A (2:42)

Yeah, well, that's what I wanted to kick things off with. There will be a founder's letter in. In the report and I've totally written

B (2:50)

is ready to go and I'm happy to talk about six T minus six days to publish.

A (2:55)

Let's get a preview of like, what are your thoughts on the market? And I'll chime in too. But like, the state of the app market in 2026 is weird.

B (3:05)

Uh, see, that's a word. The. Well, I think it's like, it's hard to talk about apps without kind of zooming out to look at the broader, like, human macroeconomic condition right now and what's happening. Because, you know, as we're talking, this is this, you know, March 2026, the opus 4546 and GPT5. Three are a couple months old. We've had a huge step function in Capab. Those tools. Vibe coding has gone from being a sort of insider term to like something everybody's doing. It's become mainstream. This sounds like some. This sounds like a hypothetical story I would make up about the future, but it's really happening. It's like every. Almost everybody's. And you know, personally, from my experience, I've been dabbling in these Vibe code tools. You know, it was cursor in 2024 and then I was playing with maybe like codecs and stuff and Claude code over the summer last year. And then, you know, this, this past winter or like December, we started to see the, the birth of the Vibe code. Platforms like Vibe Code App and Roark and Replit and like many others have started to get into mobile and, and

A (4:12)

get really good at it. Is the difference?

B (4:13)

Yeah, well, that's the thing. It's like, I think, you know, back in the summer when I tried some of these tools, it was like, this kind of works. But like, you know, for somebody who'd built a lot of apps, I was like, I know I could do this better probably. And like, this is just kind of a frustrating and expensive experience. But in 2025, at the beginning of 2026, it's like, I think I'd have a hard time competing with this tool. Right. Even if there are some rough edges and the trajectory is really clear. And so that. That news kind of got out. And so, you know, this is just talking about the last four months. We've really seen this, this explosion and that is happening everywhere, I think in the economy. But I think we've maybe Seen it most acutely in the subscription app landscape. Like, you know, revenue cap. Personally, we've seen a. I don't even know what it is like tripling in the number of apps getting submitted on an ongoing basis per day. And it's continuing to grow. This is as of the beginning of March 2026. Like it's, you know, usually we would have these like step function, like Covid was a step function, or we'd have like a new iOS release, sometimes would bump the like rate of app deployments. But like, we've just been seeing this like steady acceleration of app deployments over the last few months. And yeah, I mean it's just, it's directly downstream of this technology. And like now the question is, what does that do? We've been talking the AI story for a couple years right now. ChatGPT's app came out in 2023. They 2024 and 5 were the ramping years for these consumer AI apps. Like, not just ChatGPT, Suno, like anyone 11 Labs. You can think of all these like great consumer AI brands and then all the other like, you know, long tail of like AI implementing tools. Those were all. Now we're seeing like just the total, like flooding of the market with these new apps. And I think it adds some very interesting macroeconomic questions that we don't have. The. That'll BE in the 2027 report, I think, because in some degree it's going to be a supply and demand question. Like, you know, obviously apps was constrained on supply for a very long time. Like it was expensive to make an app, it was hard to make an app. You'd have a good idea, you had to have somebody who could code it, you had to have the ability to deploy it. All of those costs have honestly disappeared, but have gone much, much, much lower. So we've suddenly seen a big supply shock, right? In a positive way, like a big dearth of apps sort of like rushing into the stores. But that doesn't mean the demand is necessarily there, right? So it's like, it's probably, at least for a short period, competing over fewer and fewer dollars or not, not fewer dollars, but like an equal share of dollars. And so I think maybe some of this is being bore out in the data a little bit, but like, you know, at least immediately, there's going to be a knife fight over demand on the app Store as more and more apps compete over similar users.

A (6:55)

It does feel like though, in 2025 especially the AI apps gave people a reason to open their pocketbooks a little more. And like the Sensor Tower report came out and showed and we talked about this. I talked about this with a partner from Adreessen Horowitz in one of the minisodes that I was actually surprised at the Sensor Tower report that AI spending on AI generative apps increased like three and a half billion last year. But there were a bunch of other categories, short video and entertainment and productivity and others where it was like an increase of billions year over year of revenue. So it was pretty broad based and maybe there are more dollars, but it's like there are more dollars across way

B (7:39)

more apps every year. You're going to have a baseline. Whatever the GDP is should be your baseline, right? GDP growth is 5%. That should be our baseline. But the App store's been doing 20 plus so it's like there's always been a little bit more. I think it's likely that all of this increased supply will actually incent demand. Right? It'll cause like more money to flow in. It's like, you know, so it's not a fully, it's not a fully fixed pie. It's like these things, feedback on each other. But I do think it's like when you have a shock like this where suddenly all these apps appear out of nowhere, the demand is going to take a while to actually come. And that is a prediction for the future. But I have a feeling there's going to be these like supply constraints get dropped, supply increases, takes a while for demand. But like I also am very bullish on demand. I mean maybe we're seeing it. We haven't really seen the like AI productivity gains hit consumer spending yet. I don't think we may be in the most recent jobs at least in the US like now jobs report, productivity report. We had really strong productivity growth in the US in the last quarter of the year. And so I think everybody who's working in like knowledge work can see all these tools being applied to like I can suddenly do what used to. I used to have to hire a contractor to do or it would take two to do. We were just talking about podcast prep and like all these things that are just now, all this white collar work that's now like automated, like that should be. I mean aside from the people who aren't getting hired yet anymore, like that will sort itself out hopefully. But like there'll be a lot of productivity leads to surplus, right? And so that surplus will get redistributed and it's reasonable to think that some of that redistribution will go into essentially luxury goods, which are, you know, for the most part, B2C apps would fall into like a luxury category. Right. Things that people don't necessarily strictly need. That might take years yet, but I think it's a reason to be very bullish. Like, even if short term, all this competition pours into the app store and it's bloody and we're fighting and we're doing like competitive ad spend against each other and like, it's a little ugly for a little while. I think if AI does just like increase the baseline productivity of the world, I think there's a. It's reasonable to think that a lot of that excess, that surplus will get recaptured in like luxury spending on software on the app stores. At least that's one bull case, right? The bear case being OpenAI becomes all the apps or whatever. Like there's only three apps in the future and none of us have a job, I think is the extreme bear case. I don't. I'm not super worried about that. I think there's actually data in here about outliers and I think that will. Outliers will continue to be a big thing, but I don't think that necessarily means, like the middle and long tail are going to disappear. So.

A (10:03)

Yeah, Another Andreessen partner was actually on the 20 VC podcast and I saw somebody talking about that today on Twitter and their thesis is that most. The average person wants to be entertained and waste time, not be more productive, which is interesting.

B (10:21)

I mean, why do we. We work to spend money on things we like, right? Which is like entertainment, whatever, the thing that's driving us. We're a consumer economy, right? Like, you might work in a B2B whatever, but at the end of the day, consumers drive modern capitalist societies, right? And like, that's typically. It's like having the bigger car and the bigger house and like, all of these things have driven a ton of economic growth. And I think B2C apps are like a great thing to sop up that surplus.

