What Founders Have To Unlearn To Become Great CEOs

Spenser Skates has spent more than a decade building Amplitude from a YC startup into a public company, and in that time, he's had to reinvent himself just as much as the product. Joining the Lightcone pod, he talks through the shift from founder to large-company CEO, the skepticism his team initially had toward AI, and the moment they realized the next wave of analytics would require a full reset. He walks through the hard reorganizations, the bottom-up experiments, and the mindset changes that let Amplitude move fast again.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 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 going to be a reinvention of analytics in the next few years. And, you know, we, we want to be the ones to go lead it.

• 0:37Harj Taggar?

  Welcome back to another episode of the Light Cone. Today, we're really excited to be joined by Spencer Skates, CEO and co-founder of Amplitude. So Amplitude went through Y C 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, Spencer.

• 0:57Speaker 00

  Absolutely. Good to see you here, Harj.

• 0:59Harj Taggar?

  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.

• 1:21Speaker 00

  People got mad at you for that?

• 1:22Harj Taggar?

  Yeah, people got really mad. Turns out that like, there are actually a lot of grumpy engineers that don't believe in AI. So I was curious to hear for you as like 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?

• 1:40Speaker 00

  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, we were frankly skeptics on AI for a while too. So started to become relevant in 2022, 2023. There's discussion, but we didn't, 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 is 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

• 2:24Speaker 00

  board meeting once you had like, you know, all these like 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? What's your AI strategy? Yeah, exactly. Exactly. Yeah. Actually, that literally was a question like from one of our execs to me is 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 going to replace all these jobs and like, you know, it's going to do all these things and we're not going to, you know, it's going to create this world of abundance and it's, it's just going to totally reshape how we're building

• 3:09Speaker 00

  products and shipping them and how our customers are using them. But the, the reality was if you use any of these models at this point, it's like, it was not, 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 gigantic. 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, but what stuff falls in what buckets like, oh, yeah, you should do more of this AI thing. It was very, very, it was that, that, that was, that was frustrating. And so I think there was, there's frankly skepticism on my part. There's, there's skepticism in the part of my co-founders and, and some of the broader team with an amplitude about what was actually going to be possible with it. But something changed.

• 3:55Speaker 00

  Yes. Well, I think you, you saw the transformative effect that AI had on software engineering. Like, no question, if you were using, I mean, started by Cursor, but then, you know, all these other amazing tools, Claude Code, Codex, like tons, you know, tons and tons of others. It was, it was very clear that you would be a lot more productive using these things.

• 4:20Speaker 00

  So that was kind of the first of us saying, okay, there's something there, there, and let's go after this. So we really started on this path in earnest in around October of 2024. And kind of two things happened then. One, I hired a new engineering leader, this guy Wade Chambers, who's a Silicon Valley legend. The other is we acquired this company, Command AI, also a Y C company. In both their cases, they were kind of the change agents that Amplitude needed. So Wade had been working on AI in his previous company and had known a bunch of people who were on the bleeding edge of leveraging the capabilities of models. They had been building a product where they were trying to, they're doing a bunch of different things, but they were trying to

• 5:04Speaker 00

  smartly trigger guides to end users just based on if they were confused. And they, you know, had created this, this chat bot that very much like an intercom fin that would

• 5:17Speaker 00

  yeah, interact with users and, you know, help them answer support questions and stuff like that. And they had been, you know, on, on leveraging a bunch of model capabilities. That was kind of the, the first point that we started to, to get serious about it. And then since then, it has been a very, I'd like to think we're kind of coming up. And we just launched a whole bunch of AI products in the last few weeks. We did AI feedback, we did AI visibility, we did our MCP server. And then we're going to go much, much bigger in December, January and February, where we are going to be coming out with what we call the cursor for analytics, which I'm incredibly excited about. And I think will dramatically change how people use and leverage analytics.

• 6:00Speaker 00

  But it's, it's taken to transform, you know, Amplitude as an organization. I like to think we're still small, we're about 800 people. Product engineering and design, that organization is about 200 people. So, you know, it's like you can know most people in it and, and change pretty quickly. It's still taken us a full year to get the team kind of fully on board and ramped and like believing and seeing and building.

• 6:25Harj Taggar?

  Chat GPT launches, AI starts taking off. And it sounds like your investors and board members. People who aren't in the day to day are sort of like, hey, what are you doing with this AI thing?

• 6:33Speaker 00

  Yeah.

• 6:33Garry Tan?

  They read about it in TechCrunch or something.

• 6:34Harj Taggar?

  Yeah, exactly.

• 6:35Speaker 00

  Yes, exactly, exactly.

• 6:36Harj Taggar?

  What about internally? Like, what was the vibe internally at Amplitude on the team? Like, was there anyone internally asking, hey, like, should we be building AI products or doing something with AI?

