What Founders Have To Unlearn To Become Great CEOs

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 on the next few years, and, you know, we we wanna be the ones to go lead it.

Welcome back to another episode of the Lite Cone. Today, we're really excited to be joined by Spencer Skates, CEO and cofounder of Amplitude. So Amplitude went through YC in winter twenty twelve. 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.

Absolutely. Good to see you here, Hajj.

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. They don't want to build the products.

People got mad at you

for that? Yeah, people were 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?

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 I'll just tell you the 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 I think, you know, to just to defend the skeptics for a second, I think I I remember being in a board meeting once. You had, like, you know, all these, like, board investor finance people, and you had all these salespeople who were like, hey, Shouldn't you look at this AI thing?

Like, isn't that getting hot? Shouldn't you guys do it? And it's What's like

your AI strategy?

Yeah. Exactly. Exactly. Yeah. Actually, that literally was a question, like, from one of our execs to me.

It's like, we gotta get our AI strategy. What's our AI strategy, Spencer? And I'm this is the wrong way to think about what it is we're doing. It's like, if you guys think it is you guys think you can figure it out, go do it. And I remember one of my cofounders, Jeffrey, actually was the most frustrated because I think he saw a lot of grifting happening in AI being like, 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 it's just gonna totally reshape how we're building products and shipping them and how our customers are using them.

But the the reality was if 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 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 what stuff falls in what buckets. Like, yeah.

You should do more of this AI thing. It was very that was frustrating. And so I think there there's frankly skepticism on my part. There's there's skepticism on the part of of my co founders and and some of the broader team with an amplitude about what was actually gonna be possible with it.

But something changed.

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, ClaudeCode, 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.

And 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 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 YC 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 smartly trigger guides to end users just based on if they were confused. And they, you know, created this chatbot that very much like an intercom fin that would, 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. I mean, 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. But 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 change pretty quickly. It's still taken us a full year to get the team kind of fully on board and ramped and believing and seeing and building. ChatGPT launches, AI starts taking off.

And it sounds like your investors and board members and maybe people who aren't in the day to day up sort of, hey, what are doing with this AI thing? What about the They rent about

it in TechCrunch or something.

Yeah, exactly. Yes, exactly. Exactly.

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?

There were a few people that were kinda testing out ideas, but I I think we're so focused on our regular motion. Like, we were coming out with a lot of other products outside of analytics. We were doing know, you we launched experimentation. We were building session replay internally. We're building this thing activation, which targets your users based on their behavior.

And so there 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 and there's this revenue that's just sitting here if if we go build these things. You know, there are a few folks that were messing around with it, and there there were some people that had used Cursor and other things.

But the the the organization as a whole did not have it's not like it was conscious and aware of this change, this 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 to embrace. By early twenty twenty five, 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

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

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, ten years out, if if, you know, if even that close. And one of the things that is 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, 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 gonna have to train the 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 what we do is we train the team. We had our like, one of our product leaders, you know, vibe code like a dark mode for Amplitude in front of the entire organization. It was actually very scary, but actually, it it happened you know, they ran into a bug, but they'd happen 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, 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. So step one was actually not like, here's what we need to build at Amplitude with AI.

Yes.

And forth in and believing in them.

This is the core difference between building product in 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 gonna 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. They can tell you what they want. 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 gonna be able to describe what's possible.

Give me a faster horse.

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.

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. The thing 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 company. I really wanna use this tool and it's like the companies are resisting saying well it's not tested yet, it's not safe. But it seems to be a more common pattern with AI that it's going the other way.

Yeah, it's tops down.

Yeah, why do you think that's happening?

I mean, it's gonna sound extraordinarily reductive, but I think Sam Altman is the best salesperson 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, investors already bought in, executives are bought in, know, world leaders are bought in, like, you know, as a society, you know, 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. 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 are there yet.

And so this is why, you know, you had a lot of frustration. You know, in Amplitude as a case study, had 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 it's not till the last year that, you know, okay, hey, think the capabilities are here for it to transform the the business that that we're in in analytics.

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

Yes.

And there's a story of the transformation with case tags. We're just founder led to do that transformation. Sounds like this is what's going on with Amplitude two is coming from from you.

Absolutely. So I've had to learn over the last ten 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 Giuri, who's incredibly excited. You had one of our engineers, this guy named Liu Zhang, who built AI visibility. And he just wanted to He was actually going to leave Amplitude to start a company. And we're like, look, just come here, stay here, learn how to do this while getting paid, and we'll teach and coach you. And then, you know, we'll fund whenever you do go something.

