The Exchanges

Q Yeah. So I have to ask then, You come together. How does the idea for 11 Labs come to be? Was it truly inspired by bad movie dubbing?

A There was two things that coincided for us starting 11 Labs. One was through the years prior, he worked at Google, I worked at Palantir. We would meet for a Hack Weekend project together. So we would try to explore a new technology. One was in a recommendation space. One, during the crypto height, we build a crypto risk analyzer. Which wasn't very easy, and it didn't work very well, and then, and then once we did the project in audio, which was, the idea was, can it analyze how you speak, and gives you tips on how to improve speaking, um, and that kind of opened our eyes to what's possible in the technology space there, and then fast forward later that year, so we did the Hack Weekend project in early 2021. In late 2021, the moment hit from Poland, which is, wow, all movies are still Dubbed where you have all the voices from the original, whether it's male or female voice narrated with one single character. So you have one voice narrating all the characters in a flat, no emotional way. So it's like a audio book reading of a movie. It's a, as you can imagine, a terrible experience and something that we knew combining the experience from working on audio and now knowing this is a problem that, okay, this will change. A few years from now, as you, as you, as you imagined that kind of advancement, all the voices will have original emotions, intonation, sound incredible, and that ki…

AI assessment note: “In late 2021, the moment hit from Poland, which is, wow, all movies are still Dubbed”

Q So what do you do when you land on the idea then, in terms of your next steps, you move into the research layer and determine whether it's possible to actually do this?

A The way we've approached this was we, um, we first tried to like do two things in parallel. My co-founder was, okay, can we use existing technology Stitch it together and create a dub of a movie in a better way. And it quickly transpired that you get a good effect, but it wasn't brilliant. So to actually fix it, let's take a step back and fix one of those components and make it great. At the same time, when he was doing research, my mission was, does anybody actually want that dubbing product? So I was emailing all the YouTubers, uh, um, getting the, the, the email, scraping them and trying to message them. Hey, if we had a dubbing product to make your Movies available in all languages. Would you be interested in that? And, um, there's a, not, there's like, um, uh, roughly, it was like, 15% reply rate initially from the, the, the first batches that we sent. All were personalized. Um, I mean, we sent thousands of them. But the, the interest was like lackluster. All of them were, it's like, oh, I don't fully believe this is possible. Can you send us a sample? It would be great, but how will I operationalize this? YouTube doesn't support it. So it's like, it was, Somewhat of an excitement, but not like a burning problem I need to solve it. But then the second thing happened, so we started sending the samples, uh, we started speaking more with the, the, the YouTubers, and it quickl…

AI assessment note: “we first tried to like do two things in parallel.”

Q Yeah. So I have to ask then, You come together. How does the idea for 11 Labs come to be? Was it truly inspired by bad movie dubbing?

A There was two things that coincided for us starting 11 Labs. One was through the years prior, he worked at Google, I worked at Palantir. We would meet for a Hack Weekend project together. So we would try to explore a new technology. One was in a recommendation space. One, during the crypto height, we build a crypto risk analyzer. Which wasn't very easy, and it didn't work very well, and then, and then once we did the project in audio, which was, the idea was, can it analyze how you speak, and gives you tips on how to improve speaking, um, and that kind of opened our eyes to what's possible in the technology space there, and then fast forward later that year, so we did the Hack Weekend project in early 2021. In late 2021, the moment hit from Poland, which is, wow, all movies are still Dubbed where you have all the voices from the original, whether it's male or female voice narrated with one single character. So you have one voice narrating all the characters in a flat, no emotional way. So it's like a audio book reading of a movie. It's a, as you can imagine, a terrible experience and something that we knew combining the experience from working on audio and now knowing this is a problem that, okay, this will change. A few years from now, as you, as you, as you imagined that kind of advancement, all the voices will have original emotions, intonation, sound incredible, and that ki…

AI assessment note: “There was two things that coincided for us starting 11 Labs.”

Q So what do you do when you land on the idea then, in terms of your next steps, you move into the research layer and determine whether it's possible to actually do this?

