughs]

   24. AAAnish Acharya13:45

       [laughs] It's time to get back to work now. You've got this and can accomplish all of your goals.

   25. SSSteph Smith13:50

       Or, like, the new OpenAI operator model which can actually interact with things on the browser level on your computer and get tasks done for you, like pay a bill or, you know, make a graphic design or hire someone to landscape your yard, something like that. I think there's always a lag because the models have to be released to developers and they have to be tuned by the developers-

   26. AAAnish Acharya14:12

       Mm-hmm

   27. SSSteph Smith14:13

       ... and so it takes a while. But I would expect to see maybe an explosion of fun and unique and interesting products built on models like that on hopefully the next list or two, um, because it feels like we really have seen an explosion on the model side, and it is right there in terms of, uh, manifesting at the apps level, too.

   28. AAAnish Acharya14:33

       So one of the examples of this is Deep Research, um, which if you've played with it, is completely magical.

   29. SSSteph Smith14:39

       Yeah.

   30. AAAnish Acharya14:40

       But it's a primitive, right? It's not a product. It's something to build other things with. Um, so it's really unclear if Deep Research is gonna be used to, you know, write college theses or is it gonna be used to find the perfect meme to match a joke you wanna make.
7. 16:08 – 18:31

   Surprises and Consistencies in AI Adoption

   1. AAAnish Acharya16:08

      So those are the things that, you know, you thought might be on the list, but you didn't actually see there. What about the opposite?

   2. SSSteph Smith16:14

      I mean, I think the fact that the vibe coding products like the Bolt and the Cursors and Lovables made the mainstream consumer list is just a testament to how widely they're used by the technical audience. Like, they have gotten to saturation so quickly. I think Gary Tan had some tweet that, like, 95% of YC companies or something are now kind of building using those tools.

   3. AAAnish Acharya16:35

      Mm-hmm.

   4. SSSteph Smith16:35

      So it's something that every dev- nearly every developer now is probably using, which was maybe a surprise to me how quickly we reached-

   5. AAAnish Acharya16:41

      Totally

   6. SSSteph Smith16:41

      ... saturation. We've talked about this, but a continuing surprise, so I don't know if it counts as one, but I still am surprised every time, is how many companion products are on the list and also how many of them rank so high. I think we had three companion products in the top 10. Two of them were s- um, NSFW oriented. Maybe not surprising when you think about, like, traffic on the internet in general outside of AI-

   7. AAAnish Acharya17:08

      Mm-hmm

   8. SSSteph Smith17:08

      ... but a lot of people are even using them as, like, interactive fan fiction.

   9. AAAnish Acharya17:11

      Mm-hmm.

   10. SSSteph Smith17:12

       And some of the biggest fan fiction sites in the world are also, you know, top 100, top 200 global sites, so it makes sense in that way. And then I guess my last surprise would be there's actually quite a bit of consistency in the list over the past four versions. There's always new entrants, which is really exciting, but across the four lists, there's now 16 companies on the web ranks who have made it every single time-

   11. AAAnish Acharya17:37

       Mm

   12. SSSteph Smith17:37

       ... and have kept the streak going, uh, which is pretty remarkable when you think of how early we are in AI-

   13. AAAnish Acharya17:43

       Yeah

   14. SSSteph Smith17:43

       ... but I think a testament to how those companies have cemented their brands, their products, their kind of, I guess, status and consumer consciousness, um, and, and I think a testament to the fact that, like, real businesses have been, have been built in consumer AI already.

   15. AAAnish Acharya18:00

       You know, to add to that, one of the surprises for me on companion was not seeing more multimodality.

   16. SSSteph Smith18:05

       Yes.

   17. AAAnish Acharya18:06

       Kind of the first glimmers of that at scale were Grok.

   18. SSSteph Smith18:09

       Yeah.

   19. AAAnish Acharya18:09

       You know, and Grok added a bunch of, uh, voices with-

   20. SSSteph Smith18:12

       Mm-hmm

   21. AAAnish Acharya18:12

       ... some real aesthetics and points of view.

   22. SSSteph Smith18:14

       [laughs]

   23. AAAnish Acharya18:14

       You know? Uh-

   24. SSSteph Smith18:15

       That's a good way to put it.

   25. AAAnish Acharya18:16

       Yeah.

   26. SSSteph Smith18:16

       Yeah.

