Lenny's Podcast: Product | Career | Growth - Why ChatGPT will be the next big growth channel (and how to capitalize on it) | Brian Balfour (Reforge)

Starting point is 00:00:00 Everyone's always complaining. SEO's dead. It can't grow. Word of mouth is so hard. All of the ingredients for new distribution platform are essentially happening. My prediction, the new distribution platform will be chat GPT. There's a bunch of signals that they're about to launch that. This is a huge opportunity for companies to get on it.

Starting point is 00:00:16 It ends up being a prisoner's dilemma. Don't trick yourself into thinking that you can't play the game. The cycles seem to be getting shorter and shorter. So you actually have a smaller amount of time. If you don't do it, your competitors are going to go to the new platform and your customer expectations change. There is no opting out of the game. This is the opportunity to disrupt an incumbent. If you're a late-stage company, you place multiple bets.

Starting point is 00:00:36 For startups, it's a totally different ballgame. You have to choose one and go all in. Think about companies like Zinga that grew on Facebook and then became massive companies. Building a great product is one of those things that's necessary, but not sufficient. And actually, the separation is between those that build really great distribution. Well, it would be the backup, if not chat, JCP. My hypothesis of whose best positioned would actually be it. Today, my guest is Brian Balfour.

Starting point is 00:01:01 Brian is the founder and CEO of Reforge, a company that I've been a long-time fan and advocate of. Historically, Reforge has focused primarily on teaching courses on product and growth. But more recently, they've transitioned to building their own products, including a product called Reforge Insights and a bunch more of really cool stuff coming very soon, prior to Reforge Brian-led growth at HubSpot. And over the course of his career, he has seen the rise and fall of every major distribution channel, including Facebook's ad platform, Google Ads and SEO, and the Apple App Store.

Starting point is 00:01:31 Based on what he's seeing, he is predicting the emergence of a brand new and powerful distribution channel that will likely arise in the next six months centered most likely around ChatGPT. It is really rare for a new growth channel to open up. It's been a long time since the last one appeared, and the people who recognize this and hop on it early are the ones that reap the most rewards. So this is a huge deal. In this conversation, Brian shares what he's predicting, what he's seeing, why, this is a big deal and what you should be doing about it right now. I highly recommend you

Starting point is 00:02:02 listen to this full conversation and discuss the ramifications with your team. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. Also, if you become an annual subscriber of my newsletter, you get a bunch of incredible products for free for one year, including lovable, replet, bolt, N8N, linear, superhuman, Descript, whisperflow, gamma, perplexity, warp, granola, magic patterns, raycast, chapier, and Mobbin. Check it out at Lenny's newsletter.com and click ProductPass. With that, I bring you Brian Balfour. Today's episode is brought to you by DX, the developer intelligence platform designed by leading researchers. To thrive in the AI era, organizations need to adapt quickly.

Starting point is 00:02:42 But many organization leaders struggle to answer pressing questions like, which tools are working, how are they being used, what's actually driving value? DX provides the data and insights that leaders need to navigate this shift. With DX, companies like Dropbox, booking.com, adion, and intercom, get a deep understanding of how AI is providing value to their developers and what impact AI is having on engineering productivity. To learn more, visit DX's website at getdX.com slash Lenny. That's getdX.com slash Lenny. This episode is brought to you by Basecamp. Basecamp is the famously straightforward project management system from 37 signals. Most project management systems are either inadequate or frustratingly complex, but Basecamp is refreshingly clear. It's simple to get started, easy to organize, and Basecamp's visual tools help you see exactly what everyone is working on and how all work is progressing.

Starting point is 00:03:39 Keep all your files and conversations about projects directly connected to the projects themselves so that you always know where stuff is and you're not constantly switching contexts. Running a business is hard. Managing your projects should be easy. I've been a long-time fan of what 37 signals has been up to you, and I'm really excited to be sharing this with you. Sign up for a free account at basecamp.com slash Lenny. Get somewhere with base camp. Brian, thank you so much for being here, and welcome back to the podcast. Yeah, thanks for having me.

Starting point is 00:04:10 Excited for this one. I'm really excited to have you back. We're just going to dive right in. Essentially, you've uncovered a really important trend or insight about how products are going to grow differently in the future, how growth is changing. And this is something that I think a lot of people need to hear. So I asked you to come on to share what you're seeing. I also think it's just very timely. I think you said, like you're going to say in the next six months, things might significantly change.

Starting point is 00:04:37 So I'm really excited to do this. We're going to spend this whole conversation on this insight to set us up. What is just the big idea? What's the high-level idea here? Just like you, I've spent my whole career just like really passionate about startups, you know, figuring out how to build products that win, that emerge. in new markets. And one of the things that I have, you know, learned over time or one of the things you hear a lot is from a lot of folks is to when you have to like really build a great product.

Starting point is 00:05:07 A lot of the device kind of boils onto that. And one of the things that I feel like I've banged my head against the wall in a lot of ways of my career is actually telling people that building a great product is one of those things that's necessary, but not sufficient. And actually the separation is between those that build really great distribution. And so this general partner, his name's Alex Rampel, he's at Andresen War Horowitz, actually wrote this blog post 10 years ago back in like 2015. In the essence of the blog post, he basically says one thing, which is that startups is a game of trying to get distribution before the incumbent can copy.

Starting point is 00:05:49 So it's this kind of concept of escape velocity. And so, you know, on that note, right, which I think is like a very good summary of like what you're trying to do in a startup and distribution is that we're right now living in this environment where that game of startups kind of getting distribution faster than the incumbent has gotten way harder in a lot of ways. And in some small cases, has gotten a little bit easier. But if we think about this, the way that it's gotten harder in some of the things that probably a lot of founders or folks working on the growth. I'd probably feel is that one is that incumbents can copy faster these days, right? So that window that you have to get that escape velocity is actually shrunk. It's decreased. The second thing is that a lot of the organic distribution that we've had, especially over the past few years, has really shrunk as well. So everybody's talking about the decline of SEO and, you know, clicks declining. But you also

Starting point is 00:06:48 see it in some other cases, right? A lot of these social platforms, don't really let you send as much traffic to sites. You know, LinkedIn just changed their algorithm, which is really dropped organic distribution. Obviously, the Twitter to X transition that happened, right? Like TikTok's almost always been like that. And then the third way that it's gotten harder is that AI is really good at writing software, right, in code generation.

Starting point is 00:07:12 And so everybody's kind of feeling this infinite increase of competition, especially at the startup level. And, you know, YC's pumping out six of the same thing every single cohort, right? Like, that's what it literally feels like. So it's gotten way harder. This game, this escape velocity game, has gotten a lot harder. It's gotten easier in some very exceptional cases, like a cursor or something where AI has kind of been like the spark.

Starting point is 00:07:33 You know, I know you wrote the blog post about the race car engine. And I think you said, like, there's like the spark plug in the engine, right? And so AI kind of really created that a new type of spark, a new type of interest of early adopters to fuel some new players in a short period. of time, right? And so it's amazing to see something like cursor overtake market share of something like GitHub co-pilot in nine months or less, right? Like that's how fast it happens. It's kind of crazy. But the main thing that people need to understand is, okay, well, if that's the game I'm playing, right, how to get to escape velocity before the incumbent, like what are all

Starting point is 00:08:08 the ways to do that? And to really figure that out. And there's multiple ways that this can happen, but one of the major ways, one of the major, major ways that we always see is that this can happen when new distribution platforms emerge. And because when new distribution platforms emerge, startups are usually the fastest to take advantage of them. It's slower for the incumbents to move. It gives startups this opportunity, essentially, to play this game. So Casey Winters wrote this blog post about two years ago,

Starting point is 00:08:42 maybe like 18 months ago, about the AI technology shift. And his key point was the AI technology shift has been a technology shift that has not come with the distribution shift yet. So if you look historically, we've had a bunch of technology ships from, you know, to internet to the cloud, to mobile, to social, like all of these different types of things. And some of them come with distribution, new distribution platforms, new ways to distribute products, and some of them don't. But the most powerful ones, the most impactful ones are the ones that do come with these new distribution platforms. And so his second key point was that these two things don't actually happen at

Starting point is 00:09:20 once. Usually you get the technology shift, then you get the distribution shift a little bit later. So now we're a couple years from that post. We are a couple years into AI technology shift. And one of the things that I am seeing is all of the conditions, all of the ingredients for a new distribution platform to emerge are essentially happening. And so I think we're at an inflection point where we're going to see this emerge really fast. And the key thing for everybody to know is that as new distribution platforms emerge, they follow the same four-step cycle. And it's kind of a game that you're playing,

Starting point is 00:09:55 that everybody's playing. And so just like any game, you kind of need to know the rules of the game. You need to know the steps of the game in order to have any sort of opportunity to win. And that's kind of like the thing that I've lived through, once again, both painfully and also in good ways. And is something that I'm keeping my eye on

Starting point is 00:10:16 and something that I've been talking about. So before we go into that, you know, four-step cycle, I figure I'll pause there to see if you have any follow-up questions on that. Okay, this is amazing. So essentially what you're saying is we've all these ways to grow. There's SEO, there's paid growth, there's sales. All these channels have been around for a long time. They're extremely saturated.

