Lenny's Podcast: Product | Career | Growth
00:27:27 · Amol Avasare
[00:27:27] S1: Yeah. But the thing is we've been tracking at 10X year-on-year, and that's the thing that we keep in mind. And I think it ultimately comes down to our fixation of this company about the exponential. I think if you look at anyone who's talking from Anthropic about basically anything, we always talk about the exponential. It's effectively as model capabilities continue to grow on an exponential and the tools around them enable a better job of diffusing that into useful use cases, you basically just keep unlocking new markets where the value of those markets significantly dwarfs what the value of the previous markets were. And agentic coding's a great example. It didn't exist a year, a year and a half ago. And then now just the value of agentic coding is bigger than the previous market of AI coding use. And so I think that is the core thing here where just that the future product value is in order of magnitude higher than it is today. And I think about, I don't know, a normal business, number of companies that I maybe mentioned, or you think about a trading app or a grocery delivery product, many of the leading companies, they're great businesses. But if I think about what is the product value that a company, like a standard, call it a grocery delivery app, what is the product value you get as an end user today versus two years from now? I look at it as like, okay, in two years from now, even if you're shipping all these new products, as an end user, the value you get- You're shipping all these new products. As an end user, the value you get from that product maybe goes up 30 to 50% if the company's done a really good job of shipping new features. It's not exponential though. And so if I think about, "Okay, you're here today. In two years, you're going to have 30 to 50% more product value." Then as a growth team, the relative differential of the product value in two years from now relative to today, I can actually capture a decent percentage of that with the small to medium optimizations that typically have higher conviction as opposed to larger bets. But for Anthropic, it's not really that way, where because of the exponential and our products being very, very, very ... The product value coming from AI, the product value that we will deliver in two years' time is probably a 1,000x, a 100 to a 1,000x what it is today.
00:29:54 · Amol Avasare, Lenny Rachitsky
And so if I think about that, and it's like there's so much value on offer, you need to shift more towards, "Okay, we need to take larger bets and we need to not miss the forest for the trees." And so that's why we still do all the smaller optimizations. It really matters, and no one else is going to do some of these things and so we need to do it. The compounding value is not immaterial, but we do take on much larger core productey type of swings as well. So you mentioned the Chrome Extension. That is now the thing that underpins a number of use cases on Cowork and Claude Code as well. And that's something that the growth team built. That's a very AI-peeled product that is a very research-heavy product that we were just bullish on it. We had an engineer who was very bullish on it and we were just like, "Hey, no one else is doing it. We're going to do it." And so that's the sort of thing that I wouldn't have done at another company. [00:30:53] S0: Oh, wow. I did not know that. So one takeaway here is there's stuff to extract from your advice that is only true in Anthropic and then there's, what can other companies learn from this experience that you've had? So one is, is your sense that if you're working in AI, shift more of the pie chart towards bigger bets because in the future, the opportunity is so large, you want to find those as soon as possible versus micro-optimize?
00:30:53 · Lenny Rachitsky, Amol Avasare
[00:30:53] S0: Oh, wow. I did not know that. So one takeaway here is there's stuff to extract from your advice that is only true in Anthropic and then there's, what can other companies learn from this experience that you've had? So one is, is your sense that if you're working in AI, shift more of the pie chart towards bigger bets because in the future, the opportunity is so large, you want to find those as soon as possible versus micro-optimize? [00:31:25] S1: To be more specific there, I would say that if the primary value that your product delivers is underpinned by AI as a central element of it, then I think you should operate this way. So I don't know, companies like Lovable, Cursor, all these great businesses that are, as the exponential rises, their value props are also going to continue to rise significantly. If you're building a product where it's an AI-first product, then I would definitely operate in this way. I think if you're building a product where it's not necessarily an AI- first product and you have some AI features that are on the side, but it's not the core of your value, I don't know that I would operate this way. It would depend on how is the rest of the product org staffed and how is the growth org staffed in relation to that.
00:31:25 · Amol Avasare, Lenny Rachitsky
[00:31:25] S1: To be more specific there, I would say that if the primary value that your product delivers is underpinned by AI as a central element of it, then I think you should operate this way. So I don't know, companies like Lovable, Cursor, all these great businesses that are, as the exponential rises, their value props are also going to continue to rise significantly. If you're building a product where it's an AI-first product, then I would definitely operate in this way. I think if you're building a product where it's not necessarily an AI- first product and you have some AI features that are on the side, but it's not the core of your value, I don't know that I would operate this way. It would depend on how is the rest of the product org staffed and how is the growth org staffed in relation to that. [00:32:14] S0: Okay, awesome. And then in terms of the way you are structured, I thought that was really interesting. It's a combination of different sorts of things. So there's the API growth, there's Claude Code growth, but then there's also personas, like a vertical of knowledge workers and B2B. Is that intentional, some specific bets and one just broad market opportunity?
00:32:14 · Lenny Rachitsky, Amol Avasare
[00:32:14] S0: Okay, awesome. And then in terms of the way you are structured, I thought that was really interesting. It's a combination of different sorts of things. So there's the API growth, there's Claude Code growth, but then there's also personas, like a vertical of knowledge workers and B2B. Is that intentional, some specific bets and one just broad market opportunity? [00:32:35] S1: When you have one product, it's easier to have a growth team that's more purely on the funnel. It's like you have the conversion, you have activation, you have monetization. But as you start to get into having multiple products, I think that's harder because if you do that, then if you just have one activation team, for example, but then you have Claude Code, you have Cowork, you have all the other things. They're very different audiences and they're very different sets of cross-functional stakeholders internally. So we're kind of looking at, what is the thing? And all org structures are not perfect and they're right for a point in time, but we're looking for what is the structure that allows us to have as much focus. Focus is a really big thing, and on audience and problems. And also, the tie-ins to cross-functional partners is really, really important. The folks on our Claude Code growth team, they work extremely closely with Cat and Boris and the others on that team. And so that tie-in is really important as well.
00:32:35 · Amol Avasare, Lenny Rachitsky
[00:32:35] S1: When you have one product, it's easier to have a growth team that's more purely on the funnel. It's like you have the conversion, you have activation, you have monetization. But as you start to get into having multiple products, I think that's harder because if you do that, then if you just have one activation team, for example, but then you have Claude Code, you have Cowork, you have all the other things. They're very different audiences and they're very different sets of cross-functional stakeholders internally. So we're kind of looking at, what is the thing? And all org structures are not perfect and they're right for a point in time, but we're looking for what is the structure that allows us to have as much focus. Focus is a really big thing, and on audience and problems. And also, the tie-ins to cross-functional partners is really, really important. The folks on our Claude Code growth team, they work extremely closely with Cat and Boris and the others on that team. And so that tie-in is really important as well. [00:33:34] S0: So you've done growth at a lot of different companies, a lot of basically, let's call it traditional growth before Anthropic. How else is growth as a function and as a skillset changing with the rise of AI, AI products, and AI startups?