A The way we've approached this was we, um, we first tried to like do two things in parallel. My co-founder was, okay, can we use existing technology Stitch it together and create a dub of a movie in a better way. And it quickly transpired that you get a good effect, but it wasn't brilliant. So to actually fix it, let's take a step back and fix one of those components and make it great. At the same time, when he was doing research, my mission was, does anybody actually want that dubbing product? So I was emailing all the YouTubers, uh, um, getting the, the, the email, scraping them and trying to message them. Hey, if we had a dubbing product to make your Movies available in all languages. Would you be interested in that? And, um, there's a, not, there's like, um, uh, roughly, it was like, 15% reply rate initially from the, the, the first batches that we sent. All were personalized. Um, I mean, we sent thousands of them. But the, the interest was like lackluster. All of them were, it's like, oh, I don't fully believe this is possible. Can you send us a sample? It would be great, but how will I operationalize this? YouTube doesn't support it. So it's like, it was, Somewhat of an excitement, but not like a burning problem I need to solve it. But then the second thing happened, so we started sending the samples, uh, we started speaking more with the, the, the YouTubers, and it quickl…

AI assessment note: “we first tried to like do two things in parallel”

Q is a small check, which, you know, he very kindly offered, um, and the other was like, no offense, it was super freaking early, And it was like, well, why wouldn't OpenAI do this that, no offense, two very young guys in London are doing, like, how is this not going to be done by them? How do you answer the question, well, duh, why won't OpenAI just do this?

A They definitely will do, do something, but I think they, you know, they, they lack the, the, the genius that, uh, that, that, that, that, that I'm happy my co-founder and the team has, but I think the true, true, true longer answer is, one is focus. You really, I think in the early days, especially, you know, when we spoke then, there was just so many different things you could do in AI space, and I think we took this bet that we want to really own and win in the voice AI research and product space. All our, our work is, is, is directly tied to, to, to, to, to voice. Then the second thing is, I actually think the number of researchers in the world working on voice and being exceptional is super small. Probably like 50 to a hundred people at like this top level and, um, and, and Piotr and, um, and, and people around him were able, so Piotr was able to assemble one of the best teams in the space. I think we have five to 10 people that are in the top In a top hundred, like there is like a mighty team, which, which I'm kind of time and time again, surprised how incredible they are. Um, and to make it specific, I mean, text to speech was one that kind of have blown everything out of the water. Then speech to text is beating open AI, Gemini on benchmarks. Now music, which is again, something that no big company has, has yet been able to crack or do. Um, so it's a, it's a, it's incred…

AI assessment note: “the true, true, true longer answer is, one is focus.”

Q unit economics of a lot of companies that we see today, whether it's your replets, or your lovables, or any of companies like this. Well, any kind of application layer companies, period, really. They generally have pretty tough unit economics, generally speaking. Um, do you think that is a fair criticism, or do you think it is simply short-sighted, given the changes we will likely see in the cost structure?

A Of course, the unit economics in most of those cases that you mentioned is pretty, pretty poor, but I think the strategy is that yes, one, the models will optimize in cost, and then two, they will be the brands that customers trust, and then they can actually use a lot of the signal back. And I think to 11 Labs' example too, we, I think our unit economics is much healthier than most of those companies. We control our research, our product, and distribution, but it's still, if we had a new model that we need to release ourselves, we would Optimize less for, for the cost structure so we can get that magic out quicker than other competitions even can think about creating their own model.

AI assessment note: “unit economics in most of those cases that you mentioned is pretty, pretty poor”

Q Speaking of kind of good partners, Right now, we're doing the human plus agent. We're so friendly, and we make each other better, and there's a time when human plus agent just becomes agent. Do you think we are seeing a lot of resistance from employees within companies towards agents coming in?

A We do, but the, the, the way we've seen this, like, kind of transition happen now is where you will have more specialized humans where the agents are taking more of the manual parts that nobody really wanted to do or was effectively very easy to, to, um, to, to, or very, didn't require domain expertise. So like a good example is like if you're taking appointment scheduling, uh, if you are doing a refund, All of those, of course, assuming you have the safeguards and authentication place, are pretty easily done with AI. But then suddenly, if you need to help a patient navigate the outbound flow after going from hospital or understand analysis, that cannot be done with AI. There's too much, too much at stake, and you need a deep domain expertise. Um, so we've seen, like, kind of the transition where that side of, of, of people helping in that kind of last mile is even more valuable. Well, of course, AI can help with those easier tasks across. And I think this will continue. Of course, the percentages will shift where you will have even more, um, automation as it goes deeper, and then even more value assigned to the people doing that domain expertise, because ultimately it will help automate the task at hand.

