Building One of AI’s Fastest-Growing Companies | Mati Staniszewski, ElevenLabs — searchlore

Building One of AI’s Fastest-Growing Companies | Mati Staniszewski, ElevenLabs

David Senra Podcast

Published Sep 9, 2026

Search this video

0:02

We ran into each other at Michael Dell's event a few months ago and you're like, "Oh, I'm very curious how building a company today is different from building one in the past."

0:11

And Michael has 40 plus years of experience.

0:13

He's been dominating for decades.

0:14

And when I saw him, we had like a 30-minute conversation about this.

0:18

You read all these biographies of history entrepreneurs.

0:20

And you just see this over and over again.

0:22

It's like, "Oh, this time is different."

0:23

Turns out, "No, this time is not different."

0:25

And Michael's like, "No, no, I actually think this time is different."

0:27

So I want to start with like how you think about building your company AI native from today.

0:36

>> Yeah, Michael is a legend.

0:36

He is he must have so many interesting perspectives especially like he's still running the the company.

0:41

So it will be interesting whether he applies some of that difference to to um to the current running of the show.

0:47

But for us, you know, in some ways, given we are first- time founders, me and P, my my co-founder, my best friend of 15 years, 11 laps is the first venture we started. That's insane. You started in 2022.

0:59

You launched before the first version of Chbt, right? >> We did.

1:06

We It was still a year when the the topics of the day were uh crypto and metaverse.

1:10

So, 2022 was still a year where like everybody was obsessed about those two.

1:14

So it was a perfect time because we could actually focus and build on a a lot on the AI side.

1:20

>> What were you doing before you founded this company? >> I was a pioneer.

1:23

So I was helping build optimization models and bring optimization models to the customers.

1:26

So um NHS during the COVID response on how you distribute vaccines across across UK or working with oil and gas industry and figuring out how to optimize um the energy uh uh work.

1:39

So a lot of optimization models and then working with customers on like actually figuring out how you bring that into into the production.

1:47

And my co-founder was at Google and he he did a lot of the text uh models for knowledge graph before that did research at university around image uh visual models.

1:57

So incredible brain the smartest person I know for developing a lot of the research work and I was happily on that intersection of building the product and bringing it out to the customers.

2:08

So that was before Palanteer was black rockck building risk models bringing it out to customers and by background study mathematics.

2:13

by background study mathematics. So good intersection of the things I liked and now at 11 Labs that's also what what I do and that's also from the company lens when we started that was the whole goal of like can we combine research and product deployment under one hood on the research side built all the audio models starting with model to produce speech texttospech model and that was that 2022

2:35

the first model that could finally cross that human like quality and then over time now it's entirety of audio models transcription models localization models orchestration for voice conversations with agents and then on the product side can we unify that as one platform that helps people businesses transform how they would communicate with their audience >> wait so the first idea you started with audio >> we started audio >> why

2:59

>> the actual trigger point comes from where you're from from Poland very peculiar thing if you watch a movie in Polish all the voices whether it's a male voice or whether it's a female voice get narrated with one single

3:12

character so you have one voice narrating the whole the whole movie all the emotional the inonation disappears and um and it's still so we grew up with this everybody in Poland grows up with it it's like you know one person dabbing

3:24

and then in 2021 we retested or re experienced this still happening in in in their content and then second thing happened which was >> okay >> it was still happening in movies in 2021 that you'd watch in Poland >> yes >> same thing that was happening when you were a kid >> exactly okay >> and it's it's it's crazy because it's you know of course it's cheaper easier easier to do quicker timeline, but the the quality is is poor. Like as you can

3:46

Like as you can imagine, it's a it's a pretty terrible experience.

3:50

And that was like a trigger point.

3:52

In the future, that experience will be completely different.

3:55

you will have original voice, original emotions, original inonation and actually be able to experience that in that incredible way which is very timely because just uh a week ago we we released finally a model that is able to do that extremely well and and finally bring the content from one language to another.

4:12

But maybe more broadly that was also our eye openening of how we interact with technology.

4:18

How you can interact through technology will will change and that will apply the language barrier that will break but also just the general conversations with devices with digital world will happen differently across different modalities across different channels and we wanted to do >> this is what you thought back in 2022 or what you think today?

4:34

>> In 2022 we knew that you will you will need to unlock the stories the content across the modalities and channels.

4:39

We didn't yet know how quickly the kind of the shift from static to interactive will happen.

4:44

We hope this will happen, but we didn't know how quickly.

4:46

So the first idea was first idea was >> dub static content that I was watching.

4:54

I'm watching a movie in Poland.

4:54

I want this to actually feel like I'm watching in my native language. >> Exactly.

4:59

>> That had to be appear like a tiny business though, right?

5:00

At the time, like if that's your initial idea, you were you didn't go you weren't going into it thinking this is going to be a giant business.

5:07

It's like you're one of the fastest growing startups today.

5:11

>> You know, we we actually thought there huge business at the time, too.

5:12

So, we thought it's like if if we think about all the content, all the stories out there, how incredible if they were available in audio and and and and it's it's the whether it's some of the biggest streaming companies, whether that's TV, whether that's the conversations, all of those could be could be actually delivered in the local language.

5:30

So, we f we thought it's actually huge and I still think it's huge.

5:32

And then if you shift this to to the conversation we're having now, could this be in the future this version where I speak Polish and you understand me in English or I speak English and you understand me in any language that you want.

5:43

In Hitchhiker's Guide to Galaxy, there's this idea of a bubble fish that you put next to the ear and you can understand everything around you regardless of the language that you speak.

5:50

So we knew that we will get there, but initially it was like dubbing.

5:53

So I'll give you like a full full full way of how kind of it it it progressed.

5:57

Initially I was dubbing and then as we started diving into what do we need to do to solve dubbing we realized there are three steps in dubbing process.

6:05

There is transcription step then it's translation step to another language and then you need to regenerate that in another in another in another language.

6:12

Um but the research that existed at the time for each of those steps wasn't very good.

6:18

>> Which companies were doing the research?

6:21

>> There was a good Nvidia models uh open source models.

6:24

>> But wait is just an independent research or it's not any of the big companies?

6:27

No, I mean everything was poor. Everything was robotic.

6:28

Everything was pretty robotic.

6:30

It was still, you know, it was um still like you could you could immediately tell it was like a robotic voice.

6:37

Um and and and nothing really crossed that uncanny valley yet.

6:40

crossed that uncanny valley yet. Um there was one good open source paper an open source uh repo that I'm trying to recall that was that was pretty good but very unstable and still took so much time to generate that was like the best and Nvidia had some good research on

6:54

some of those components for especially on the speech to text side translation was okayish I mean at the time was incredibly doing incredibly well well um and then you had the kind of Google translate version of that but all of the components to do dub were were not good enough it. Uh so that's part one, the

7:10

Uh so that's part one, the research wasn't there.

7:14

And part two, when we started testing the dubbing idea with a lot of initially creators, the message we are getting back from the creators is like great, I would love to get dubbing one day, but today I have different problems.

7:26

My problems are I want to postproduce and change the line that was recorded in the wrong way.

7:29

Or I want before I record my video, I want to be able to uh uh narrate the script and how see how it sounds.

7:36

or instead of me speaking over a video, could I just have AI speak over that?

7:40

So before I like even think about dubbing, can you give me that?

7:44

And that was for us was like, okay, before we can solve dubbing, let's solve the research component to generate speech and make it sound great.

7:51

And on the product side, let's actually deliver for people to be able to just narrate content.

7:57

So like let's p down and ignore for for a second the language shift.

8:02

Let's just help bringing content alive with audio with a high quality I want to tell you about the presenting sponsor of this podcast, RAMP.

8:09

I have been reading a lot about SpaceX lately.

8:11

SpaceX is one of the most valuable businesses in the world, and one of the main themes in the history of SpaceX is constantly attacking and questioning your cost.

8:21

Ramp helps many of the most innovative businesses in the world do exactly that.

8:24

The median company running on RAMP cuts their expenses by 5%.