And I didn't want him to do AI visibility, but he was like, oh, I think that there's a huge opportunity here 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 product launch doubled new sign ups to Amplitude, which is wild, You know? Like, every week, it's like we're getting twice as many sign ups to our free plan as we did from before our AI visibility launch, all the way to what we're going to be launching in January, which is we're going to launch a what we're going to call Ask AI, which is a global chat interface, very much like Cursor, 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 all been very bottoms up, and then it's about, you know, for me and for Wade, to sculpt, Okay, how do we set these up in the organization for success?

So not many large companies like yourself have been able to do this transformation. Lot of them are

still hard.

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?

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 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 Craftful team and Jana, who's been phenomenal.

And we brought in Eric and Frank from Inari. We brought in also a YC company. We brought out Enzo and Ferruccio from June, also I think YC company. Yeah. So we brought in all these great YC founders, and then kind of melded them with a lot of longtime ampleteers.

And that combination has been very, very special.

What are the specific differences? For people who are really successful, think especially engineers, who are successful in sort of pre AI SaaS world, kind of grew up in that environment, and then you compare, what are sort of the things that they're, I don't 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 are like AI native engineers and believe in it deeply.

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

Is it 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, kind of I don't know. It feels very cliche to say, but 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 previous 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, starting with questions and you're not seeing your data, that 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 gonna create something amazing.

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 realized 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 three, 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 b to b SaaS and or building, you know, sort of standard web two point o software, 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.

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 moved 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, okay. Well, hey.

We'll 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 b to b companies are figuring out.

Speaking of things that you have to give up in order to do this, what happened to the existing Amplitude road 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? Only, 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?

It's not like there's there's totally separate products. Like, the goal of, for example, 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 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. Like, you know, for example, one big thing that we're gonna be coming out with in session replay in the next few months is zoning, which is this way where you can look at a web page 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 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 big change we did organizationally is we had a lot of 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. But the existing team is still gonna do you know, work on making the Amplitude product great, and that work is is is just as important.

Because I I I think the timeline for change in the business world is the cycles are just much, much, much longer.

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?

No. You know, I think by doing the AI week and 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 got to focus in.

Let's say no to some of these 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 gonna be awesome. So, yeah, people will naturally kinda self select in or out. And it's a 200 person org, so you get a whole spectrum of this.

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

Yeah, which one?

I think, yeah. That's a problem. Think it was the AI visibility treat, I think like generally, I think you were making the point that, the, a lot of these startups are sort of like features, not companies. And obviously like at YC, we're going take the other side of it.

Hell

yeah. And I would argue that-

You guys have a have a visibility company that fills like every batch. Yeah.

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

We find founders not ideas.

I love it. But AI visibility aside, I guess you you've gone through the whole journey. Like, you were in the batch. You started a company. Now you're running a public company.

I think we would argue the side of just that the advantage that startups have in general is just they don't have an existing customer base, they don't have revenue, their customers are gonna be more forgiving if the 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, are, what are like, what are the advantages that like incumbent companies have over the business? Do you think about it?

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 the SEO world. But it's so easy to do. You know, we did it, you know, as I mentioned, probably more like a few months and a few weeks, but 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 AirOps is doing, 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 that's their real business. And so I think all of these visibility businesses, like, you can get it for free from us. You can get it, you know, if you're gonna be able to get it free from a lot of other places, and you're gonna have to construct a real business kind of downstream. And 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 and just and that's that's great because, you know, now a lot more people can get visibility without having to, you know, go through all the hoops of paying a company and get like, you know, tons of, tons and tons of value out of it.

You have like, 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 are markets where you would imagine, like, oh, like, incumbent's actually really good and, like, we should just stay away and AI is not gonna 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 gonna like, we could really compete with them.

I I mean, honestly, I I joke about this, but anything Google's trying to do, I think that Google is the worst b to 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 to 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, making it work from a product standpoint, I think, is very ripe for disruption. Honestly, so we've seen it in coding. We're starting to see it 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 gonna be a cursor moment in analytics in the next two years, no question in my mind, where people are gonna use analytics with AI, and you're gonna 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. Know, yeah, there's a general you know, there's probably multiple generalized agent builders every YC batch now, too.

And so having a strong point of view for a particular buyer that cares about some things. Like one of the ones I saw recently was like, I think there's all these studies being like, hey, enterprise is failing to adopt AI. And if you look at, you kinda 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. Because it's like, set my Wi Fi 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, 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. I mean, we also spend a lot of

time helping people figure out the idea, actually, and and obviously, like

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

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? So before Amplitude,

we started this company called Sonolight, which was a voice recognition. It was like an 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. As far as we could tell, we're 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 kinda 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 That's probably an interesting place for us to go to. And we ended up choosing voice recognition, not because we were passionate about the space.