AI assessment note: “We do, but the, the, the way we've seen this, like, kind of transition”

Q Any advice on angel selection for founders in the early days?

A The way we approach it is like, so we had standard, of course, the venture capital to whether it was the help of their network, with the brand, with making sure we arrived in a specific region. But, um, but on angels, we would usually optimize for, um, do they have domain expertise that we don't have? That's one category. Second, can they help us validate ourselves in specific, specific circles we might not have access to? Uh, so like if you are an AI founder, it's maybe valuable to have set of AI founders in there. So you are part of the same events, the same, same, same, same conversations. Um, and then of course the, in our case, it was, can we have some of the go-to market expertise where we, where we didn't have, we had a lot of self-serve, some volunteer experience, but the sales led, how can we bring that in place as well?

AI assessment note: “on angels, we would usually optimize for, um, do they have domain expertise”

Q Okay. Nineteen million dollars in the account. Most people suddenly then go on a hiring spree and not two people hiring spree, but like a proper hiring spree. But you favor very small teams. You've said this to me before, but Luke said it to me. Why do you favor really small teams?

A I think the first piece is that more people frequently doesn't fix the problem. It's like you, you, you, you don't need that many people to do something special. That's the first thing. Second is you, by keeping, and as an organization today, we are, you know, we're 250 people, but really it's more like 20 teams, uh, couldn't go to market of like five to 10 people that are just executing on specific project where, um, where They have higher ownership. They can move extremely quickly. They, um, they see the results and iterate with reality a lot quicker to improve that. And I think this just works in such a beautiful, beautiful way. Of course, there are other challenges with this, but.

AI assessment note: “more people frequently doesn't fix the problem... They have higher ownership. They can move extremely quickly”

Q Don't go too far there, Matty. Um, did you, because you kind of did the pre-seed raise and the beta launch at the same time. Did you have product market fit on the beta launch? Were there early signs that it was working?

A Oh yeah, that's a, okay, so got, got the, the good, um, good timeline, a piece there where we actually raised the round in mid, like a Q-free of twenty-twenty-two, but we announced it in Q-one of twenty-twenty-three. And the reason we do that, and we do that all the time, is that we don't want to announce a round just for the sake of announcing a round. Our philosophy was always the round should have another purpose, which is Bring the product out and help you get the product into the users and celebrate a set of customers to show that you are arrived in a specific sector, uh, bring a new research model into play. So every round that we would do would always tie into a product announcement. So we actually hold in, hold on for announcement for a few months until we had our beta release and then we triggered, which was January, 20, 23. Um, but your, to your question, initially When we worked on dubbing and, and the first early days, and we were like emailing, we didn't have product, product market fit. It was like very clear that, you know, people were slow to reply, then we sent samples, they weren't engaging, so we, so we didn't through the 20, 22 period. And then when we shifted from dubbing into narration, voiceovers, then the product market signal started to hit. Maybe it's there. We, we had a first, um, and I remember this thing, there was three things that happened. First,…

AI assessment note: “when we shifted from dubbing into narration, voiceovers, then the product market signal started to hit.”

Q is a small check, which, you know, he very kindly offered, um, and the other was like, no offense, it was super freaking early, And it was like, well, why wouldn't OpenAI do this that, no offense, two very young guys in London are doing, like, how is this not going to be done by them? How do you answer the question, well, duh, why won't OpenAI just do this?

A They definitely will do, do something, but I think they, you know, they, they lack the, the, the genius that, uh, that, that, that, that, that I'm happy my co-founder and the team has, but I think the true, true, true longer answer is, one is focus. You really, I think in the early days, especially, you know, when we spoke then, there was just so many different things you could do in AI space, and I think we took this bet that we want to really own and win in the voice AI research and product space. All our, our work is, is, is directly tied to, to, to, to, to voice. Then the second thing is, I actually think the number of researchers in the world working on voice and being exceptional is super small. Probably like 50 to a hundred people at like this top level and, um, and, and Piotr and, um, and, and people around him were able, so Piotr was able to assemble one of the best teams in the space. I think we have five to 10 people that are in the top In a top hundred, like there is like a mighty team, which, which I'm kind of time and time again, surprised how incredible they are. Um, and to make it specific, I mean, text to speech was one that kind of have blown everything out of the water. Then speech to text is beating open AI, Gemini on benchmarks. Now music, which is again, something that no big company has, has yet been able to crack or do. Um, so it's a, it's a, it's incred…

AI assessment note: “the true, true, true longer answer is, one is focus.”