• 6:45Speaker 00

  There were a few people that were kind of testing out ideas. But I think we were so focused on our regular motion. Like, we were coming out with a lot of other products outside of analytics. We were doing, you know, we'd launch experimentation. We were building session replay internally. We're building this thing, Activation, which targets your users based on their behavior. And so there was a lot to do. That was just kind of right in front of us. That was clear, like, okay, hey, we can be much more competitive with, you know, and there's this revenue that's just sitting here if we go build these things. You know, there were a few folks that were messing around with it. And there were some people that had used Cursor and other things. But the organization as a whole did not have,

• 7:29Speaker 00

  it's not like it was conscious and aware of this change, this massive change that was about to happen. I give a lot of credit to Wade and I give a lot of credit to the command team of being the tip of the spear in terms of showing people what is possible and then getting the organization to embrace. By early 2025, I was convinced and I was like, all right, we have to be very aggressive on this. So the first order is to train the organization of what the capabilities of AI are, specifically engineering.

• 7:59Harj Taggar?

  What was like the lightbulb moment for you? When did you flick into, this needs to be my priority?

• 8:04Speaker 00

  It's hard to say that there was, there was one moment. We've always had this vision at amplitude of a self-improving product, where you have a product that dynamically responds to your user feedback. So it knows what features you like. It knows when you're getting frustrated and stuck. It knows how to change things based on your input as a user. And I had always thought this vision was like, you know, 10 years out, if, if, if, you know, if even that close. And one of the things that was becoming clear, it was actually a lot closer. That, that moment was actually probably a lot closer than we had realized. Because of what we saw happening on the coding side with AI. I said, okay, look, we, you know, whether or not a self improving product is going to be possible.

• 8:49Speaker 00

  It's clear at least a step towards it. We're going to have to go do it. So, and the way to do this is we're going to have to train the organization on this. I started working with James, the founder, CEO of Command, as well as Wade, our engineering leader to figure out how do we train the organization on AI. And then we, we came up with an AI week and unfortunately for a bunch of reasons, we weren't able to actually do that until June, but that was a, that was a key pivot point. What we did was we got a bunch of the existing leaders in the organization. So, you know, our VPs of product, our engineering managers to use this technology and to see what was possible about it. And then during that AI week, what we do is we train the team.

• 9:33Speaker 00

  We had our, like our, one of our product leaders, you know, vibe code, like a dark mode for amplitude in front of the entire organization, which was actually very scary, but actually it happened, you know, they ran into a bug, but they happened to sort it out. It was actually kind of a cool moment because the entire engineering product and design organization saw what was, it's like, wow, okay, you know, all of the leaders with an amplitude are saying this is the thing and they're showing how they're doing it and, you know, I better get with this as well. And then the rest of the week, you know, so we did training for about two days. And then the rest of the week was just, you know, like a hackathon and work on stuff you're already doing, except, you know, do it faster and better by, you know, getting set up with cursor as well as a bunch of these other pieces of tooling.

• 10:12Harj Taggar?

  So step one is, was actually not like, here's what we need to build at amplitude with AI. Step one is just get the existing team using tools and

• 10:20Speaker 00

  Yes, yes.

• 10:21Harj Taggar?

  believing in them.

• 10:22Speaker 00

  This is the core difference between building product and SaaS and building product with AI. In SaaS, SaaS, I mean, it's the best business model and the best product delivery system of all time. You go to your customers, you ask them what they want and what they're going to pay for. You prioritize that list and you start building it. You get them to those customers and then you just do the whole thing over and over again. That's the delivery loop that Amplitude has mastered over the last decade. And you know, that's, that's our core competitive advantage, you know, as, as an analytics company is we're better at that than anyone else. The key is you can go to your customers and they can tell you what they want.

• 10:57Speaker 00

  With the capabilities of AI, because they're so jagged, you, it's a technology first understanding of what is possible. And so if you go to your customers and tell them and ask them what they want, like they're not even going to be able to describe what's possible.

• 11:11Harj Taggar?

  Give me a faster horse.

• 11:12Speaker 00

  Yeah, give, give me a faster horse, you know, or, or it'll be asking for something that's not quite possible or possible in the wrong way. Or like, hey, you know, I want something that ships insights to me and, you know, does it in this particular way. And you'll get all sorts of different visions of it.

• 11:26Speaker 00

  And what's much more important is you, you have to be familiar with the capabilities of the models. And then how those can map back into what your product does.

• 11:36Harj Taggar?

  The thing that I just find really surprising about this is usually the way it works with new technologies is like the engineers are the early adopters. And they are usually like bugging their like company. I really want to use like this tool and like, and it's like the companies are resisting saying, well, it's not like tested yet. It's not safe, but like, it seems to be a more common pattern with AI that it's like going the other way.

• 11:57Speaker 00

  Yeah, it's tops down.

• 11:58Harj Taggar?

  Yeah. Like, why do you think that's happening?

• 12:00Speaker 00

  I mean, it's going to sound extraordinarily reductive, but I, I think, I think Sam Altman is the best salesperson of, of this generation by no bar none. Like I think he has done an exceptional job stating a very ambitious vision, getting a lot of people rallied behind it at OpenAI. Showing what's possible and convincing, you know, the entire world of the impact that this technology is going to have. And so you have these, you know, exact investors already bought in, executives are bought in, you know, world leaders are bought in. Like, you know, as a society, we, you know, the, the people in power have said, hey, this technology matters. And the reality is the capabilities are still trying to catch up and it's not clear if they'll catch up to those aspirations.