8:27

And one thing SpaceX has demonstrated is that a religious dedication to controlling costs can help actually increase revenue because you can pursue opportunities you couldn't otherwise.

8:38

And we see that in the RAMP data, too.

8:40

The median company running on ramp also grows their revenue by 16%.

8:45

So when you're running your business on RAMP and your competitors are not, you have a massive competitive advantage that compounds over time.

8:51

Ramp is the only platform designed to make your finance team faster and happier.

8:58

Many of the top founders and CEOs I know run their business on ramp.

9:00

I run my business on ramp and you should too. Go to ramp.

9:03

com to learn how they can help your business save time, save money, and grow revenue. That is ramp. com.

9:11

Deal is how the best founders turn the world into their talent pool.

9:13

[music] I've been studying how history's greatest founders operate for a decade.

9:18

And one thing they all have in common is they understand that recruiting and hiring the very best talent is [music] your most important priority.

9:23

A players recognize other A players which is why top companies like ramp, Shopify, 11 [music] Labs, Uber and Door Dash all use deal.

9:32

Many of the top founders I know have personally invested in Deal after using their product and what they discovered is that deal is the best company in the world [music] at building infrastructure for global hiring.

9:40

Deal will help your business hire, pay, and manage any [music] worker anywhere in the world.

9:45

So you can retain the best talent anywhere and spend the rest of your time focusing on what you do best, delivering value to your customers.

9:51

The founder of 11 Labs has a great description of the [music] value deal can give your company.

9:56

He said, "We built 11 Labs to break down language and communication [music] barriers.

10:00

With deal enabling us to hire and support exceptional talent anywhere, we can accelerate [music] our innovation and bring more voices, stories, and ideas to every corner of the world.

10:10

Deal is trusted by over 40,000 [music] businesses.

10:14

Learn how they can help your business today by going to deal. com/enra." That is deal. comra.

10:23

>> Let me make sure I'm understanding this correctly.

10:24

You're like, we're going to dub.

10:26

We're going to reach out to creators first.

10:27

So, I'm, you know, reaching a couple million people in English.

10:30

Let me see if I can get this guy to say, hey, can I translate to can we dub this for Polish or Spanish and all these other things?

10:35

And then the feedback you're getting is, yeah, that's kind of nice, but I have a lot I have many more immediate concerns, and can you help me with XYZ? >> Exactly.

10:43

And it's kind of was two things at the same time were great because that was also true on the research side where you have this like free steps you need to solve in dubbing.

10:49

Nothing in the space is good.

10:51

We need to solve one of those steps ourselves.

10:53

That's where Pra comes in and is able to create and assemble the best research team to solve it and he himself is an incredible researcher to actually bring that to life. >> Yeah.

11:02

Cuz I'm friends with uh Mr.

11:02

>> Yeah. Cuz I'm friends with uh Mr. beast and I remember talking to him about this a few years ago where >> you know he was the largest creator in the world and he used to run separate YouTube channels and he told me he's just like yeah for my Japanese like the Japanese versions of my videos it's like

11:18

he doesn't just dub them he'll hire like a voice actor that's like the voice is famous in that country >> yeah one day you you should uh whether with us or any other company you think you should dub your podcast it's so much knowledge that could bring be brought into so many different entrepreneurs

11:32

worldwide like in Japan um if if if those conversations where >> it's funny you said Japan cuz um I I was thinking I knew we were going to talk today and I've been thinking about you the last few days and um I'm working on this episode for the founder of Honda >> uh for my other podcast founders and what's surprising about that is you know

11:50

there it's not Honda the cars at this point when this guy's live it's the most he he created the most successful uh mass-produced motor vehicle in history which is the Honda Super Cub and the way they describe their company he's like we're a research lab for engines. >> Literally, that's what he's like, "All I

12:05

>> Literally, that's what he's like, "All I do is think about engines all day."

12:07

Uh, he actually separated out and made the Honda R&D a separate company cuz he thought it was so important.

12:13

And then they were just funded by a percentage of sales, but then they turned over all the research to the manufacturing division.

12:18

And he's just like, if you just have a research division and you only tell them to experiment and you staff with engineers and researchers, he's like, they're going to constantly invent new things.

12:27

And then the if you're a manufacturer, you can figure out how to apply those to products.

12:30

M >> like I would never think you would think oh they're a car manufacturer.

12:33

No I'm I'm this is a research team >> to be honest you know and you started with this question.

12:38

This is not too dissimilar from how I think about how we run 11 labs today.

12:41

I know that's why I'm telling you this.

12:45

>> It's very much look there's a focused research lab, there's research engineering on bringing that to the product work and then we have a lot of small teams running after specific product problems that we can solve and then of course the wider the go to market and deployment of how you bring that to the customers worldwide.

13:00

But it's uh the general philosophy is like a lot of small teams usually less than 10 people having flexibility autonomy to just run ahead and apply and apply their best judgment in in in what we can solve for the customer. >> Okay.

13:14

You need to say more about this though because this is where I still I'm a little confused by this.

13:17

Somebody doesn't know who you are doesn't they just met you for the first time.

13:21

They don't know what 11 Labs is.

13:22

Like describe to that person how you view your own company.

13:26

It's like a research lab.

13:28

Is that the word you're going to use?

13:29

Like how would you describe this?

13:29

I would introduce consistently the company as a combination of research and product deployment.

13:37

Research is frontier audio models, text to speech, speech to text, orchestration.

13:41

Product is one platform that helps companies transform how they communicate with the world around them.

13:49

And that can be marketing with helping them tell a story like RAMP creating their Super Super Bowl ad.

13:53

their Super Super Bowl ad. It can be support working with Deutsche Telecom on creating voice agents for their call center or it can be sales helping on inbound sales qualification to make sure that that streams through or even wider operations and working with the government of Poland to help create an agent that can take a healthcare appointment follow up with a patient to

14:14

remind them about that appointment ask how they are feeling and that kind of one combination of between those is building the research building the frontier of of all voice of all audio and on the product doing the part of applying that audio, combining that with knowledge, combining that with the creative work to then to then allow companies uh people to to change how they communicate. >> And you are solely focused on audio

14:35

>> And you are solely focused on audio >> on the research side, solely focused on audio product.

14:38

We combine the best of audio with integrations, knowledge, LLMs to help deliver for for >> Explain why you're you think it's so important to be solely focused on audio on the research side.

14:50

We think we have um incredible talent to to be able to to go after that.

14:54

The focus is so important in effectively building the best architecture for those audio models.

14:59

And this like we think audio is a there's a a good combination of not only science but also the arts that you need to solve.

15:06

It's it's a little bit subjective.

15:07

The the voices that you produce will be subjective.

15:09

Uh so you really need to get it right.

15:10

But ultimately as you think about AI models, there's data compute architecture that you need on audio.

15:17

We think a lot of the problems that still exist are on the architecture side.

15:22

We want to be solely focused on solving those architecture problems.

15:26

So you can actually get the best quality out there.

15:28

A lot of the team, a lot of that the people that that work on on our side are the best audio researchers in the in the world.

15:34

They're also excited by the premise of being able to continue deploying the best frontier audio models.

15:42

>> And do you feel you have technology on the other side that no one else in the world has? >> We think so. Yes. There's a weird analogy.

15:48

I'm so glad I'm reading this book at the same time we're talking because like uh for Honda, they kept trying to get him to diversify. He's got other products.

15:55

Obviously, he builds a bunch of things with engines.

15:57

But he's like, "Does that product have an engine?" And they're like, "No."

16:00

He's like, "Then I'm not building that product."

16:02

He's like, "I just do I focus on engines and sometimes it's on two wheels and four wheels and everything else, but it's like just engines."

16:07

It's very similar to what you're saying about audio.

16:10

And he also said that he felt he had the best engine technology in the world and no one else like could replicate what they did.