Q I am so thrilled we could do this. Now, I spoke to so many people beforehand, and I have to say, Luke was phenomenal on your team in prepping me so much, but I do want to start a little bit with the origins pre. You grew up in Poland, and this was Luke's. How did growing up in Poland impact your mindset towards the world and company building first?

A You know, in Poland, the, it's a, it's a very different, much smaller world. So it's, um, for growing up, I was in a very lucky position where I was in suburbs of Warsaw, then went to high school in Warsaw, then kind of started seeing more of that world, which, um, which was of course incredible because that kind of opens your eyes of like what's possible, that there's so much world beyond what you've seen, the smaller cities. And I think in a similar way, as you think about building 11 Labs now, it's, It's, um, the scale of what, what we don't know is still ahead of us, and this is like what's exciting, that we know that if we climb those, those traditional hills, the mountains, we will see increasingly more. Um, and I think the second thing was in, um, I saw the transition where in, in, in suburbs of Warsaw, I was in like a public school, so, uh, school where, where you would have just any, any kids that would live in the area. And in high school, and where I met my co-founder, You would have, um, a slightly different crowd, like a crowd of, of people that would, when competitions, uh, need to go through a few steps to get there. And, and suddenly that like kind of density of talent was the most motivating factor to like explore more, learn more, and do more, which now we are trying to, of course, replicate that, that 11 Labs where, and any other company I'm sure too, it's li…

AI assessment note: “density of talent was the most motivating factor... now we are trying to, of course, replicate”

Q unit economics of a lot of companies that we see today, whether it's your replets, or your lovables, or any of companies like this. Well, any kind of application layer companies, period, really. They generally have pretty tough unit economics, generally speaking. Um, do you think that is a fair criticism, or do you think it is simply short-sighted, given the changes we will likely see in the cost structure?

A Of course, the unit economics in most of those cases that you mentioned is pretty, pretty poor, but I think the strategy is that yes, one, the models will optimize in cost, and then two, they will be the brands that customers trust, and then they can actually use a lot of the signal back. And I think to 11 Labs' example too, we, I think our unit economics is much healthier than most of those companies. We control our research, our product, and distribution, but it's still, if we had a new model that we need to release ourselves, we would Optimize less for, for the cost structure so we can get that magic out quicker than other competitions even can think about creating their own model.

AI assessment note: “Of course, the unit economics in most of those cases that you mentioned is pretty, pretty poor”

Q I was most inspired or given hunger because my dad always said, like, when we went into Chelsea, like, oh, it's, it's a better life here, and like, this is where people who've won live, and I didn't live there, and I wanted to fucking live there, and it fed me with this, like, insane hunger. Where did your insane hunger come from in those early days?

A The early days, I mean, definitely it was, you know, the combination of family, My older brother kind of trailblazed going abroad to study, then motivated us to, like, you need to do the same. This is really helpful. And then the second, it was really this community of people in high school. Meeting my co-founder, um, was extremely smart. Meeting some of our close friends, uh, and, like, kind of going through this cycle of motivating each other. It's like, yes, we want to study at the best university. Yes, we want to go deeper and Crash this exam. And, um, and I think this was huge, huge element for, for, for all of us just, just, just, just going after it and knowing that maybe it's possible. Um, at the time, at the time everything fell distant and it's still, you know, many of the things do, but, uh, but I think without that kind of motivation through the people, which would be not possible.

AI assessment note: “it was, you know, the combination of family, My older brother kind of trailblazed”

Q with some chronology. I have so many questions that I want to ask you, but some chronologies. We mentioned that kind of the V-one and building to beta, and I think it was, uh, where was it, uh, twenty-twenty-three that you raised the pre-seed, Jan 23. Um, how did the fundraise process go? You're two young guys saying, hey, we're going to do this. How did the pre-seed fundraise go?