• 12:44Speaker 00

  And so you have, to your point, Harge, the opposite disconnect happening where, you know, yeah, you have a lot of desire for this thing to happen, but. You know, it's not clear if the capabilities are there yet. And so this is why, you know, you had a lot of frustration, you know, in Amplitude as a case study, you had a lot of frustration from engineers being like, man, I see just tremendous, what they feel is grifting in AI where it's a lot of talkers, not many doers. You know, it's not till the last year that, you know, okay, hey, we think the capabilities are here for it to transform the, uh, the business that, that we're in in analytics.

• 13:17Diana Hu?

  One thing that comes to mind is this mode of running the company more like founder mode is even more present.

• 13:25Speaker 00

  Yes.

• 13:25Diana Hu?

  There's a story of the transformation with CaseText, where we're just founder-led to do that transformation. Sounds like this is what's going on with Amplitude 2 is coming from, from you.

• 13:35Speaker 00

  Absolutely. So I've had to learn over the last 10 years how to be, go from being a founder to being a large company executive. There is no way to understand what is possible than being, using the technology and being on the front lines of it. And so, you know, that's why it's like, yeah, you train the entire organization and it's a much more bottoms-up thing on what is possible. And so out of that AI week came basically all the AI stuff that we're working on now. So our MCP server, which we didn't even plan for, like, that was actually one of our engineers, Brian Giore, who's incredibly excited. You had, uh, one of our engineers, this, this guy named Leo Zhang, who built AI visibility and he just wanted to, he was actually going to leave Amplitude to start a company and

• 14:18Speaker 00

  we're like, look, just come here, stay here, learn how to do this while getting paid and we'll, we'll, we'll teach and coach you and then, you know, we'll fund when you, whenever you do go something. And I didn't even want him to do AI visibility, but he was like, oh, I think that there's a huge opportunity here, uh, to like build something for free and give it away. And, you know, now that's, now like, you know, it's, it's been this explosion. Like we have that lot, product launch doubled, uh, new signups to Amplitude, which is wild. You know, like every week, it's like, we're getting twice as many, uh, signups to our free plan as we did, uh, from before our AI visibility launch, um, all the way to what we're going to be launching in January, which is we're going to launch, um, a, what we're going to call Ask AI, which is a global chat interface, very much like Cursor.

• 15:01Speaker 00

  Where you will be able to chat with, yeah, chat with AI and ask it to pull certain charts for you or do analysis or figure out why something has happened to you for, within, within, you know, your data and pull that back out to you, to our agents, to like so many different things have come out of this from, but it's, it's all been very bottoms up. And then it's about, you know, for me and for Wade to, to sculpt, okay, how do we set these up in the organization for success?

• 15:32Diana Hu?

  So not many large companies like yourself have been able to do this transformation. A lot of them are still stuck and it's been probably very painful to overcome. What are the things that you had to give up to get to where you are right now?

• 15:46Speaker 00

  I mean, we've done two reorganizations in the, the engineering product and design organization since the, since the start of this year. And so, you know, there were leaders and executives and different people who were very much kind of in the SaaS modality, but were not on the bleeding edge of AI that just unfortunately were not quite the right fit for what we were trying to build in the future. And so ended up having to move folks out of the business. I mean, doing that level of reorganization, you know, twice in a year is very disruptive. We've also acquired other companies. So we brought in the Craftle team and Yana, who's been phenomenal. And we brought in Eric and Frank from Inari. We

• 16:28Speaker 00

  brought in also a YC company. We brought Enzo and Fruchio from June also, I think, YC, YC company. Yeah. So, so we've brought in all these great YC founders and then kind of melded them with a lot of longtime amputees. And that combination has been very, very special.

• 16:45Harj Taggar?

  What are like the, the specific differences? For people who are really successful, I, I think especially engineers, like who are successful in sort of pre-AI SaaS world and grew up in that environment. And then you compare like, what are sort of the things that they're, I don't know if lacking is the right word, but what are the things that they can't see or they're not as naturally adept at as people who? Came up in sort of post AI world and like AI native engineers and believe in it deeply.

• 17:10Garry Tan?

  To say the more uncomfortable thing, like, is it an age gap?

• 17:13Speaker 00

  Is an age gap? It's not an age thing per se. It's a mentality thing. Like, in the SaaS world, you can take, you can do that loop I talked about earlier. Talk to customers, ask them what they want, prioritize that list, build it, deliver it, do it again. Like, you, you, you kind of, I don't know, it feels very cliche to say, but you, you want to take kind of the state of the art in whatever field you're building for, and then start to say, okay, if I were to redo this in an AI native way, why? On the flip side, I think what a lot of these AI native teams are really missing is they haven't learned the product and the problem and why things are solved the way they're solved. And so like, they try to create these new interfaces from scratch without drawing on the

• 17:55Speaker 00

  previous, you know, expertise that's happened over the last decade on whatever problem that they're solving. And so, you know, if you try to build an analytics interface from the ground up, where you're just, say, you know, starting with questions and you're not seeing your data, it's actually, that's actually has its own set of challenges. And so I think, you know, what I'll say with the Amplitude team is like, there's some incredible engineers there. I think the ones that have adapted the best have always been very in tune with, okay, the code is not an end in itself. It just, like, shipping it, that's just a side effect of solving whatever problem for the customer. And then, hey, now I need to get up to speed with this new technology. And if I can marry those two things, then I'm going to create something amazing.