Starting point is 00:10:36 Everyone's always complaining. SEO is dead. It can't grow with SEO anymore. It can't grow. Word of mouth is so hard. There's so many amazing things. Now that's hard. Paid is so hard.

Starting point is 00:10:45 It's just like all this money. Tax are rising. Exactly. All these things. Yeah. So all these saturated channels. And what you're saying is there's an emerging new channel that has not yet been saturated. And this is a huge opportunity for companies to get on it.

Starting point is 00:11:01 And you'll talk about timing because it's a little tricky to even know exactly when to go big on this. That's right. But that's a huge deal. This has been a long time since there's a new way to grow that you can actually use as a lever for growth and not just hope for the best. Okay. Yeah. Before you get into the cycles, do you want to tease what the answer is just to give people a little hint, or do you want to keep it secret? Well, to be clear, right? Like, okay, so my prediction will, we don't have a clear winner yet. My prediction of the new distribution platform will be chat GPT in some ways that people probably already think it's happening in some ways that it won't.

Starting point is 00:11:40 but the thing that is less important, or like that is more important than whether I have predicted the exact winner correctly, the thing that's more important is to understand the cycle and evaluate like how to determine where you want to place your bets and how to place those bets, which I know, which I know we'll talk about because I'm, I could be wrong about the chat GPT prediction and what's going to happen there. There's, I think there's going to be two parts of it. There's going to be what they do with like a chat GPT. search experience, but I think the bigger thing will be whatever they do with launching a third-party platform on top of chat GPT. There's a bunch of signals that they're about to, that they're about to launch that. I'm pretty sure it's going to be chat GPT. The thing I'm way more sure about is that some new distribution platform will emerge and it will follow the same four-step cycle. That that's kind of the key. So could be wrong on the first piece. I am very confident on the second piece. Okay. Excellent for shadowing. I completely agree if it's anything. It would be chat GPT at this point. Let's get into it. What are the what are the cycles that platforms generally

Starting point is 00:12:48 follow? Yeah. And I'll give some examples of this, but let me explain the four, the first four step, the four steps of the cycle first. And then we'll go through a bunch of examples of all those individual steps. So the four steps are essentially, one is like I call a step zero. It's the conditions of the market have been met. Step one. is about a moat. Step two is about a platform opening. And step three is about the platform closing for control and monetization. So let me kind of briefly explain each one. Step zero is about the competitive market being met, the conditions being met. And there's a few part pieces of this. One is that typically what happens is that a, there is consensus that there is going to be this

Starting point is 00:13:33 new huge category, right? Think social, think mobile, like all those types of things. things. And in this case, right, these AI, like chat platforms, like a chat GPT or a clock. So there's consensus about that, but there's no clear winner yet. And you typically have somewhere between five to seven, you know, major players really battling it out. Right. So, and they're all kind of looking for what is the edge. What is the thing that is going to, that is going to help me win? Because all of these dynamics, in all the history, they either end up in monopolies or duopoly. And so the stakes are really large. And so the competition is fierce.

Starting point is 00:14:13 So that's kind of step zero. And I think we could all agree that we are in that mode, you know, right now. We've got open AI battling with Claude, battling with Gemini and Google, with whatever meta comes out, with their new team, you know, so on and so forth. And there's huge amounts of capital. There's consensus, like all the types. They are in a fierce composition. So that's step zero. step one is then these players somebody essentially identifies whatever the moat is the thing that is going to help build them defensibility and help them hit escape velocity and become that monopoly or duopoly in that single category and once they figure out what that mode is then they need to press the advantage right they need to figure out how to gather that moat as fast as humanly possible and it tends to be that you can't

Starting point is 00:15:05 do that by yourself. And so you kind of need the help of an ecosystem in order to gather more of that moment. And that typically comes down to third party content creators or app developers and other businesses. And so they all establish like a third party platform, right, that has some incentives built in. And usually the value exchange is, hey, you develop on top of my platform, right? You add more use cases, you know, more engagement, like all of these things to my platform. And in exchange, I'm going to give you something in return. And usually that thing that's in exchange is I'm going to give you some new form of distribution for your application and for your business. But what essentially happens as we go over time is that we go into step

Starting point is 00:15:53 three, which is the closing period, which is at some point, all of these companies end up starting to lock down the platform. And this tends to happen for reasons of like monetization and growth, right? They either competitively don't want, you know, somebody to use their own, you know, platform to disrupt themselves. Like we saw that in the early Twitter days with things like Vine and Periscope, right, like shutting those things down unceremoniously, right?

Starting point is 00:16:24 Or they need to find ways to monetize at a deeper and deeper level because all these companies, like, they have to grow. And, you know, Google's the classic example here of just more and more real estate has either been taken up by either ads or their own, you know, first party applications. And so that's the keys. Like, they close it down by doing one of two, by one of a few things. They either shut it down entirely. Two, they develop their own first party applications to absorb the highest use cases. Or three, they artificially depressed the organic distribution that they gave you in the step. prior to push you towards paid mechanisms in order to monetize. And so I think we should go through like multiple examples here, but that's kind of like the core essence of the four steps. And so I'll pause there. Awesome. So it's essentially figure out what's going to make create defensibility long term.

Starting point is 00:17:18 What's your remote? Bring everyone in. Hey, everyone. Welcome to Facebook. Everyone joins Facebook and that okay, all the developers build on Facebook to bring in more people on Facebook and then they're like, okay, now you got to pay. There's a toll. But you love this so much and you're so hooked all your friends that you hear. You may as well stick around. That's right. That's right. Amazing. Okay. So yeah, a few examples would be great. Yeah. So you just hit on the first one.

Starting point is 00:17:39 This is the first one that I always think about because this is where I learned about this cycle very early in my career. Like one of my first companies was during the whole the Facebook platform boom, you know, social gaming, all of those applications. And I live. the full cycle. And I'm very short period. I lived the glory days and just the absolute horror days. And it was very painful. But this is exactly what happened. So let's go through the four steps. So step zero. Facebook was in a brutal battle with MySpace, Friendster and a few others. People forget this. People forget that there is actually like a bunch of competitors at that time. And in fact, those competitors were bigger than Facebook at the day. They had more users back in 2007 when Facebook

Starting point is 00:18:25 launched their third party platform. But one of the key things is that Facebook was very early to the insight about the direct network effects in that there's going to create real lock in that the more friends, the more of the global network that was on there, the more that it was just going to feed and hit this escape velocity. And so at the time they launched their platform, I think they were maybe like one fourth, one fifth the size of something like MySpace or even Friendster Orkitt. Like these are some of the names. at that time. But they opened up their third-party platform. And what was the value exchange? They went to third-party developers and they said, okay, we've created this canvas. They used to call it

Starting point is 00:19:05 the canvas. And they were like, you can put anything in the canvas that you want, an app, a game, whatever. You can monetize in any way you want. We just want this sidebar real estate on the ads. That's what we're really interested in. And so there is this mad gold rush on that Facebook. Sorry, the other part of that was not only will you put it there, we're going to give you access to all of these notification channels and feed to get distribution for your application. That was the other piece of it. And so you had this mad rush of developers coming in,

Starting point is 00:19:37 and you had this huge social application, social gaming boom. People just grew incredibly virally very fast. But eventually, essentially what happened over time is they kept peeling back that value exchange. They first were like, actually, you know, those dollars that you're making inside that canvas area, well, we want a percentage of that. So they changed that. And then they figured out their ad systems and then they started peeling back, you know, they started suppressing access to all of the organic channels that they had. Eventually, they went all the way towards absorbing the highest, you know,

Starting point is 00:20:19 use cases into their own first party platform, things like first party applications. applications, things like events, photos, all those types of things, and basically shut down the platform for dead. And these companies that have basically built on top of this platform, you know, the other thing is by the time they started closing all those things down, all those competitors that we talked about, they were so far ahead at that point because they had built off the back of all these developers coming, adding use cases, bringing more users onto the platform, like identifying that mode. But they were so far ahead. It didn't matter. It didn't matter what the other folks did at that point. And that's what kind of really gives you confidence to start closing down. But there's so many other examples of this, right, if we go through it, right?