A Pre-seed was tough. Pre-seed was hard. We, it was, you know, similar questions that you asked. It was like, how will we fix research? The second question, which was very interesting, we think the market is very small for what you are solving, which at the time was like, you know, it's like a combination of AI, voice, like nobody was thinking about that. So, so that was, that was, that was surprising to us, which we were very disagreeable. And third was defensibility. Will it actually be better than what in Cubans from the, the, If A&G companies will actually solve or, or like, how will you outcompete that in the long term? So these are the three. So it was tough. I think we spoke with, with a good amount of, of double digit, um, investors.

AI assessment note: “Pre-seed was tough. Pre-seed was hard.”

Q Any advice on angel selection for founders in the early days?

A The way we approach it is like, so we had standard, of course, the venture capital to whether it was the help of their network, with the brand, with making sure we arrived in a specific region. But, um, but on angels, we would usually optimize for, um, do they have domain expertise that we don't have? That's one category. Second, can they help us validate ourselves in specific, specific circles we might not have access to? Uh, so like if you are an AI founder, it's maybe valuable to have set of AI founders in there. So you are part of the same events, the same, same, same, same conversations. Um, and then of course the, in our case, it was, can we have some of the go-to market expertise where we, where we didn't have, we had a lot of self-serve, some volunteer experience, but the sales led, how can we bring that in place as well?

AI assessment note: “on angels, we would usually optimize for, um, do they have domain expertise”

Q I'm a romantic. I hate this idea of a roadshow, where it's like, I'm gonna meet everyone, and then I'm gonna compare term sheets, and then I'm gonna decide. It's like, what happened to the partnership?

A The, well, but it's, you know, the truth is, the other way is, is true, where a lot of the investors, um, want to give the term sheet, but that is before any show of partnership. So how do you know that this is a good partner? How do you know whether they are giving you good terms? Especially if you're a FaceTime founder, you never run this. You don't know how much you are valued. You need to have some relative comparison, and this can happen through conversations of other companies, other founders, or, um, comparing yourself to other companies in the field, or running, running some form of a process. Roadshow probably sounds pretty bad because it sounds like a lot. You probably, like, the way we approach fundraising was always, you know, especially in the early days, like, queue, queue investors we really care about, and First speak with maybe one or two that maybe aren't a priority so we understand whether, like, we are at all kind of perceived in the, the, the, the kind of the, the messaging that we want to put across makes sense. If it does, move straight to the, the, the top ones.

AI assessment note: “How do you know whether they are giving you good terms?”

Q You say go vertical there. Normally when you have verticals, you have kind of a maturing of organization, you have titles. Titles is something that you decided to get rid of. This is very counter traditional org structures. Why is it better to not have titles?

A Yeah, there, there are, there are some incredible companies that, that, that, that, of course, that similar, Stripe being one, one example. But in our case, it was, especially Dan, super small teams. So we have team of five. A lot of people, people join, and what we wanted to, to, to optimize for is like, one, the main thing that matters is the impact. You can join, and you can be the most impactful person from day, day zero in, in any of those teams. Um, so the title shouldn't define What is your level of, of decisions? Second thing with the small teams that happens is that you have a lot of those small teams. Uh, so if you start looking at who gets the title or not, it just becomes a distraction, uh, given that teams are, uh, uh, like the small units that just keep, keep, keep executing. Um, so that was the second thing. And the first thing we wanted to like also make it very clear in that mix where And still do. If you are joining 11 Labs today, you can transition to being a leader of any team of any function super quickly. And titles felt limiting to that. We felt like people joining in and seeing that kind of the wider set of organization already having set of roles defined for them would make this a little bit harder. And, and that's not like you can have a lower tenure and be a manager of people with much longer tenure if you are the right, the right person. So titles, w…

AI assessment note: “titles felt limiting to that”

Q I was most inspired or given hunger because my dad always said, like, when we went into Chelsea, like, oh, it's, it's a better life here, and like, this is where people who've won live, and I didn't live there, and I wanted to fucking live there, and it fed me with this, like, insane hunger. Where did your insane hunger come from in those early days?

A The early days, I mean, definitely it was, you know, the combination of family, My older brother kind of trailblazed going abroad to study, then motivated us to, like, you need to do the same. This is really helpful. And then the second, it was really this community of people in high school. Meeting my co-founder, um, was extremely smart. Meeting some of our close friends, uh, and, like, kind of going through this cycle of motivating each other. It's like, yes, we want to study at the best university. Yes, we want to go deeper and Crash this exam. And, um, and I think this was huge, huge element for, for, for all of us just, just, just, just going after it and knowing that maybe it's possible. Um, at the time, at the time everything fell distant and it's still, you know, many of the things do, but, uh, but I think without that kind of motivation through the people, which would be not possible.