16:14

replicate what they did. There is a you know common question as we think like internally of like it's it's 100% true of well how you you described it now too and like when we think about new product the big question is do we think we have a unique advantage by applying our audio models in that product experience if the

16:31

product experience doesn't have a big bottleneck in that audio and the voice communication side then it's not our forte explain a situation where you realized that you shouldn't go after that opportunity could you give an example of what you So you're describing >> the um example would I give two slightly different spaces. One is on for for a

16:50

One is on for for a long time the um and I think it's still true the ideal version in the in the audio space is um if you create a marketing campaign is how that combines with a lot of the image and video work to deliver better content.

17:08

two years ago, we would have first try to see whether we can help people create effectively lip dubbing or avatars for um for for their content.

17:14

So let's say you switch from one lang to another, you need to move the lips or let's say you want to narrate something, you create an avatar.

17:22

That was roughly two years ago.

17:24

A lot of the models that existed on that site just weren't good enough.

17:29

enough. and deploying a product in the space would be such a defocus and such a shift for the company that it didn't have the audio as a superpower it still had a bottleneck of the quality of avatars quality of a lot of >> because the problem to solve there is video not audio >> exactly so like this was like still poor

17:47

so even if you had the best audio applied into that work it's still the experience wouldn't be very good so we decided to not to effectively um pause any of that effort for today is of course shifting now I think there's a good set of open source models now that exist in that space where the combination of audio image and video can actually deliver that result. So we are

18:04

So we are revisiting that today and the the the recent London ads engine of bringing an ad and bringing that internationally and shifting things in the video perfect use case of that but still a conscious decision we are taking is not creating the model from scratch.

18:19

So like true text to video or like you know v3 type models that exist.

18:24

We want to be at that intersection where we know the audio can give you the unique advantage which is usually you already have an existing asset.

18:31

You need to modify that asset add that audio component and bring it and bring it home.

18:35

Do you feel this like intense focus or relentless focus on audio is kind of like defense against like the larger labs? >> For sure.

18:45

>> You talk about this in the company. >> We do.

18:47

I the big part is like our focus is audio on the research side and that's where where we want to we want to win.

18:52

where where we want to we want to win. I think that we also talk about this like in the long long term that advantage that we have today will hopefully still be there but it might not be as big on just the pure research that's why the other components that's why the product is so important and that's why the ecosystem is so important that we build

19:09

around that product and maybe just to explain what I mean by the ecosystem of course there's the the the brand and trust that you built but there are also other parts that you can build and in our case this was investing into effectively a marketplace model where people can create an asset, we authenticate it and then you can share it and earn compensation as a result. So

19:26

So like trying to create a completely different model for how that works.

19:32

>> Give me details about that cuz I don't I don't >> like an example is voices.

19:36

>> So we did it with voices where people can create your voice.

19:38

We authenticate it then you can share your voice your AI voice and passively as your voice is being used you earn compensation.

19:44

We have 20,000 voices today on the marketplace.

19:48

Um, and new people that that come in now have a selection of different accents, different styles, uh, um, different languages, of course, different uh, uh, age, gender that you can pick every time you use it that person can do.

20:04

>> You as a company make these voices, any of these voices, or is it just third parties?

20:08

>> We of course created a system for people to to to do that.

20:10

And some of them we like when we see pockets that are missing, we'll ourselves try to go after and find people to fill those pockets that are missing and create those voices for the wider ecosystem to benefit.

20:22

>> No one knows about 11 reader.

20:22

You have to do a better job.

20:24

I was listening to your episode with John Carlson who I love and I don't think he even knew he kept saying he's like why doesn't this exist and you're like there's an app and then the followup he told like no dude I use that app.

20:36

What you're asking for John is he already has it.

20:37

you need to like show it to them on your phone when you were recording the podcast with them. So I use George.

20:42

That's the voice I in fact we do all these like research reports for the people that come on.

20:48

>> Being a user that's amazing.

20:49

>> No, of course it's it's it's a fantastic product and it turns every document into essentially a podcast that I can, you know, listen to when my eyes are busy.

20:58

But the funny thing is we do these research like dossas about everybody comes on and so I put the one about you into 11 reader.

21:03

So, I'm listening to you about you win your own product.

21:06

But like in George's case, is that coming from you guys?

21:12

Did somebody is somebody else getting paid when I'm listening to George?

21:15

>> Somebody else is getting paid.

21:15

That's a a great voice actor that uh that worked with us for now for a long time.

21:19

And every time you listen, he he gets paid. >> Do you understand?

21:23

When we sat down, I was like, you're you you're one I keep running into you everywhere.

21:28

And so that's was like, dude, we got to just do a podcast together.

21:30

And but like you're so confusing to me and in a great way.

21:34

This is not like a negative thing because like I was like, I don't even know how to describe your company.

21:38

You're doing all this research, but then you have all these other different products.

21:41

This is very unusual, especially for somebody that's so super focused, but you know, like it's it it is it is very fair.

21:46

And I think we are seeing that everywhere across AI companies of like, you know, the the model becomes the platform becomes application.

21:52

But for us, the unifying theme across all of them is is that angle of communication.

21:56

Like we think how you communicate as a company as you how you think about content communicate all of that is changing and we want to be at the intersection of that.

22:03

We build [snorts] the best models to help you do that and then build a platform that effectively delivers that content delivers the knowledge delivers the conversation a completely new way and that's of course there's just so many different applications.

22:15

There's 11 reader that lets you enjoy content a completely new way.

22:20

>> So research platform applications on that platform. >> Exactly. >> Okay.

22:23

>> Okay. and and and you know like we explicitly are not planning to touch any of the intelligence or knowledge work or coding not our strength not our domain but we are >> there's a vicious battle too >> very vicious battle lots of lots of great companies in there but what we would love to be is if you think about

22:41

the next three years or however many years there will be probably three platforms that you said all the interactions on those platforms we want to be the leading platform for those interactions for that communication way explain that >> the whole way and and that kind of builds on that theme. How you engage

22:57

How you engage with content, how you engage with the the that company will change.

23:00

We want to help people, companies have one place, one platform where you can set it up, you can set up your integrations, you can bring your knowledge, you can bring your brand, you can bring bring your assets from from the company and then deploy that for entirety of customer journey.

23:17

Whether that's in the marketing example where you tell that story through content, capture that knowledge back about the user.

23:25

user. Whether that's in sales when you're trying to engage and bring their your product to that to the customers whether you are supporting that across the customer journey or maybe in a simpler way as you're trying to understand the customer journey every onbrand interaction that that journey has we would love to be able to capture and help you make that better for >> okay so let's let's make this concrete

23:46

because I still like I want to be able to wrap my head around this let's take your like most deeply integrated customer yes >> right and say you know it's Goldman Sachs I'm making this up and this is how they you they use this product all the different products they use like who is the the company or one of the companies that is most deeply integrated with your company and explain how all the

24:06

different suite of products that they're using that are powered by your technology telecom is a great example they will use a lot of the audio work to create their podcast and their app and the magenta they will do that for the ads so they can create ads and distribute that to their audience they will a lot of our 11 creative work to be able to do that then they will use a um uh uh our 11 agents work for in call

24:31

center where you call in you want to help you get that help through the voice agent integrated with the knowledge from docom so you can um make sure that if you somebody's calling in to learn about the product they get information very quickly if they are calling to get support on how to um get a refund or the recent billing request they can get that help and then more recently they even deployed agent inside of the network. So

24:54

So if you are a T-Mobile subscriber, if you call, you can ask agent to join the call and help you out, schedule a booking or real time translate your conversation to the other person and they'll use our effectively combination of agents work and bringing that real time dubbing to be able to communicate in other language and that across all of that all of that information is captured back.

25:17

So you understand how customers engage with uh with in this case with the the full spectrum of of of the journey marketing the support and then the wider operations even sales and we help them do all that. >> Okay.

25:32

So in a situation like that cuz um I think you you mentioned like obviously a huge increase in your revenue that's growing really fast is like you're targeting bigger companies, right?

25:40

What was the first product Deutsche Bank used from you? >> Uh do sorry.

25:47

Yeah, the the first was marketing.

25:49

So it was two years ago we we we the the kind of the most of the that the the two years ago still most of the agents weren't really very very good.

26:00

They they weren't very reliable. They weren't very quick.