Starting point is 00:21:02 So just before you get other examples, just something I'll highlight here. One is the mode they identified in theory was the friend graph, I imagine. Just like once we have all your friends, you're not going to want to go anywhere. I imagine it's also important to note you may not, this is kind of like a natural thing that would happen if you build the thing and it grows and you're like, oh, maybe we should change strategy. I imagine not everyone even knows this is what will happen and they kind of organically evolve their strategy. Or do you think everyone's just like, this is our going to be our plan step one, two, three, four? I think a different version of that question is I think some people could sit here

Starting point is 00:21:35 and interpret this as all these folks are evil. Right. And that's not what I'm saying, right? Like, that's actually not what I'm saying. I want to be very, I want to be very clear on that. because I think, you know, a lot of the, a lot of this cycle happens because of competitive and capitalistic, like dynamics and pressures. It's, it's the same environment that enables, like, creating amazing new companies, right, here in the U.S. So, and there's, there's like two sides of the coin. And so you go through this cycle because it's a competitive environment. You're trying to figure out how to beat competitors. And this is one of the strategies to beat competitors. But at some point, like, you just have to continue growing. You still have, you have to, you have to,

Starting point is 00:22:14 grow those dollars. The market does not reward flat companies if anybody's notice, like, you have to keep growing. And so they have to keep finding ways to grow as well as prevent their own disruption, right? They can get so big and they can give access, so much access of distribution to new developers. They don't want to enable their own disruption as well as they need to keep growing. And so my guess is anybody who is kind of sitting in their shoes, you know, owning their platform, it's going to follow the exact same playbook and the exact same reasoning.

Starting point is 00:22:47 And, you know, look, sometimes it happens also because it actually is the best thing for the user. Facebook's channels did get super spammy and like all of those things. And that was part of the reason, you know, they'd play this, but let's be honest, it wasn't the only reason, right? Like a lot of it was, a lot of it was for these other reasons.

Starting point is 00:23:06 And so I don't think it's evil. It's just you need to know how to play that. You just need to know how to play that. the game. That's competition. That's business. They're playing you, so you need to play them. Like that might be a little sadistic or something, but that is, that is business. That's, you're in a game of competition. Yeah. Essentially, the incentives are pointing you in this direction. Capitalism. This is that capitalism works. Yeah. And so it'll pull everyone in this direction, even if they, they want to avoid it. Let's do a couple more examples. Yeah, we'll go through

Starting point is 00:23:34 them quick. You know, I think everybody's probably, Google's an interesting one because it played out over a much longer period of time. You know, Facebook happened over the course of about, in five this year or something like that. Google kind of did it like very slowly over years, but same thing, right? Early massive competition against Yahoo, I don't know, altivista. Like us, you name them all, right?

Starting point is 00:23:55 That was even before my, that was even before my time, right? They were first to really identify these data modes and incentivizing essentially web developers, content folks to optimize, you know, for their search algorithms. It creates this great, great distribution mechanism.

Starting point is 00:24:11 everybody's kind of building content and everything, you know, for them. But over time, slowly but surely, right, they did two things. One is more and more that real estate became ads that they were monetizing. So they're suppressing organic distribution in order to push people towards the ads, as well as absorbing a bunch of the highest value first part of use cases, things like travel, you know, as an example or even like, you know, like restaurant search and like all those types of things. You know, the Yelp, former Yelp CEO. and founder has been out there saying a lot of things about these practice. So same exact cycle.

Starting point is 00:24:48 Mobile went through the exact same cycle, right, iOS, created a new distribution mechanism. They were in massive competition. They had a ton of competition among different phones when they first started on. They found the defensibility. It was more about the apps. They got on all the developers, created the app store, like all these types of things. But over time, we've seen more and more restrictions there on that front. And then most recently, right, like we've seen.

Starting point is 00:25:11 This happened in smaller places, too. LinkedIn as an example, first went through this wave with company pages, right? They were like, ah, companies, you know, come on, promote your company page, bring in more users, like all that type of stuff. And then get all these followers. And then, of course, they get almost no distribution now through your company page because they're pushing you towards ads. And then they recently just did this with personal profiles too, which is they really boosted distribution for individuals to create content. for that platform. They then introduced the thought leader ad format, a way to monetize those individual posts. And now you've seen them really pull back on that organic distribution.

Starting point is 00:25:52 So this happens in big forms and it happens even in smaller use cases as well. But once again, the steps of the cycle are exactly the same. And the key part about this too is it the broad trend is that the cycles seem to be getting shorter and shorter and shorter and shorter. So you actually have a smaller amount of time to play a game. Okay, and the big aha here is, yes, this will end maybe not great for you, but there's this magical period when they're open to customers and users where you can grow like crazy because they want everyone to come and they give you a distribution. And what you're saying essentially is chat GPT, potentially some other platform maybe is about to enter this mode. Yeah. Well, let me first, before we get to chat TPT, I think the natural reaction when you first realized this,

Starting point is 00:26:41 is screw them. I'm not playing that game. Right? That's what I feel like most people, like how they react, right? Because the unfortunate truth is that a lot of companies don't predict that last stage and end up in a really hard, hard position, right?

Starting point is 00:27:00 So many companies got completely killed during, you know, the crash of the Facebook social platform. Apple's 30% tax, you know, basically destroyed a bunch of types of applications and business models because it just you couldn't, you feel like it just wasn't like margin effective. Like all so many companies built on, you know, SEO loops, right, that are in serious, serious trouble right now if that's their only channel. So, so all of these things, right? And so I think the natural reaction is, yeah, like, like, why would I play this game if I'm a startup or or a company? And you can even see this with like

Starting point is 00:27:41 ChatGPT as an example, right? They just launched these like deep research connectors. One of them was my former company HubSpot. And, you know, if you sat inside HubSpot and you were just thinking in isolation, you would be like, well, why would I want to make all of my data accessible through chat GPT and have like all of the usage you start to accrue there, right? Like it doesn't really make sense in isolation, but we don't operate in isolation. Once again, we operate in a competitive environment.

Starting point is 00:28:10 And what's going to happen is that if you don't do it, your competitors are going to certainly go to the new platform and your customer expectations change and you have to rise to those customers' expectations. Like, they're going to start expecting you to be in these new experiences and all these things. And so it ends up being a prisoner's dilemma, right? Which is like, there is no opting out of the game. You have to play the game. And so it's better to be early than to be super late to this.

Starting point is 00:28:40 game, especially, especially if you are a startup, right? That is kind of like the key, that's kind of like the key opportunity. And so we'll talk a little bit more about how to play the game more, but it's, it's better to be early as well as than the key, the harder part about it is anticipating that last stage of the cycle and figuring out how to sequence away from something before that last cycle comes. So I think that's the key part. But let me pause there, and then I'll talk a little bit about chat, GPT. and some of my reasoning behind that. Cool.

Starting point is 00:29:12 So what you're saying is not only is there going to be this big opportunity to grow. If you don't take advantage of it, somebody in your space will. So it's not only there's an opportunity, but this is something you need to do because you might miss the boat. And I think about companies like Zinga that grew on Facebook and then became massive companies. And, you know, if they didn't do that, they would have missed the boat. Someone else would have eaten that lunch. I don't know.

Starting point is 00:29:35 I'm thinking about the technology bros podcast on Twitter right now, TPP. where they basically figured out on Twitter you can create this live stream and you see it all day in your Twitter feed just like, hey, they're broadcasting and it's a really cool distribution channel. So I think there's like a big call to arms here almost of just the opportunities emerging

Starting point is 00:29:55 and you basically need to pay attention. You can't opt out. That's right. Let's chat. Yeah, so let's talk chat. So look, like let's go through this cycle. We right now, we're in that competitive environment. Like we said like all those players,

Starting point is 00:30:08 we talked about Chat CPT, C++, Claw, and I, all these folks, they are battling it out, right? And we've seen this with, you know, the talent wards, especially over the past, you know, month or so. And so there's no clear winner yet, but there's consensus around the category. The second thing is then, okay, has the moat been identified and who seems to have identified at the first or as further alone? I think there's, you know, my hypothesis, and I think there's a lot more consensus around this now than there might have even been three months ago, is that, the mode is really about is about context and memory. You know, these models, you know, by themselves,

Starting point is 00:30:46 if you compare them side by side, you know, they kind of generate the same result. And so that the actual difference maker is which one has more of your context and because it's the context plus the model that produces the best output. And then and then that kind of starts to accrue to this loop around memory. The more you use it, the more it's able to store memory around you, which kind of feeds more personalized context, which produces better outputs, right? It ends up being, you know, another one of those flywheels, another one of those loops. And so if you look at who's farthest on this, it definitely is chat GPT, right? Like they were kind of the first ones to memory. They've been investing a lot in these different types of data connectors, essentially context connectors,

Starting point is 00:31:29 you know, gathering all of this context. And so you can really start to see it in the usage. But the second thing is, and one of the pushbacks I've gotten on my prediction has been, well, what about like Google and Gemini? Like, they have so much distribution through Chrome and like all of this other stuff, right? But it was D.D. Das, who's VC at Menlo Ventures, actually published some good data on retention of all of these different ones. And I think the second reason I predict chat GPT is like if you look at history, once again, it was never the person who had the biggest. distribution at the moment of time, it was the one that had the best retention and engagement. Google had the best retention and engagement over the others. Facebook had, it was smaller, but had way better retention and engagement over the others, right? So on and so forth.