   27. AAAnish Acharya18:16

       Yeah, but it's... Look, it's, it's just interesting that that feels... And then of course Character's got voice mode and ex- you know, and more, but it feels like Character is, and companionship, is such a horizontal category.

   28. SSSteph Smith18:26

       Yeah.

   29. AAAnish Acharya18:26

       There's so much latent demand, and it'll really increase-

   30. SSSteph Smith18:29

       Mm-hmm
8. 18:31 – 19:40

   The Future of AI Applications

   1. AAAnish Acharya18:31

      You know, the other interesting thing is that, um, a lot of the text to code work, my assumption was that there was a small number of people who were creating sites that were heavily trafficked, and that explained the rise of them.

   2. SSSteph Smith18:42

      Mm-hmm.

   3. AAAnish Acharya18:43

      But actually, the majority of the traffic, correct me if I'm wrong here, Olivia, is from people doing creation-

   4. SSSteph Smith18:47

      Mm-hmm

   5. AAAnish Acharya18:47

      ... not just consu- consuming other people's creations. So there's just, it really shows how much demand there is to make things, um, even if- People are not that interested in consuming them

   6. OMOlivia Moore18:58

      Yeah. You can track the traffic of, like, apps that people have launched on Lovable.app-

   7. SSSteph Smith19:03

      Mm-hmm

   8. OMOlivia Moore19:03

      ... versus visits to Lovable.dev, which is where-

   9. SSSteph Smith19:06

      Right

   10. OMOlivia Moore19:06

       ... people go to make-

   11. SSSteph Smith19:07

       Right

   12. OMOlivia Moore19:07

       ... a Lovable product. And, like, Lovable.dev has more usage-

   13. AAAnish Acharya19:10

       Significantly, right

   14. OMOlivia Moore19:11

       ... or more visits, significantly-

   15. AAAnish Acharya19:12

       Yes

   16. OMOlivia Moore19:12

       ... than, you know, traffic to Lovable.app, which gets back to what I was saying before. Like, we have not even seen the first wave of viral products built on top of Lovable and Bold.

   17. SSSteph Smith19:22

       Mm-hmm.

   18. OMOlivia Moore19:22

       And, and so when that happens, I think the, the, um, awareness of these types of platforms is gonna go significantly up, too.

   19. AAAnish Acharya19:30

       I mean, the App Store is gonna be chaos.

   20. OMOlivia Moore19:32

       Yeah. [laughs]

   21. SSSteph Smith19:33

       [laughs] Yes.

   22. OMOlivia Moore19:33

       Yes.

   23. AAAnish Acharya19:33

       It is gonna be chaos.

   24. SSSteph Smith19:34

       Mm-hmm.

   25. AAAnish Acharya19:35

       We're gonna need an AI just to solve that-

   26. OMOlivia Moore19:36

       Yes

   27. AAAnish Acharya19:36

       ... AI app management problem.

   28. OMOlivia Moore19:38

       Yeah.

   29. SSSteph Smith19:38

       Completely. And I mean, to that

9. 19:40 – 20:32

   Traffic Trends and User Demographics

   1. SSSteph Smith19:40

      end, you talked about the fact that there are some consistent players.

   2. OMOlivia Moore19:43

      Yeah.

   3. SSSteph Smith19:43

      One of those players is ChatGPT, which we, you know, we, we've talked about as kind of like the starting gun-

   4. OMOlivia Moore19:49

      Yeah

   5. SSSteph Smith19:49

      ... of some of th- this application development. ChatGPT has been at the very top of the list.

   6. OMOlivia Moore19:54

      Yes.

   7. SSSteph Smith19:54

      Has it been that way for every-

   8. OMOlivia Moore19:55

      The whole time

   9. SSSteph Smith19:55

      ... e- every single-

   10. OMOlivia Moore19:56

       Yes

   11. SSSteph Smith19:56

       ... iteration of this?

   12. OMOlivia Moore19:57

       On web and mobile.

   13. SSSteph Smith19:59

       But maybe what would surprise people is that the traffic to ChatGPT hasn't always been-

   14. OMOlivia Moore20:03

       Yeah

   15. SSSteph Smith20:04

       ... the same trajectory.

   16. OMOlivia Moore20:05

       Yeah.

   17. SSSteph Smith20:05

       So maybe, can you talk about that, and what did we see this time around?

