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

Intro

00:00As 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 going to 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.

00:14As 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.

00:33My name is Dylan Fox. I'm the founder and CEO of Assembly AI. 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 Excel Insight Partners Daniel Gross and Nat Freeman and Smith Point.

00:50That's led by Keith Block from Salesforce.

One Bowl of Pasta, Seven Days of Code

01:04My 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 MMRPG games. I love just working on technology.

01:19So in college, I started this company that helped other college organizations fund raise online and people that donated to this student organization would get like local rewards in their community. It was a terrible idea and it was, you know, didn't go anywhere.

01:38But we learned a lot about starting 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.

01:55It 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.

02:12So after college, I didn't get a job. Uh we had shut the startup down. I just opened up a bunch of credit cards 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.

02:33That'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.

02:48After, you know, almost 2 years of doing that and going into credit card 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, the 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.

03:12Got 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

Why I Became Interested in Voice AI

03:24when 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.

03:37So 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.

03:52And 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 CDROM. It was like a $10,000 evaluation agreement that you had to sign.

04:09I didn't even have a CDROM 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 going to just get orders of magnitude better and that was going to make what was a small market huge.

04:32That 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.

04:53That 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.

No Product, No Customer, Still Got into YC

05:17I left my job and then a few months later got into Y Combinator. I had no clue I was going to 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 going to do.

05:31You 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 from Daniel?"

05:49And 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'd submitted the application.

06:05It 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.

06:19That was probably one of the most stressful periods of my life. It 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 raising capital is like just going to make things happen.

06:35It doesn't. No investors are going to 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?

07:05Are 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.

EO Partner Highlight

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How a Startup Wins with Deep Subject Matter Expertise

08:23Most of my day is spent talking to customers, working with our product teams, playing with our product, and seeing where it's working, 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.

08:38I 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.

09:03And 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 road map, what would you prioritize?

09:16Those 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 really excited about what our customers are building.

09:30Like I see some of the apps they launch and they build and it's like like I want to go talk about them with my friends cuz 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.

09:44We'll handle this month alone about five pabytes 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.

Just Start with a Website

10:07Speed 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.

10:20They 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 is bad, that's where the AI models still do struggle today.

10:43And 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 want to try to optimize everything you can for speed.

10:59You 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.

11:21So I think that really fast iteration loop is important for startups to have with customers and the markets that you're you're working in.

Focus on Ours, Not Theirs

11:34When 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.

11:51You 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. like we're super laser focused on, okay, people building voice agents, people building notetakers, people building sales intelligence apps, these are the 10 things they really, really care about.

12:12And 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.

12:33You 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.

13:00One 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.

13:16And 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. 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 want to focus on.

13:42That realization has helped me a lot as a founder realizing, okay, we're on our our own journey. Startups are all look different. All their journeys are different. And just be really focused on making a great product, on making customers super happy.

13:55And that's that's the north star.