A (10:49)

Yeah, exactly. And then thinking about, you know, all these new apps, they are still competing with YouTube and TikTok and just for Mindshare, like, can you get somebody to close the TikTok app or link out from the TikTok app to your app and actually spend a few minutes there.

B (11:06)

That's maybe the limit limiting factor on this going fully asymptotic, right? Like at some point, like, you run out of. There's no more time and attention in a human's life, right? To.

A (11:16)

Until the AI is doing all the work and then all the free time then goes back to abs. That's, that's. You go, that's a bull case.

B (11:22)

It's probably not going to look like, oh, people just work 30 hours now. But it, it, it might be, you know, it's gonna happen in subtle ways. I don't know how society is gonna like adapt and like infuse this stuff, but I do think that there are reasons to believe we're gonna have like echoing supply and demand shock. A limited resource is one of them. Just like consumer lag on understanding these things. People just figuring out, you know, everybody's vibe coding their little pet project app right now, which is cool. And it's like the ideas they already had. I think we're waiting on the next generation of ideas, which is like incorporating these models. They're vibe coded apps. They're. I mean, Calai just sold for like a bajillion jillion dollars or whatever, if you believe Twitter. And like, you know, that was an example of a. I want to say it's vibe coded, but it was like AI assisted development certainly, and AI driven. You know, like there, there was certainly a lot of, a lot there, but like it was a novel application of, to an old problem with using AI. Right. And I don't think we've necessarily cracked all of those, like revisited every problem we've tried in software. And then also like the models are going to continue to improve. Like their multimodal nature is going to get better. Like, there's so much, you know, if you just want to look at like the technology of these LLMs, like, obviously their base intelligence of the LLM is getting better year over year. But I think a lot of the advancement we've seen alongside has just been like harness engineering. Like Claude code and codecs. Yeah, Obviously they're powered by the models, but a lot of what makes them great is the harness. It's like how do they read files, how do you interact with them? The ecosystem. Right. And so that stuff isn't just pour more GPUs on it and make them go brrr. Like, you have to have engineers, they have to think about stuff. And so I think that same analogy too, we need to go through in a lot of apps where it's like, yes, we have this raw intelligence now. Yes, anybody can grab it off the shelf. The hard part is actually like, how do I apply this novelty to my problem? And that's not just like slap the sparkles on it. Right. Don't get me wrong, slap the sparkles on it do that too. But I think that's going to take time as people acclimate to this technology. And we're still like early mid cycle. I mean, yeah, on that stuff, especially every year the models are different. Right. So imagine that today's models, just imagine they had instantaneous voice and video interaction. Right. That that would change everything. Right. Again, as they say on Twitter. So like there's just so many more advances that can happen within these base models that is going to continue to drive like more opportunities and stuff. So I still think we're pretty early.

A (13:48)

We've talked a lot on this podcast and inside revenuecat about the being bullish on the power of these mini supercomputers in our pocket to improve the human condition.

B (13:58)

Now they're hooked up to actual supercomputers. Yeah.

A (14:01)

And so like there's so many more problem spaces and ways that things can be solved with LLMs and going deeper in niches. You know, Rick, our, what is he now? Chief revenue officer, he wrote a great piece though about just the bull case of like, you know, being so many more people building apps, so many more apps being shipped, the power of LLMs to address problems in new ways, to go deeper into niches, go broader. Like there's just going to be more software doing more for humans in the future. And I think that's a reason to be bullish. And I think a lot of that is going to happen on iPhones and Android devices.

B (14:42)

You think so? Those are going to be my question. Like, I go back and forth. I think it's reasonable that the phone that will persist. Right. It's hard to beat a tiny piece of magic glass that has a massive supply chain built up behind it and like, has like a form factor that seems not super far from optimal. Right. But also people are historically terrible at predicting the future. So like I'm, I'm not going to say that for sure.

A (15:08)

I'll go out on a limb and I've thought about this a lot and had this debate on Twitter various times over the years. But humans are inherently visual creatures and this whole idea of like, oh, you're just going to wake up and like ask ChatGPT, hey, what's my calendar? And like, what's the weather look like? And all that and then they're going to respond in voice and you're just going to have all this like voice first communication and stuff. A picture is worth a thousand words. That's a saying for a reason. And I think even if you're using voice to interact a lot. You're going to want some kind of display. So yes, maybe it does switch to like, you know, glasses with a heads up display. But even then, like, we're such a long way from that technology being good enough to have enough of an interface.

B (15:50)

We haven't got a good enough prototype to even validate if it's a good thing.

A (15:53)

Yeah. And then what do people spend most of their time doing anyway? They're on Instagram looking at pictures and videos and things like that.

B (16:00)

We don't need that. You know what I mean? There's not much more bandwidth to be squeezed out of like a next form factor. Right. You know, the phone. Yeah, it's a very high bandwidth, it's very good form factor. It's well engineered and if it does

A (16:12)

move to glasses, it will just be like a evolution of the phone in a way.

B (16:17)

Look, you could have called in 2007 that you wouldn't have your Macs anymore. But I think pretty much everybody, with the exception of the like casual computer user who like, is just browsing email, anybody who's like serious about compute, like in any way, like still uses a computer. Right? And I think even most people still use computer. I don't know what the penetration numbers are actually. I think I'm, I'm 80% bullish. But I do want to like, I want to leave myself. Stranger things have happened, right? Stranger things have happened. Who knows, maybe when the meta glasses, the AR glasses get really good, we have a different opinion. But I don't know, there's not a strong track record right now of any of these devices going completely viral. But like you would say that too in 2005 about smartphones right?

A (16:58)

On Twitter and kind of in the forefront of all this with like us tech nerds. It does seem like there's a lot of people who think it's going to happen a lot faster than it really is.

B (17:09)

The singularity.

A (17:10)

No more just that like, oh, the phone's going to be absolute.

B (17:13)

Apps are going to be, we'll call that the app developer singularity. For all intents and purposes, like apps

A (17:19)

are dead is like a saying for the past 15 years.

B (17:22)

It's like, yeah, cursor's dead too. Like everybody thinks things are dead.

A (17:27)

It's all going to happen much more slowly than, than you would think reading Twitter. I mean even like I get on the hype train of like, you know, robots are going to be doing my laundry and dishes. It's like, yeah, eventually 20 years.

B (17:41)

Yeah, I'm not going to make any bets on the state of subscription apps in 20, whatever that is. 56. No, you're 46. 20, 46.

A (17:49)

But we've got some time to keep building these. These little apps that help people.