26:01

So marketing was the the most the most obvious one.

26:03

So they started with that.

26:05

They deployed that the quality of the content was was uh was great.

26:10

Um so people could engage with the podcast effectively.

26:12

the use case that you mentioned of like you know bringing your um uh uh uh notes and then being able to read them out loud.

26:19

They were just creating that daily for all the customers so they could read about what's happening in the world through the podcast with 11 voices.

26:26

Um so that was the first use case.

26:29

Then of course support is a combination of voice but also the integrations.

26:33

Let's talk about how you expanded them from one product to the next.

26:37

Like how do you actually do that >> in that case?

26:40

The main and I ask mostly like how do we partner with them to help them bring that product to life or >> they start with one but you have 10 different products you could sell them.

26:50

So how do you go from one to two and then two to five and so on and so forth?

26:54

>> Yeah, I think the main thing is one um you of course deploy the first one you make sure that there is value behind that.

27:03

So across any customer engagement we try to make sure that we don't only prove concepts we prove the impact prove the value and only after that we try to get the companies working with us at the broader scale.

27:13

So we proved the impact on the marketing side to get the support going.

27:17

What you actually need to do is not only the audio you need to build the integrations.

27:21

So you need to connect it with all the CRM systems that that Deutsche Deceio how you make sure that that connection exists.

27:36

So you would spend a lot of time on integrations making sure that their logic is respected on how when you do pick up the phone call the agent behaves the way you want it to behave.

27:44

So here are four deployed engineers would partner with the team spend a time and and bon in this case in Germany working through side by side together on the integration on just being able making sure that the agent follows the flow that you want has the knowledge that it should have and then in that step the the hardest thing in any voice agent uh work is actual deployment of how you actually test that it works.

28:08

Um so then you need to trial that with uh with initially simulated that you verify the calls then you do it at smaller scale >> and you're doing this with FTEEs.

28:19

>> Yes, we do all that with FD then we deploy and then of course we scale over time.

28:24

>> When did you realize that a huge path to greatly increasing your revenue was doing FTEES >> and before I answer this and of course the last part is you know like as you deploy the job isn't done.

28:32

You still want to continue evaluate monitor and refine the behavior over time.

28:37

Um, and that applies across all of the all of the use cases.

28:41

NFDs for that are great too.

28:43

Um, so I used to be at Palanteer, so it's a it always felt like a like a big like a big thing of how we want to work with with customers.

28:50

It's like almost I don't like the word customers because like in many ways I feel like all of them are like partners where you are working together on on the same problem and trying to solve that.

28:58

So there was a lot of the philosophy of the FD was there from the start to make it specific working with the partners side by side on their problem.

29:10

>> Hold on this is actually really interesting.

29:10

So tell me what you observed that was working at Palunteer were like if I start my company I want to do that too and why?

29:17

I think the the the most incredible thing was that like you were meant to be on the same side of customer obsessed of their problem and and try to understand them deeply from the beginning.

29:32

So I used to work at Black Rockck before Palanteer in Black Rockck when I joined given the compliance security the first month or two you when you send an email it gets verified by by your team gets trained before you send it externally.

29:47

So it's like a a pretty detailed flow of making sure that it's good.

29:52

In Palunteer when I joined after the on boarding in the first month I'm like okay you now need to work and understand a customer you're flying to Aberdine to North Sea to work side by side with them understand what's happening and then bring it back.

30:06

And that was complete shock for me and like the kind of the approach and culture of like I have never almost interacted in a customer on the blackbox side and now here I am in the first weeks and like meant to go there and like be next to them which was crazy. I thought it was great.

30:21

great. I thought it was that mentality and like every time kind of you are going to be there on the I'll call it front line loosely on the front line uh to to work with them and bring that knowledge back understand what is actually the problem what's fixable

30:37

problem and and and and then actually fix it um and that mentality is so true now at 11 apps too where all of our FDES our go to market team too is is going to obsess of like how can I actually be there with the customer understand the problem and and work with that. There

30:52

There was other companies that I think were great.

30:54

The small teams, they had usually small deployment teams that worked on on a lot of that that the best idea wins.

31:00

Um concept was very true where in that small team you very quickly assembled the best knowledge of what you think should be done for that customer and you had power to then actually enact on it.

31:10

>> Define small >> about five people was considered implant big and in 11 laps is going to be also relatively big.

31:15

relatively big. I'll tell you something more though on the FD side because of course now you probably see every every company doing FDES and in our case FDES are part of the product team they are not part of the go to market team they are part of the product team they

31:31

they are deeply embedded on understanding what's the road map of the product but there's a second reason which is one you want all the fds to actually solve the customer problem and stretch your product in that direction but second thing you want them to do is bring any of that knowledge back to the product. So the product becomes better

31:47

So the product becomes better for the next generation of companies building on top of it.

31:51

And I feel like the second part is always that frequently uh missed was like first okay if these are you know doing effectively a lot of the the the hard integration work to solve the problem.

32:05

But if you don't do the second step of how you actually learn the the expertise and bring it back to the product then it's effectively just services or or just u just >> wait say more about that second part.

32:15

So you're get you're gleaning information through trial and error working closely with them.

32:20

Then you can take that back and spread that knowledge across the other tens of thousands of customers that you have.

32:26

Is that what you're talking about? >> Exactly. >> Okay. >> Exactly.

32:28

And it's a product knowledge of like how you operate with you know there are simple things.

32:32

Let's say you build an integration.

32:33

How do I now have that integration available to everyone that's a simpler version of that but let's say you are working in healthcare space.

32:42

In healthcare space, if you deploy the the the the work, then you want to optimize the product experience for the right uh uh the if you are not starting as a second customer, you want to make sure that you have >> so wait a minute, you're using you're using your customer base as almost like R&D, another form of R&D.

33:03

>> You are definitely accelerating your R&D through understanding the domain that that that you're working with.

33:07

And it's a it's you know >> their problems are not very rarely a company's problems is unique to that company. >> That's right.

33:13

And that and the beauty of that is like kind of everybody benefits because you work with one customer you learn you bring that into the product experience.

33:20

You learn with another one you learn you bring that back to the product experience.

33:23

Both of those customers benefited from having the product optimized um for the better work.

33:29

The domain expertise they have is still theirs.

33:31

You can win based on the domain expertise but the product experience of how you build based on that domain expertise can be abstracted can be reusable.

33:39

>> What else did you learn working at Pounder?

33:41

>> They also uh were very u very much of no title organization which we carry over at 11 Labs uh which does help in that in that best idea wins approach where people do feel um I feel like I'm mimicking you on the on that shirt.

33:56

[laughter] >> I thought the same thing.

33:56

I was like you don't have to if you don't want to.

33:58

It's I know it's a complete coincidence.

33:59

Uh uh change >> we're leaving that part in.

34:03

[laughter] >> No titles, relatively flat organization, very few layers.

34:07

So it's like all you know between me and and and the seuite I worked there before the DPO it was four five uh steps or or less.

34:16

So you always felt like a proximity between Yeah, I think it was like four or three actually.

34:22

So like there was a good proximity of being able to to to to work together.

34:26

At 11 laps we have a couple of five today like maximum uh depth of of of of how many layers there should be and and hopefully over time actually there will be fewer no more layers if if AI helps you run the organization the way we would like to run.

34:42

>> Well say more about that.

34:42

What do you can you not do today in the way you run your organization that you hope AI can change in the future?

34:48

I think there's u like always you want the information from the the the kind of the the person working as closely to the problem.

34:58

So let's say you're developing a product you want to work you want to speak with the engineer that actually develops that product rather than their manager.

35:04

If it's a client conversation similar you want to understand what is that client saying from the person on the ground rather a manager summarizing that information and giving that to you.

35:15

And I think that that information flow will change with AI where you will have access to everything that's happening in a better granularity than you could ever have before because it summarizes that back and back and forth.

35:26

Second, I think that in general roughly at 11 laps, most people will have close to 10 direct reports.

35:35

So pretty pretty wide B set which helps us build that small team approach that we that we have.