AI assessment note: “definitely it was, you know, the combination of family... this community of people”

Q with some chronology. I have so many questions that I want to ask you, but some chronologies. We mentioned that kind of the V-one and building to beta, and I think it was, uh, where was it, uh, twenty-twenty-three that you raised the pre-seed, Jan 23. Um, how did the fundraise process go? You're two young guys saying, hey, we're going to do this. How did the pre-seed fundraise go?

A Pre-seed was tough. Pre-seed was hard. We, it was, you know, similar questions that you asked. It was like, how will we fix research? The second question, which was very interesting, we think the market is very small for what you are solving, which at the time was like, you know, it's like a combination of AI, voice, like nobody was thinking about that. So, so that was, that was, that was surprising to us, which we were very disagreeable. And third was defensibility. Will it actually be better than what in Cubans from the, the, If A&G companies will actually solve or, or like, how will you outcompete that in the long term? So these are the three. So it was tough. I think we spoke with, with a good amount of, of double digit, um, investors.

AI assessment note: “Pre-seed was tough. Pre-seed was hard. We, it was, you know, similar questions”

Q So many things I want to unpack there. You said about kind of the, the timing of your announcements and aligning it to actually kind of material news items. Do you have any big lessons on announcements, how to do launches that you found particularly work well that other founders should know?

A So that's the first one. A hundred percent, like, I, I, it's like for, for us, the, the making announcement close to something big you want to announce from the product, from the user, From hiring perspective, tie it with that. Don't, I don't think celebrating the number itself is the right way. I mean, in a, in a way, it's like you're giving away the company. So it's, it's, it's, it's like almost like, what are you doing it for? And you want to show as much of that as possible. So that was the first one. Second is, I think it's very easy to optimize for the, the, the, and maybe I'll cover it up front. Depends, of course, on whether you are self-serve users and creators, developers are optimizing for enterprise and sales lead, but second thing would be you really want to focus on how you actually get the users rather than just the media PR element. I don't think the latter is actually as valuable as it seems to a, to a first-time founder. For us, I remember when we did the beta, we were speaking and, um, with some of the bigger publications, and one rejected us, the other one accepted us, and we felt like it's a big deal. Then we did all the prep for the interview. We did the, the, the, the, the actual news, and then it was posted. We hold it like everything around this post that they told us the deadline for, and it had no impact. I think it, I mean, it's like probably a few m…

AI assessment note: “focus on how you actually get the users rather than just the media PR element”

Q I'm a romantic. I hate this idea of a roadshow, where it's like, I'm gonna meet everyone, and then I'm gonna compare term sheets, and then I'm gonna decide. It's like, what happened to the partnership?

A The, well, but it's, you know, the truth is, the other way is, is true, where a lot of the investors, um, want to give the term sheet, but that is before any show of partnership. So how do you know that this is a good partner? How do you know whether they are giving you good terms? Especially if you're a FaceTime founder, you never run this. You don't know how much you are valued. You need to have some relative comparison, and this can happen through conversations of other companies, other founders, or, um, comparing yourself to other companies in the field, or running, running some form of a process. Roadshow probably sounds pretty bad because it sounds like a lot. You probably, like, the way we approach fundraising was always, you know, especially in the early days, like, queue, queue investors we really care about, and First speak with maybe one or two that maybe aren't a priority so we understand whether, like, we are at all kind of perceived in the, the, the, the kind of the, the messaging that we want to put across makes sense. If it does, move straight to the, the, the top ones.

AI assessment note: “investors want to give the term sheet, but that is before any show of partnership.”

Q Are those 20 teams organized by function or by project?

A Uh, a little bit depends the, the, the, in the product by like a product, um, product area. So we have a team working on our studio interface, team that will be responsible for all the core experience when you log in, team responsible for the entire voice agent suite, and within that there's a team working on some of the more enterprise components, another team working on some of the self-serve elements. So all of the teams will be organized there on the product area, and then the other parts We tried to shard it pretty quickly, so, you know, we will have a separate team for talent, of course, then the team for people, and they will have a high degree of, of independence when they actually execute, which, which helps.