• 18:37Garry Tan?

  I guess one of the weird things that I've noticed in my own behavior is we have an internal agent infra at YC, and it has access to all our, you know, databases and everything like that. And then Jared recently told me I'm like, sort of a super user for it. And then what I realize is, I don't, basically, it actually fails most of the time still. But I just like, try and ask it in a different way. I tried, you know, if it failed with Gemini 3, then I'll try it with, you know, Claude, I'll try it with GP 5.1, like, I'll change the reasoning levels, like, and then eventually I figure it out. And it's like, and it works. So, whereas like, in B2B SaaS and or building, you know, sort of standard web 2.0 software.

• 19:18Garry Tan?

  It's like, man, if it broke even once, like this thing is a piece of crap and I'll never use it again. So it's like a weird, yeah, you have to like rewire your brain to be, it's like working with a child right now.

• 19:30Speaker 00

  This is why I think a lot of the hype in that AI killing SaaS is way overblown because particularly for a lot of business workflows, like very high guarantees on performance are fundamental to it. You know, if you put a record into your CRM, that stuff better be there, you know? You don't want it, oh, well, it put this in with 80% probability. It's like you want it to be there and SaaS does a great job of that. It actually took a set of existing workflows that were handled on prem or by paper and just move them to the cloud. And so it wasn't really like, it wasn't any workflow transformation. And this is where I think Andre Karpathy's point is totally right, where a lot of these businesses are trying to overshoot the mark and just say,

• 20:13Speaker 00

  okay, well, hey, well, just have this agent handle this workflow end to end. Actually, the editing and redoing it, like you, like you talk about Gary is actually incredibly important. And so how do you create a product that allows you to do that really well? I think is the key challenge that a lot of AI B2B companies are figuring out.

• 20:30Jared Friedman?

  Speaking of things that you had to give up in order to do this, what happened to the existing Amplitude roadmap? Like you had all these other things that you were working on before the company got AI fervor. Did you throw out the whole roadmap or like half of it? How are you thinking about like allocating resources between these new AI bets and the like existing stuff that makes the money?

• 20:46Speaker 00

  It's not like there's, there's totally separate products, like the goal of, for example, our, what we're calling Ask AI, which is the chat interface in Amplitude, is to make it easier to use the existing product. And so, you know, as we've looked at next year, there are four big priorities we have. One is rebuild Amplitude to be AI native. The second is make it much easier to use. The third is make sure our other products outside of analytics have parity with the competition. And the fourth is serve marketers really well so that we can take on a bunch of the legacy martech guys. There's still like basics that we're doing or foundational things we're doing. On our session replay product, on our experimentation products, on our guides and surveys product.

• 21:30Speaker 00

  Like, you know, for example, one big thing that we're going to be coming out with in session replay in the next few months is zoning, which is this way where you can look at a webpage and then see the analytics overlaid on top of it, which is super cool functionality. And so that we're still doing in the same way. I think what getting the team to embrace AI from the, from the ground up has happened, has allowed us to do is one, you know, they're a lot faster and more productive, so they're shipping a lot more, which is absolutely amazing. And then two, they are looking at these problems with this lens. And so the, the, the big change we did organizationally is we had a lot of these, these AI projects as kind of side projects for a bunch of people. And we said, okay, let's have a dedicated team that kind of goes after them.

• 22:13Speaker 00

  But the existing team is still going to do, you know, work on making the amplitude product great. And that work is, is, is just as important because I, I think the timeline for change in the business world is the cycles are just much, much, much longer.

• 22:28Jared Friedman?

  And how do you allocate people between the teams working on the new AI stuff and the more traditional SaaS stuff? Did they self-select into different groups? Is like, is there like a, like a, like a challenging cultural divide there that you have to navigate?

• 22:41Speaker 00

  No, you know, I think by doing the AI, we can make it clear. We had this whole metaphor, we talked about burning the boats, like we're all in on this. And there were some people that got even more into it and they very naturally self-selected into a bunch of, a bunch of this work like we, and it's, it's crazy. It's like, it's not just, hey, engineers, it's like designers too. Our very best designer at Amplitude, this guy named Will Newton, we actually had him spread among way too many projects. And he was like, no, I gotta focus in like, let's like say noted some of these for, for a little bit. So I can go really deep on this chat interface at, you know, and, and make sure that when we launch this thing in early next year, it's, it's going to be awesome. So yeah, people will naturally kind of self-select in or out.

• 23:26Speaker 00

  And, um, you know, it's, it's a 200 person org, so you get a, you get a whole spectrum of this.

• 23:30Harj Taggar?

  Can we talk about the thing that you said that made people angry on the internet?

• 23:33Speaker 00

  Yeah, yeah. One.