35:41

approach that we that we have. And that too only works if you if you can amplify a lot of what's happening across all the teams all the people that you that you work with and to summarize information of what's happening in their teams how they performing what are some of the

35:56

gaps that definitely helps and helps shift it from reactive to proactive I think too by what I mean by this is frequently in the past I think you would rely on on on specific individuals surfacing the information to you now as we think about 11 laps and we run is that you can summarize all what's

36:14

happening all the data of what's working what's not and you get that signal I get that signal and I can proactively engage on where I think it's not working um which helps it helps of course everybody across the company because you you have that same ability wherever you are I think that the the the maybe last last

36:30

part which is very related to those two why it's even possible today we we took a choice to be extremely transparent with with a lot of the the data that we have uh a lot of the the docs that we write so everybody has almost access to all the docs that are there in the company. Um, which ultimately helps you

36:44

Um, which ultimately helps you create that system where you can actually tap into that knowledge. >> Okay.

36:51

So, I want you to say more about this because I think this is one of the things I want to talk to you about cuz you're relatively young.

36:55

This is your first company.

36:56

Your first company you built, you got into AI right away and then you were perfectly positioned for this huge explosion.

37:03

Obviously people have been talking about AI for 80 years or whatever but like you're at the right place right right time with I think the right set of skills based on what the company you built so far.

37:11

So like how different do you think in the future the way you run your organization can be than what it is today?

37:19

>> I think the small teams approach will definitely be there across across many of the of the of the companies that I I I believe will be created in the future.

37:28

It also helps with like very different piece which is like if you just think about adopting AI technology in our case it doesn't have to be a top down mandate of like you need to use this technology to get better and then the teams enable others given it's it's relatively small

37:42

and independent people bottoms up adopt what they think is best and are able to run with it straight away so that helped a lot in that sense I'll give it two others which we believe strongly on one in in a lot of the small teams that we have and of teams that we We bring even nontechnical teams. We bring engineering

37:58

We bring engineering talent in those teams.

38:00

So our talent team, our ops team, our legal team, all of that will have engineers that help both automate some of the work but also elevate everybody else in in in in how they are using AI.

38:13

I think that will be a bigger pattern in the future across the companies too where I think increasingly some of the the biggest and smallest companies will try to infuse all teams with engineering resources so they can they can get smarter.

38:27

>> Is there any function that is like centralized at 11 Labs that then all these small individual teams can then access like um I spent some time with Luca Ferrari of Bending Spoons >> and he had this >> wild idea wild idea to me where he's just like well HR is actually really important.

38:42

He thinks like the fact that tech people are like dismissed of it is like ridiculous.

38:46

And he's like, "But my HR is like 50 people and they're all engineers."

38:49

And then it's like one centralized HR that every single other cuz he owns I don't know how many companies.

38:57

They all utilize it, but it's just like 50 I think 50 engineers in HR and then all the different structures, teams and companies he has like tap into that for that resource.

39:08

>> Of course, there are centralized functions.

39:09

functions. Legal is a good example of of of course of like how we are running that needs to be very central enablement of how we help people across go to market and other teams how they are kind of learning the craft of of how to sell 11 laps and as you said it's you know there's so many different products you need to be very particular about how you

39:29

deliver that to the specific customer so it's not confusing the customer and in in in what we are offering or what we do so so yes so so there's a good amount of those functions But they they all too similar to Lucas approach all of them will have a good amount of engineering in them and figuring out how you scale that operation. So it's not becoming hundreds

39:47

So it's not becoming hundreds of of people in all locations but how you can use the few people that you have and and really bring that knowledge everywhere.

39:55

One of the biggest one for us is is is probably around revops of like how you or like the revenue engineering effectively function.

40:01

We have so many tools that help you get the knowledge um whether it's code during the conversations, transcribe, bring it back, make it easier for you to to to fill on a field so you capture that knowledge and and then don't have to spend manual time.

40:18

And then of course increasingly we dog food a lot of our own work.

40:21

So we're trying to figure out how we can create AI agents to help replace part of that work but still operate within the team.

40:27

So a good example is AISDR.

40:29

people going on the website today on 11 apps.

40:32

You can fill in the drop down form uh and and leave information about your company, but you can also speak with uh with voice agent and leave that in a in a in a in a quicker and and and different way.

40:41

So, you've seen a lot of people go through that flow uh and then interestingly two things happen.

40:47

One, people are both making their experience easier, they enjoy it more, but two, they leave a lot more information than they ever would for the drop down form.

40:54

tell us so many about the problems about the wider set of use cases so we can connect them better.

41:00

>> That's really interesting.

41:00

So because they're speaking and not typing, you get more information >> 100%.

41:04

It's uh I mean it's of course a quicker way of doing it, but also people just feel more at ease instead of, you know, going through this manual drop down form.

41:12

It's just uh just a a better I feel like a better way on on leaving the information.

41:17

the information. Um but now because it's it's we think it's going to be such a big part where everybody every company will have their revenue engineering function but in our case we want that kind of AISDR function to be part of the company we don't we we want it to to to

41:34

help everybody across wherever you are we are global company so it's central and then deployed to each local team so each local team can refine it for the local local new ones but developed of course centrally I found one of my all-time favorite quotes when I was reading the book 0ero to1. The quote says, "The single most

41:51

The quote says, "The single most powerful pattern I have noticed is [music] that successful people find value in unexpected places."

41:56

And they do this by thinking about business [music] from first principles instead of formulas.

42:03

That is exactly what Apploven has done with their advertising platform.

42:06

Apploven connects you with over a billion potential new customers [music] inside mobile games.

42:10

Apploven allows you to capture undivided attention.

42:15

Apploving ads [music] are full screen video ads that are watched for an average of 35 seconds.

42:19

That is retention that blows other ad platforms out of the [music] water.

42:24

And you can launch on Apploven in minutes.

42:26

You set the goal and Apploven achieves it.

42:30

There's no complex [music] setup, no expertise needed, and Apploven scales quickly.

42:35

They can put your ads in front [music] of over a billion potential customers.

42:40

Other businesses have seen immediate results have scaled to hundreds of thousands of dollars of spend per day and increased their revenue by millions.

42:47

So you want to get started quickly before all of your competitors are on AppLoven.

42:51

And you can do that by going to apploven. com. That's apploven. com.

43:00

You still think of 11 Labs as a single company just with how many how many different products do you guys have right now?

43:05

Uh we have uh three kind of core product lines and then we have additional three that are developing developing bets.

43:14

>> But how many different like applications?

43:17

>> Well, within each of those we'll have say no but like let's say six are the kind of the core and then within that you can do of course maybe like you know 20 30 different things.

43:26

>> Yeah it seems like you have a ton. >> Yes.

43:28

>> Like 11 reader for example. >> Yes.

43:30

But it's you know it's like learn reader or learn productions which help you with the human loop human loop aspect to correct the content and localize that to another language.

43:38

>> Where's all the revenue coming from?

43:39

>> The biggest lines are on the on the on the agent side and the creative side.

43:41

So the the number of use cases that deploy conversational agents is is is just skyrocketing today for us.

43:50

>> And are you seeing a specific industry that's adopting them faster or no?

43:54

>> The I think the quickest today for us is fintech.

43:57

Super quick >> like Revolute. Revolute. Exactly.

43:59

Clara, Pug Bank, like all of those companies are are just moving moving moving at another speed or customers bank in US here.

44:08

[snorts] Um then uh the healthcare, retail, e-commerce and telos are the four of the biggest ones.

44:16

Fint is moving the quickest of course it's you know slightly different regulatory aspects.

44:22

Um but then I think the healthcare telos is kind of the second and retail e-commerce is is just this year started started going for the wave.

44:30

>> I want to ask you one more time.

44:30

I just want to go back to this in case we missed anything.

44:33

Is there anything else that you learned working at Palunteer that we didn't talk about that you think is valuable?

44:37

Well, this is a stretch and I'm a biased biased, but uh in Palunteer frequently there was this concept of like how um how you you you need you need a little bit of the understanding of the art to do your job well or like people need to uh uh um need to effectively try to be artists even if if if if we aren't.