   18. OMOlivia Moore20:07

       Yeah. So it was basically flat for a while, which I think was surprising to a lot of people. Between February 2023, basically for a whole year, through February 2024-

   19. SSSteph Smith20:18

       Mm-hmm

   20. OMOlivia Moore20:18

       ... it was essentially flat in monthly visits to the website. And I think, like, at that point, from the data that I've seen, basically 50%-plus of the traffic was students-

   21. SSSteph Smith20:28

       Okay

   22. OMOlivia Moore20:29

       ... um, who were using it [laughs] for essays or homework problems.

10. 20:32 – 22:47

    Resurgence and New Use Cases

    1. OMOlivia Moore20:32

       But the vast majority of other people, me included, to be honest, had not maybe found a daily active use case for ChatGPT-

    2. SSSteph Smith20:38

       Yeah

    3. OMOlivia Moore20:38

       ... yet. And it's completely resurged, uh-

    4. SSSteph Smith20:41

       Mm

    5. OMOlivia Moore20:41

       ... more recently. So they 2X'd the number of visits on web since then. They actually made their own announcement, too, where they counted across web and mobile.

    6. SSSteph Smith20:50

       Mm-hmm.

    7. OMOlivia Moore20:50

       And in the past six months, they grew from, um, 200 million to 400 million weekly active users.

    8. SSSteph Smith20:57

       Wow.

    9. OMOlivia Moore20:57

       Which is especially surprising because it took them nine months to double before that, and it usually gets way [laughs] harder to double at scale, not easier. Um, I think from our perspective, and if you even plot it on the graph, you can kind of track the increases to the release of new models that unlock new use cases. So, like, the new o1-reasoning models, the 4o models, which were kind of multimodal for the first time-

    10. SSSteph Smith21:22

        Mm-hmm

    11. OMOlivia Moore21:22

        ... and then Advanced Voice Mode. Uh, and then they've also launched some new products, like the operator that can perform tasks on your computer, like Canvas, where you can write more naturally.

    12. SSSteph Smith21:32

        Mm-hmm.

    13. OMOlivia Moore21:32

        So it's both bringing in, like, new users who never tried it, and then taking people like me, who, honestly, I was maybe a weekly, if not less than weekly user.

    14. SSSteph Smith21:41

        Did you find your daily active use case?

    15. OMOlivia Moore21:42

        Yes. And now I'm a, I'm a daily active, but across several use cases now.

    16. SSSteph Smith21:46

        Mm-hmm.

    17. OMOlivia Moore21:46

        Like, some days I'm driving and talking to it voice mode. Some days I'm working on a memo and I'm generating something with deep research. [laughs] Some days I'm doing, you know, some random other project and I'm brainstorming ideas with it. Um, so I, I would expect that to continue as they release new models.

    18. SSSteph Smith22:01

        And have you heard from the ecosystem in terms of what more frequent use cases have, have emerged, kind of like yours, in terms of if, if before it was a lot of students writing research reports-

    19. OMOlivia Moore22:12

        Yeah

    20. SSSteph Smith22:12

        ... are there now... Is there a sense of understanding of what those newer use cases are?

    21. OMOlivia Moore22:16

        Yeah. I think it's gotten a... It's gotten better at some things related to coding. It's gotten better at data analysis. And then, I mean, the, the reasoning models, it's, it's hard to overestimate, uh, because in the past, like, you couldn't even rely on ChatGPT to tell you how many Rs were in strawberry-

    22. SSSteph Smith22:33

        Right

    23. OMOlivia Moore22:33

        ... accurately. [laughs] So it was hard to feel good about really tasking any sort of, uh, delicate or serious work to it.

    24. SSSteph Smith22:40

        Mm-hmm.

    25. OMOlivia Moore22:40

        And so I think there are probably a long tail of use cases that people have just migrated over now that they have more confidence in the models.

11. 22:47 – 25:30

    Competitors and Market Dynamics

    1. AAAnish Acharya22:47

       You know, what's interesting to add to that is that Claude is not a traditional number two player.

    2. SSSteph Smith22:51

       Mm-hmm.

    3. OMOlivia Moore22:52

       Mm-hmm.

    4. AAAnish Acharya22:52

       And typically the number two player has 10% of the market share and, you know, and, and just sort of 10% of the product quality. And instead, Claude sits in this very interesting place where it seems like it's more beloved-

    5. OMOlivia Moore23:03

       Yeah

    6. AAAnish Acharya23:03

       ... by a smaller number of people. It's better at creative writing. You know-

    7. OMOlivia Moore23:08

       Yep

    8. AAAnish Acharya23:08

       ... it seems to have more of a personality, which is interesting, 'cause at least I think it's designed to be more constrained.