• 23:35Harj Taggar?

  I think, yeah. I think it was, it was the AI visibility tweet, right? I think like generally, I think you were making the point that um the, a lot of these startups are sort of like features, not companies. And obviously like at Y C, we're going to take the other side of it.

• 23:51Speaker 00

  Hell, yeah.

• 23:52Harj Taggar?

  Would argue that.

• 23:53Speaker 00

  You guys have a, have a visibility company, it feels like every back.

• 23:56Harj Taggar?

  It's, it's a point, it's become a, a popular idea, that is true.

• 23:59Garry Tan?

  We find founders, not ideas.

• 24:01Speaker 00

  I love it.

• 24:02Harj Taggar?

  But AI visibility aside, I guess you, you've gone through the whole journey, like you, you're in the batch, you started a company, now you're running a public company. You know, I mean, I think we would argue the side of just that the start, the advantage the startups have in general is just like they, they don't have an existing customer base, they don't have revenue, they can like, their customers are going to be more forgiving if a thing doesn't work yet. And these have seemed like advantages for like new startups attacking incumbent companies with like an AI product. But from your perspective, what are, what are like, what are the advantages that like incumbent companies have over them? How do you think about it?

• 24:34Speaker 00

  I think the real business has to be downstream of AI visibility. It's a valuable, there's value in it, like, you know, just like there's value in, in the S E O world, but it's so easy to do. You know, we, we did it, you know, as, as I mentioned, in, in, in a, it's probably more like a few months and a few weeks, but we, we did it very quickly. And gave it away for free and it's been this incredible lead generation for us. And so the commoditization is going to happen real, real fast. I mean, you talk about like, you know, people talk about, hey, SaaS going away because of AI, I think that's a great example of it. And so in contrast, if you look at, I think businesses that have done very well here, so like, there is a business, I think, that is very viable here, which is what Air Ops is doing.

• 25:19Speaker 00

  Where they're, yes, they have some visibility aspects, but they have a whole content generation business to help you create blog posts and other material. On that, you know, and, and that's the, that's their real business. And so I think all of these visibility businesses, like you, you can, you can get it for free from us, you can get it, you know, you're going to be able to get it free from a lot of other places. And you're going to have to construct a real business kind of downstream. Maybe to give the flip side of it, like, you know, I, I think innovation in the space is great. You know, it's already moved a lot in the last few months. One of the advantages we have is because we have an existing revenue base of hundreds of millions. We can give away this for free, you know, and just, and that's, that's great. Because, you know, now a lot more people can get visibility without having to, you know,

• 26:04Speaker 00

  go through all the hoops of, of paying a company and get like, you know, tons of, uh, tons and tons of value out of it.

• 26:10Harj Taggar?

  You have like, you, you were Spencer, the founder, like right out of college, started a company. Now you're like public company CEO. Let's say, and so you have all this knowledge from seeing like what things look like at scale. Let's say you went out and started another company again and you were looking at like markets to go into. And you were thinking about like, where, where are markets where you would imagine like, oh, like this incumbent's actually really good. And like, we should just stay away and AI is not going to give us an advantage. And, and which are ones where you'd be like, oh yeah, like actually, no, that's totally vulnerable. And they, they're not going to like, we could really compete with them.

• 26:42Speaker 00

  I, I mean, honestly, I, I joke about this, but anything Google's trying to do, I think that Google is the worst B two B company of all time. And there's an incredible opportunity to compete with them. So, you know, I'd look at email, I'd look at a lot of workspace stuff. I think what the Notion guys, for example, are doing as a competitor, Google Docs is, is very exciting. Institutionally, Google's, Google's way too slow and way too conservative. That to be able to do this. And so it's only when other companies start to innovate that they get their stuff together. You know, same on this coding thing, you know, they, they've proven it can work from a technology standpoint, but bringing it to market, selling it to customers, uh, making it work from a product standpoint, I think is very ripe for disruption.

• 27:23Speaker 00

  Honestly, so we've seen it in coding, we're starting to see in support, we're seeing, you know, we think there's a massive opportunity in analytics that, that we're uniquely positioned for. I think, you know, there's going to be a cursor moment in analytics in the next two years, no question in my mind, where people are going to use analytics with AI. And you're going to be like, why did we ever do it the old way? And I can't even imagine going back. I think there's a lot of very generalized agent builders. And I think picking a particular problem and a particular buyer is going to be a much more successful way of building a business, you know? Yeah, there's a general, you know, there's probably multiple generalized agent builders, every Y C batch now too. And so, um, having a, a strong point of view for a particular buyer that cares about some things.

• 28:08Speaker 00

  Like, one of the ones, um, I saw recently was like, I, I think. You know, there's all these studies being like, hey, enterprise is failing to adopt AI. And if you look at, you kind of dig into the why behind it, there's all these security and compliance concerns. And so, okay, I think there's a huge opportunity to solve those, to get much faster adoption of these products. There has to be a Uber for tech support. When I was in high school, I ran my own IT support business, just helping people around the neighborhood fix their computers. Cause it's like, set my wifi network up, set my printer, you know, whatever. And the fact there's still not a scaled solution, it just blows my mind for this. Like, you have a lot of people that, you know, are older,

• 28:51Speaker 00

  that are not native to technology, that have a bunch of money and want this stuff to be set up. And you have this young generation that desperately needs money, that has a ton of expertise in technology. And so, a business that matches those, that's kind of supply and demand.

