What Founders Have To Unlearn To Become Great CEOs

**Spenser Skates** (0:00)
There is a point that you get to a year, maybe two years in, where from a rational standpoint, you probably should quit. But for whatever reason, those successful ones don't. And so that is the number one filtering criteria. The best advice I can have is be clear in your own head about what you're trying to learn, and then, you know, be open to where it comes from. And that's why I think people fuck that up a lot. They don't get really crystal clear on why they're trying to build a startup or what they need to do to be successful. There is gonna be a reinvention of analytics in the next few years, and you know, we wanna be the ones to go lead it.

**Harj Taggar** (0:37)
Welcome back to another episode of the Lightcone. Today, we're really excited to be joined by Spenser Skates, CEO and co-founder of Amplitude. So Amplitude went through YC in winter 2012 Amplitude is one of the world's leading analytics platforms, and they're used by some of the biggest companies in the world, like Cursor, DoorDash and Walmart. Thanks for joining us, Spenser.

**Spenser Skates** (0:57)
Absolutely, good to see you here, Harj.

**Harj Taggar** (0:59)
So I was really excited to have you here because both of us made people on the internet angry recently, specifically on X or Twitter. I made them angry because I said that a lot of the reason incumbent tech companies can't build AI products is that the engineers are kind of grumpy and don't believe in AI and its capabilities, so they don't want to build the products.

**Spenser Skates** (1:21)
People got mad at you for that?

**Harj Taggar** (1:22)
Yeah, people are really mad. Turns out that there are actually a lot of grumpy engineers that don't believe in AI. So I was curious to hear for you, as a company that started well before the AI wave and is now trying to move in, is moving into AI and building more AI products. How has that change been for you and what have been some of the challenges you faced?

**Spenser Skates** (1:40)
It is hard as a larger company to reorient and rebuild your company to use AI well. And this is, I think, to your point, the huge advantage that a lot of earlier companies that can build from the ground up in this way.
I mean, I'll just tell you the Amplitude story. So we were, frankly, skeptics on AI for a while, too. So it started to become relevant in 2022, 2023 There's discussion, but we didn't really do that much. And it wasn't until late in 2024 that we're like, okay, we need to get serious because I think this has the potential to reshape analytics and what we're doing. I think, you know, just to defend the skeptics for a second, I think I remember being in a board meeting once, you had all these board investor finance people, and you had all these salespeople were like, hey guys, shouldn't you look at this AI thing? Like, isn't that getting hot? Shouldn't you guys do it? And it's like-

**Gary Tan** (2:35)
What's your AI strategy?

**Spenser Skates** (2:36)
Yeah, exactly, exactly. Yeah, actually, that literally was a question from one of our execs to me. It's like, we got to get our AI strategy. What's our AI strategy, Spencer? And I'm like, this is the wrong way to think about what it is we're doing. It's like, you guys think it is, you guys think you can figure it out, go do it. And I remember one of my co-founders, Jeffrey, actually was the most frustrated because I think he saw a lot of grifting happening in AI, being like, oh, it's gonna replace all these jobs and like, you know, it's gonna do all these things and we're not gonna, you know, it's gonna create this world of abundance and it's just gonna totally reshape how we're building products and shipping them and how our customers are using them.
But the reality was, if you use any of these models at this point, it's like, it was not clear at all. I think if you look at the capabilities of any of these models, it's like, they're very, very jagged. So there's some things they're exceptional about, and there's some things that they're just absolutely terrible about. I think the frustrating part is to be told by someone who has no clue about, you know, what stuff falls in what buckets, like, oh yeah, you should do more of this AI thing. It was very, very, it was, that was frustrating. And so I think there was, there's frankly skepticism in my part, there's skepticism in the part of my co-founders, and some of the broader team with an amplitude about what was actually going to be possible with it.