A Product Market Fit Show | Startup Podcast for Founders
00:25:12 · Pablo Srugo, Dylan
[00:25:12] S1: Do you remember some of the first use cases, some of those first customers, what their use cases were or maybe even one of the first things you remember where you were like, wow, we're powering this application. This was what we've been building towards. [00:25:25] S0: Yeah, so one of our first customers was building this product where they were analyzing TV and radio stations 24/7 and then they were looking for certain brand mentions that were spoken and alerting those brands when their names were mentioned. That was one of the first customers we had and they actually found out about us on Hacker News. The CTO reached out and they checked out our API and they liked it and they built this product with it. Then there were a few others. Some of the initial customers were in the call center space, so analyzing customer support calls to create insights. There were some voice agent, like voice bot applications in the early days too. You're seeing a lot more of those now, but primarily in the early days it was media contact center type use cases. [00:26:17] S1: Based on Crunchbase, what I see is you raise this YC thing, you raise this million-dollar round, and then the next thing that's listed at least there is 2020 raised $50 million. What happened between? Was there a smaller, a C+ or a series A or something that bridged that gap? [00:26:32] S0: Yeah, so we raised a million dollars after YC in 2017. Then I think it was right after COVID, it was the summer of 2020, we raised a $5 million round and that was also from angels. It was Daniel Gross, Nat Friedman.
00:26:32 · Dylan, Pablo Srugo
[00:26:32] S0: Yeah, so we raised a million dollars after YC in 2017. Then I think it was right after COVID, it was the summer of 2020, we raised a $5 million round and that was also from angels. It was Daniel Gross, Nat Friedman. [00:26:49] S1: What was traction like at that point? [00:26:51] S0: We had passed a million dollars in ARR. We had decent traction at that time. We were growing pretty quickly and we're still a super small team. I think we were sub10 people. Then it was a year and a half later that we raised the A and then a couple months later our B and then most recently our C. The 2020 is really when things started to compound and the trajectory really changed. [00:27:16] S1: What do you attribute that to? Was that just basically the stack getting good enough, getting over that bar where all of a sudden people could just build all these applications on top of? [00:27:24] S0: Yeah, it was a combination. It was macro, market adoption, matured in part because the tech was getting better, right? As the tech gets better and early adopters demonstrate its capability out in market that pulls the market forward and then more people adopt. That's just been happening. Then of course 2022, this whole… [00:27:46] S1: Gen AI wave.
00:27:46 · Pablo Srugo, Dylan
[00:27:46] S1: Gen AI wave. [00:27:47] S0: All this innovation has just taken that market adoption and accelerated it more than I think anyone could have imagined even 18 months, two years ago. It's hard to remember beginning of 2023, there's one mainstream LM, and now there's thousands and there's open-source models and there's tons of companies in this space. This acceleration we're in the middle of is very new, but I think it will continue to be honest. [00:28:14] S1: Perfect, well, let's stop it there. Let me just end with the two questions that we always end on. The first question is, when did you first feel like you had true product market fit?
00:28:14 · Pablo Srugo, Dylan
[00:28:14] S1: Perfect, well, let's stop it there. Let me just end with the two questions that we always end on. The first question is, when did you first feel like you had true product market fit? [00:28:23] S0: It's interesting, right, because for us, I knew that there was market demand even before we started building the thing, whereas with a lot of companies you don't know, hey, are people going to want this service or is there going to be product market fit for this type of product or service? For us, similar to self-driving cars, you know that Level 5 self-driving cars will have product market fit even though they don't exist yet. Now, of course, if they cost a million dollars per vehicle, the addressable market is probably much smaller versus if they cost $10,000 or if there were just robotaxis everywhere. There is a question of economics, but there's not a question of market demand, unit economics, but not market demand. For us, I always had conviction that there was market demand and product market fit for what we were building. That being said, I think that, we serve many different use cases, so we have people building so many different types of things with our API. There's still opportunity for us to improve product market fit for what people are predominantly choosing to build. That's really the work right now. I would say it never stops because the market's changing what customers want to do and users want to do is always evolving, but I always had conviction that there was product market fit for what we were building.
00:28:23 · Dylan, Pablo Srugo
[00:28:23] S0: It's interesting, right, because for us, I knew that there was market demand even before we started building the thing, whereas with a lot of companies you don't know, hey, are people going to want this service or is there going to be product market fit for this type of product or service? For us, similar to self-driving cars, you know that Level 5 self-driving cars will have product market fit even though they don't exist yet. Now, of course, if they cost a million dollars per vehicle, the addressable market is probably much smaller versus if they cost $10,000 or if there were just robotaxis everywhere. There is a question of economics, but there's not a question of market demand, unit economics, but not market demand. For us, I always had conviction that there was market demand and product market fit for what we were building. That being said, I think that, we serve many different use cases, so we have people building so many different types of things with our API. There's still opportunity for us to improve product market fit for what people are predominantly choosing to build. That's really the work right now. I would say it never stops because the market's changing what customers want to do and users want to do is always evolving, but I always had conviction that there was product market fit for what we were building. [00:29:33] S1: Final question, if you could go back to when you were just starting Assembly AI back in 2016, 2017 with one piece of advice for yourself, what would that be?
00:29:33 · Pablo Srugo, Dylan
[00:29:33] S1: Final question, if you could go back to when you were just starting Assembly AI back in 2016, 2017 with one piece of advice for yourself, what would that be? [00:29:42] S0: I would have advised myself to take a longer-term view in the first year, especially coming out of YC. Slow down. Now that you're done with YC, what do you want to accomplish over the next two years? Where do you want to be in two years and then just work towards that. I think, like I was mentioning earlier, coming out of YC, you're trained within those 90 days to just be like, the clock is ticking, the clock is ticking, the clock is ticking. You're always thinking that when you're running a startup because there are macro factors, right? Other people are competing in the same space. You can’t just operate on your own timeline. I would have given myself, urged myself to take more permission to think longer term about what I want to have accomplished within a year or two years and then break that back down into quarterly goals and use that as a foundation of hiring and prioritization versus trying to just make quick progress as quickly as possible. [00:30:40] S1: Perfect, well, thanks a lot, Dylan. I mean, you're now one of the leading companies in what is probably the hottest sector. Really appreciate you taking us through the early days and what it took for you to build what's now having so much success. Appreciate you jumping on the show. [00:30:55] S0: Yeah, thanks for having me on. Appreciate it.