• 29:06Harj Taggar?

  I mean, we also spend a lot of time helping people figure out the idea, actually. And obviously, like-

• 29:11Speaker 00

  It's hard. It's really hard. It's extraordinarily hard.

• 29:14Harj Taggar?

  I don't think everyone realizes how Amplitude started out. Could you maybe talk about your journey to actually finding the Amplitude idea and maybe reflections on it a decade later?

• 29:22Speaker 00

  So, before Amplitude, we started this company called Sona Light, which was a voice recognition, I was like, early version of Siri. And it had this really amazing demo, actually, where you could, it listened in the background for your voice. And this was before any of the, hey Siri, hey Alexa stuff. And so, it like, listened in the background on Android phone. And as far as we could tell, we were the first to come out with the technology. We didn't know anything about what made for a successful product or business or company. And we were just kind of taking our shot on that. We were just two kids at a, at a college that were like, okay, what's a problem that seems barely at the edge of possible? Let's, let's, you know, that's probably an interesting place for us to, to go to. You know, and we ended up choosing, choosing voice recognition, not because we

• 30:05Speaker 00

  were passionate about the space. So, we, we did YC with that. We did, went through the whole batch, did demo day, did this amazing demo on stage. We got tons of press written about us. But the product and the tech, it was just not good enough. It wasn't a good enough product. And so, we ended up, right after demo day, deciding to shut that down. And then, we had always built our own analytics in-house, you know, cause like, it's what you do as an engineer. You're always like, I want to build this instead of paying Amplitude money. Because it was very clear to us, the-

• 30:37Speaker 00

  This was the right way to build product. It was you could look at what people did in your product. You would understand them deeply and you could build and iterate on a better product. And so we ended up, and when we showed what we had done in the analytics side to a lot of other companies, they were like, hey, we want this. And so that, right after YC winter 2012 demo day, we ended up pivoting to amplitude. And that was, I think that was June of 2012.

• 31:00Harj Taggar?

  Analytics was a pretty crowded space at that point.

• 31:02Speaker 00

  Extraordinarily crowded.

• 31:03Harj Taggar?

  They did that factor into your thinking about getting into it at all?

• 31:07Speaker 00

  A little bit, you know, and so you have to ask yourself, it's like, okay, why do you think you're different? We knew this was a particularly good problem for, compared to voice recognition, you know, and a lot of this AI stuff, frankly, that was, those were probabilistic problems, so you could not get a right answer. And we were a bunch of algorithms engineers coming out of MIT. And so this problem of how do you, analytics, it seems amazing because it's like, okay, you build this really scaled distributed system and you can get a right answer and it's just about doing it better and faster. That sounds great and amazing in comparison to voice recognition. I think in retrospect, you know, we got lucky that we were particularly suited for that problem. And then the other part of, the other point of view I think I had was that I'd see all these great engineers and these great founders

• 31:51Speaker 00

  who built these amazing pieces of technology, but just did not really understand how to, how to get it in the hands of customers and sell it and all that. So I'm like, okay, I'm going to go fall, I'm going to go all in on learning how to do that. I don't even think I do that particularly well, but just because we were willing to do that and kind of build the next thing and build the next thing and build the next thing, you know, you compound that 10 years later and now you're the leader in the space.

• 32:14Garry Tan?

  Do you have like a method for learning these things? Like one of the things I remember was, um, once you went to amplitude, then it was, you know, B2B sales. And then you got really good at it, but you didn't know anything about it.

• 32:24Speaker 00

  I'm not good at B2B sales, to be clear. I still feel an imposter to this day.

• 32:29Garry Tan?

  But being able to do it at all, like from an engineering background, I mean, and being willing to learn how to do it and realizing like, oh, this is actually my go to market and I have to do it this way.

• 32:39Speaker 00

  Yeah. Analytics, I think in particular, there are some products that you can adopt without selling in that like people just, you know, they have single player mode, you know, cursor is a great example, Slack's a great example, but there's some where you need to convince multiple people at the same time that you're going to go do it and that requires a sales motion. The number one misconception I had was like, this would be something you learn out of a book or on a website or, you know, you kind of read about, but one, you have to do it. And it's like, two, you just want to get someone who's good at coaching you. So we worked with this guy Mitch Morando, who coached, you know, was a sales exec who had gone on to coach a bunch of other companies. And I just happened to randomly meet him through, through Sensor Tower guys, actually.

• 33:21Speaker 00

  And I was like, okay, this is the expert I need, you know, teach me everything you know about sales. He's like, whoa, whoa, slow down. And then he would just come in once a week and just beat me up and just being like, hey, you don't really, you know, what's the customer pain? And I'm like, oh, they want some dashboards or charts. Spencer, that's not a business pain. Like, what's the pain? And so after a while, like finally get the message. It's very much like learning a sport or to play an instrument in a lot of ways. You're not going to do it reading a book. You want to just do it and then get a little bit of advice and coaching on the side. Like, that's the, that's the much, much better approach.

