00:15:29 · Aditya Agarwal, Waseem Daher
[00:15:29] S1: Yeah, one of the things that I find hardinteresting about listening to people I admire is that they all often offer contradictory advice, particularly around startups. Everybody seems to have some set of things that they believe have led to essentially a place that you admire. And so I think a lot of the actual journey in starting a company is one of self discovery, right, which is then being able to map like, who am I and what works best for me? Right? And then being able to find the people that you also remind, like, this person actually seems to be cut from similar cloth. Because otherwise, it's very easy to get inundated because... And if you really do them... Like, if you kinda go out and canvas, there's a lot of contradictory advice about, like, early stage ideation, early stage philosophies. So I'm often, like, more kinda seeing, like, what resonates with me, what actually maps to my world beliefs. So it sounds like you're a man of action. [00:16:28] S0: I like that phrasing. I'll take that. [00:16:30] S1: Okay, all [00:16:30] S0: yes. But I agree with you. I mean, there's some tweet, and I don't know who sent it, was like, the entrepreneur's advice is like, these are the numbers that helped me win the lottery. It's like, yeah, okay, cool. It's not like... That's not that actionable for me. I might [00:16:45] S1: steal that one.
00:16:45 · Aditya Agarwal, Waseem Daher
[00:16:45] S1: steal that one. [00:16:46] S0: That and like, this advice is kinda worth what you're paying for it, which is everyone's advice is sort of an imperfect distillation of what they thought worked for them, which it may or may not actually be like what it really did, and I have been surprised, even just in reviewing my own notes, how much revisionist history I have about the world. [00:17:08] S1: Yeah. I mean, I think that it's actually really hard to go back. So I famously, my team is, they don't love me for this, but I hate post mortems because you're trying to go and relitigate a decision that was done in the past. But my firm belief is that it's actually very hard to go and re litigate it using the exact context window that you had at that point in time. So, we can try to re litigate it using new decisions. But trying to go and literally the question is, how would I have done it differently? I'm like, that question doesn't make any sense to me. Right. Because I'm no longer that person. So, we can choose to how would this decision look different today. But that's a very different question than relitigating something that happened in the past. But with that framing, I'm curious, what are some of these things that you have learned about yourself as an entrepreneur and your ability to navigate the mine is one that you might be different today or might be different when you started Pilot relative to when you started, let's say, Ksplice?
00:18:10 · Waseem Daher, Aditya Agarwal
[00:18:10] S0: So what evolved in our thinking across these three startups? I think one is we were much, much more attuned to market size, which is in the first company, again, it was just like, oh, this is cool. Let's do it. In the second company, it was like, this is a problem we have, and this seems like the world needs this, and it seems big enough. Let's do it. And then with Pilot, I think it was much more like, okay, well, actually, the TAM here is like every small business in The United States, and they all need accounting, and they need tax prep, and they pay a lot for it, and, you know, you multiply the numbers, and, like, the numbers are very big. The TAM is, like, functionally infinity. Like, we spent a lot more time kind of pressure testing against that as opposed to literally for Case Plus, it was like, this seems cool. Like, let's go do it. I think that was correct if your objective is to build a venture scale business, which was our objective. Like, in some ways And you have. And we have. And in some ways, like... One of the, like, maybe not as noble motivations for doing Pilot was a little bit like, you look around, you see, like, these other unicorn or public company CEOs, and you're like, yeah. They're smart, but, like, they're not they're not smarter than we are. [00:19:23] S1: Like, you know, I'm like, we
00:19:23 · Aditya Agarwal, Waseem Daher
[00:19:23] S1: Like, you know, I'm like, we [00:19:24] S0: can do this. Like, I mean, if they're doing it, like, we can probably do it. So there's a certain amount of, like, we chip on our shoulder about that too. And it's like, obviously, that's an input too of, like, okay. Fine. What kind of thing do you wanna build? Because the other path... And this is now, like, more in vogue, and I think, you know, in 2017 when we started Pilot, it was not. It was like, well, you build this thing that's super small, and you don't take a ton of capital, and you have huge ownership. And actually, that probably maximizes dollars in your pocket, but it's a very different shaped thing. [00:19:52] S1: It's interesting. Yeah. So by the third company, you were thinking a lot about markets from day one. Yes. And less about, is this fundamentally something cool? Is this something that is flashy? It's like, hey, I just don't want to take market risk. [00:20:08] S0: Yeah, I think we believed that basically that the technical risks were extremely surmountable by our team because it was just a very, very strong technical team, on almost any domain. It was like, fine, so what are the things that we really need to derisk? What is the market opportunity, and what is the market risk? [00:20:26] S1: What do you think is the biggest market opportunity today?
00:20:26 · Aditya Agarwal, Waseem Daher
[00:20:26] S1: What do you think is the biggest market opportunity today? [00:20:31] S0: Oh, I don't know. I mean, I think that, like, our thesis when we started Pilot in 2017 was this, like, tech enabled services thesis. And at the time, I think it was, like, fairly contrarian. Now, I think it's a pretty consensus view. But very clearly, is a bunch of stuff that today is services that will become done by tech companies, and with all the margin expansion that will come from that and all the TAM expansion that will come from that. [00:20:58] S1: Maybe to ask it another way, it's interesting, right? Pilot's timing is interesting, which is that you're totally correct that back when you first started, probably the biggest question that you got was, is this a services company or is this a tech? Mean, we've spent a long time talking about this, right? Definitely. Today, it's obvious, right? It's like, yeah, of course, AI is going to make these essentially knowledge workers. You'll have knowledge workers who are operating at 1X. Maybe five years ago, the best ones were 3X to 4X. But now you can have people operating at 20x, 30x, with the right set of tooling, right set of essentially LLMs in the loop. How does one capitalize on that almost market realization given that Pilot has also been around for nine years? So how do you, in some ways, not be too early?
00:21:44 · Waseem Daher
[00:21:44] S0: And I think we were a little too early. Okay. Which is... I mean, obviously, we were the right amount of early. We were not too early. We, like, are in in prime position to take advantage of all the new stuff that's coming out, like all the capabilities that are available via LMs. And our thesis was the computer has always been the computer is eventually going to do 99 of it. And I think in 2017, had you asked me, would have said, well, deep learning, neural nets, because that's what everyone talked about back then. But it's like there was a very clear path from the computer does none of the work, which was the status quo at the time. Even if you got the computer to do 70% or 80% of the work, that's still tremendously impactful. And I think the thing that LMs have unlocked is like, well, fine. Now it's probably not 80%. It's probably 95%. Maybe it's 99%. It's like, Okay. But that's like a difference of degree rather than a difference of overall capability in this specific domain. And I think for us, it's like, okay. Well, when this stuff becomes available, you sort of have to lean into it. And then you also need to be kind of thoughtful about, like, well, what is the moat or, like, what is your defensible kind of advantage? Like, every single Y Combinator batch for the past eight plus years has had, like, an AI accounting company in it. At least one. It's just, like, literally every batch. It's like, someone's like, we should do AI accounting. No one's doing AI accounting. Or I don't know. I guess we think we can do it better than Pilot. And there's a certain amount of just... You kinda just, like, wait it out. Yeah. Like, actually, there are real advantages to brand and size and scale and, like, install base, and there's a bunch of, like, hard learned lessons that we've had to contend with that, at first blush, you don't see. So there is a little bit about you kind of just have to outlast the other people in the space.