B (17:53)

Yeah, yeah. And I mean, like, look, I think developers are gonna go where the economics are. People came to the App Store because it was the place to build where they could make money. Like, that's not gonna shift, like completely overnight. And I still, I called them call. I called it to somebody yesterday. The wet layer, Like, I think there's gonna always be a wet layer of software between, like the human and the human. I just think there will be because there's always gonna be like that last 10% that a, that a bot can't just like one shot that like OpenAI doesn't quite understand natively in the model. There are just certain things where, like even today that we could automate, but we don't. You know what I mean? Like, because people want people in the loop, right? Like sales. Like, could you automate, say, like, completely? Yeah, like, people try. It's like called self serve, right. But there's still this like, niche. I mean, call it niche. It's like you're selling big ticket items. Like, you people want a wet layer. Like they want like a human in the loop. Right. And it's not necessarily. Doesn't even make it better. Right. It just makes you feel. It's a feelings thing. I don't know what that looks like in software at scale, but it's plausible to think that there's at least a case. But I don't know. David, this could be a podcast by horseshoe salesman in 1910. Do you know what I mean? Like, convinced. Oh, yeah. It's going to change, but it's not going to be that fast. These things are loud and noisy and they break down all the time, you know, talking about cars. So I always want to leave the possibility that we're just like, we're just like out of step. And I think if, you know, if anybody of our listeners are worried about it, could be worried about it. I mean, you're playing in a market. Like, anytime you're in a market, you need to be smart and you need to be like, eyes up and you need to be, you know, if you want to win and compete, like, you have to be thinking a little bit ahead. So you should be trying these tools. You should be looking at what's going on in the market. You should be at the same time not losing the fundamentals, which is like helping customers achieve their goals and like talking to users and like all of these things. I think that's maybe one anti pattern I've seen is like maybe the open call rage has been a thing that was like, oh, finally an AI is going to run my company, get me to 10k, mrr, make no mistakes. And like that's cool. There's definitely leverage and claw tool like open claw and things like this. But I think the problem with free leverage is that everybody gets it, you know, like, so it's like it very quickly. The alpha, like the advantage it gives you over the market is, is fleeting. Right? So as long as you have some information that other people don't, you know something that other people don't, that's how you get like lasting alpha and lasting competitiveness in the market. So anyway, well, it's been a great podcast, David. Thank you.

A (20:20)

We're done here. We haven't even talked numbers.

B (20:23)

All right, the boring part now it's like we numbers, we don't need to talk numbers.

A (20:27)

Now I know most of you who read the report are just going to skip over the methodology section, but the methodology section is bigger and better than ever before. And we actually explain in a lot more detail than we have in the past a lot of what went on behind the scenes to generate the numbers, what they mean and stuff like that. And so to better understand report, spend a few minutes, read the methodology. I'll give a few highlights. In preparing the report, we didn't just look at all data. We did filter by apps that have active subscription revenue and meet minimum thresholds of installer revenue. So we did actually like lob off the kind of. I don't even know. I should have asked this. I don't know if it's like 10% or 25% but like this is not data from like, you know, the app that's only gotten 10 installs and one subscriber or something like that.

B (21:19)

We do some data preparation certainly that we think is appropriate to getting good

A (21:24)

signal and then for revenue cat customers to understand. It is all fully anonymized and aggregated so you're not going to see any individuals data in there. I've begged for years to figure out some way to include scatter plots because they're an easier way to like really understand distributions, but that would technically show individual user data. So we don't do scatter plots.

B (21:44)

You'd always do a distribution distribution and then just make up a fake scatter plot sample Monte carlo style or 2027 we'll do that.

A (21:52)

And then one interesting note this year and definitely worth kind of like reading the description in more detail. But we separated AI apps from non AI apps to just kind of get a sense for like what's going on in the market.

B (22:06)

And we've emailed all of the investors of non AI apps. So it's time to get with it, get with the program.

A (22:11)

And so just as an overview, whether an app uses AI or ML models for its primary value is kind of how we're trying to. And it is fairly subjective. This is not an objective measure. There's not like a checkbox people do in the app store of like, this is an AI app.

B (22:28)

You know, when you see it, yeah, sparkles, it costs more.

A (22:33)

So that, that part is not, you know, perfect. But we did our best and it is interesting to kind of make those comparisons. And some of the comparisons and we'll talk about it is that, you know, AI apps are commanding a much higher average revenue per user and things like that. So it is interesting to break it down by those first chart. Apps are booming. We kind of already talked about this, but when you look at the chart, it's freaking wild. In 2022, in January of 2022, 2,000 new subscription apps were launched per month. In January 2026, 14,700. Over 14,700. So a 7x 7x increase in the number of subscription apps four years.

B (23:19)

That's a lot. I can concur. We are seeing a similar thing actually. And most of that growth is concentrated in the last six months, I think.

A (23:28)

One thing to note real quick too, this is data. These two slides we'll talk about at the start are actually from app figures data.

B (23:34)

Yeah, it's not.

A (23:35)

This is the entire market. This is not just revenue. Cat. Although we're shipping in a large, very proportionate.

B (23:43)

Yeah, to that. I mean we certainly like have tracked that curve. But yeah, I think, I mean this goes back to what we were just talking about. But like we're in unprecedented times, as they say. But yeah, again, it's just like the natural what happens when you drop the cost of production massively. You get a. You get an oversupply or I mean they called an oversupply. You get a massive supply boost on apps, which is great. I think app we've seen Apple trying to catch up. Like app review has been like bogged down. Like we've been obviously like trying to handle all the interest and demand. Interestingly, this is like B2B insider stuff. But like these new customers are easier than old. Like, you know why they talk to the bot. The bot does everything. They don't even like an API. Like, I don't even know we're a company really. They just set the account up there. You know, the wet layer just does the oauth thing and like, we're done. But like, we have not seen a, like an increase in our ticket volume, which has been interesting, I think also we've gotten just better. The product gets better so we tickets go down. But like, it's been really.

A (24:39)

We've done a lot of work, you know, building their revenue cat mcp and like, we put a lot of work into making it really easy for agents to do the implementation.

B (24:46)

Like, it's just in terms of like watching. Like, it's a good. It doesn't. It's not really relevant for this crowd. But like, it's a good anecdote on like, why the charts that and ratios you got used to in the old world don't really apply because it changes. Just change. Things change. Like you wouldn't expect like I think a thousand more. 7x more users, 7 times more tickets. Nope, we've got 7 times more users per month. And like same number of tickets. Just like, what? And then you're like, oh, it's because they're already talking to an AI. So they just keep talking to the AI and can solve 90% of those problems for them, which is great.

A (25:18)

One thing I was surprised in these I figured numbers is that iOS now accounts for 77% of all new subscription app launches, and that's up from 67% in 2023. I would have thought that if you're vibe coding an app, why not just use React native and launch it on both platforms? But apparently a lot of folks are just either going native or still just not bothering to launch on.

B (25:44)

I mean, one thesis I'm just riffing, but like, could be the App Store schlep, like getting all your accounts approved, getting all your stuff in place, your bank accounts, da da da da has become a larger proportion of the painful part of building an app. So like only doing that on one store reduces, you know, you don't have to also go do that on play, right? So maybe that's part of it. Right. As a ratio of total work. But also it's not a huge shift, like 66 to 70 or whatever it was.

A (26:10)

Yeah, gosh, I didn't even think about that. But no, that's a really good point. Like, if you're vibe coding an app over a Weekend and the agent's doing most of the work. If two hours of, like, figuring out how to create a Google Play account and like, entering your social. Social or setting up a company and getting your duns. Now you got hung up on getting a DUNS number.

B (26:30)

Ye. I'm still hung up. I. I've been. I'm. I'm two months into getting a new App Store account set up. Never going to happen. I'm done. I'm retired.

A (26:38)

It's like that. It's funny that just setting up an account is one of the harder things in building an app.

