Lenny's Podcast: Product | Career | Growth
01:00:22 · Lenny Rachitsky
[01:00:22] S0: It's interesting that another way to think about this model you've described is building... The strategy of building on top of LLMs and becoming a GPT rapper. Because essentially, this tech allows you to say, create a cursor that is incredible. And then you could argue, oh, you're just gonna be this rapper 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. Yep. To use that euphemism. Yep. 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?
01:01:24 · Brian Balfour
[01:01:24] S1: It might be just, like, a tad too early. Like, we're, like, right on that edge, but, you know, some of the questions I'm asking myself is I I... Like, I'm kind of going through all of these these players and where our 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 OpenAI offices, like, at that front desk, that they are having, you know, meetings with potential preferred developers, like, talking about that we could probably sit there and and and log it. So I I do think some people are going to be in a place to develop, preferred relationships and and make a note. And if you're you're in that spot, then you you should definitely play that card. A lot of early stage charts will be in that card place. Other than that, I would say, we we still need... Like, once they launch these platforms, it's like, we... You can't do much else until you really kind of know what the the value exchange is and what they're gonna 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, you have to capitalize extremely quickly. And a lot of times, it's just it's hard for leaders to do that because they don't want to create a feeling of whiplash into the unknown. We've got all these projects in play. They all... You you know all the things. So I think that's, I think that's probably the the the last part of what what we can be doing right now versus just, you know, kinda staying on top of everything as as it emerges.
01:03:13 · Lenny Rachitsky, Brian Balfour
[01:03:13] S0: As you were talking, this reminded me, I recently noticed that ChatGPT 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, ChatGPT. What 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 ChatGPT from... I don't know. I don't even know if I can from the You [01:03:39] S1: can in you can in Substack now. Yeah. I just saw that setting in there. Yeah. [01:03:42] S0: Okay. Oh, interesting. But that's the... A 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 then this is how... The way I felt. Like, take it all. Just, like, it's good. It'll... It's... It... 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. [01:04:07] S1: Yeah. That's right. Yeah. Like, if if you if you don't do it, you know, somebody else's. Yeah. And I think... And and I think that's also kinda what all the major media publishers are really contending with right now.
01:04:07 · Brian Balfour, Lenny Rachitsky
[01:04:07] S1: Yeah. That's right. Yeah. Like, if if you if you don't do it, you know, somebody else's. Yeah. And I think... And and I think that's also kinda what all the major media publishers are really contending with right now. [01:04:18] S0: I guess I need a licensing deal in your check, so... Anyway. Okay. I I wanna go on a totally different tangent. We weren't planning to talk about this. I know that, I said this. We're gonna be fully focused on this one topic, but there's something you mentioned to me before we start recording that I think will be really interesting to a lot of people. So you guys at 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 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, gonna be really helpful to companies that are struggling with adopting AI tools and seeing gains.
01:05:08 · Brian Balfour
[01:05:08] S1: Yeah. Just to quickly explain that tran... Transition so it it makes sense for people, which is, you know, I sort of Reforge 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. And they have all this amazing knowledge, and I wanted to encode it in useful and practical ways for others. Right? That took the form of courses and content and product and all that kind of stuff at the beginning. Along the way, everybody kept asking us to essentially build the tools to implement what we taught. Because with anything, it's 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? And so people kept asking us to to really close that gap, and we said no for the longest time. 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, Reforge Insights, which acts like your AI product researcher, kind of aggregates all the feedback from all the sources, uses AI to analyze it, helps you explore it, but also, will 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 net new insights. So complete the full cycle. We're gonna watch two other major products as part of this platform before the end of the year, but, we'll we'll save that for some some future episode. So that's kind of been our 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 ten years, companies have been coming, to us to help them drive some sort of transformation with our learning product. You know, most people... Most companies are not coming to us to, just like throw a bunch of courses in front of...
01:07:33 · Brian Balfour
They're 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, 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 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 native? How how do I adopt this stuff? And and so we've seen a pretty wide spectrum in... From both perspectives of how companies are approaching this. And I'm sure everybody's seen the, like, AI... I call... We've been calling them, like, the AI manifesto memos from CEOs out there that proclaim we are now AI native. You know, It's some grandiose way. Right? There's behind the scenes, there's actually some incredibly stark differences in the actual teeth of what backs up those 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 a lot... What what you... There's there's other parts that's like, okay. Wanna communicate this. You wanna 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 building it into your career ladders, or some people are starting to introduce this as questions into their performance reviews, all those types of pieces. 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 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 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 and do things to to to replace that. So that was one.