So 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. Know, because like, it's what you do as an engineer. You're always like, I wanna build this instead of paying Amplitude money. Because it was very clear to us this was the right way to build product.

It was you would 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, were like, hey, we want this. And so that, right after YC Winter twenty twelve demo day, we ended up pivoting to Amplitude. And that was, I think, was June 2012.

Analytics was a pretty crowded space at

Oh, that extraordinarily crowded. Did that factor

into your thinking about getting into it at all?

A little bit. 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 this AI stuff, frankly, that 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 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 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 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 gonna go full I'm gonna 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 ten years later, and and and now you're the leader in the space.

Do you have, like, a method for learning these things? Like, one of the things I remember was once you went to Amplitude, then it was, you know, b two b sales, and then you got really good at it. But you didn't know anything

about I'm not good at b two b sales, to be clear. I still feel an impostor to this day.

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.

Yeah. Analytics, I I think in particular, there are some products that you can adopt without selling and that, like, people just, you know, they have single player mode. You know, Cursor's 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 gonna 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 book or on a website or, you know, you kinda 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've coached, you know, as a as a sales exec who had gone on to coach a bunch of other companies. And I just happened to randomly meet him through through the Sensor Tower guys actually. And I was like, okay, this is the expert I need.

You know, teach me everything you know about sales. He's like, woah, woah, 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, it'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 gonna 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.

I mean, you 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?

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's such a positive some help others pay it forward mentality. I mean, Mitch was an YC is an amazing one.

You know, it was 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 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.

Can I ask, like, one more kind of meta question? Hearing you speak about your experience at Amplitude is just really inspiring to me because, like, you go all the way into the details. You have this capability to, like, hyperfocus. And then, I guess, like, how do you direct it? Like, how do you know that you're hyperfocusing 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 ten 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 holing on something?

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, 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 kind of the goal, you know, you create a goal tree that goes down from there. Okay, let's figure out what product to build. Let's figure out how to sell that product. You know? And then it it just kinda falls into place.

I 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, 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 wanna quit the business, and you feel that deeply. And the best counter to that is I kinda go back to the why of why I I kinda came into this business.

And so I think if you get that top node really right, you can always kinda 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 and make the world a a, you know, a a better place in my own little way.

So I I just I 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 I see you guys see it all the time, which is like, hey. You know, I'll do it. And if it takes off, I'll 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 gonna get through it. Like, if you look one of the big takeaways like, I 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.

Intrinsic motivation.

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

I mean, embedded in that, you know, I'm taken by earlier you're 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 then 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 you know, you were the leader of a great many people, and they have families and lives.

Oh, yeah.

Know, hopes

and Betting their careers on Yeah. On what we're doing here. It's a it's a it's a very deep responsibility. As a founder, your job is always to run 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 head first into it and lead from the front, and they will rally the 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 because because being a large company executive is different. 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. Gotta do in people, you gotta do it on the product, you gotta do it with customers, you gotta do with the press. In fact, 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 this very hard that is a very hard thing to unlearn. 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, is like hierarchy.

Mhmm. There is a reason for hierarchy.

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

many 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, you have all this leverage, and you actually work less hard. You get product market fit. You're running you know, like, you're deploying, like Yeah. You know, we're 350,000,000 in revenue, and and, you know, we're deploying close to that in terms of total spend every year.

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 leverage that you have as a large company executive that you don't as a founder, which is awesome. And, you know, it but it's a different very different tool set and a very different set of skills in order to build a business successfully. And that's been the hardest transition by far.

I think this will be really interesting next couple 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 a 100% of the time, which is like obviously not possible when you have 800 employees.

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

So there's just like a lot more nuance to

how to

do it.

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 experience it yourself and get coaching from others who do, and that that's how you end up figuring it out. But that that transition to large company executive, that one's a really hard one.

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

Oh, yeah.

Oh, yeah.

Oh, yeah. Gross sell

down problems. 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.

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 YC's 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. It's still incredibly hard, but, you know, now it's like, okay. You at least have some guidance. Doesn't exist for a lot of the later stage stuff as you grow up, so I'm very appreciative that that that you guys are building that.

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

No. Of course.

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?

You know, I still feel like an impostor on this thing to this day, but I 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 know, 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. 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 unfilled. 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. And so, you know, I'm at least trying to kinda share my story, put it out there, put my hot takes on, you know, 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 I wanna be able to express who I am. I don't wanna

have Argue with people on the Internet.

I I I don't wanna 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 wanna be able to say it.

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 Hell yeah. Every company Hell yeah. In the world.

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

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