Lenny's Podcast: Product | Career | Growth
01:13:07 · G2 Patel, Lenny Rachitsky
So timing, market team, product number five is brand. I had a mentor one time that told me, Mark Lewis, he said, "Jeetu, don't ever go to a company who's lost their brand mojo, because very hard to resurrect it back." If they have lost their product and you cannot fix the product. But do you think Sybase is coming back? No. Once you lose your brand and once you lose the trust, people don't come back to you that much. It's very hard to do. And then number six is distribution. Just because you build it, they will not come. You have to make sure that you figure out a scaled mechanism of getting that offering to many, many people. And so timing trumps market, market trumps team. Team trumps product, product trumps brand, brand trumps distribution. You don't have all six, you don't win. [01:13:54] S1: What an amazing nugget to have at the end here, just so I understand how you think about this is, do you have a template that you work through when you're thinking about a new business unit or new product to launch? Is it is timing, right? Is market, what market do we start with? How do you actually operationalize?
01:13:54 · Lenny Rachitsky, G2 Patel
[01:13:54] S1: What an amazing nugget to have at the end here, just so I understand how you think about this is, do you have a template that you work through when you're thinking about a new business unit or new product to launch? Is it is timing, right? Is market, what market do we start with? How do you actually operationalize? [01:14:09] S0: It's actually exactly like that. I will ask myself the question on, "Is this the right time for us to go out and double, triple, quadruple down?" We might still be in experimentation mode, but do I need to double down on this right now because this might not manifest for another seven years and then we're going to be too early. And by the way, you have to know the difference between a megatrend and a hype cycle. When there's a megatrend, don't fight it and don't succumb to the temptation of trying to go out and do vanity work for a hype cycle. And there's a big difference between the two. And I think having the judgment, the older you get, the better that judgment gets. It's just miles. But having that judgment is really important because you see a pattern recognition at some point. [01:15:00] S1: I imagine AI megatrend.
01:15:00 · Lenny Rachitsky, G2 Patel
[01:15:00] S1: I imagine AI megatrend. [01:15:02] S0: AI is a megatrend in my mind, and there's a bunch of hype cycles we've had where I never particularly subscribe to them. The easiest way for me to tell is, the way it's described, is it easy to understand what this could do in its ultimate form for most people, or do you need to have a PhD to understand what someone's saying? When you feel like you need a PhD to understand what someone's saying, chances are it ain't going to be a megatrend, because by definition, a megatrend is it's going to impact a large population of the world. And if the thing is too complicated, chances are it's not going to have that level of effect, outsize effect. [01:15:43] S1: That's an awesome heuristic. I imagine you're thinking Web3 as a classic example. [01:15:46] S0: Yes. Web3 was the one that I actually cite all the time. I couldn't understand what it had been. And all of these people were kind like, "Oh, Web3, Web3." I'm like, "I couldn't make a heads of tails out of a use case." But with AI, it's like you go to ChatGPT, you ask it a question, you get an answer. I get this. This is easy. [01:16:05] S1: So going back to your framework, just to kind of close the loop there, it's really interesting that timing is the first variable you look at. This could be an amazing idea. You got the right team, amazing product that works really well, but the timing may just not be right. And no matter how awesome it is, it's not going to work.
01:16:05 · Lenny Rachitsky, G2 Patel
[01:16:05] S1: So going back to your framework, just to kind of close the loop there, it's really interesting that timing is the first variable you look at. This could be an amazing idea. You got the right team, amazing product that works really well, but the timing may just not be right. And no matter how awesome it is, it's not going to work. [01:16:21] S0: Steve Jobs put away the iPad because he thought that the iPhone was a better idea. And timing wise, he actually made exactly the right call. The iPad became successful because of the iPhone success. The reverse order might have not had the same effect, but he had to make sure that he focused on one thing and he actually puts the other, he said, "The timing's not right, but I'm going to get back to it." So by the way, when timing is wrong doesn't mean that you scrapped the idea. It just means that you might put it on ice for a bit. [01:16:50] S1: There's a lot of that happening right now where people try to do a thing and now AI actually makes it possible. And now they're like, "Oh shit, it was way too early."
01:16:50 · Lenny Rachitsky, G2 Patel
[01:16:50] S1: There's a lot of that happening right now where people try to do a thing and now AI actually makes it possible. And now they're like, "Oh shit, it was way too early." [01:16:58] S0: And the other thing you have to keep in mind is you have to also be good enough to know that when something is going to be ready in six months, you can't think about what it's doing today. AI is moving so fast right now. One of the things I tell my team is, fast-forward six months from now and anticipate what that's going to do and get prepared for that world. Don't get prepared for the world of today thinking that you're not going to be able to get there because in six months your assumption sets are going to be different. And please don't actually then bias yourself with the assumption sets you have right now to not move forward. One of the worst things I think companies do sometimes is they put too much emphasis only on solely on experience. And I think experience is good, but experience can actually be meaningfully bad in some areas where you get too biased. And so you almost have to say that I have to have the ability to unlearn. And combination of experience with complete inexperience is what creates the magic because the inexperience allows you to ask questions that you might have never had with experience. And the combo of those two gives you the best of the pattern recognition, plus the charting new territory that's never been walked on before.
01:18:10 · Lenny Rachitsky, G2 Patel
[01:18:10] S1: Yeah, this is a trend I've been hearing on this podcast that people worry about young people and people graduating out of college right now and jobs and AI. But they're the people that are most open-minded about what AI can do for them and how to harness AI and not code in the way people have always coded. It's just like, okay, this is the way it works now. [01:18:29] S0: Experience, Lenny, can jade us, and I always say when people say, "Oh, entry-level people will never be hired again." That's the stupidest thing a company can do, because now what you've done is you have completely shut the door to new fresh ideas. I cannot think today the way I thought when I was 19. There is just no way that I can do that. But what I can try to do is I can try to make sure I surround myself with enough amount of my time to get exposed to that thinking and then couple it with what I know and maybe have something better than what either of those two could have had by themselves. [01:19:04] S1: Yes. Well, with that, Jeetu, we have reached our very exciting lightning round. I've got five questions for you. Are you ready? [01:19:11] S0: All right. [01:19:12] S1: First question, what are two or three books that you find yourself recommending most to other people?