B (26:45)

Yeah, this is a bottle. The bottlenecks have shifted, you know, so I don't know. It's interesting.

A (26:49)

Another chart we included from app figures is the share of revenue in 2025 from cohort of when the apps are built. Am I explaining that while you want

B (27:01)

to take how old are the apps?

A (27:03)

How old are the apps that are making money?

B (27:06)

What changed?

A (27:07)

Older apps are making most of the money. I mean, and it's not a change. It's just like a state of what's going on today. 69% of revenue in the app stores is coming from apps that were released before 2020.

B (27:20)

I almost commented on the doc to be like, most of history is in the past news at 11, right? It's like, of course. But, like, winners win, they compound. And I think we'll always. I don't know if it's shifted precipitously. I think you could imagine a world where, like, you know, more revenue is coming from newer apps would be a story in terms of, like, a higher dynamicism in the App Store, like, just more tumult. But it's just like, come on. Like, you're not gonna just like, the compounding advantage that Strava and Class Dojo is a good example, maybe. And like, I was also thinking Duolingo, like, all these, like. And then of course, like, the. The media companies, Netflix and. Yeah, those are gonna just continue. They're not gonna shrink. You know what I mean? Most likely they might trade a little bit back and forth. You know, I would love that we should go back and do so. We could reproduce a Sosa 2020 because, like, I think you'd probably see the same story and be like, most of the apps are produced before 2015. It's like, yeah, of course.

A (28:17)

Yeah. It just takes time to mature. The interesting thing on this chart, though, is that you do see 2022 and 2023. They kind of bucketed it weird. But 2020 to 2021 is 9% of the revenue, 2022 to 2023 is 14 of the revenue. So there was a bump in 2023 and I would imagine that's actually mostly chat GPT. Yeah. Open air.

B (28:38)

Yeah. I mean, I don't know app figures, numbers. Right. So like 2023. Yeah, it wasn't just chat GBT, it was like, it's like all of these like you know, in the next 10, you know, a lot of these like foundation models launched their products in 2023 which. Yeah, that's probably what you're seeing there. It's interesting that's, that is interesting when you see like a displacement like that where the, where the older cohort's actually producing a smaller share at that kind of really illustrates the shift that we've gone through.

A (29:05)

And this is going to be really interesting to follow up on in the coming years because this is the chart that's going to show you disruption. Like are these newer cohorts of apps disrupting older apps and like taking bigger shares, growing faster, you know, capturing wallet.

B (29:21)

A supply demand question implies the demand is limited. Right? Which if demand's growing fast enough, everybody's growing and just that's different rates. Yeah, it's hard to visualize.

A (29:29)

So an interesting one to look at now and I think it'll be even more fascinating in the next couple of years. But speaking of growing faster, that's the next thing I wanted to talk about was we have a chart in here talking about year over year growth in mrr. And this is fascinating and it's just a perfect illustration of power laws is that the top 10% of apps grew 306% and the bottom actually lost money and the median app only grew 5.3%.

B (30:03)

So what was the GDP growth of the last year? Yeah, about 5.3%. Isn't that funny how these things level out? But that's a median, right? It's not an averaging of all those things. Actually probably if you average the average of the App store is much higher because those outliers just contribute that top 5%. That top 2% of MRR growth last year probably drives a huge chunk of the total MRR average movement and that won't affect median as much. But yeah, I mean that's winners and losers. The sorting machine, that's what stripe called it a bunch in their annual report this year is the sorting machine is. I don't know who they didn't come up with that. But like these markets are just sorting machines and they're going to sort the fittest to the top and the least fit to the bottom. And. And yeah, I mean, we've seen, you know, again, I'll draw B2B. Like, we've seen just insane, meteoric growth rates at the very top tippy top of companies like Cursor just announced yesterday that added like a billion in revenue in a month and that company or in a quarter and that company's only two years old or something like this. Just totally unprecedented. We're seeing that too in these AI apps. Right. Like if you were the app that has the model that's the best, like, you can just get numbers that never were possible before because that just that level of differentiation was never possible for, like, you could be the best, whatever. Like, I use my friend Flighty, the best, like flight tracking app ever. I don't know if they ever, you know, had that level. You know what I mean? Like, and stuff. It's just like you have this ability that if you've done the capex capital expenditures to build one of these models, when you go to monetize it, it's truly better. I mean, that's why the Capex spending is so crazy. It's because it's like the returns are there. I wouldn't anybody, I think unless Sam's listening or Dario's listening or I don't think anybody should feel too bad if they're not in that, that, that top, top, top category. Like, there's a lot of as. It means half the apps are above 5.3. You're beating that GDP. You should be, you know, you should be kind of happy about that in some way right now. If you're doing. You lost 33 last year. It's like, oh, you know, maybe rethink your strategy.

A (32:04)

Rich get richer, poor get poorer. Yeah. That's just the way things probably people

B (32:07)

with apps, they've abandoned. Right. It's, you know, you have to think about that too. It's like just because, oh, I'm in.

A (32:11)

I'm in that. I'm in that stat.

B (32:13)

Yeah. If you have an app in this data set, you've written it off for whatever reason. You might just be moved on. It might. And it's not be the best ROI anymore. So there's. That's always in the data set too. So these are not like all strivers. Right. These are not all apps that are trying necessarily.

A (32:25)

I had a big launch in 2024 that did really well. And then we did not follow that up with marketing.

B (32:32)

Yeah. I mean, basically like treading Water implies effort, right? It implies like you're continuing to adapt and whatever the new marketing thing is and whatever the new features thing is. So.

A (32:42)

But it is interesting that the top 25% of apps grew 80% year over year. And it's a bigger market and there's more money and so there are more apps making more money than ever. And as concentrated as it is in those top apps growing 300% year over year, 25% of apps growing 80% year over year. Like there's a lot of growth happening and a lot of apps making a lot of money.

B (33:05)

So yeah, I mean, just think of the return on capital, right? Like, even if you're spending most of that, I don't know how the economics of the Calais ideal went. I thought, David, you're trying to get him on the podcast. Maybe we get some more details, sales. But like, you know, if you think, you know, they probably, I don't know, or maybe margin break even the whole time, right? Just reinvesting in growth. But then you have a big liquidity event at the end. You know, that's a way to monetize that all, all of a sudden and stuff. So it's like, if you can in any way drive 80% growth, even if it's break even, like, that's probably a good bet. If you think you have something like, with some amount of durability, which, like a good fitness app, it might, might be right?

A (33:40)

And with subscriptions, it's, it's that compounding if you have reasonable retention, the million dollars of ad spend this year, let's say you had the median retention, which is near 30, we'll just say 30. I think it's 27. But if you have median annual retention and you spend a million dollars in here in March of 2026, then March of 2027, that's $300,000 in free cash flow. And I've talked to a lot of apps.

B (34:06)

If you have a 1x like cacti, LTV or whatever, like, yeah, you can

A (34:10)

profitably spend a million dollars this month

B (34:13)

in the first year.

A (34:14)

Yeah, yeah, yeah. Just barely break even that next year. That's just free cash flow.