Starting point is 00:32:21 And so the data that DD published clearly showed that both the retention curves, which I know you and I have both written about at, you know, at exhaustion, level off at significant portions higher than all the other platforms, as well as those retention curves have been shifting up dramatically over time. You can start to see the effects of memory. And they have the very elusive smile curve, right? The ones that you just like, and the only other times, I've seen, you know, all of those dynamics very few times in my career. And they tend to be the folks like Slack and in like all of the big winners. It's just like so elusive. And the smile curve, just to just so if people haven't done it,

Starting point is 00:33:06 that is essentially retention goes up over time. It goes down a little bit. And then you come back to it and you use it more. Yeah, that's right. And it's usually the result of some type of network a factor or something else. And it's an early indicator that that that platform is on a trajectory to hit escape velocity. The third piece is that, and they haven't really hidden these, but there's all sorts of signals that they're about to launch a third-party platform

Starting point is 00:33:35 they've been hiring for a bunch of roles. I've seen multiple postings on like product manager, engineering roles, all the kind of stuff for, you know, quote unquote agent platform and all those pieces. And so it feels pretty inevitable that they will, one of these players will need to launch a third party platform

Starting point is 00:33:53 in order to, you know, serve all the possible use cases on, you know, on these tools. There's going to be some value exchange, which is like, hey, for your agent to be effective,

Starting point is 00:34:04 you probably need access to context and memory and distribution, right? So there'll be some values that integrate to us and we'll give you those three things, right, which is going to drive more users and more usage. And we're going to go through the steps of the cycle. And you can already see this, right? Like, you know, they're starting to form preferred partnerships, right, with some of the bigger players, which paves the way for smaller third party players. It kind of gives when's credibility to the platform.

Starting point is 00:34:33 It's like, well, if HubSpot and X, Y, Z are doing it, then I should probably do it too. It's like that type of that type of mentality. But that's why I think out of all of these platforms, ChatGBTGPT has the best shot right now. And then a bunch of folks are always like, well, what about Claude? I really like cloud. I use Claude. Well, the problem with that is like, I think ChatGPT at this point has like at least a 10x difference on MAU. So if you're a developer, right, and you're comparing those two platforms and you're looking at it and you're like, well, chat GPT has 10x a number of users and better retention engagement, it's like, what's the logical choice of which one you're going to prioritize your scarce resources on, right?

Starting point is 00:35:18 And so those are just some of the reasons that my prediction is on chat GPT. And in the blog post that I wrote about this, I actually then played my own devil's advocate and said, okay, here are some reasons why it might. not be a chat GPT, but I think we're in that part of the cycle. That's my prediction. I might be wrong in the prediction of chat chat chat ch pt, but I really think I feel very confident we're going to see this cycle play out again. Two follow questions here. One is what's your, what would be the backup? If it's not chat chapit, it sounds like it might be Gemini Google. My hypothesis of who's best positioned but is not executing on it right now would actually be Apple. Because through the, the devices, they basically can see everything. So they have the ultimate view into your context, right? They're sitting at that, they're sitting at that level. But I don't know what they're doing.

Starting point is 00:36:15 It's like, from an execution standpoint, maybe they're going to surprise us with something crazy magical. But I haven't, we haven't seen any external signals around this. So, so that's probably just based on, on what really estate and where people live in the stack would own. And then I think right behind that, I would probably put, I would probably put Google because of owning the context of things like email and the distribution points of search and Chrome and Android and those types of pieces. But, and a lot of people point to them. But my experience with all of their products is like going back to the retention and engagement thing is, is that if we could take a look and inside their metrics, I think what we would see is a bunch of flyby users in their mouths.

Starting point is 00:37:06 Like, they're kind of sprinkling the Gemini bucket everywhere. And I'm, I've, I've like literally clicked on it accidentally multiple times. And so my guess is a huge portion of their miles is it is exactly that of like what's happening right now. And so, you know, look, they just, um, they, they just acquired a very talented team from, uh, from windsurf. Just the team, just the team, part of the team. Yeah, we'll see. And things are changing dramatically on a week to week basis. So we'll see if they're able to press those advantages in a very clear way.

Starting point is 00:37:42 But I think the window is very small for them if chat GPT plays their cards right, because they clearly have the escape velocity right now. And if they just keep pressing that advantage in the right way, I think it's going to be very hard for Google to counter in the amount of time this last. On the clot piece, I'll just throw this nugget out. I had Mike Krieger on the podcast, had a product CPU at Anthropic and asked them just, you're losing to chat GPT. How do you approach the future of Clod?

Starting point is 00:38:14 And he very specifically said, yes, they've caught lightning in a bottle. This is just going to win based on what I've seen at Instagram. And so we are specifically focusing on what is Anthropic and Cloud incredibly good at, which is developer tools, coding, backend stuff. So they're actually leaning more and more into that. And if you've seen that revenue recently, they're making, I don't know, like approaching 10 billion a year, some crazy amount of money.

Starting point is 00:38:37 So they're actually doing super well just in a different use case. Yeah, I'm glad you mentioned this because this brings up something that we skipped, which is there are smaller platforms that have existed and will also emerge in this environment as well. And that's kind of like what you're alluding to is this tends to happen as like things end up, you know, growing into more niche. is like even if you look at social, right, like LinkedIn emerged as a subset of the social world. But I'll, but even on these smaller platforms, these new distribution channels, they, they go through

Starting point is 00:39:11 the same cycle. I'll give something, you know, really a very opposite example of the ones that I gave. Like look at the platform Udeme, right? They, they are a platform for course creators, right? I don't know if most people know this, but when they started, their rev share to creators was something like 80% to creators. They started very high. And that brought on all the course creators, got their whole marketplace going, like so on and so forth. I believe it was about a year ago, they announced that they're essentially pushing that rev share down to something like somewhere between 15 and 20%. They're somewhere at like 25 and 30%. Right. So another example, right, of like they closed down organic distribution order to monetize, like all that kind of stuff. And the same

Starting point is 00:39:58 thing will happen in this AI world. I believe, you know, cursor is very clear like cursor's on the path to also probably create some type of agent platform, right, for developers. So that'll be like a smaller ecosystem to play in for some products. There's all sorts of, it feels like everybody has the same strategy at this point as everybody wants to launch an agent platform. I imagine some of these other horizontal productivity tools will do the same thing, maybe like a notion or an air table or like a Monday.com or something like that. So there will be smaller platforms that will emerge and they will follow the exact same cycle that I am that I'm also discussing.

Starting point is 00:40:40 But yeah, in terms of like the biggest kind of consumer one, that's where I think chat GPT has probably the most escape velocity and yeah, others will focus on different areas. And just to be clear, I love clot. I actually use both Cloud and chat GPT all for different things. I have lots of love to go around for all these tools. I'm not, my prediction has no, no bearing on which product I like the most right now. I also love Cloud.

Starting point is 00:41:08 So I think with, so the key point here you're making is that there's almost a number of distribution channels emerging. Many of them will be niche. So I think of LinkedIn if I want to like LinkedIn for me as a very targeted audience for folks that listen to this podcast. So yeah, even though it's not, I don't know, Google. or Facebook or whatever, it's still incredibly valuable for the specific thing that I do. For sure.

Starting point is 00:41:31 So I think this is even more interesting that there's going to be a number of distribution channels that emerge out of this whole AI wave. The other thing I'll note real quick, you mentioned this idea of everyone's building agents. I just had Brett Taylor on the podcast, who's building Sierra,

Starting point is 00:41:43 and we actually, he made me realize why everyone's building agents partly. One is because the outcome-based pricing that you can charge with agents is incredible, because one, you can actually attribute their impact on your businesses are why. You can actually see this is saving an agent $15 because it's all the case. And it's attributable and it's autonomous.

Starting point is 00:42:07 It's just doing it on its own. So with that, you can charge per outcome. You can say, we'll charge you a dollar every time it solves an issue. So the monetization opportunity is huge. The margins go up like crazy. Can I just ask a question about that? Do you think that has longevity? in the sense that

Starting point is 00:42:26 that makes sense in the current environment that we're sitting in right now because people are kind of comparing these outcomes relative to

Starting point is 00:42:34 what it costs them today with pure humans but once again competition comes in at some point and so that feels like that creates a pretty ripe

Starting point is 00:42:43 opportunity to you know undercut and come into and then you have like the disruption theory kind of playing out as well and so

Starting point is 00:42:52 obviously depends on like the infrastructure costs and compute costs to to run these things. But I just wonder how much of that is temporary versus, versus something that'll be long term. So you're saying that dollar will come down to like 50 cents, 25 cents? Or are you saying someone's going to come with a whole new business model and disrupt that whole approach? More of the first. Yeah, like it's just competition erodes that away essentially. Yeah. Yeah. Yeah. That's a good point. Some margins will be hire for a while and then they'll come down. Yeah.

Starting point is 00:43:23 Unless there's something else that creates a like durable pricing power, right? I wonder if that, yes, I wonder if what that is.