45:00

uh uh like one of the phrase that was used was artist colony if that was ever publicly said.

45:07

said. I never fully appreciated the strength of that but I do feel like a lot lot more about this now as we kind of intersect that AI and creative space in many ways whether it's building the audio research models there's a lot of nuance and how that's delivered like even the every voice that is delivered

45:25

you like George and 11 reader like everybody will have their own preference and and how you make sure you capture those voices how you deliver those preferences is is is a tricky challenge and then two as you work with some of the brands that are trying to define how they communicate with the world. that too requires some a lot of the of

45:40

that too requires some a lot of the of the of the art in that and we're trying to to bring of course a lot of the the people to combine that but blending that art and science panter definitely tried to do I think I'll let judge to it successfully but we also will will try to do and and and and hopefully are

45:58

doing good steps in that direction whether it's the voice marketplace that we spoke about uh whether it's having a lot of creatives in the company building projects with us or or around us or the kind of for engineers or for the creatives almost to to work with the customers. I think that blend will be

46:11

customers. I think that blend will be increasingly important and everybody talks about taste now how like taste will be defining front of of AI and um behind the buzz word I think there is there is a lot of truth to that where yes increasingly everybody will be able to create everything and um and what

46:28

defines above good product experience good deployment experience will depend on on on um on how the design language sounds how how how tasteful it is how you bring that across so I think you tried to do it we are trying to do it too >> yeah I think what you're getting at is there's this guy named Edwin Land. Uh

46:42

Uh he's the founder of Polaroid.

46:44

I discovered him because um he was Steve Jobs hero and Steve Jobs was talking about >> Yeah, I remember it.

46:50

>> I've talked I talked about on Founders episodes over and over again.

46:52

I should get a framed picture of Edwin Land and like put him in the studio or something.

46:57

But uh he was the one that invented what the idea that Steve Jobs used where he's like I want to build a company at the intersection of technology and liberal arts.

47:03

And the reason he just came to mind is when you brought up taste, he has this great quote where he says taste is as rare as a unicorn.

47:08

And so it's like people talk about all the time, but it is definitely like a limiting factor and it will I think like will always be like a limiting factor. But I love this idea.

47:18

I think this is my issue with a lot of um why I don't live in San Francisco.

47:21

Francisco. Like I drop in there, we do a bunch of recordings, obviously have a bunch of friends that are tech founders, but it's just like I feel this J like the new crop of tech founders is like they they they lack the humanity where

47:33

like one thing I liked about Steve Jobs or Edwin Land or the founder of Honda, they would say over and over again, it's like I'm just inventing technology to enhance humanity where I think a lot some of these people is like I'm inventing technology to replace it. So

47:43

So this leads me to another thing that I wanted to ask you about since you worked at Palanteer.

47:47

You've seen Alex Karp be one of the only people and he's done it for like a year and a half and now it's like really really like I think caught his perspective has caught on where he's just like if you're running these labs and you keep going on TV or giving interviews talking about I'm building like nuclear weapons grade you know technology and it's going to take everybody's job.

48:05

I see too many conferences which I want to ask you about.

48:09

>> No, I haven't I haven't been there. >> Okay.

48:10

So I was just there I was only there for a few hours and and Karp was the one that uh spoke first and he's just like what do you think is going to happen?

48:17

He's like your technology is going to get nationalized.

48:19

Do you have any opinion on what like his perspective on this? >> Not directly.

48:23

So, so of course you know we've seen what happened at Antropic case recently uh given we we we we spent um and most of our team is in Europe spend a lot of time with the European teams and governments of how we think about building sovereignty and and and and how important this this this will be.

48:39

Uh so no direct answer to your question.

48:41

I do agree so much with the the other part of what you said which is AI really needs to work for the people.

48:46

is to amplify human potential rather than replace it.

48:49

And um and I and then and and I I hope we will do a lot of of the work and are doing a lot of work in that space.

48:56

But I hope in the some of the interviews that you mentioned and some of the the conversations from other companies um that this will be an increasing theme of how how they can bring that to to reality too.

49:07

The reason I um bring that I ask you that question is because uh I think me and you were at a dinner with Scott Woo, founder of Cognition.

49:15

I just recorded an episode with him.

49:17

I've spent a bunch of time with Scott over the last few years, even before they launched Devon.

49:20

Um I met him and what I think he does well and what you do well is you guys are always talking about the positive benefits that your products are creating for people.

49:31

Like I think you told the story of a woman had lost her voice before she got married and then she worked with you guys to recreate and so therefore she could essentially redo her vows in her own voice.

49:43

It's like a perfect example of that.

49:46

>> Voice is such a incredible identity that like probably and the case that you mentioned is some of our proudest work where we can work with people that lost their voices to LS due to fraud cancer and work with them on on bringing it back.

49:59

That is that is one example.

50:01

Recently we uh we we worked with a musician that lost his voice.

50:04

Um and he wanted to still perform.

50:08

So he worked on recreating that voice.

50:10

Um we we set out a concert and he did a concert with his old band together with a AI voice.

50:19

Um and now he's touring and in UK he's going across places and and and and and touring across um or or our or congresswoman last year lost her voice and still wanted to inspire others to do the work and and and was in the in the congress with for the first time with AI voice trying to to bring that to life.

50:37

Um and the I mean the common theme is like the voice carries s such an like additional element of of emotional impact of of recognition.

50:44

you the moment you hear someone's voice, you recognize it if you know someone.

50:48

Um, of course that has a second part which is like how we safeguard and how you think about safety across that future where voice can be created.

50:56

Uh but yeah, that's that's the the the work across there the the the um today it's over 10,000 people where we worked on on bringing their voices back and um and hope to continue that and outside of the the accessibility space of course what what happens in education wider culture here to we partner today with 800 organizations to help to help bring the technology to to the people out there. Isn't that a crazy one?

51:22

Actually, that's a crazy story.

51:24

Recently, uh, sorry to interrupt you.

51:26

There was um the there's a like first of all, a legend, a guy called Tim Green.

51:32

He used to be a best-selling author, a uh one of the top NFL players.

51:35

And then unfortunately, he got ALS and and couldn't do a lot of that work.

51:41

And from all the things you could imagine him doing, he decided to go the complete extreme and he did a podcast.

51:46

So, he started a podcast.

51:48

I'm gonna have to find this guy and chase him down.

51:50

No, >> it's a Well, you should you should have an interview with him and he he's >> That's not what I meant.

51:55

That's not what I meant, Maddie. >> Okay. Okay. Fair. Fair.

51:59

>> Then I will destroy him.

51:59

No, [laughter] >> but he he's uh and he does extremely well.

52:05

He he has great guests at Harneck recently on on his podcast, some of them flare players.

52:11

And uh and this year he won an Emmy for his work. So it's like, wow. So he's uh incredible.

52:16

Wait, so you made that voice though?

52:20

>> We we Yes, we we do his AI voice. >> That's incredible.

52:23

>> So that was uh one of our proud small brick contribution to to his work, but it's it's just so crazy like how like, you know, it's like the most extreme thing you can do and and and he does it.

52:36

He inspires I I don't know how many people got got inspired, but like we had from hundreds to thousands of people reach out that thanks thanks to him on like how can we get our voice back too in the same way.

52:45

Well, I think you hit on something which makes is one of the reasons um and I discovered this accidentally is like what makes podcasting so powerful is the voice where it's like you know obviously I like love to read.

52:55

I mean there's books all around like scattered around the house everywhere obviously have like I don't know I have like a thousand books in my other library like probably 600 unread um and there's some authors where I literally just fall in love with what they do and read every single thing they've ever written.

53:11

But if you would ask like my emotional attachment to my favorite authors or my favorite writers like Cormack McCarthy for example in fiction compared to like my favorite podcast which is like not at all comparable.

53:21

It's like I feel like I know because of the voice and like the the human like element of that I just feel like I know them in a way that I could never know like my favorite, you know, writer. >> For sure.

53:31

I mean you also it's it's it's a you're in the conversation now and it's like you you the voice carries so many other dimensions than text.

