Investors Don't Make Your Product Better | AssemblyAI, Dylan Fox

1. 0:00 – 0:58

   Intro

   1. DFDylan Fox0:00

      As a founder, you just have this instinct for some market. That's the hard thing about being an entrepreneur, being a founder is, like, most people are not gonna believe in what you're trying to do until all of a sudden they do. I loved the idea of the product that we were building. As long as I feel really happy about the customers that we have and they're happy, then that's, like, the validation I'm in search of. You have to just, like, stay the course and keep going and keep showing up even if, you know, it's hard and even if you have doubts and moments. You just have to, like, keep going. My name's Dylan Fox. I'm the founder and CEO of AssemblyAI. We've built the industry's most accurate and easiest to use developer platform for speech AI. We've raised over $130 million in funding to date from Accel, Insight Partners, Daniel Gross, and Nat Friedman and Smithpoint. That's led by Keith Block from Salesforce.

2. 0:58 – 3:23

   One Bowl of Pasta, Seven Days of Code

   1. DFDylan Fox1:04

      My older brother, he would order all the hardware online, and he would, you know, be in our basement making computers, and I would watch him. And being around computers as a kid, playing video games, I was addicted to these MMORPG games. I love just working on technology. So in college, I started this company that helped other college organizations fundraise online. And people that donated to the stor- student organization would get, like, local rewards in their community. It was a terrible idea [laughs] and, and it was, you know, it didn't go anywhere. But we learned a lot about starting a company and being a founder through that experience. What I learned from that experience was that I loved being a founder and I loved programming. And with programming, it wasn't so much the programming that was addictive. It was just this open-ended world that you could just build stuff. Any idea you had with programming, you could make it into something real, and then you could get feedback from users, and you could then keep building and keep building. And so it was this process of, like, building something that I found just so addictive. So after college, I didn't get a job. Uh, we had shut the startup down. I just opened up a bunch of credit cards, [laughs] and I went, like, $30,000 into credit card debt, basically just, like, learning how to program and, like, reading programming books and building apps and just, like, all day that's what I would do in my apartment. And I would make, like, one big bowl of pasta every Sunday and just, like, eat that all week with Diet Coke as I was just, like, spending all day just programming and building stuff and seeing if I could launch anything new. After, you know, almost two years of doing that and going into credit card [laughs] debt, I was like, "Okay, I need to go get a job." But I had found that I was really most interested in machine learning and natural language processing. And so there was a team in San Francisco at a company called Cisco that was hiring for machine learning engineers to focus on building natural language processing products and interfaces around Cisco's collaboration products. Got really into neural networks and more advanced machine learning and deep learning while I was out there at that job, and that was, like, 2015, 2016 time.

3. 3:23 – 5:12

   Why I Became Interested in Voice AI

   1. DFDylan Fox3:24

      When I, when I got the job at Cisco and I knew I always wanted to start another company, I'd always spend nights and weekends just still tinkering with random ideas I would have. And I think the Alexa launched around the time I was in Cisco. So the Alexa product was, like, the first computer you could talk to. And I as a machine learning engineer that was working in natural language processing, I wanted to start experimenting with my own ideas for voice interfaces or voice products, voice-driven products. And the leading company at the time that was building that technology was this big company, and I contacted them to try to get access to their developer SDK, and they mailed me a CD-ROM. It was, like, a $10,000 evaluation agreement that you had to sign. I didn't even have a CD-ROM drive to, like, load their SDKs. It was just this complete archaic experience as a developer. I really wanted this super accurate, really easy to use developer platform because I saw back then that the technology was gonna just get orders of magnitude better, and that was gonna make what was a small market huge. That was a really exciting thing that I just wanted to build and work on. As a founder, you just have this instinct for some market, and that's what gets you excited about working in that market or building in that market. And so for me, that instinct was voice interfaces and speech AI technology. That is one of the most important modalities for AI. And so we're really excited about that potential, and especially that potential to create really accurate and amazing AI for speech and voice, and then just put it into the hands of developers to build really creative stuff with and really amazing apps with.

4. 5:12 – 7:16

   No Product, No Customer, Still Got into YC

   1. DFDylan Fox5:17

      I left my job, and then a few months later got into Y Combinator. I had no clue I was gonna get into Y Combinator. I just wanted to submit the application as really a thought exercise to, like, crystallize what I was working on, what I was gonna do. You know, I figured, like, no chance I'm getting in. Alone, no progress, no traction, no product, just an idea. But there was a YC partner at the time, Daniel Gross, who had worked at Apple, had worked around Siri. Got an email. It's like, "Hey, what's your accuracy rate?" Fr- [laughs] from Daniel. And then the next day they were like, "Hey, we'd love you to come in for an interview." And so I bought a ticket home. I flew back to San Francisco where I was living at the time. The next day drove down to, to Y Combinator for the interview, got in. And I had submitted the application, it was like 30 days late past the deadline. I went in the first day, and it was like all these other companies had so much progress, so much traction, and I was just getting started. And it was a really hard idea to get started with, like, creating AI models for speech. That was probably one of the most stressful periods of my life [laughs] was, like, those, those three months in YC where I was just, like, really trying to get things off the ground, working mostly by myself. A lot of founders think that getting into Y Combinator or raising capital is, like, just gonna make things happen. It doesn't. No investors are gonna hand you customers, make your product better, fix things. You still have to make everything happen. So we just again, like, showed up every day and just tried to make progress and just, like, kept at it. I've really just tried to focus on is, like- As long as I feel really happy about the product that we're making and the customers that we have and they're happy, then that's like the validation I'm in search of is, do I feel happy about our product? Are customers happy? Like, those are the things I try to get validation from, not what do other people think about our company or what we're doing.