AI assessment note: “all of the teams will be organized there on the product area”

Q You say go vertical there. Normally when you have verticals, you have kind of a maturing of organization, you have titles. Titles is something that you decided to get rid of. This is very counter traditional org structures. Why is it better to not have titles?

A Yeah, there, there are, there are some incredible companies that, that, that, that, of course, that similar, Stripe being one, one example. But in our case, it was, especially Dan, super small teams. So we have team of five. A lot of people, people join, and what we wanted to, to, to optimize for is like, one, the main thing that matters is the impact. You can join, and you can be the most impactful person from day, day zero in, in any of those teams. Um, so the title shouldn't define What is your level of, of decisions? Second thing with the small teams that happens is that you have a lot of those small teams. Uh, so if you start looking at who gets the title or not, it just becomes a distraction, uh, given that teams are, uh, uh, like the small units that just keep, keep, keep executing. Um, so that was the second thing. And the first thing we wanted to like also make it very clear in that mix where And still do. If you are joining 11 Labs today, you can transition to being a leader of any team of any function super quickly. And titles felt limiting to that. We felt like people joining in and seeing that kind of the wider set of organization already having set of roles defined for them would make this a little bit harder. And, and that's not like you can have a lower tenure and be a manager of people with much longer tenure if you are the right, the right person. So titles, w…

AI assessment note: “the main thing that matters is the impact... titles felt limiting to that”

Q Don't go too far there, Matty. Um, did you, because you kind of did the pre-seed raise and the beta launch at the same time. Did you have product market fit on the beta launch? Were there early signs that it was working?

A Oh yeah, that's a, okay, so got, got the, the good, um, good timeline, a piece there where we actually raised the round in mid, like a Q-free of twenty-twenty-two, but we announced it in Q-one of twenty-twenty-three. And the reason we do that, and we do that all the time, is that we don't want to announce a round just for the sake of announcing a round. Our philosophy was always the round should have another purpose, which is Bring the product out and help you get the product into the users and celebrate a set of customers to show that you are arrived in a specific sector, uh, bring a new research model into play. So every round that we would do would always tie into a product announcement. So we actually hold in, hold on for announcement for a few months until we had our beta release and then we triggered, which was January, 20, 23. Um, but your, to your question, initially When we worked on dubbing and, and the first early days, and we were like emailing, we didn't have product, product market fit. It was like very clear that, you know, people were slow to reply, then we sent samples, they weren't engaging, so we, so we didn't through the 20, 22 period. And then when we shifted from dubbing into narration, voiceovers, then the product market signal started to hit. Maybe it's there. We, we had a first, um, and I remember this thing, there was three things that happened. First,…

AI assessment note: “when we shifted from dubbing into narration, voiceovers, then the product market signal started to hit.”

Q Speaking of kind of good partners, Right now, we're doing the human plus agent. We're so friendly, and we make each other better, and there's a time when human plus agent just becomes agent. Do you think we are seeing a lot of resistance from employees within companies towards agents coming in?

A We do, but the, the, the way we've seen this, like, kind of transition happen now is where you will have more specialized humans where the agents are taking more of the manual parts that nobody really wanted to do or was effectively very easy to, to, um, to, to, or very, didn't require domain expertise. So like a good example is like if you're taking appointment scheduling, uh, if you are doing a refund, All of those, of course, assuming you have the safeguards and authentication place, are pretty easily done with AI. But then suddenly, if you need to help a patient navigate the outbound flow after going from hospital or understand analysis, that cannot be done with AI. There's too much, too much at stake, and you need a deep domain expertise. Um, so we've seen, like, kind of the transition where that side of, of, of people helping in that kind of last mile is even more valuable. Well, of course, AI can help with those easier tasks across. And I think this will continue. Of course, the percentages will shift where you will have even more, um, automation as it goes deeper, and then even more value assigned to the people doing that domain expertise, because ultimately it will help automate the task at hand.

AI assessment note: “We do, but the, the, the way we've seen this, like, kind of transition”

Q You've got Andreessen introducing you to celebrities, and you've got Nat and Daniel, two of the brightest minds in AI, who are querying APIs that no one else does. Are the Americans just playing a different game to the European VCs?