Starting point is 00:43:34 That's probably the second piece of this. Yeah, yeah, that's probably the second piece of that hypothesis, I feel like, yeah. Yeah, I think,

Starting point is 00:43:39 I guess the opportunity there, the moat would be the data, like similar to how cursor is collecting more feedback on what is people want in their code suggestions, maybe in theory, Sierra F in as more and more

Starting point is 00:43:50 data over time and there's kind of this network effect. Yeah, that's right. Yeah, so let me revise that. Yeah, it's like, I believe in that as long as it's paired with the second piece. Otherwise, it gets competed away. Yeah. Good tangent. Okay, one more question.

Starting point is 00:44:06 What's the, what is your prediction on timeline for when things, when the opportunity appears? And what do you predict, as of the day we're recording, what do you predict will be the next couple things that open, that chat chabit and let's just focus on that releases to start to open up this platform to get everyone in there.

Starting point is 00:44:26 Yeah, well, look, I'll first give the disclaimer that I feel like any thoughts on timing in the AI market are very, I've been very hard to, it's always shorter. That's where we should buy us. It's always shorter than you think of like when something's going to happen. That's what it's felt like from the seat that I've been sitting in. And but my guess is this, we're going to see the next major steps of this play out over the next six months. And so I think we just saw one of the pieces drop around this, which was their recent, which was chat GPTs recently launched agent mode. And so it's kind of a general purpose agent, you know, and I think that starts to introduce all of the users to using agents and they're kind of figuring out and placing it in the different tiers.

Starting point is 00:45:17 business models, all of those pieces. But it's likely that no general purpose agent is going to fulfill all of the infinite use cases successfully. And there's two reasons for this, right? Users struggle with horizontal tools. They can do everything. And that's exactly why they struggle to adopt. And so they typically need more specific entry points. But also the more specific use case you get, sometimes you need specific UI, specific data, like other specific ingredients, you know, to properly fulfill that use case for, you know, for a given audience. And so I think their agent mode was a step in this direction. What I would expect to see play out next is that they will, they will either launch, they will announce the platform or what they're going to announce

Starting point is 00:46:05 with preferred partners or what they're going to announce first is basically a set of preferred partners, the guinea pigs. You know, an initial 10 to 20 folks that are like bringing agents to their platform. And what that does is it essentially, once again, it's a credibility card. You do special deals with some like right brand names

Starting point is 00:46:29 to give the platform credibility and it kind of creates this desire from everybody else to come on, you know, to the platform. And then the step after that is starting to open it up the platform. And this is where the real, you know, where we'll really start to figure out what this game is going to look like

Starting point is 00:46:46 because they basically have to define what the value exchange is. What are they giving you access to, right? And what are they incentivizing you with to come on to the platform? So that's one version of it. The other version of it is just like the replacement to search. There will probably be, you can also see them starting to make more moves here, which is like deeper attribution in some of the results, like those types of pieces. They're bringing in shopping, right?

Starting point is 00:47:14 like that's one of their recent announcements as well, kind of native into the UI. Essentially, they will form new monetization mechanisms around that stuff as well. And that's actually going to be very important because for them to going back to the moat around memory and context is that, you know, they will want to incentivize as many people to their free tier as possible. But given the cost of AI, they have to cover it somehow. So they're going to need some monetization mechanism. So the more that they can cover that free usage with things that aren't subscriptions, I think that probably also kind of feeds them out. So I think those are some of the next steps on two different vectors, more of like a third-party

Starting point is 00:47:55 developer platform and more of the, you know, kind of content, whatever you want to call it, AEO, GEO, I don't know what acronym is, every we've all decided on yet. Let me know if we have. And I think those will be, I think those will be the next, the next steps that we'll see. Now, that's what I think for chatypte. I think the thing that we should talk about is like, essentially what I would advise folks, especially startups, is you're placing bets. At this part of the cycle, you're placing bets.

Starting point is 00:48:26 We don't, the winner is 100% guaranteed, as I mentioned. And so you essentially at some point will need to make some decisions about, you know, where to place your bets. In the Facebook days, all those other social networks, they also came out. you know, with their own platforms, right? And iOS had Android and some failed initiatives from Windows. I don't even remember what that platform was called, right? And you can look back and whoever placed their, you know,

Starting point is 00:48:56 the iPhone was actually very, in iOS as a good one, which is if you had only aligned your bets to Android, you probably lost. If you somehow found a way to play on both ecosystems, you could be a winner. but if you only aligned to iOS, you could also be a winner, right? So, like, that's just right. Like, you had to have iOS as part of your betting strategy in order to win.

Starting point is 00:49:20 So everybody right now, like, you're probably at the cycle and trying to figure out, well, you all need to, everybody will need to figure out where are they going to place their chips? How are they going to bet? And depending on how you bet, really depends on what your current position is in the marketplace. You know, if you're a late stage startup,

Starting point is 00:49:36 let's start with that, or like a late stage company, you can afford the luxury to place multiple bets and kind of spread your chips and kind of wade it out a little bit to see who the winner is and then really throw your muscle behind that winner. You have that luxury a little bit. And of course, but the risk of that, the risk of that is that sometimes the incumbents wait too long to make that decision. And that's like kind of the key question they will need to answer. The key question for startups is totally different. You don't have the luxury to spread your chips. You have to go all in. You have to choose one and go all in. You have scarce resources, scarce attention from the market. And so it's a totally different

Starting point is 00:50:23 ballgame. Higher risk, higher reward, for sure. And that's part of the betting strategy for startups. And so that's kind of what you have to do is you kind of have to figure out your betting strategy and then, you know, we can talk a little bit about how you might evaluate and pick the right course for you. But that's where we're all at right now is where we're kind of, we just entered the casino. We just cashed, put some cash in for some chips. And now we, now we've got to figure out, you know, what tables and where to place those chips. I love this analogy. Okay. So just to be crystal clear about what listeners should do, what founders should do, what founders should do with product teams should do. The advice here essentially is

Starting point is 00:51:04 integrate with chat GPT, maybe Gemini, maybe if Apple has something, actually integrate with what they launch. So it could be a login thing, could be a search thing, could be a connect and suck up your memory and context. The advice here is you need to do this

Starting point is 00:51:22 because this is potentially the way that most companies will start to grow and your competitors may overtake you. Yeah. If we had to like really simplify it, It's essentially play the game. Don't opt out of the game. Don't trick yourself into thinking that you can't play the game. That's number one.

Starting point is 00:51:41 And then number two, no matter who you bet on, just make it a focused bet. Because if you look back, all the failures are the ones that tried to, you know, play multiple games at once with scarce resources. And that just tends to never work if you're an early stage startup. So those two things. Play the game. Put a focused bet. This episode is brought to you by Miro.

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Starting point is 00:53:04 Help your teams get great work done with Miro. Check it out at mero.com slash lenny. That's MIRO.com slash Lenny. So you were head of growth at HUBSpot for a long time. And you gave that as an example, HuffSpot. Why would they integrate? Why would they give away all their data so that, Chedge, if you can suck it up and you never have to go to HOPP spot,

Starting point is 00:53:24 you're just working through their agent. would you at HubSpot be like, yes, we got to do this. This is the game we got to play. Yeah, 100%. And that's exactly what I think you see them doing. And I look to be very clear, I have not talked to anybody at HubSpot about this. I have not talked to Darmesh about this.

Starting point is 00:53:40 But Darmesh, I think, has also like published, publicly published about this, but that the right thing to do is essentially even though you don't, you understand how the cycle plays out and you don't necessarily,

Starting point is 00:53:55 necessarily under what you understand what your exit strategy is once you get out, it's better to be early. Know that you need to figure out an exit strategy and figure out that exit strategy along the way versus waiting and then being super late and then know what the exit strategy is. And I think that's essentially what that's exactly what you see them, see them doing. They're trying to be as early to this stuff as possible. and I think it's a pretty smart play, even though we might not necessarily see

Starting point is 00:54:29 what the exit strategy is out of this cycle for them. So going back to that amazing quote that you shared at the beginning of the conversation by I think it was Alex Ram Paul. Yeah. Of that startups win by finding a distribution channel before the incumbent copies of them. And what you're saying here is this is the opportunity

Starting point is 00:54:50 for startups to disrupt an incumbent. This is the opportunity for someone to disrupt Salesforce, I don't know, Service Now, all these guys that have been around for a long time. Yeah, it's going to be one of the major ones. Now, look, you've already seen players that have been able to hit this escape velocity, you know, the cursors and stuff of the world. And so, once again, there's multiple ways to hit that escape velocity, but this is going to be one of, this is one of the major ways to do it,

Starting point is 00:55:19 is to basically hit yourself to a new platform. Look, you did it yourself, actually. You hitched yourself to substack super early. You took a focus bet. Yeah, yeah. I was like, I don't know why that just hit me, but you took a focused bet and you've benefited from it in a disproportional way than those that kind of came later. And I think that's actually a great meta example here as I sit here and think about this. Yeah, that's actually the way I thought about when I was moving to substack.