    9. OMOlivia Moore23:14

       Yeah.

    10. AAAnish Acharya23:14

        And then it's also strangely much, much better at coding.

    11. OMOlivia Moore23:17

        Yes.

    12. SSSteph Smith23:17

        Yep.

    13. AAAnish Acharya23:18

        Why? I don't know. But it, but it's very interesting to see there's a place for both ChatGPT-

    14. OMOlivia Moore23:22

        Yeah

    15. AAAnish Acharya23:22

        ... and Claude-

    16. SSSteph Smith23:23

        Mm-hmm

    17. AAAnish Acharya23:23

        ... and Mistral and potentially other models, all to sort of, uh, augment each other.

    18. OMOlivia Moore23:28

        To me, the really interesting thing about this list when it came to general LLM assistant usage was, like, we only had 10 days of data for DeepSeek for January because it-

    19. SSSteph Smith23:37

        Mm-hmm

    20. OMOlivia Moore23:37

        ... launched at the end of the month, and it shot up from literally nothing to number two on the list, you know, 10% of ChatGPT scale-

    21. SSSteph Smith23:45

        Wow

    22. OMOlivia Moore23:46

        ... uh, on web within a week, a little bit more than a week. On mobile it had even less than that, five days.

    23. SSSteph Smith23:54

        Mm-hmm.

    24. OMOlivia Moore23:54

        And it was number 14, and if, if it had had five more days, it would've been number two.

    25. SSSteph Smith23:58

        Yep.

    26. OMOlivia Moore23:59

        And, and the gap is even narrower there, uh, between DeepSeek and, and ChatGPT. So again, to Anish's point, like, that was a surprise in that we could see kind of a broad-based LLM product go-

    27. SSSteph Smith24:11

        Mm-hmm

    28. OMOlivia Moore24:11

        ... go so viral still and capture so many users.

    29. SSSteph Smith24:13

        Yep. And DeepSeek was obviously the story when it came out.

    30. OMOlivia Moore24:17

        Yes.
12. 25:30 – 29:23

    AI Video Models and Trends

    1. OMOlivia Moore25:30

       Yeah.

    2. SSSteph Smith25:31

       Talking about trends that we're seeing on the list, um, you mentioned AI video before.

    3. OMOlivia Moore25:35

       Yeah.

    4. SSSteph Smith25:35

       But anything else you wanna call out there in terms of its presence on the report?

    5. OMOlivia Moore25:39

       Yeah. I mean, two of the video models were Chinese video models, which is super interesting. The models are less copyright sensitive in their training data. [laughs] Uh, and, and so-

    6. AAAnish Acharya25:50

       That's a great euphemism.

    7. OMOlivia Moore25:52

       Yeah.

    8. SSSteph Smith25:52

       [laughs]

    9. OMOlivia Moore25:52

       They're maybe more realistic and more prompted here and in the outputs as a result. But also, just in China, it's easier to hire people to kind of caption videos.

    10. SSSteph Smith26:00

        Sure.

    11. OMOlivia Moore26:00

        They have maybe a greater volume of researchers doing image and video stuff versus other stuff. So that makes sense, and I think we c- we might expect to continue to see... I think Sora, in some ways, was a little bit disappointing for some people.

    12. SSSteph Smith26:13

        Mm-hmm.

    13. OMOlivia Moore26:13

        And, and whereas, like, the Chinese video models were maybe better than a lot of people expected, given-

    14. AAAnish Acharya26:18

        Yeah

    15. OMOlivia Moore26:19

        ... the relative lack of capital that they've raised.

    16. AAAnish Acharya26:22

        That's right. I think an interesting trend is just seeing Krea on the Brink List.

    17. OMOlivia Moore26:26

        Yes.

    18. AAAnish Acharya26:26

        You know, Krea is the single best place to access all the models and all the tools.

    19. OMOlivia Moore26:30

        Yep.

    20. AAAnish Acharya26:30

        And the nice thing that they do is stitch all of these things together to make them greater than the sum of their parts.

    21. OMOlivia Moore26:35

        Mm-hmm.

    22. AAAnish Acharya26:35

        So insofar as we live in this sort of multipolar world of models, image models, video models, language models-

    23. OMOlivia Moore26:42

        Yeah

    24. AAAnish Acharya26:42

        ... there'll be a role for aggregators like Krea to put them all together in a thoughtful way.