B (34:18)

So yeah. And then. And those retention rates get better if the product is sticky. It's like. And you also build, I mean there's all these like compounding things. You build, you build a list right now you have even all your churned customers become people you can market to, like more or less in perpetuity and like, and all of these things. So I think there's still apps and this is maybe a meta thing but like apps is like a venture target is still like a very rare asset. I don't think there's a ton of apps that's like venture capital is the right financing but there's certainly still like good financial engineering that you can do to like grow these apps with, you know, capital very quickly and it can pay off in some cases.

A (34:53)

It was really interesting talking to Olivia Moore from Andreessen Horowitz though. She's pretty bullish on consumer. I feel like there's. It's.

B (35:02)

If you can make a hundred bets.

A (35:04)

Well, yeah, yeah, it keeps going in waves. And what she shared and what we're seeing is some of these consumer apps are growing faster and exploding in ways and you know, if you lump in some of these like lovables and replits and other stuff, a lot of that growth is actually consumer growth of people who are tinkering with these and playing with them and using them for those kind of things versus like not strictly B2B growth. So yeah, it'll be interesting to see though how how venture capital, PE and others treat consumer moving forward as the market grows, as competition gets harder.

B (35:40)

I think probably right now, at least on the PE side, it's probably going to wait a little bit because I just don't think everybody really knows there's a lot of like B2B software roll up PE that's probably of questionable valuation at the moment. That might just be a January, February 2026 thing, but I think so. When growth curves are unpredictable, that's actually when ventures should be playing. Right? But then when we kind of understand these financial assets a little bit better, that's where like lower risk portfolio builds like PE and stuff do.

A (36:10)

And that's where I do feel like and again I talked to Olivia about this in the, in the minisode we did is that it is a blue ocean now of how do you rethink all of these entrenched consumer apps? Like what's the AI first calm and calm's not necessarily going to be the one to build that.

B (36:30)

You have to make the choice if you're that if you're that firm. Right. You have to make the choice to reinvent yourself. Right. And to probably break some of your precious eggs or whatever in the process. And that historically not always been the case that that firms have like adapted

A (36:45)

and that's where 2026 and 2027 might be the years we see the next like chatgpts where they, you know, launch this year and get to hundreds of millions of revenue.

B (36:54)

And Claude's on a run. Their super bowl ad paid off. Like, they're like anthropics making a. Making a real run at consumer already. We thought this was like a one category by OpenAI app figures just shared data that.

A (37:06)

That the Claude app went from making like hundreds of thousands a month a day.

B (37:11)

It was a day.

A (37:11)

Oh yeah, a day. To over almost a million dollars a day in revenue. So that. That just exploded when it seemed obvious that ChatGPT had won that market.

B (37:20)

Yeah, I mean it's look, consumers are, I will say, like the ChatGPT app defined the category, but that rarely. That the category initial category definer remains. I mean, maybe not rarely, but it's not given. And if nothing else, they create space. So like I don't. Don't count. Like. Like there's a lot of great. You think of Perplexity Gemini. These are probably categories that I don't know how many of our listeners are playing in. This is a handful of companies. But that same mindset can apply to every other niche where it's like, yeah, so and so's own this category for a million years. But like, if you're a little hungry, you've got some tokens to burn and some ideas like, I don't know, go. Go poke a bear. You know what I mean? See what happens. Like, why not?

A (38:03)

Yeah. And for a lot of these apps, people are going to use multiple. Like I have Claude and chatgpt.

B (38:08)

Yeah, I have a. I have a Claude Max. I have Chat GPT, Mac or Codex Max. I have all of them. So it depends on the day. You know what I want for which each thing. Gemini. I have a Gemini subscription too. I have them all.

A (38:18)

We just keep coming back to. I think there's still so much opportunity

B (38:21)

and we should have a. So someone year, David, where we get on. We just. There's no more opportunity. Sorry, no podcast. That'll be. You'll. You'll know there's no more opportunity. When we've all done. We've all paper hands this thing and we've all exited a private equity whatever. That's how you'll know you won't get a podcast. Oh, man. Humor. It's humor, David. It's jokes. It's fine.

A (38:41)

So the next thing I did want to talk about is one of the key takeaways from the report. I think it's like page four in the report. Hard paywalls crush freemium on download to paid hard paywalls convert five times better than freemium. They do 10.7% download to paid by day 35, versus 2.1% for freemium app. Huge.

B (39:04)

No day like the present. You know what I mean? That's my thesis on why that's so much better, but I'm surprised it's that stark, honestly.

A (39:14)

This is a tough one because, I mean, I have a hard paywall in my app. I've talked to a lot of people who are moving to hard paywalls. This really does boil down to a strategy decision of, are you building something that's going to be a category leader where that freemium base is meaningful? Are there advantages to having that freemium base? Are they telling their friends about it? Are there network effects? Are there data effects? You know, is there a reason to have users in the app? Yeah, and if not, I mean, a hard paywall does kind of make sense.

B (39:48)

And unless you have a viral thing you're trying to do or like, you know, you want your brand to be. Yeah, I mean, I think this is not necessarily new. I think it's just become more standard practice. And like, I would say, like, not doing this is probably becoming the exception. Unless you're just a side project or whatever, then you don't feel comfortable, don't force yourself to do it. But if you're like, if you've got a good product, if you believe in it, if it's valuable, you think it's valuable, and you're doing spend, you're doing acquisition, I think you'd. Unless you're very, very, very dedicated to it. I think it's worth considering for the right app, though.

A (40:27)

Freemium can be super powerful. I did. One of the minisodes I did was with Michael from Mojo, and their app does more than 50% of revenue. Not on the first day. And so we'll get to stats in this report. But, you know, Most apps see 80% of their conversions on the first day, day zero. That people are opening the app. But he sees that as a superpower, is that they have a generous free tier. And so they do convert a lot of people on day zero on that first day. But then they had. They're able to convert a ton of people over time. And one of the things that he talked about in that episode is they're doing a paywall all launch for freemium users. And they're tasteful about it. They only do it once a week and stuff. But it's like now, instead of getting this one shot, you get somebody in, and if they retain and keep using the app, you've got a lot of opportunities to keep hitting them with like, oh, check out this free feature, premium feature, you know, upgrade here.

B (41:24)

There's probably. There's a spectrum, right? It's not hard paywall or no pay. No full freemium. And you know what I mean?

A (41:31)

Maybe even a phase. Like you launch hard paywall and then you get the product where you feel good about it and then you switch to freemium.

B (41:39)

Yeah. I think your acquisition strategy should inform this probably more than just our one anecdote and stuff. But yeah, I've saying on this podcast, David, since we've had a podcast, people undercharged. They don't believe their stuff's worth it. They have imposter syndrome and all these things. They think everybody's gonna get mad at them because they didn't give them something for free. Look, always we were. I was having this debate today about stuff and revenue, Cat and us charging for it. And it's like, look, they could just not have it. We could just not make it. Is that better? What do you want? You know? You know, so it's like, it's a. I think it's a thing that this is like a first time, second time founder thing some too, but some people are just super sensitive about it. And like also just pricing is so transient. Like, people don't like. If you try it and people don't like it, you guys roll back. Nobody's gonna know. You know, it's fine. But it's def. Something to try.