Starting point is 00:55:46 Just like, I feel like there's those wave rising and I want to ride this wave, even if maybe it's not the best place or maybe, you know, they take a cut, all that stuff. But it worked out really well. That's right. I think it worked out very well. It worked out really well. And to be honest, it felt like it was too late when I started six years ago. It felt too late. Yes.

Starting point is 00:56:06 Oh, say more about that. It always feels too late, I think, to people that join. Like, Mark Andreessen has his famous quote. He's like, I came to Silicon Valley in the 80s. I thought it was over. It was too late. I missed all the opportunities. That's fair.

Starting point is 00:56:19 Yeah. So, yeah, there was just a lot of newsletters. They were doing really well. million subscribers. I'm like now. And what do you say to people now who want to join substack? That's learned from this example. A lot of times when people think that it's too late, it's definitely not too late. And it's always only just getting started, especially if you're like on Twitter all day,

Starting point is 00:56:35 listening to podcasts like this where we're surrounded with this bubble of everyone talking about something when in reality, like 1% of people know anything about what you're hearing about every day. Yeah. Yeah, that's so interesting. Okay. So coming back to the advice, say someone is sitting there's sitting. there and talking to their manager, like, Brian just shared all this mind-blowing advice. We got to

Starting point is 00:56:57 pick our battles. We got to pick our platform. What would your advice be for them to decide where to place their bets? Yeah. So I think this is a great question because once again, you know, put my personal prediction aside for a second. And I would encourage everybody to think about it from first principles from their, like who their audience is, what their product is, what stage of company either at like all those, all those, their current strengths and weaknesses. You got to take all this into account. But if I had to boil it down to a few criteria, the main things I would think about is when you're looking at new distribution channels and new platforms, um, to choose on one kind of going back to what we said before is the better signal is retention and depth of

Starting point is 00:57:38 engagement of the users on this platform, then it is like pure kind of user level like Mao or some, some other like number of signups. So, you know, one of those, of the metrics. So look at that number one. Number two is there's some element of like user quality and monitor, an ability to monetize the users on this platform. I think the starkest example here would be, you know, iOS and Android. It's like even though, even today, it's something like Android has 70 some percent of devices, but only 30 percent of the market share by dollars and it's the exact flip for iOS. So it kind of goes back to what we were talking about earlier, which was, If you bet on Android only, you probably lost.

Starting point is 00:58:22 But if you bet on iOS only, even though smaller user base, you were still able to parlay that into a win later. The third thing to look at is as these platforms emerge, just analyze what the value exchange is. So what are they giving you to incentivize you to develop on their platform? And like all these platforms are a bit of a, it's a bit of a game of whoever understands the rules and how to arbitrage the rules the best, right, tend to be the ones with the edge and figure that out.

Starting point is 00:58:58 And then finally fourth on my criteria would be pure scale, right? Obviously, even if you have those other three, but there's, you know, 200x difference in scale and momentum, then like obviously you probably have to choose the bigger platform. But last but not least is as you go through these criteria, this is, these are how you think through entering the game. You know, and once you enter the game,

Starting point is 00:59:29 then you immediately need to move to starting to think about how to exit the game. Knowing once again that that last step is going to come at some point in the future, that there's going to be some closure for monetization, then that's where you have to start thinking through your strategy to exit. And that comes down to things like, okay, well, how are you going to own an important part of the user experience or workflow? Or, you know, how are you going to accumulate specialized data in context that the major platforms don't have?

Starting point is 01:00:01 Or how do you create, you know, different types of like micro network effects, like all, of these types of things? So just once again, though there is the entrance criteria, but once you figure out of, that out and you feel like you're in the game, you immediately need to move towards, okay, you know, what, what's my exit plan here knowing this is all coming? It's interesting that another way to think about this model you've described as building the strategy of building on top of LLMs and becoming a GPT wrapper, because essentially this tech allows you to, say, create a cursor that is incredible. And then you could argue, oh,

Starting point is 01:00:40 you're just going to be this wrapper and why wouldn't anyone, like, they're getting all the money here. Everyone can copy you. Like, what's your defensibility long term? And the answer is what is the moat you will build over time sitting on top of this thing that will make you more and more valuable long term and not have to rely on this thing? So it feels like you could use the same framework for building a GPT wrapper business. Yeah. To use that euphemism. Yeah.

Starting point is 01:01:04 So say someone is sitting there today, is there anything they can do to start making a bet? Is it simply creating an MCP that allows LMs to suck in your data? Is that the one thing you could do today? Is there anything else that's available today to start using these platforms? Or is it just a little too early and they haven't released the good stuff yet? It might be just like a tad too early. We're like right on that edge. But, you know, some of the questions I'm asking myself is I'm kind of going through

Starting point is 01:01:34 all of these players and where are customers and target audience? live and I'm asking myself, you know, the question, okay, if this player launched, you know, some type of platform, like, how would we evaluate it, you know, so on and so forth. It's hard to, you can also try to cozy up to these folks. I would place a large portion of my net worth right now that if we could sit in the open AI offices, like at that front desk, that they are having, you know, meetings with potential. prefer developers like talking about that. We could probably sit there and

Starting point is 01:02:13 and log it. So I do think some people are going to be in a place to develop preferred relationships and and make a know. And if you're in that spot, then you should definitely play that card. A lot of early estate charts won't be in that card place.

Starting point is 01:02:30 Other than that, I would say we still need once they launch these platforms, it's like you can't do much else until you really kind of know what the value exchange and what they're going to expose for you, but also just be prepared to turn your strategy on a dime and go all in. I think that's probably one of the hardest parts of this is that these things emerge and you have to capitalize extremely quickly. And a lot of times it's just it's hard for leaders to do

Starting point is 01:02:55 that because they don't want to create a feeling of whiplash into the unknown. We've got all these projects and play. You know all the things. I think that's, I think that's probably the last part of what we can be doing right now versus just, you know, kind of staying on top of everything as it emerges. As you were talking, this reminded me, I recently noticed that chat Chapti is driving me to my newsletter, more traffic than Twitter. And I feel like that recently shifted. I didn't even know this was a thing until I just started looking through my referrals. I'm like, chat JPT, who the hell is going on there? And I think it's like a different version of what you're talking about, but essentially it's like, in theory, I could block chat GPT from, I don't know. I don't even know.

Starting point is 01:03:38 I can for being doing all my stuff. You can and substack now. Yeah, I just saw that setting in there. Okay. Okay. Oh, interesting. But that's the similar kind of decision is like, is it better for me for it to be recommending my stuff and telling people, hey, go check this thing out? Or is it better to block it off? And I think, per your point, and this is that way I felt, like, take it all just like, it's good. It'll, it's, in that, it's better that it's like from Lenny's newsletter than something else. So someone else will come in and eat that market share.

Starting point is 01:04:06 Yeah, that's right. Like, if you, if you don't do it, you know, somebody else is. And I think, and I think that's also kind of what all the major media publishers are really contending with right now. I guess I need a licensing deal in New York. So anyway. Okay. I want to go on a totally different tangent. We weren't planning to talk about this.

Starting point is 01:04:24 I know that I said this. We're going to be fully focused on this one topic. But there's something you mentioned to me before we started recording that I think will be really interesting to a lot of people. So you guys are reforge are now building actual SaaS products that people. can buy. It's not just courses. I don't know if people know that, but let's make sure people understand this. There's actually products for product teams. So maybe just explain that briefly. But the thing that I think is really interesting here is you work with a lot of companies now selling them AI tools. And you have noticed a very big difference between the companies that are really

Starting point is 01:04:57 good at adopting AI tools and seeing gains from them from those that don't. Talk about just what you see there. And because this is, in theory, going to be really helpful to companies that are struggling with adopting AI tools and seeing games. Yeah, just to quickly explain that transition, so it makes sense for people, which is, you know, I sort of re-forge just with the interest that there was all these incredible leaders out there growing, you know, on the front lines of some of the fastest growing companies,

Starting point is 01:05:26 and they have all this amazing knowledge, and I wanted to encode it and useful and practical ways for others, right? And that took the form of courses and kind of, and content product, all that kind of stuff at the beginning. And along the way, everybody kept asking us to essentially build the tools to implement what we taught. Because, you know, with anything, is like you can learn as much as you want. You can listen to my podcast, your podcast, Lenny, like, whatever, as much as you want. But if you don't actually put it into action and implement it, then it's not really going to create value, right?