• 33:53Garry Tan?

  I mean, you've said this several times, even in this hour, that, you know, you find certain people who are really, really great. If you could, you know, give your, the 20 year old version of yourself, like the cheat sheet on what you learned about finding those mentors, like are there, you know, is there, is it like, I know it when I see it or, you know, there's a track record or?

• 34:14Speaker 00

  Oof, it's so hard. I mean, I've been extraordinarily lucky and this is one of the great parts of Silicon Valley is there is such a. Positive some help others pay it forward mentality. I mean Mitch was an amazing, Y C is an amazing one. You know, is very clear. I mean, 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. So you first need to be clear on what you're trying to do. 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. And then from there, you know, how you get the, how you get the mentorship or advice may come from a lot of different directions.

• 34:52Garry Tan?

  Can I ask like one more kind of meta question? Hearing you speak about your experience at AmpliTus. It's just really inspiring to me because like you go all the way into the details. You have this capability of like hyper focus. And then I guess like, how do you direct it? Like, how do you know that you're hyper focusing on the thing that, you know, really is the number one thing? Like, do you have like a cycle in the back where you're like, I just, you know, spent 10 minutes thinking about blah. But like, is that actually the most important thing or not? Like, how do you, you know, prevent just like rat holding on something?

• 35:25Speaker 00

  It's hard. One of the things I did before starting a company was getting real clear in my head as to what I wanted to do with my career and why. And one of the takeaways I had was, uh, you know, you want to dedicate yourself to a mission that's greater than yourself. And you'd be part of contributing something larger to humanity. And what I knew how to do was to, you know, build software and sell it. And so I'm like, okay, what's the best way I can do that? You know, starting a company and then from there, it's just, you know, you're like, you kind of, you, the gold, you know, you create a gold tree that that goes down from there. Okay, let's, uh, let's figure out what product to build. Let's figure out how to sell that product, you know? And then it just kind of falls into place.

• 36:09Speaker 00

  I, I find that where people get screwed up the most on that is they are not clear. And by the way, being starting a company, it's extraordinarily emotionally painful. Like I do not recommend it for the vast majority of people. I mean, there's so many times, like every few years I've gotten to a spot where I feel like I want to quit. The business and you feel that deeply. And the best counter to that is I kind of go back to the why, why I kind of came into this business. And so I think.

• 36:38Speaker 00

  If you get that top node really right, you can always kind of anchor or go back to that. You always know, okay, look, if I just continue to see this through somehow, I don't know necessarily how it'll lead back to, hey, I'm gonna create a, you know, build technology and make the world you know, a better place in my own little way. So I just, I, that would be my number one advice for, you know, anyone that that's coming out of school or thinking of starting a company is get really clear on that. I think the worst, I see you, you guys see it all the time, which is like, hey, you know, I'll do it and if it takes off, I'll double down. If not, I'll go back to grad school or a job or whatever. And that's like the freaking worst of this because you have to put up with uncertainty for long periods of time. You have to have all these existential questions hanging over your head. It's, it's, you're not going to get through it.

• 37:23Speaker 00

  Like if you look, one of the big takeaways, like I read founders at work. And one of the really clear takeaways from any of these journeys is 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. Now, not to say, you know, that, you know, there's no guarantees. Getting that, that top node really clear so that you can anchor on it over very long periods of time is the most important I found.

• 37:55Garry Tan?

  Intrinsic motivation.

• 37:56Speaker 00

  Yeah, if you, if you're doing it for like recognition from others or, or, you know, hey, you know, because you're going to get paid a lot or whatever else, you'll, your, your ability to last through is going to be much, much worse than someone else's.

• 38:08Garry Tan?

  I mean, embedded in that, you know, I'm taken by earlier, you were saying like at every point of amplitude, there's sort of a moment where you have to learn how to do something and like grow into that. And then being a public company CEO is one of those things. Walk me through like the, you know, how you started, like the, you know, the intrinsic motivation and now it's like, it feels like you have a really big responsibility on your back. It's like, you know, people look to you for leadership and you know, you were the leader of a great many people and they have families and lives.

• 38:37Speaker 00

  Oh, yeah. Yeah, I mean, they're betting their careers on, on what we're doing here. It's, it's a, it's a, it's a very deep responsibility. As a founder, your job is always to To the most difficult problem in the business and lead from the front. And so if there's an incredibly difficult piece of code, a difficult product or design problem, a difficult customer, you know, a difficult employee problem, whatever, you need to go, the great founders will go headfirst into it and lead from the front and they will rally the rest of the team behind them. Even if you look at the successful founder CEOs, after about a decade, most of them leave. And in my mind, it's actually for this very reason is could be because being a large company executive is different.