5. 7:16 – 8:19

   EO Partner Highlight

   1. SPSpeaker7:16

      [upbeat music] As a founder, you already know ideas are the easy part. It's the execution, actually building the product, that slows everything down. That's where Lovable comes in. It's not just an AI tool, it's your on-demand engineering team. Simply describe your idea. Lovable then builds a full front-end, back-end, and database so you can launch real production-ready software without writing code. It's already powering over 100,000 new products a day, helping 2.5 million builders turn ideas into software just by describing what they want. No devs, no delays, no excuses. They're launching in weeks, not months. And guess what? These teams are still tiny. In fact, team EO is also using Lovable to build our upcoming EO School platform, and we're loving it. If you're a non-technical founder or just want to build without bottlenecks, try Lovable today for free. Use the promo code EO20YT to get 20% off your first purchase of the Lovable Pro plan.

   2. DFDylan Fox8:17

      [gentle music]

6. 8:19 – 10:07

   How a Startup Wins with Deep Subject Matter Expertise

   1. DFDylan Fox8:23

      Most of my day is spent talking to customers, working with our product teams, playing with our product, and seeing where it's working and where it's not. Founders and, and startups, you really need to have this deep, deep subject matter expertise in your market and in your customers, in your product. I think in a lot of ways it's like undervalued and underappreciated versus functional expertise. Don't always have a lot of confidence in your functional expertise, and I think that's where startups can win. You know, there's a lot of people out there that have amazing functional expertise but don't have the deep subject matter expertise that you have or that your team has over a certain market or a certain customer or product. And so when I talk to customers, I don't want the flattery. I want like, "Where does our product suck?" Some of the questions I ask are like, "Hey, what are the top three things that you don't like about our product?" Or, "If you were in charge of our roadmap, what would you prioritize?" Those types of questions are really helpful because, you know, they give you that feedback and that insight over like where do you need to continue to push. I'm never satisfied with our progress. I am really excited about what our customers are building. Like, I see some of the apps they launch and they build and it, it's like, like I wanna go talk about them with my friends 'cause they're so cool and inspiring and exciting. And as all these new applications around speech are continuing to take off, the amount of speech data we're handling, it just continues to grow rapidly. We'll handle this month alone about five petabytes of speech data through our API platform. That's about 10X the size of the entire Spotify library and catalog. And usage to our developer platform is growing over 250% year over year. So the scale is, like, pretty insane.

7. 10:07 – 11:32

   Just Start with a Website

   1. DFDylan Fox10:07

      Speed is probably more important now than ever. There's so many use cases that we're seeing developers want to build apps around that they need really good speech AI for. They need new capabilities. They need better tech. They need better models. They need, you know, all this stuff. They're hungry for it because the opportunities are enormous. An example of where a lot of speech AI models will struggle today is with hallucinations. So having an in-person meeting with 10 people, or you're having a phone call and it's windy and the quality's bad, that's where the AI models still do struggle today. And that's an amazing opportunity because there's so many applications that are limited by those things. And so we're really excited to keep making the models that we're creating better and better. And as a startup company, you wanna try to optimize everything you can for speed. You can start by just putting up a website and advertising the product that you want to build and just putting like a, you know, contact us button on there and see what are people reaching out about. Are people reaching out? What do they want from your product? And that can be really helpful to get validation early on, are you building the right thing, uh, before you go spend a ton of time building. So I think that really fast iteration loop is important for startups to have with customers in the markets that you're, you're working in.

8. 11:32 – 14:11

   Focus on Ours, Not Theirs

   1. DFDylan Fox11:32

      [gentle music] When you're making an AI model, like, at so many points you have to decide between trade-offs, right? What type of data do you use? What type of thing do you optimize for? When you know who you're building this AI model for, then you can make all those trade-offs a lot more intelligently in a way that makes your AI model have more product market fit for who you're building it for. You can always change your focus as you learn, right? But I think it's important to, like, have a focus and then you learn, and then you can focus other areas. So, like, we're super laser-focused on, okay, people building voice agents, people building note takers, people building sales intelligence apps. These are the 10 things they really, really care about, and so let's make sure our models are hyper-optimized for those things, and let's build the right training data, and let's build the right model architectures, and let's do all of the things we can to absolutely max out in those dimensions. And that's how we're constantly keeping our models the most accurate and the easiest to use for the developers that we're building for. You might come to Assembly and maybe our models aren't as good for you as another model. And usually if that happens, it's because that's not an application or a use case that we're really focusing on, at least not right now. So for us, the way we really maintain our competitive advantage is by just really clearly focusing on who we're building for, and not building general purpose tech, but building tech that's optimized for a specific use case and market. One of the biggest things I've learned is that every startup, you have your own journey. It's easy to compare yourself to other startups. You know, you have friends that are founders and maybe they're a stage or two ahead. But startups are not franchise businesses, I think is one of the biggest things that I've learned. And what I mean by that is, like, you have to really figure out what your journey is, and every journey is slightly different. And there's a lot of startup dogma that you don't have to subscribe to [laughs] and in a lot of ways can actually make it harder for you as a founder because you feel like there's all this stuff you have to do, when in reality you just have to really build a great product, make your customers happy, and that's what you wanna focus on. That realization has helped me a lot as a founder, realizing, okay, we're on our, our own journey. Startups are, all, all look different. All their journeys are different. And just be really focused on making a great product, on making customers super happy, and that's, that's the North Star. [gentle music]

Episode duration: 14:11