Starting point is 01:05:56 And so people kept asking us to really close that gap. And we said no for the longest time. And then about a couple years ago when AI really started to inflect, it really created this moment. that, oh, wow, now we, there's this opportunity not just to encode this knowledge into content, but also into the products, the software, the tools that we use ourselves. And so we started to take a really big bet on that and started to develop this new platform for AI native product teams. The first product we launched is called, is called Reforge Insights, which acts like your AI product researcher, kind of aggregates all the feedback from all the sources, uses AI to analyze it,

Starting point is 01:06:33 helps you explore it, but also we'll start to identify, like, what are the gaps, the things that you don't have in your feedback today and auto-generate the research to go gather all those new insights. So complete the full cycle. We're going to watch two other major products as part of this platform before the end of the year, but we'll save that for some future episode. So that's kind of been our journey. And so we've seen inside companies that are going through this transformation from two perspectives. One is obviously selling in that tools. But the other perspective is for 10 years, companies have been coming to us to help them try some sort of transformation with our learning product. Most people, most companies are not coming to

Starting point is 01:07:17 us to just like throw a bunch of courses in front of them. They're trying to solve some big business problem, some transformation. Now, that used to be things like we've got to figure out this growth thing, right? Or I'm going from sales led to product led. Or I'm, you know, I'm turning, I have more project managers and I need to transition to product managers, right? Like something like that. Like, or there's some business problem. They're going through some transformation and they saw us as part of that transformation and we got to partake in quite a few of those types of transformation. Now, of course, the transformation that everybody's going through is, okay, how do I become more AI need of? How do I adopt this stuff? And so we've seen a pretty

Starting point is 01:07:59 wide spectrum and from both perspectives. of how companies are approaching this. And I'm sure everybody's seen the like AI, we've been calling them like the AI manifesto memos from CEOs out there that proclaim we are now AI native. It's some grandiose, you know, way, right? But there's behind the scenes, there's actually some incredibly stark differences

Starting point is 01:08:29 in the actual teeth of what backs up. memos and backs up those executive decrees that, you know, we should all be, you know, AI. And and so just to kind of point out a few of them, which is, one is that there, I think the most impactful thing that you can do is form really hard constraints. So what, what you, there's other parts that is like, okay, you want to communicate this. You want to establish an owner of who's going to drive this. You want to build in incentives and rewards. And you see this all playing out in things like, you know, building it into your, you know, your career ladders. Or some people are starting to introduce this as questions into their performance reviews, like, you know, all those types of

Starting point is 01:09:21 pieces. And but the thing that is actually moving the needle are the companies that are defining incredibly hard constraints. So one company that we worked with, developed, up this constraint that they benchmarked against other companies of their revenue size and the team sizes for their stages. And they set a benchmark that we will be one-fifth. Each of our functions will be one-fifth the size. And what that did is it created a constraint that you couldn't hire above that level and it forced people to essentially find ways to adopt AI and do things to replace that. So that was one. You've seen these other ones. I mean, you've seen these other ones, I can't remember from what company this might have been Shopify or another who is like,

Starting point is 01:10:06 you are not allowed new headcount until you prove to us that you are not able to accomplish this with AI. That's like another hard constraint. But you also see these other constraints on the smaller level, which is, you know, executive saying, I will not do a product review or review a PRD unless it comes with three prototypes, you know, something like that. And so that's, that's the hardest one. Those are the biggest constraints. But I think the biggest change that I'm seeing is, and the things that separates out, the top few percent making this change, and everybody else is essentially making the hardest decisions. And that hardest decision is going to come down to exiting people. So in every transformation, what we see is essentially three groups of folks.

Starting point is 01:10:56 You see your, we call them the catalysts, the people kind of leading the charge, the people who are experimenting. you know, doing this on their own time, like all that kind of stuff. You then have your, what we call your converts. These are folks that will make the transformation. They will adapt. But they need structure. They need permission. They need a clear outline. They need a clear plan. Right. And I don't say this in a negative way. It's just that, you know, that's how some people operate. Right. And so you, and so that's where things like all the things that we were talking about before, which was like the decree, the permission, the clear budgets, the rewards, like all of those types of things. But then inevitably, you have a certain percentage that are anchors, right? And

Starting point is 01:11:41 they're dragging their feet. They're kind of, you know, silently creating friction in the background and like all those pieces. And there's a big difference in how I think companies are treating and thinking about their strategy for those folks. One group is kind of like, ah, we're going to work with them very passively. Others have set a hard deadline. They're like either make the, they're going to either make the transformation by X date or we're going to exit folks. And a lot of people look at this as being really harsh. I think a lot of people would think that, especially individuals. But let me kind of explain it from a more of like a CEO perspective. A lot of these companies are seeing this AI transformation, the ones that are taking it more seriously, as this isn't, adopting new tools. This isn't a light change. This is a fundamental culture change of how we

Starting point is 01:12:34 operate as a company, right? And you can't have 20, 30%, whatever meaningful number of it is of your company, trying to operate in a completely different way, in a completely different culture. Cultures thrive on density, right? And that's why there's sometimes the best ones feel like cults, you know? And so as a result, from that perspective, it's like, hey, like, we, for us to be successful, for this to be the best thing for all employees, we all need to be operating around the same cultural principles and stuff. And if that's not you anymore, then we're defining a plan to exit it. But I would say that less than 10% of companies we see are taking this hard stance. But I would say they are probably the ones that are farthest along,

Starting point is 01:13:23 getting the most adoption and are seeing the most results of the ones that are taking those hard stains. So there's a bunch of other stuff I can talk about, but that's kind of the high level of kind of what we've seen across a bunch of different companies. That is incredibly interesting.

Starting point is 01:13:38 I'm glad we went there. I have a newsletter post coming out soon probably before this episode that touches on a lot of advice along these lines. I'm excited for you guys to keep seeing these insights into companies and sharing more of this. because this is, I think, what a lot of people are looking for.

Starting point is 01:13:55 Just like, things aren't quite clicking at our company. We keep hearing everyone. It's getting so much more productive. All these companies are running more efficiently, and it's not working here. And so I think that's the kind of advice a lot of people are looking for. So thank you for sharing all that. Brian, is there anything else that you wanted to touch on, anything else you wanted to leave listeners with before we get to our very exciting lightning round?

Starting point is 01:14:15 Well, actually, just a couple more points on this topic. Oh, yeah. We should go. It's like, is there's probably two more things. I would say about this. One is that, so if you're a CEO listening to this, I would say that most CEOs or most executives are incredibly disconnected from the actual AI adoption taking place inside their companies. I think a lot of executives who have done these decrees and all that kind of stuff think it's kind of happening naturally. But we talk to both groups. We talk to tons of

Starting point is 01:14:46 end users and we talk to tons of executives. The story we hear from the end users, the PMs, the hinge, all that kind of stuff that we talk to, kind of using all this stuff. One of the main questions we ask them is, you know, if somebody, if we're talking to somebody who's picked up a prototyping tool, say, well, how many other people on the product and design team are using this? Almost 90% of the time, it's like, ah, it's like me and this one other person and everybody else hasn't like taken it up, right? And so there's a huge disconnect. And we heard one story, I can't say the name, but it's a company we all know. It's a major tech company, tech forward company.

Starting point is 01:15:24 CEO's been out there talking about being AI-native. We talked to one of their principal PMs. Person was early to the prototyping tools. This person shared a prototype of the designer, the Inge Manager. The designer and Inge Manager escalated it to the VPs. It caused this whole conversation. Month later, it was like kind of still stalling out. This PM happened to then, you know, attend a happy hour where the CEO was at and approached the CEO and told the CEO about the experiment that they were running with prototyping and stuff.

Starting point is 01:16:03 And the CEO was like, this is fantastic. Like, why, you know, like, like, where is it at right now? I was like, oh, well, X, you know, X, Y, Z happened. And the CEO had no idea. And then the CEO was like, okay, let me take care of it. And then the next day, it happens. So one is that you have to go to the ground floor on this stuff. Some of the best companies like Shopify and others are measuring actual adoption and usage.

Starting point is 01:16:29 They've gone to the extreme, like I'm kind of on that, on that front to get a bunch of signals in close to the ground. But it's just that it just goes to show that this is, you know, I don't think we want to talk about quote, founder mode. But the reality is it's not just about getting into the weeds of your product, but with something the sizable, you've got to get into the weeds of the transformation to really understand what's going on and adopt it. So that's point number one. The second point I would say is, Freread on, we do this podcast called Unsolicit feedback. You know, Fried Masavat had this great quote on it. He was like, look, the slowest, your output is constrained by the slowest part of your system. And I thought, that's stuck in my head because it's absolutely true. And so if you think about AI adoption as a system, there's all parts of the system that could be slowing adoption. It might be that people don't feel permission or they don't have the budget or they don't have the knowledge or like destruct, like all these types of things. But in a lot of these cases, it's things like IT legal procurement are the slow as part of the differential and are kind of setting the pace of all of this output.