A Mm, we love our partners. I mean, we have, um, and recent team is so, so incredible, their network. I mean, now Sequoia with Andrew is just another, another level two. Iconic team, uh, also crazy help. Um, NEA too is just like bringing all the time. But they're all US. They are all US. So I think they are playing a different game. I think the, you know, they're, they are all from our experience so far, a lot more keen to take the risk. Like, You know, even our conversations are always like, how do we bet bigger rather than like optimize for, for, for, for, for the negatives. Um, the one check I always try to do with, with Piotr for any of the partners that we bring beyond the capital network brand is, is always for the person you, you partner with or the person you partner with, how will they behave if it's not going well? So we usually try to get any of the back references for, How, um, how did they behave when the company was, was failing? And, um, and all of the ones that we had are, are, are in a very positive, like they actually were, were really on the, on the side of the founder helpful when it was not going well, even more so than when it was going well. And I was doing the same check with some of the checks with, with, with other companies. And, um, maybe this is like getting used to that. And like, you know, in U S the kind of the set of companies that went up and dow…

AI assessment note: “So I think they are playing a different game.”

Q You've got Andreessen introducing you to celebrities, and you've got Nat and Daniel, two of the brightest minds in AI, who are querying APIs that no one else does. Are the Americans just playing a different game to the European VCs?

A Mm, we love our partners. I mean, we have, um, and recent team is so, so incredible, their network. I mean, now Sequoia with Andrew is just another, another level two. Iconic team, uh, also crazy help. Um, NEA too is just like bringing all the time. But they're all US. They are all US. So I think they are playing a different game. I think the, you know, they're, they are all from our experience so far, a lot more keen to take the risk. Like, You know, even our conversations are always like, how do we bet bigger rather than like optimize for, for, for, for, for the negatives. Um, the one check I always try to do with, with Piotr for any of the partners that we bring beyond the capital network brand is, is always for the person you, you partner with or the person you partner with, how will they behave if it's not going well? So we usually try to get any of the back references for, How, um, how did they behave when the company was, was failing? And, um, and all of the ones that we had are, are, are in a very positive, like they actually were, were really on the, on the side of the founder helpful when it was not going well, even more so than when it was going well. And I was doing the same check with some of the checks with, with, with other companies. And, um, maybe this is like getting used to that. And like, you know, in U S the kind of the set of companies that went up and dow…

AI assessment note: “So I think they are playing a different game.”

Q Are those 20 teams organized by function or by project?

A Uh, a little bit depends the, the, the, in the product by like a product, um, product area. So we have a team working on our studio interface, team that will be responsible for all the core experience when you log in, team responsible for the entire voice agent suite, and within that there's a team working on some of the more enterprise components, another team working on some of the self-serve elements. So all of the teams will be organized there on the product area, and then the other parts We tried to shard it pretty quickly, so, you know, we will have a separate team for talent, of course, then the team for people, and they will have a high degree of, of independence when they actually execute, which, which helps.

AI assessment note: “So all of the teams will be organized there on the product area”

Q Fuckers. Uh, what's your biggest piece of advice to a founder who has a moment like that where you just feel the air come out of the company? How do you inflate the company again after such a damaging blow?

A I don't think the first reaction should be that, like, hey, everything is fine. I think you should, you should, like, be authentic and tell the team what you are feeling. Like, how has this happened? And actually the, the, the go through, like, what have we done wrong? And, and, you know, that, that frustration was clear. I don't think we, I, I, like, I, I think it was valuable for us to talk to, like, we are angry at ourselves. This is wrong. And then as we move from that stage, like, yes, we are angry. What are we actually going to do about this? And, um, and move to that second stage very quickly. Uh, but I think, you know, I, I, I think I've done a mistake sometimes of just going to the second stage, like kind of, it's not a problem. Let's just go through and solve it. I think it's actually super valuable to, to, to, to, to talk through what, what has happened. Uh, but then, you know, you need to, you need to go into the second thing, and then, and then in the long term, that will work out. You know, it's, it's, it's, then you can, the relentless execution will prove itself out and, and, and show it to the world. And the worst if you repeat the mistake, then someone needs to feel the, you know, feel, feel the repercussions. But, If you've learned from that and haven't repeated that mistake, it's fine.

AI assessment note: “be authentic and tell the team what you are feeling”