Lenny's Podcast: Product | Career | Growth
00:57:38 · Lenny Rachitsky, Keith Rabois
[00:57:38] S1: And this advice is not just consumer. You're also talking like DoorDash has SMB-ish- [00:57:43] S0: Yeah, like Square and things like that. [00:57:45] S1: Square, yeah. [00:57:46] S0: Square is a good example. Anything sub mid-market, I think it's directionally dangerous. [00:57:52] S1: And the advice here is basically trust your insights. You need to have the insight yourself. You can't find it [inaudible 00:57:57]. [00:57:57] S0: I think typically the best companies- [00:57:59] S1: Yeah, interesting. [00:58:00] S0: There's foundational insight. And people don't necessarily want to hear that, but there's logic, you can asset test and pressure test the logic. To some extent, when Brian first pitched me on Airbnb, there was some interesting evidence he already had that this was going to be successful. The number one, the one that stuck with me at the time was he gave me the exact number of Craigslist listings that said, "I want to rent someone's bedroom." And it was actually a reasonable number. It was 30 in the Bay Area. But given that you had to literally type it in and have the epiphany yourself, I was like, "That's a lot actually. That's probably a real market there." And as soon as he said that, I was already leaning in. And by the time he finished his three-minute monologue, I was like, "This is the coolest thing ever. I need to invest." [00:58:57] S1: Yeah. And I think Airbnb was a good example where he was solving his own problem, saw an opportunity. Wasn't talking to people, "Hey, would you do this sort of thing?"
00:58:57 · Lenny Rachitsky, Keith Rabois
[00:58:57] S1: Yeah. And I think Airbnb was a good example where he was solving his own problem, saw an opportunity. Wasn't talking to people, "Hey, would you do this sort of thing?" [00:59:04] S0: And people would've said if he'd sampled the wrong people, definitely would've got feedback that was like, "No, very high risk." That's a good example where you had sampled 10 random people, good chance that nine plus percent would say, "No, I would never do that." [00:59:19] S1: You know what's really interesting? I was just watching Taylor Swift's acceptance speech at this award show, iHeartMedia something or other. And she gave this really powerful speech that when she was starting out, she was just kind of at home working on songs, learning piano, just in a room on her own and had thousands of hours to just iterate and learn and get better. Versus today, if you were to do this, you'd be posting it, sharing it, people giving you feedback constantly. And her advice is just find ways to just not expose yourself to people for a long time.
00:59:19 · Lenny Rachitsky, Keith Rabois
[00:59:19] S1: You know what's really interesting? I was just watching Taylor Swift's acceptance speech at this award show, iHeartMedia something or other. And she gave this really powerful speech that when she was starting out, she was just kind of at home working on songs, learning piano, just in a room on her own and had thousands of hours to just iterate and learn and get better. Versus today, if you were to do this, you'd be posting it, sharing it, people giving you feedback constantly. And her advice is just find ways to just not expose yourself to people for a long time. [00:59:53] S0: So I have a couple of friends who are artists in the music industry, and I think what she's saying is one of the reasons why it's sometimes difficult for artists who had success to recreate the success. Because the first success was not data-driven, was not customer feedback driven. It was like, "I'm creating this and it's resonating." Then because they have an audience, someone, either they or their manager or whoever, the label, blah, blah, blah, blah, blah, wants them to get feedback. And it creates derivative works, not strictly legally, but derivative works, they're less inspired. There's a podcast that Jack Altman did with my friend, Alex, from The Chainsmokers. He actually talks about this at some length that they created this song that actually didn't resonate with their normal audience, but actually resonated with a different audience, which is interesting. So I think you can get trapped with success. It's a good illustration actually.
00:59:53 · Keith Rabois, Lenny Rachitsky
[00:59:53] S0: So I have a couple of friends who are artists in the music industry, and I think what she's saying is one of the reasons why it's sometimes difficult for artists who had success to recreate the success. Because the first success was not data-driven, was not customer feedback driven. It was like, "I'm creating this and it's resonating." Then because they have an audience, someone, either they or their manager or whoever, the label, blah, blah, blah, blah, blah, wants them to get feedback. And it creates derivative works, not strictly legally, but derivative works, they're less inspired. There's a podcast that Jack Altman did with my friend, Alex, from The Chainsmokers. He actually talks about this at some length that they created this song that actually didn't resonate with their normal audience, but actually resonated with a different audience, which is interesting. So I think you can get trapped with success. It's a good illustration actually. [01:00:57] S1: There's also this concept of the ugly baby in Creativity, Inc., I don't know if you read that book, Ed Catmull, about every idea at Pixar, every great idea starts as this ugly baby that no one wants to help and pay attention to and just, "Get those out of here."
01:00:57 · Lenny Rachitsky, Keith Rabois
[01:00:57] S1: There's also this concept of the ugly baby in Creativity, Inc., I don't know if you read that book, Ed Catmull, about every idea at Pixar, every great idea starts as this ugly baby that no one wants to help and pay attention to and just, "Get those out of here." [01:01:11] S0: It's like a startup. I mean, that is actually the startup. I use this prism as an investor, which is when I make a seed investment or series A investment, let's say, I want half of my friends who are VCs to laugh at me. Literally laugh because I know most of the people I compete with pretty well. And so I'm running this algorithm through my brain. Are these people going to laugh? If so, this is potentially a great investment because it's an ugly baby. And ugly babies are the ones where there's real alpha. [01:01:37] S1: That's so interesting you say that. I did some research recently on what are signs. We interviewed, this is me and Terrence Rohan. I don't know if you know him, VC. We interviewed early employee, people that have joined early generational companies many times. They joined OpenAI early before anyone knew about it. Palantir, really early, Stripe. And so we asked them, "What did you look for?" And there's three patterns. And one of them was exactly that. The idea, people laughed at them. They thought it was crazy. This is never going to work. Palantir, for example, OpenAI, for example. [01:02:08] S0: Yeah. My parents used to laugh at almost all my jobs in tech. It used to be very funny. They thought I was going to be homeless because most of them did not make sense to them.
01:02:08 · Keith Rabois, Lenny Rachitsky
[01:02:08] S0: Yeah. My parents used to laugh at almost all my jobs in tech. It used to be very funny. They thought I was going to be homeless because most of them did not make sense to them. [01:02:17] S1: That's classic parents. No idea what the hell people do in tech. Yeah. [01:02:22] S0: They did appreciate Stripe though. My mom always appreciated Stripe. [01:02:23] S1: That makes sense. [01:02:26] S0: And always tried to lobby me to invest, and I finally listened. [01:02:30] S1: Nice. Good job, Mom. She earned her keep. Okay. We just shifted perspective because Keith's iPad was dying. Classic, that's maybe the downside of the iPad [inaudible 01:02:41] [01:02:41] S0: The downside of the iPad is I use it too much. [01:02:44] S1: That's product market fit. Okay. I want to actually follow up on this discussion we're having about just finding great companies. A lot of people are starting AI companies now. There's so many launching. As an investor, I'm just curious, what's a sign that this is a worthwhile idea considering the endless number of startups launching? And maybe what are some just flags that are like, "Okay, maybe don't work on that idea"?