A (42:29)

I wanted to have this conversation and be a little more nuanced because if you go look at the report, it's like, oh, hard paywall is obviously the thing to do. Like, it's going to make me five times more money.

B (42:39)

Well, maybe just paste Sosa into Claude and just make more money. Make no mistakes, you know, I don't know. That might outperform a human overthinking it. Right? Let your bot do the overthinking. But I think it falls into the same category as everything. You know, David, there's this. Make it a good report and then there's like, you know, all the nuance, right, Is maybe it doesn't fit in the report always, but I don't think there's any. I don't. I think the data is true. And like there's just this, like, this is in life and software, you know, there's no time like the present, right, when somebody's in your app and they're using your app. The cross section of intent and numbers and everything is usually just at its peak. So like make as much hay out of it as possible because seven days from now, even if you're out app is great for them. They're not going to care as much. So maximize that moment.

A (43:27)

And that's the thing about freemium is that they, people actually have to retain for them to open the app and see your paywall again.

B (43:35)

Yeah, yeah, yeah, you have them now. Like you're going to miss a shot. You know, you're going to lose half of them in a 50, you know, 50% day one retention would be great. So you're going to lose half of them tomorrow. And again, it's like they've already crossed a lot of chasms to get to you. They searched, they had intent, they downloaded, they opened, they went through your onboarding. Right? You're never to have embass primed and as jazzed about your product as they are right now. So like capture it on the hard

A (44:01)

versus soft paywall or hard paywall versus freemium. The one thing I was surprised is that retention on the hard paywall was right in line. I mean, a little lower than year one retention for freemium. So, you know, I kind of would have guessed, you know, an app that forces you into the decision day one and you can't even use the app. I would have assumed human meatbag intuition. Like those people will probably churn at a higher rate because you force them into the decision. But it's pretty equivalent. Like the P90 retention on freemium is 58% and for hardware paywall it's 54. But the median is 27.7 for freemium and 26.8 for yearly, a kind of a wash in the median. So you're not sacrificing retention or. I mean, each app is going to be different, but in aggregate, people aren't sacrificing retention by doing a hard paywall.

B (45:00)

It's actually a little bit, it's a little bit non, non obvious to me that I wouldn't move it, but because usually anytime you like change something substantial, it's going to move your mix. But there's probably two forces there. I'm not going to speculate, but there's probably one that increases and one that decreases and they're just balancing each other out. Out would be my guess, but. But yeah, it's free money. Just do it.

A (45:22)

All right, the next thing I wanted to talk about was the window to win a user is closing. 55% of all three day trial cancellations happen on day zero, this is another chart that when you look at it, it's just massive concentration, just stark that

B (45:39)

it's a flip side of the same thing point we just made. Right. Which is like, you know, most of the things happened in that first thing day, you know, including them canceling your trial. Right?

A (45:50)

Yeah. People start that trial and then immediately go turn out. This is, this has been a growing trend. I don't think we shared year over year numbers here, but I believe it's, it's been a continued trend that this goes up every year then more and more super savviness.

B (46:04)

Right?

A (46:05)

Yeah.

B (46:05)

Apple's also been more betterer about like sending out notifications and things. But that makes sense. I mean, good, good, you know, good.

A (46:15)

Yeah.

B (46:16)

I love an auto renewing trial. Auto converting. It's great for, it's great for app developers. It's seamless for consumers. But also I think if consumers are opting out, it's good too. Let them do it.

A (46:27)

You know, one little tactical point, I talked to Anmol from Duolingo in one of the minisodes and he said Duolingo had been experimenting with that trial reminder, kind of the Blinkist trial reminder paywall where it's hey, we'll remind you about the trial so you can cancel it. Well now Duolingo experimented with letting people choose what day they want to get the reminder on, which draws attention to hey, like we're going to remind you about this free trial. And so they saw a conversion uplift from that.

B (47:00)

So yeah, I mean you're, you're getting people to not Cancel on date 0. Yeah, that's what you're doing, I think, I don't know.

A (47:08)

But then you're, then you're reminding them so you know, maybe the notification gets lost or whatever, but who knows?

B (47:14)

Who knows? These are, these are consumers buying at willing prices. David, that's interesting. I mean certainly a good look. I'm still a big fan of the blankets paywall. I think in the reminders and stuff. I think it's an app brand positive and trying to trick people.

A (47:25)

All right. Next thing is Google's billion dollar leak. Not a huge fan of that framing. I don't. It just, it is what it is. Google Play is a very different platform with different, and consumers with different forms of payment. But it is really interesting that nearly a third of all subscription cancellations on Google Play are involuntary billing failures.

B (47:47)

Yeah, we see this all the time. The customers being like, why am I getting so many billing issues?

A (47:52)

Yeah, I don't Doubling.

B (47:54)

I don't, I couldn't tell you exactly the, the reasoning for that. I don't know if it's just like economics of who owns Androids. I don't know if it's like the way they do this.

A (48:03)

Some of it's payment method because Google

B (48:05)

will let you use prepaid cards and stuff like this.

A (48:08)

Yeah. So then your balance runs out and then the billing fails.

B (48:11)

Yeah. The physics are just very different. There's not an auto recovery path like there is on iOS. I mean there's just, there's just a whole number of reasons. It just compounds the fact that makes like Android. So even if you get. You still see like, you know, whatever. I don't know what our blend is, but it's 10, 15% Android revenue versus the rest iOS probably in web. But like you see why it's not just a market's not there. It's like also the bucket's leakier, the conversion's harder, you know, and stuff. I'm good on Google for putting in the good fight, keeping it going. We need two platforms, but yeah, it answers your question about why people are continually increased their iOS concentration from earlier.

A (48:49)

As I was researching this, Google did share one of their like developer pages that folks who turn on grace period. And there's another feature. I don't remember it off the top of my head, but you need to be, especially on Android, you need to

B (49:03)

be thinking about this, managing this problem. Yeah, well, I mean there's also like communication things you can do, like you can support and we have, we have good hooks for this in revenue Cat. To make it easier, you should do all the things right. Like especially once, once Android's beyond just like experimental revenue for you.

A (49:18)

And it kind of makes sense. Like the Apple platform is way more oriented around keeping your credit card up to date. Everything is Apple pay. You've got your Apple subscription. That keeps your photo library in the cloud. It feels like as a platform they do kind of more strongly incentivize you to keep your billing updated. Keep, keep money flowing through their systems.

B (49:41)

It's the whole benefit of having a great retail partner. Right. They make the buying experience good, they keep consumers coming and you're willing to pay a fee for it. Right. So.

A (49:49)

And then speaking of churn, on Google Play, we did include an interesting chart about the reasons for cancellation. So there's actually an API that we call and get this data from our customers because Google asks when you cancel in Google Play, why did you cancel? And then we're able to get that data and then aggregate it. And so it's interesting. The top reason is cost related and it swept back and forth. I think last year it was maybe not enough usage, but I mean, are

B (50:18)

those not the same answer though? You know what I mean? Like it's not enough usage to justify the cost. Right there. Sort of like interrelated reasons. Right. So necessarily read.