53:37

many other dimensions than text. like text of course you imagine you interpret but it doesn't have [snorts] the emotion it doesn't have the inonation doesn't have the imperfections it doesn't have the pauses >> the imperfection is really important cuz you know some we have some guests that come on here and they're like okay I said like too much it's like that's how

53:52

you speak it's like we yeah we can edit it out if you want but like I slur my words I say I make all these kind of weird things like but that is just how I am I don't ever want to be appear on a like a podcast and you meet me in person it's like this guy doesn't even sound the same like the imperfections people admire imperfection ction or excuse me authenticity way more than they do perfection. >> That's true. You know, it's actually >> That's true.

54:13

You know, it's actually finally even applies in a a non-human way, in a voice agents way too.

54:17

We we initially we are trying to create a perfect voice agent that doesn't do any sound. It didn't sound human.

54:24

And then of course the obvious thing and that that that was the clearest is like the ums themsel like skyrocket.

54:35

Everybody was like wa this is so human. This is good.

54:37

I am happy to speak with that.

54:39

So uh so yeah it's making it imperfect.

54:41

It's almost now the the the element of that but voice does carry that information.

54:46

It it kind of connects you in a completely different way.

54:50

And why I think also it's such a hard research challenge because here you know in text you don't have that many of those um of of of those dimensions.

54:58

You need a lot of data of course to create a good language model but you don't have the dimensions of every voice being different every voice sounding different to every person.

55:06

Um so like even doing benchmarks for text to speech is extremely hard because usually different models will have different voices that already makes them uncomparable.

55:18

Did you know when you were younger that you wanted to be an entrepreneur?

55:23

>> I I would say I didn't know this was the path for >> You did or did not? >> Didn't.

55:27

>> I was, you know, I uh >> Cuz you're European. >> In Poland. It was Yeah, for sure.

55:30

A little bit of that though.

55:32

I you know, you're joking, but I think it's true.

55:35

>> No, I'm being serious.

55:36

>> Taking like the the risk of of like not, you know, like starting something.

55:40

It it wasn't like a common conversation ever happening.

55:46

happening. I mean I had a lack of having incredible family that kind of gave me opportunity to study abroad and then that kind of opened your eyes of like okay now you can work with some of the great companies and then when you work with those great companies then you realize like you can actually do things

55:59

you can like pantry was great for that for sure where it's like you can actually go and work with the customer try to figure out the problem you can take that seemed very risky to me but you can do that um so kind of step by step that opened the eyes of like okay maybe this is a path maybe it is

56:13

possible to start your own thing and from the time you had that realizations at the time you started 11 labs what was the >> so then as you kind of >> was it a year two years you were like what was it >> so over my time as a pantier my co-ounders p time at Google we would do start doing a hack weekend projects

56:29

together so through the years we try to explore new technology and build together I think few years prior we we knew that we would love to work on something together but um but you want to work something about that you are like you think it's a true problem and you're obsessed about and um and And that came to us in 2021. So a few years. So a few years. Two years. Two, three years.

56:49

>> How many acquisition offers have you had? >> Like concrete ones? Three or four. >> When's the last one?

56:55

>> Last one was last year. Like June last year. >> You going to sell? >> No.

57:00

>> The reason I ask you, >> AI is changing the world.

57:01

We can build at the frontier of that change.

57:03

We we we are we are we are going all in.

57:05

This is uh this is I mean then don't pay attention to your VCs, dude.

57:11

>> Their incentives are different than yours.

57:13

The reason I ask you is there's two two reasons this came to mind.

57:14

And you know, some of this is like all intuition.

57:16

You can't even describe this.

57:18

But Evan Spiegel sat in that exact same chair that you're in.

57:20

You know, people gave me They're like, "Why you want to interview Evan?

57:23

Uh, you know, look at his market cap."

57:26

I was like, "I don't give a about his market cap.

57:28

Like, I don't look at companies that way.

57:29

I'm obsessed with products and like that dude has soul in the game."

57:31

Like, and I hope he wins.

57:32

I have no idea like I I I don't know anything about, you know, just I don't you like Snapchat Specs, anything, whatever.

57:40

just like he is differentiated.

57:42

I just there's just something about him that I like that I like just want him to work out well, right?

57:48

And so that and I'm getting the same exact vibe.

57:50

I was like, man, I want Matty to like win. I want him to succeed.

57:53

There's just something very likable about you.

57:54

And then the second reason is because obviously Scott Woo, he's he's coming on the show like every few months because I I really like Scott a lot. >> I cuz he's genius. He's so so good as well.

58:03

Not articulate and brilliant and optimistic, but everybody is running at that dude right now.

58:10

Everybody like the the amount of people that want to buy his company and this is something we talked about and like I hope he holds out because I I would like to see a lot more people just be like, "No, I'm like in this forever.

58:22

It's not just to get a big bag of money, you know, like you go listen to to to Travis from Uber, you know, he made billions and billions of dollars from Uber and he's just like that did not make me happy.

58:32

I need something to work on.

58:35

Um, and see that's why that answer the question cuz I asked Scott that too and he's just like well there obviously a ton of people trying to to either get him or his entire company and all his talent and he's just so far said no I'm not selling. >> Love Scott.

58:49

I think they should build independent company too.

58:51

So I think they have an opportunity to be one of the hyper AIs of the future or or however you call the the hyper clouds of the future.

58:59

Um so I think he I think he can do it.

59:02

He's he he has they have a incredible team and I think we can do it too.

59:06

I think it's you know well I I really mean it.

59:08

I think the opportunity that um that currently exists for entrepreneurs of of with the wider shift the the things haven't been written and it's like it's such a such a good good time to build something special and and >> I think shows like this are really important because most of the podcasts are made by VCs, right?

59:26

It's just like the content that entrepreneurs >> the content that entrepreneurs >> self- serving in many ways.

59:31

I feel >> well the content entrepreneurs are consuming are created by VCs.

59:33

This is a weird thing to me.

59:35

Um, and what I would say is like the amount of founders that I've talked to that have sold their company are like Like like I had something, it was going really well, they gave me a bunch of money, now they tell me what to do.

59:46

I was like, what did you think the money was for?

59:48

Like no one's just going to give you a bunch of money and then you still retain the independence to do whatever you want.

59:53

And then it's in all these freaking biographies from Ted Turner to like there's just a million people that talk about after the fact.

59:59

And they got huge bags, billions of billions of bags.

1:00:01

Like I'd give the billions back if I could just have my company back.

1:00:04

And listen, man, I think you're smart and driven, but highly likely like 11 Labs is probably the best idea you will ever have in your life. And you're how old? >> 31. >> Okay.

1:00:14

So, you're going to sell your best idea at 31.

1:00:16

You got four decades ahead of you. Maybe five. Hold on.

1:00:18

And you're going to work on your second, third, fourth, fifth best idea.

1:00:22

Dude, the money's not worth it.

1:00:24

It's not worth You're going to get the money anyways.

1:00:26

>> The Well, you're convincing me something I'm already convinced of. >> I know.

1:00:29

But, but they all say this the founders all say this and it's like really hard when they're just like, "Dude, I'm going to drop 50 billion on you."

1:00:35

Like it just just the numbers are getting crazy.

1:00:37

So, I understand why people do it. I'm not knocking them.

1:00:39

I'm just saying I would like I'm very interested in entrepreneurs >> that there's no price.

1:00:45

>> Like again, I've repeated this over and over again.

1:00:47

It's super important to understand.

1:00:48

It's like everybody's like, "Oh, if you love what you do, you do it for free."

1:00:51

No, there's another level.

1:00:51

If you love what you do, they couldn't pay you to stop.

1:00:54

How much money would you have to give Steve Jobs and say, "I'll give you two trillion, Steve, but you can't work in Apple." He'd say, "Go yourself."

1:01:01

There's not a dollar amount in the world that could stop him from doing that.

1:01:04

And the world is better because he didn't stop doing it. >> I'm with you there.

1:01:07

It's you know the the I I agree.

1:01:10

Many people I think will say it.