Starting point is 01:17:42 And you can also see this in just product teams, which is, you know, a lot of, there's been all this talk about, you know, product managers are becoming the new bottleneck because engineers are speeding up. Well, that's because people are speeding up one part of the product system and not the other parts. Which makes sense. Like they adopted all of this tooling for engineers because they're the biggest headcount and the most expensive and like all that type of stuff. But product is an output of design PMs and engineers. The system is there not to produce code. It's to ship product, right? And shipping product is the function of those three things. So if you just accelerate one part of the system, you're just going to move to the bottleneck to another part and your actual product output, the output of the system doesn't accelerate either. So I think you like really got to, people have to really understand those two things. It's like what is actually happening on the ground floor? And what is the slowest part? What is the thing that is causing, you know, the slowest part of the adoption, just like attack, attack. them ruthlessly if you're really serious about making this transition. What a while time we're living through. It is a wild time. Yeah. All these ways that we're also used to. Okay, this is how we do it.

Starting point is 01:18:54 Yeah. Yeah. It's exciting and exhausting at the same time, man. That's how I think about it. That's such a simple way of describing the road. Yeah. Oh, my God. Okay.

Starting point is 01:19:05 Brian, is there anything else before we get to very excited? That's it. Let's do lightning around. Here we go. Ding, ding, ding. All right, Brian, I've got five questions. for you. Are you ready? Let's do it. Let's do it. Okay. What are two or three books that you find yourself recommending most other people? My God, honest answer is that I have not had time to finish an

Starting point is 01:19:25 entire book since I had my second child. So from a complete book standpoint, I have not been able to things that I've been, you know, that I actively read on a regular basis, just like other content out there. That'll throw out there is, gosh, Jamin Ball from Multimeter Capital writes this great newsletter called Clouded Judgment, which is kind of mixture of market thoughts as well as like market stats. That's really useful to help me keep a pulse on the market. You know, I was just reading through some like stuff from NFX that's been pretty good lately on all this. I know James career and I share, we lived a lot of the same cycles through social and stuff. So I tend to identify with that. So I don't know. Those are two things that I love reading. And sorry, I'll give

Starting point is 01:20:20 one more shout out to a different podcast, which is from two guys at Spark Capital, Nebel Hyatt, which I know from my early Boston days and Frazier, sorry, I'm blinking on the last name right now, who was head of product at OpenAAAI. And they've got a great format where it's just those to riffing on some ideas and stuff. And I highly suggest that one. I like that one a lot. Here's my reading tip that has changed my reading habits. Brian Johnson, the longevity guy,

Starting point is 01:20:52 he has this advice for better sleep, which includes before you go to sleep read for 10 minutes in bed. It does put you to sleep. I don't feel like I retain anything that I read that close to bed, though. Do you feel like you retain it? I do. I do. I'm reading fiction. Like, it's nonfiction.

Starting point is 01:21:08 I want, sorry, yeah, you want to read something calm, not like I'm learning. So I'm reading, I'm reading fiction and it's really nice. And knowing that this is going to help me sleep better makes me motivated. There's an incentive. There's a reward there. They're talking about rewards and creating behavior change. Yeah. Exactly.

Starting point is 01:21:24 And the reason to do it is his whole thing is you want to get to a low resting heart rate and then helps lower your resting heart. Yeah, I've got some other sleep tips on that front if you want to go down that path. But we'll say that's please. Let's help you for the third podcast. Okay. Next question. Do you have a favorite recent movie or TV show? that you really recently enjoyed.

Starting point is 01:21:41 It's not new, but I just rewatched Silicon Valley that I hadn't watched a number of times. And it's painful because like the first few seasons, I went through almost every one of those moments in my first startup, like hiring the gray hair and CEO, the funding falling through at the last second, like all the crazy stuff. But kind of going back and watching that, like there's just some extra nuances and stuff that I feel like they're. wrote really well that that I thought was that I thought was really good. So I've really been watching that. The other thing is that I've watched

Starting point is 01:22:18 is just more of like a just pure entertainment kind of calming thing, kind of turn the brain off is Owen Wilson's new show on Apple TV stick, which is about him as a former professional golfer and all that, you know, I won't ruin the show and stuff. But it's a nice, it's a very nice,

Starting point is 01:22:38 some calming, a little bit fun type of show. I've been seeing that on my Apple TV. Maybe I should check it out. Good tip. Do you have a favorite product? You've recently discovered that you really love. It could be a gadget. It could be a app on your phone.

Starting point is 01:22:51 It could be something in your computer. It could be nothing at all. You can't see it, but I do have, I just changed my whole setup. So now I have an ultra-gear super wide, curved screen with a very nice. standing desk from I believe it's called ergonophis er yes it's uh yeah or I think it's that ergo naus is ergo nofis erg o no f i s and it's a very

Starting point is 01:23:23 nice sleek standing desk very stable very quiet very much enjoy excellent tip and the in the current monitor very cool okay two more questions do you ever life motto that you often come back to and find useful in work or in life, something you share with folks, something that you think about when times are hard or just generally. Look, it's a little cliche at this point, but I used to, somewhere around here, I used to have the quote printed out about, you know,

Starting point is 01:23:52 the man in the arena, right? It's just like, just lots of, lots of, you know, especially in times like this where so many things are changing and there's so much competition, but so much opportunity for, create. I just, I really both respect and enjoy, uh, you know, the game and spending time with folks that are kind of in the arena, figuring this stuff out, tinkering with things. And, uh, and just, yeah, that's, that's kind of a lot what I come, keep coming back to, especially,

Starting point is 01:24:20 you know, been at a reforge for 10 years. That's a, that's a good portion of my life. And we've gone through some great periods and some tough periods. And, uh, so I tend to come back to that. That's what's always separated. Reforch from so much other content advice as it's people in the arena sharing their wisdom, not just a bunch of influencers. And it said that Chimoth made that quote

Starting point is 01:24:41 so cringy. I know. I know. That's why I know. That's why I said it's a little cliche cringe right now. Screw it up for everyone. Final question.

Starting point is 01:24:51 Brian, you don't know this, but your parenting advice on Adam Fisherman's podcast really impacted my parenting philosophy. Specifically, this line you had about independence. Oh, yes. And I'd love for you to just share that insight

Starting point is 01:25:05 about how you think about raising kids. Yeah, and I wish I could remember where I grabbed this from so I could attribute it properly. So, but basically, uh, the philosophy is like your job as, if you think about going from when they're born

Starting point is 01:25:25 until they're essentially 18 and, you know, leave the home, your job is, apparent is to essentially make them more and more independent. And so what that involves is continuously looking for opportunities for them to make even bigger and riskier decisions for themselves as they grow up and you're there as support to those decisions, but letting them make those decisions on their own so that by the time they're 18, they are a fully independent person able to think through those decisions themselves. And I'll look like my sons are young,

Starting point is 01:26:05 right? They're five and three. So it's not like I'm having them make, you know, life and death decisions or where we might buy our next house or stuff like that. But it's even small things at this age of, you know, my oldest like five and a half is really starting to learn and get curious about like money and how you spend money and where new things come from and how you you earn money. And so rather than just like buying things for him, you know, we've, he's got like money from his grandparents and stuff saved up. And we're trying, we can be like, okay, like you can buy that thing, but you're going to spend this and try to like teach him the consequences and like all that kind of stuff. And then when he breaks something, right, like, so it's just small things like that.

Starting point is 01:26:52 But thinking about the time from zero to 18 is this spectrum of independence and being a supporting role in what you're essentially doing is you're trying to move as many decisions you, as many, the percentage of decisions you make for them down to zero by the time that they're 18. Like, and that's, that's kind of something that I've kept in the back of my head since really seeing that. Thank you for sharing that.

Starting point is 01:27:20 I know I didn't tell you that I was going to ask you about this. So that was a beautiful way of summarizing it. Yeah, I didn't know where I couldn't remember that whole podcast. I had no idea what I said. but you can have said. But that's a good one, yeah. Brian, two final questions. Where can folks find you if they want to reach out?

Starting point is 01:27:36 Where can they find the products you guys offer, whatever you want to plug? And also, how can listeners be useful to you? Check out reforge.com. Check out our new products like Reforge Insights. They're on the website. You can find me personally, my writing, including a bunch of the stuff that we talked about today.

Starting point is 01:27:53 Now on Substack. So I just recently moved. So you can either go to my website, site Brian Belfour.com where I have some info or just blog.org.briyanbalfour.com where all of my new writing is taking place. But those are the two major pieces. Last but not least is that, as I mentioned, Fried Masevat, who I used to work with, he used to Slack. We just have, we have this fun podcast, the two of us get on there and riff like we were having dinner every couple weeks about different like product and strategy types of things. And so it's a, it's a fun format for us. So if that's

Starting point is 01:28:28 something you enjoy. It's called unsolicited feedback, where we give feedback and advice to nobody that ever asked for it. So it's amazing. Yeah. Perfect title. Brian, thank you so much for being here. Yeah, thanks for having me again. This is great. Bye, everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review, as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at Lenny's Podcast.com. See you in the next episode.

Lenny's Podcast: Product | Career | Growth - Why ChatGPT will be the next big growth channel (and how to capitalize on it) | Brian Balfour (Reforge)

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