A (50:27)

But, but if you combine the two. That's a good point. If you combine the two as a, as a value proposition, not using it enough to be worth the money, that's 70% cancellation.

B (50:38)

So it makes sense economics. You know, people stop paying for stuff they don't want.

A (50:43)

Technical issues is small. Found a better app is small. So like you're, you're more likely to use lose a customer because the value prop is not there than you are because they found a different app that solves that need.

B (50:55)

App developers tweets. Is that on there? No. No. Okay, good.

A (50:59)

All right, back to AI apps. So AI apps sell, but they don't stick. AI powered.

B (51:06)

Yeah, I saw. This is interesting.

A (51:07)

AI powered apps generate 41% more revenue per pair, but they churn 30% faster. Year one retention is 21% versus 31%. That's interesting. I mean it does feel like there's. There have been so many generative AI apps launch and some of them are, you know, the studio Ghibli, like when that, that exploded for ChatGPT. But a bunch of like other apps jumped on that bandwagon and released apps.

B (51:38)

I think it's like they've not, most of these have not solved the sticky like building stickiness like ChatGPT. I'm going to throw them under the bus a little bit on this. It's like, yeah, they have memory me, but like I don't feel super invested in my Chat GPT app history, right. I open it, I run a query, it's whatever and then it's transient. Codex is a little bit different because I'm like building sort of like my codex workflows and things like this, but that's a very niche thing. And I think this is one of the things that like open claw kind of blew open, which was like, just give this thing more stuff that about you, right? Give it more integrations, give it like obviously give it more power is helpful. But I think like, but even, even open claws. An example, at the end of the day, it's a bunch of integrations and skill files which are like fairly transferable, right? And that's like on the like agent side, but like you know, I think we're just in an emerging market where like new products are coming out every three months and people are willing to shift and there's not a huge like lock in effect. Now you've seen I think of the chat GPT they've OpenAI has been pushing their medical thing. Like they're like bring all your medical history in like now and, and like OB1. I think it'll be a very useful feature. But then secondly it serves a purpose for them of like okay, now if OpenAI has, I have my, my epic chart, whatever is linked to it, it has all my medical records and like all of this stuff. Like I think you start to build those. But it's gonna take a while. It's gonna take a while for these products to like really figure out what they're sticky, you know, like they're, let's assume we hit like terminal, some sort of like terminal model functionality. At some point they're gonna need to like innovate on more of the consumer features.

A (53:16)

I think it also just shows people are willing to try stuff. Like there have been so many new AI powered apps launching like to do this photo manipulation.

B (53:24)

Oh yeah, I'll sub to anything right now if it's novel, new photo thing, new audio thing, whatever, I'll try it. 20 bucks a month.

A (53:33)

People are willing to try stuff. But AI apps do need to figure this out for the long haul to get those sticky.

B (53:39)

There's the long tail, like runs like I don't know if you're building, building but I think you actually have a better. If you're like doing an applied, you have a very different problem. You're like a Strava as an example or like a Strava clone or something like this. Like you're building a, still building a data moat like of stuff. And I actually, I think this is a, it's an interesting, you know, I think that there's a lot of discussion going on like where's the defensibility in software? Because like one, it's cheaper to make software and all this stuff but there's still a ton of defensibility in that like long term customer relationship. So like Dropbox has all my photos, Strava has all my workouts, all of these things. Right. And those can't be vibe coded in a weekend. You're actually in a stronger position than these like brand new and also like mostly stateless like AI tools that yeah, I've had better stickiness for my like little personal open call deployment just because I can modify it. And I'm building, I'm building an empire inside of it, of things it can do. Not so much in my, my chat, GPTs and things like this. So yeah, doesn't surprise.

A (54:36)

All right, another hot take that deserves a little nuance. Trials of 17 days or longer convert 70% better than short trials, 42.5% versus 25.5%. But year over year, more apps shifted to three day trials. So this is one where, and I've talked to Rick about this, I think this is a correlation versus causation kind of thing. We will you get better conversion if you have a longer trial? Maybe it's worth trying, but I don't think you're guaranteed that. And the thing about three day free trials, like the reason people do that is cash flow. You brought that up.

B (55:16)

You want the money in three days, you don't want the money in 30 days. Right.

A (55:20)

And getting conversion data faster to compound experiments you're doing on onboarding and paywall and everything else like that. So it's tough because yes, in an ideal state, Maybe everybody offered 14 days or 30 days or whatever. And the data shows that those longer trials convert better.

B (55:39)

But, but it could still be a net loss if you're having to like, if you're losing that like information flow, you're losing that cash flow, you're losing all those things. Like even, yeah, you get to eke out a few points on conversion rates might not be worth it.

A (55:51)

Back to what we were talking about earlier with the day zero cancellations. I mean that, that is probably part of it is that when you have a 14 day free trial, it's like, oh, or I mean 17 plus meaning 30 day free trials. It's like there's a little bit more of a, like, oh, I've got plenty of time to check this out. And like, you know, you don't immediately go turn off auto renew because you're like, oh, I'll remember to turn that off. You know, maybe that's some of it just that. But I think there's probably a bit where the apps that are giving 30 day free trials are different kinds of apps than the apps that are offering during three day free trials.

B (56:23)

Some selection bias, right? Like, and then just like apps too that are, if you're spending a lot on ads, you're probably less differentiated. I don't know if that's true. It's not because you spend on ads, but if you're like in a competitive market, you often need to, I think everything in the. So report is worth, like, considering some of those dynamics. Like, we can't like fully separate causation and correlation. So it's perfectly plausible. Right, which is why, I mean, going back to nuance is like why you should never take one of these, these single data points and treat it as gospel. Because it's going to be different for your app.

A (56:53)

You know, run your business on it. All right, two. Two quick hits as we wrap up. We shared a really cool word chart is the distribution of paywall call to action language. So we shipped our paywall solution. Well, we shipped our first paywall solution a couple years ago, but we've been like accumulating all this data now of what people are actually using on their paywalls. And so you look at this word chart. Continue is still like the biggest. Subscribe is the second big thing. Biggest. But you've got a whole bunch of like. This is a fun chart to just look at for cta.

B (57:24)

What are some good ones? I don't have it in front of me.

A (57:26)

David Redeem offer Get premium. Get started now start for free. GoPro. I mean, there's a. Just a ton.

B (57:34)

I want to look at the long tail. Those are the ones that lots of people use. We should look at the ones that like very few people use because, well,

A (57:40)

I was reading like some of the little tiny.

B (57:41)

No, I mean like the one ups. Those are probably the weird ones.

A (57:44)

But the one I'm not seeing in. Oh no, it is in here. It's one of the smallest ones. But Try for zero dollars and zero cent. I talked to the chief product officer at Duolingo on the podcast and that was released back in I think January and he said that was like a meaningful lift for them. And like Try for free did not convert as well as try for $0 and 0 cents.

B (58:08)

Looks like you got a bug.

A (58:10)

But anyways, just another example of how the 2026 report is better and bigger than ever. Like this. It really is fun to see this word chart and look through all these different, different words and phrases in there. The last one I wanted to touch on was the cancellation timeline for annual subscriptions. This is really cool. And we've shared this in different forms over the years, but I actually really like the visualization here.