    25. OMOlivia Moore26:46

        Totally. Especially 'cause it, people who are deep in AI video understand this, but each model is kind of known for being good at specific things, like shots of people, shots of landscapes, anime, hyperrealistic. And so, uh, paying, it can, it can rack up very quickly on $20 a month subscriptions [laughs] if you're paying for-

    26. SSSteph Smith27:05

        For sure

    27. OMOlivia Moore27:05

        ... 10 or 15 different models independently versus, like, having one canvas to work with all of them.

    28. AAAnish Acharya27:10

        You also typically use the products together.

    29. OMOlivia Moore27:12

        Yes.

    30. AAAnish Acharya27:12

        You know? You usually generate an image in Midjourney-
13. 29:23 – 30:34

    Mobile vs Desktop Usage

    1. SSSteph Smith29:23

       or Z." Video actually, in general, it tends to be more of a mobile first phenomena, right?

    2. OMOlivia Moore29:27

       Mm-hmm.

    3. SSSteph Smith29:27

       We see tons of, even before AI, tons of applications that focus on creators being able to edit and splice video. What are we seeing in terms of the difference between what's working on mobile and what's working on desktop?

    4. OMOlivia Moore29:38

       Yeah. I mean, it's somewhat obvious, but, like, a lot of the things that are working on mobile are either things you wanna use on the go or where the asset, the underlying asset you're working with is easily captured by the phone. So the avatar apps work on mobile because you have, you know, 10 selfies of yourself sitting on your phone.

    5. SSSteph Smith29:55

       Mm-hmm.

    6. OMOlivia Moore29:55

       A lot of the voice first consumer products that we are seeing working actually are on mobile versus web because it's easier and more natural to talk into your phone-

    7. SSSteph Smith30:04

       Mm-hmm

    8. OMOlivia Moore30:04

       ... for language learning or for companionship or other use cases than it is to [laughs] maybe talk into your laptop, and same with homework helper apps. Like, those are really blowing up on mobile as compared to web.

    9. SSSteph Smith30:16

       So maybe another interesting breakdown that kind of represents where we are-

    10. OMOlivia Moore30:19

        Yeah

    11. SSSteph Smith30:19

        ... in the innovation curve is not just what is getting views, but-

    12. OMOlivia Moore30:23

        Yeah

    13. SSSteph Smith30:23

        ... what's actually making money-

    14. OMOlivia Moore30:25

        Yeah

    15. SSSteph Smith30:25

        ... and how those aren't always one-to-one mirrored. What is making money today?

    16. OMOlivia Moore30:29

        Yeah.

    17. SSSteph Smith30:29

        What are we learning there, and is that the same as-

    18. OMOlivia Moore30:32

        Yeah

    19. SSSteph Smith30:32

        ... you know, what's getting traffic?

14. 30:34 – 34:06

    Revenue Insights and Monetization

    1. OMOlivia Moore30:34

       So for the first time, we actually ranked the top 50 by what Sensor Tower can measure as mobile revenue-

    2. SSSteph Smith30:40

       Mm-hmm

    3. OMOlivia Moore30:40

       ... which is typically in-app purchases and subscriptions, so probably not ads, and we ranked those separately from what has the most monthly active users.

    4. SSSteph Smith30:47

       Yeah.

    5. OMOlivia Moore30:47

       And there was only 40% overlap between the two lists.

    6. SSSteph Smith30:50

       Interesting.

    7. OMOlivia Moore30:51

       So a lot of difference. The surprise to me, actually, was the main categories are the same in terms of what's making money versus what people are using. So photo and video generators-

    8. SSSteph Smith31:02

       Mm-hmm

    9. OMOlivia Moore31:02

       ... photo and video editors Uh, beauty filters and beauty enhancers, massive standalone category. And then the realm of kind of like ChatGPT copycat apps, both making a ton of money, getting a lot of users. But the companies within those categories-

    10. SSSteph Smith31:16

        Mm

    11. OMOlivia Moore31:17

        ... are very different in terms of who's making money and who has the most usage. Um, we actually found, we plotted, like, revenue per user-

    12. SSSteph Smith31:26

        Yep

    13. OMOlivia Moore31:26

        ... versus number of users, and we found the apps that had smaller user bases out of the sample set were much more likely to be making significantly more money on a per user basis.

    14. SSSteph Smith31:37

        Mm.

    15. OMOlivia Moore31:37

        So apps like Speak, apps like Otter, captions and video editing. Um, there's a lot of reasons for this. One is that, um, if you are making a lot of money per user, you're probably more of a serious prosumer app.