• 39:19Speaker 00

  And because you, you, you can't lead by example everywhere, all the time. There are places you can, but you can't do it universally because it's like, okay, you gotta do it in sales. You gotta do it in marketing, you gotta do it in people, you gotta do it on the product, you gotta do it with customers, you gotta do it with the press. It's like the list goes on, there's just too much, you have to be much more disciplined about your time and say no to most stuff. And then what you realize is you become the person you hate. You'd always make fun of big company executives for not doing any work for themselves and just like judging other people's work all the time. But there's a reason for that and you have to embrace that reason. And so it's, it's very hard, that is a very hard thing to unlearn.

• 39:59Speaker 00

  Another thing which still trips me up to this day and I hate, and I try to run amplitude differently, but there's truth to it. It's like hierarchy. There is a reason for hierarchy.

• 40:08Garry Tan?

  Oh yeah, I've learned that the hard way many, many ways.

• 40:11Speaker 00

  You need to have people who own certain things and who are responsible for leading certain teams and other people within the business. It's much easier in my mind, I think, to be a large company executive because you have all these resources and you have all this leverage. You actually work less hard, you're product market fit and you're running, you know, like you're deploying like, you know, we're 350 million in revenue and, and you know, we're deploying close to that in terms of total spend every year. So you have a lot of resources to do stuff. Now you're learning about how do you actually deploy those resources effectively? So, so, so there's levers that you have as a large company executive that you don't as a founder, which is awesome. And you know, but it's a different, very different toolset and a very different set of skills in order to build a business successfully. And that's been the hardest transition by far.

• 40:56Garry Tan?

  I think this will be really interesting next couple of years then, because like sort of this flies a little bit in the face of the most facile view of what founder mode is. Like the most facile view is like, you have to be all the way in the weeds 100% of the time, which is like, obviously not possible when you have 800 employees.

• 41:10Speaker 00

  You can't do it everywhere. You have to be clear on where you're doing it.

• 41:13Garry Tan?

  Yeah. So there's just like a lot more nuanced.

• 41:16Speaker 00

  Yeah.

• 41:17Garry Tan?

  How to do it.

• 41:17Speaker 00

  Yeah, I mean, you know, it's one of these like, you know, there's like a million management books about this thing. And, you know, they kind of all try to abstract it into some framework and it's none of them are really right. You go through it and experiencing yourself and get coaching from others who do. And that's how you end up figuring it out. But that that transition to large company executive, that one's a really hard one.

• 41:35Garry Tan?

  Well, in the immortal words of Bob Marley, one good thing about product market fit is when it hits, you feel no pain.

• 41:41Speaker 00

  Oh, yeah.

• 41:43Speaker 00

  Growth sells all problems.

• 41:44Garry Tan?

  And then hopefully people watching this will actually get a chance to experience some of the problems that you get to live on a daily basis.

• 41:50Speaker 00

  Absolutely. One of the things I'm actually very appreciative, Gary, that you and PG and Jessica and others are doing is just helping people tell these later stage stories. One of the things I think Y C has done exceptionally well is like, you know, to the extent you can have a playbook for what is like the early stage stages. You guys have, you know, written and talked about it and and made everyone out there aware of it. So they they know what the path is and what it looks like. Still incredibly hard, but you know, now it's like, okay, you at least has some guidance. It doesn't exist for a lot of the later stage stuff as you grow up. So I'm very appreciative that that you guys are building that.

• 42:26Garry Tan?

  There's levels to it, but thank you for sharing your levels.

• 42:29Speaker 00

  No, of course.

• 42:29Jared Friedman?

  Do you feel like we could turn what you did with amplitude into the playbook for how SaaS companies should reinvent themselves in the AI era?

• 42:35Speaker 00

  You know, I still feel like an imposter on this thing to this day, but I'm very happy to contribute. You have to get very judicious with your time. There are a lot of people who want your time, you know, and you could spend infinite time within people in the organization with customers, with, you know, partners, with, you know, investors, whoever. And so you have to think about like, you're like, no one owns your time, but you as a founder, you're just like, nobody cares. And so you're just desperate for anyone to give you attention. So if they do, you're like, okay, this is great. But as you know, large company, it's like, no, no, no, like you have to be very, very judicious. One of the things I am deliberately trying to do is just be more out there and vocal. So you see it on Twitter, you see it, you know, I'm just trying to be unfiltered. There's still, you know, there's still an aperture you're constrained to as a public company CEO, but most are just so conservative. They're not putting anything out there.

• 43:20Speaker 00

  And so, you know, I'm at least trying to kind of share my story, put it out there, put my hot take. On you know, politics, politics, religion, whatever, you know, products, companies out there. So at least, at least others, you know, can can learn and benefit from that, too. And honestly, it's like, it's just who I am. You know, ultimately, I want to be able to express who I am. I don't want to argue with people on the internet. I don't want to have to be this other persona that that I'm not, you know, or try to represent something I'm not, you know, if I believe and I have conviction in something, I want to be able to say it.

• 43:48Garry Tan?

  Spencer, thank you so much for spending time with us. This is super illuminating and can't wait to see Amplitude AI, the new resurgence coming into every company in the world.

• 43:59Speaker 00

  There is going to be a reinvention of analytics in the next few years. And, you know, we, we want to be the ones to go lead it. So thank you, guys.

• 44:06Garry Tan?

  You heard it here first. We'll see you guys next time.