B (58:30)

Yeah, I saw. Yeah, I agree. That's a good way to look at it.

A (58:33)

What it shows is for people who ultimately churn. When did they turn off auto renew? And when we first pulled this data years ago, it surprised me. I think we've talked about this on the podcast before. But I always expected that for an annual subscription you would see a large portion, if not the majority of people who churn, churn right before, you know, month 12, right before it renews. But no, 34%, this is across all categories. 34% cancel in that first month and only 11%. So there's a bump because month 11 is 4.7% and it bumps up to

B (59:10)

11% and then like right at the renewal time, like people turn on, but

A (59:13)

it's not like a U, it's like a a J, but like a tiny J curve. I just would, I just had always intuition would have expected this to be way higher. But anyways, what, what this says is that people are turning off auto renew when they see that charge hit the credit card or, you know, soon after. They're making that decision sooner rather than later. So just another just like we're talking about with zero day, zero free trials and getting people to retain and things like that. So like, you gotta make your impression soon because they're not just. People aren't just sticking around and making that decision. At day 364.

B (59:50)

I was just jazzed about the visualization. I thought that was like, finally we figured out a way to make it not look dumb and hard to read. So we're renovating over here. You know, wait for the Innovation Sosa report. It's gonna be even better. Yeah, no, the problem is we're gonna, we're gonna. This is the ideal and next year we're gonna try something worse. But that's okay.

A (60:08)

But do we even need visualizations? In 2026, you're just getting dumped into cloud code.

B (60:13)

Oh yeah.

A (60:14)

And have your agent tell you, oh,

B (60:18)

we're supposed to plug this, but yeah, I was just thinking about this. So it's one of the inputs. So we're working on some cool stuff here. Like, we've talked about AI stuff, but we've been hacking on Revenue Cat's own agent internally, which I'm workshopping right now. I don't know if what will announce this, but it's Revenue Intelligence Copilot. Read rico. He makes you rico. I'm really, I'm more excited about that than everybody else on the team. So we'll see how we actually ship it.

A (60:38)

I didn't know it was an acronym and I thought RICO is kind of goofy.

B (60:42)

But. No, it's Revenue Intelligence Copilot. It just happens to also mean rich in Spanish, which I think is funny. But yeah, we've. We've built a, you know, I think a Lot of people in the community have been, have kind of hacked this together, which is like pulling your revenue CAT data and maybe some other stuff. We want to bring this to like a first party feature into the RevenueCat platform as we like figure out like what does it mean to be a system of record, you know, in the future. And I don't think there's, I don't think there's any great. There's not gonna be any vendor our customers have, they feel great about that doesn't have like well built agentic interaction like built into it. And so we're, we're figuring that out. I'll be honest. You know, we're mostly a JSON and databases company. So this is like all new territory for us. But it's not rocket surgery as they say. And what we've seen this thing produce, I mean, David, you've used this.

A (61:27)

It's really fun.

B (61:27)

Yeah, it's, it's great. It's a fun way to interact with it. It also can just do things that you can, everything you can do in revenue CAT is just what the agent can do. But it's just faster. It's got, it can click faster, it can pull data faster, it adds a little bit of color, which maybe isn't even the most valuable part. The most valuable part is like it can just pull the charts a lot faster than you can. Right.

A (61:48)

So currently we've been using internally as a, as a slack bot where you can just ask like at rico, you know, how was performance last week? You know, but what's cool is like you hooked up last year's report and then you're going to have it into this year's report.

B (62:03)

So this is integrated.

A (62:04)

Yeah. The reason I wanted to bring this up is because I was going to suggest people just drop the report into a Claude project and then bounce your data in. Ask it things you should be thinking about. You know, use it in a project in claude. But like for revenue CAT customers who enabled this feature, once we release it, that, that like that works out of the box. Like you just say like how does this compare? You know, what things am I weak on compared to the, the report? What things should I be thinking about? And it's pretty smart.

B (62:36)

Yeah, these models are great. Nothing to do with US revenue. It's all just like we just gave it this stuff. It's actually a good idea. We should note this for, but we should release like a, a markdown version of the, of the report. That'd be easier for people than dropping just like a raw PDF in. But yeah, I'm, I'm super excited. I mean, I don't know. Want to plug too much of our book, but like, we're like awakening to how we can make revenue cap more AI powered and sparkly. And so RICO is kind of this first. Kind of this first iteration we're hoping to ship. Ideally, maybe this is out before the podcast drops, but we're still putting some finishing touches on it. But we're also working on, like, how do you agentically interact with paywalls? Like how do vibe code apps or vibe coding environments, like, create paywalls and stop having to like click all the time. Time. Basically, like in 2026, we're tired of clicking. No more clicking. We're typing. No more clicking. Maybe talking, but we're not clicking on things anymore. And then. And then also, like, we have an open claw skill which you can use on your. You can use it in Claude as well. Like, we'll get. We should get it on the Claude Marketplace as well.

A (63:36)

Yeah, I think we have a GPT, a chat GPT plugin now as well. Like, it's so fun internally because people just build this stuff and like, I don't even know all the stuff we have.

B (63:46)

Yeah. And we're adapting to this new world and I think we're just. We're just getting started. So hopefully, hopefully that that's live by the time this drops. If not, keep. Stay tuned. We'll find out. Six days, sign up for the beta. Yeah, for sure.

A (64:00)

All right, well, I think it's a good place to wrap up. Drop the report into an agent and just have it tell you all the things.

B (64:05)

And you listen to this podcast, you're

A (64:08)

probably listen all the way to the end.

B (64:09)

You probably had your agent summarize it is reading is. Is giving you the digest. But anyway, if you have have listened, it's fun. These are one of my favorite ones we do every year.

A (64:18)

2026 is a weird time.

B (64:20)

It's a weird year. It's. The weirdness shall increase until morale improves, I believe. So everybody buckle up. I don't think we're. I don't think. I don't think we've hit peak weird yet. So.

A (64:30)

Well, I did want to shout out the team, Peter and Lorelai and everybody else who put in all so much work. It was a huge group effort, Baron and we. We had a contractor working a lot of.

B (64:42)

I know things must be going well at revenue Cat when every year I hear less and less about. About it. So you know what I mean, the first year, it was, like a whole team effort, and now it's like, it's still a lot of people involved, but, like, it's. It's. It's operating much more efficiently.

A (64:55)

Yeah, the first year, it just. It took so much more of the small team that we had, like, as a percentage of all work done at Revenue Cat, we pulled in the ops

B (65:04)

team and, like, all this other stuff.

A (65:06)

Yeah, yeah. And then now it's like, as we've grown, it was still a massive effort, but as a percentage of all the work getting done at Revenue Cat, it's much so.

B (65:13)

Dear, dear listener, we do it for you. You know, we're like, investing our finite resources and then putting this report together, and I think we're really proud of it.

A (65:21)

So, yeah, it turned out great. And so, yeah, you've probably already downloaded the report. Check it out, and we'll see you later. Yeah. Thanks so much for listening. If you have a minute, please leave a review in your favorite podcast player. You can also stop by chat.subclub.com to join our private community.