    16. SSSteph Smith31:54

        Mm-hmm.

    17. OMOlivia Moore31:54

        And so you've probably actually gated the usage pretty significantly.

    18. SSSteph Smith31:57

        Yeah.

    19. OMOlivia Moore31:57

        Like, you have to subscribe to use the product.

    20. SSSteph Smith31:59

        Mm-hmm.

    21. OMOlivia Moore32:00

        Uh, and so there are companies on here that might be making $50, $100 million in ARR-

    22. SSSteph Smith32:05

        Yeah

    23. OMOlivia Moore32:05

        ... off of only a million users, two million users. So they wouldn't make the ranks [laughs] ironically enough for monthly active users-

    24. SSSteph Smith32:12

        Yeah

    25. OMOlivia Moore32:12

        ... but they rank really, really high on a revenue basis, which is exciting. Um, and then as anyone who looks at the mobile list knows, there's a lot of, maybe for the tech audience, seemingly random products on there of like, I've never heard of this.

    26. SSSteph Smith32:26

        Yeah.

    27. OMOlivia Moore32:27

        This is from a startup. Um, and on mobile especially, there's a very precise game that you can play with, like, app store ads and, and other-

    28. SSSteph Smith32:36

        Mm-hmm

    29. OMOlivia Moore32:36

        ... kind of paid but fairly low-cost acquisition channels. Uh, and if you're doing this as an indie developer or maybe an app studio running internationally, you're not looking for the 10X payback of acquisition costs that we might be looking for as venture investors. [laughs]

    30. SSSteph Smith32:52

        Yeah.
15. 34:06 – 36:24

    Key Learnings and Final Thoughts

    1. SSSteph Smith34:06

       All right. So there's a lot of information here-

    2. OMOlivia Moore34:08

       Yes. [laughs]

    3. SSSteph Smith34:08

       ... that we've covered. We've covered desktop, we've covered mobile, we've covered revenue versus users.

    4. OMOlivia Moore34:12

       Yeah.

    5. SSSteph Smith34:13

       And then we've also talked about the stickiness of some-

    6. OMOlivia Moore34:15

       Mm-hmm

    7. SSSteph Smith34:15

       ... of these players, right? You said there was, what was it, 16 that have showed up-

    8. OMOlivia Moore34:18

       Yes

    9. SSSteph Smith34:18

       ... every single list.

    10. OMOlivia Moore34:19

        List after list.

    11. SSSteph Smith34:20

        So what can we learn from the last few lists?

    12. OMOlivia Moore34:23

        Yeah. I feel like the biggest thing now being a consumer investor for close to a decade now, it's almost like the more you know, the less you know in some cases, 'cause it all just comes back to the product at the end of the day.

    13. SSSteph Smith34:33

        Yeah.

    14. OMOlivia Moore34:34

        Like, technologists or investors or, can have opinions on the best monetization strategy or the best, you know, growth hacks, but in the end, if the product isn't capturing users' attention and isn't retaining them, the business is just gonna be kind of a completely, like, leaky bucket of users and users out.

    15. SSSteph Smith34:50

        Mm-hmm.

    16. OMOlivia Moore34:51

        Um, so I would say the biggest... Like, often we meet with these amazing, like, PhD researchers, best in class in the whole world in terms of their technical understanding of a model or a capability, uh, and they can struggle building in consumer sometimes because often the more complicated thing is not actually the thing that is highest utility, most delightful, most helpful to-

    17. SSSteph Smith35:11

        Mm-hmm

    18. OMOlivia Moore35:11

        ... a consumer user. Um, so we always, we never like to be prescriptive on consumer products, but in, in general, we see when teams focus on either the pain point they're trying to solve or the unique experience they're trying to create, and build towards that. And if that means you're... actually the old model is better than the new model, use that. If that means it's just one AI feature instead of the whole product being built on AI 'cause it's not stable enough, like-

    19. SSSteph Smith35:36

        Mm-hmm

    20. OMOlivia Moore35:37

        ... do that. I think in, in consumer, you really have to kind of let the data, the data be your guide there. [upbeat music]

    21. SSSteph Smith35:49

        Thank you so much for listening to the a16z podcast. If you've made it this far, don't forget to subscribe so that you are the first to get our exclusive video content. Or you can check out this video that we've hand-selected for you. [upbeat music]

Episode duration: 36:24