1:01:13

In our case, we had a lack of having acquisition offers which we turned down and that was not not not an option.

1:01:20

And any of those acquisitions would you know it's not two trillion but they would have made made life u easy of course.

1:01:28

Um, but it's not I think it's that in itself should never be an interesting proposition.

1:01:33

And like you said, it's like, you know, we do appreciate this is likely the the best idea, the best timing to have that like the kind of lack of when it's all happen is such a such an incredible coincidence and like I don't know how the world will look like in 5 to 10 years like how will the universal high income piece and conversation come in?

1:01:53

How the wider society will adopt the technology?

1:01:54

How will you actually provide advant like all of those questions are out there and I think they will be a big part.

1:01:59

So, of course, the the best thing the big thing we can do for the world and for us is is just to continue building.

1:02:06

>> Did you read um Scott Woo's piece in Colossus, the Colossus magazine?

1:02:10

No, that's done by my friend Patrick.

1:02:12

I'll text it to you right when we're done. It you can put in 11.

1:02:14

[laughter] >> I'll listen to it on the way.

1:02:18

>> Put an 11 reader and listen to it.

1:02:18

But I loved what his perspective was at the end.

1:02:22

He's like, listen, >> you know, he thinks he same thing, right person, right set of skills, right time.

1:02:27

thinks is teaching AI how to code uh teaching computers how to code um is you know one of the most interesting problem he could think of and he's like listen I could accept that if I try and fail but what he felt was intolerable I forgot the word he used but it's something like intolerable is like I didn't even try

1:02:45

>> like so I was just like he's like I just want to give this one opportunity the best opportunity in my lifetime which he understands he's like around your age too he's like I'm just going to give it everything I have and see what happens It's like some version of uh uh like biggest risk is not taking any risks. Um

1:02:58

Um in some version of like you should just go after it.

1:03:06

>> Does your your co-founder think about this the same way?

1:03:08

>> Yeah, he's also all in he doesn't like public presence uh as in like interviews, podcasts, but he he truly is a genius.

1:03:15

Uh I hope one day he comes on the podcast too >> anytime he wants.

1:03:18

>> anytime he wants. He is of course a great researcher but beyond the researcher he also can bring a lot of those ideas in in business and other parts of the of the space and kind of understands what's happening and how it happens but on the research side um you know the the kind of the definitely AGI

1:03:34

pilt and and how that world will change is is very deeply in his mind and and he knows that he's he can be and he and now the wider research team are all part of that change so it's it's unique opportunity I think all of us realize that how unique the timing is and what we can do with that timing and what we can do for the world. I think that's

1:03:53

can do for the world. I think that's like it's you know that we are 4 and 1/2 years in as a company and at scale it's crazy >> because your opinion is that the next form factor isn't a device it's actually just the way you're going to interact with AI is just your voice

1:04:08

>> 100% will be one of the biggest ways like in in general intelligence keeps developing the next bottleneck of how you actually get access to that intelligence will be how you communicate with that intelligence how you collaborate with that intelligence and we can solve that we can solve that for for for everyone out there. >> 12 months from now, how do you think the

1:04:25

>> 12 months from now, how do you think the way you communicate with AI is different than it is today?

1:04:28

Then >> voice is definitely part of it, but it it kind of understands you.

1:04:31

It it is it's it's able to connect the IQ plus the EQ part of it.

1:04:36

Emotionally, understand you, knows how you're feeling, can adjust based on that, can pause, can think, can reinsert itself into the conversation.

1:04:45

into the conversation. Like you know in some crazy way through the decades we we learn how uh how technology around works and learn the language of that technology like keyboard the screen uh the coding languages even they're like

1:04:59

kind of you you need to learn how the technology works so you can [snorts] uh control it and now what I think we can solve is flip it back to how we want to communicate how the most primal way is voice comm conversation and you can bring technology on our terms. So, so I

1:05:14

So, so I think 12 months from now what will happen is is similar as we are speaking.

1:05:20

It's I think the the technology will be able to understand us at the and an incredibly better way both our knowledge both the emotional part of that conversation and deliver similar conversation we are having now. >> Yeah.

1:05:33

And if that's the case then the market for this and even the the use case the amount of people using AI will drastically explode.

1:05:38

drastically explode. But I think there's a actually historical equivalent that just popped to mind when you were speaking where it's like Alexander Graanbell was talking about the difference between the telegraph and the

1:05:46

telephone and you know the telegraph could send messages over long distances but you had to learn how to program it and use it and you had to learn like learn this language to send it and he's like the phone you just pick up and do exactly what you do already. >> Yeah 100%. >> Yeah 100%.

1:06:02

It will uh I think you know like even even I'm looking at around the room I feel like there'll be so many devices as well that will just be able to work on your terms.

1:06:09

Hopefully the screen the phone will like kind of be able to be back in the back pocket because you won't need it in the same way as you do now. So be will be cool.

1:06:17

>> When you first started the company you you you mentioned this from the Hitchhiker's Guide to Galaxy.

1:06:21

So was you and your co-founders ideal version of your product the Babelfish?

1:06:25

It was one one of the slides that we we thought that yes Babelfish will exist and we'll hopefully make it happen but less so that we will create bubblefish itself but we will enable everyone out there to have Babubblefish in their existing existing devices existing presence existing work.

1:06:41

That was definitely uh one of the the kind of the north stars that we were thinking about.

1:06:49

>> Okay, another question I have for you.

1:06:51

Uh why do you always pop up at all these conferences? I don't do that many.

1:06:54

I think >> I get these emails.

1:06:56

So, so Daniel, obviously a close friend of mine, uh he hounds me on this and he's right.

1:07:01

He's like, "Dude, you have one of the most elegant businesses in the world."

1:07:04

He's like, "All you have to do is sit inside a room and make podcasts and every single thing that you want in life will come to you."

1:07:09

And he's like, his line for this is like stay away from the circus. >> Yeah.

1:07:13

And >> so the only ones I do obviously do events for my partners like RAMP where I saw you at the ramp dinner and I I obviously love Michael Dell.

1:07:20

So I do his two and I do nothing else.

1:07:22

And because of Daniel's advice, just like stay away from the circus like the people that show up at these things, they don't they're aren't doing any work.

1:07:29

They're just there to distract.

1:07:30

Like you don't have to do it.

1:07:31

And so then I get all these emails and invitations like come to this thing and I open it up and I see your face everywhere.

1:07:36

[laughter] >> What are you doing?

1:07:38

>> What are you doing? the no I I usually try to do two per two to three per quarter usually conference events um but in our case a little bit different because for a lot of the people that are usually on the conferences they are our partners or prospecting partners or clients so so it it is usually a a great

1:07:57

way of of forcing function of having them in one place and trying to figure out how we build together that's the benefit of the breadth of the work we do that a lot of especially on the conversational agents work that applies to most of the businesses of how they think about communicating with their customers, how they are thinking about changing customer journey. So, so a lot

1:08:13

So, so a lot of the the events are are a great great way for us to to to to catch time with a lot of the the people that we work with >> and then turn them into customers >> and turn them into customers. >> All right.

1:08:24

So, you are >> or expand the one to two or five whatever this [snorts] is.

1:08:27

whatever this [snorts] is. you know the the common trope of and I and I and I remember like thinking back in the day when we started I got the first invite for one of those conferences and it's like oh this is super cool super fun and then you go [clears throat] um I'm Europeans so I drunk alcohol at

1:08:41

the time as well and then I like felt tired I didn't think I did anything and and it like it it seemed fun but but it wasn't very productive and then and then I had the pair was like not >> did you have nothing to sell at the time >> at the time I didn't I was I didn't know how to like what's the purpose of the conference. I think it was the lack of

1:09:00

I think it was the lack of preparedness on my side where I was going to the conference and just like flowing through it and I and I think it was a kind of terrible thing.

1:09:07

was a kind of terrible thing. It's like you you go there, you have the sessions and some of them are of course good but most of them are not relevant to you or your business or they are the circus part that you mentioned that like you know you feel you're doing something important it's completely unimportant

1:09:20

and um and that kind of you know then I didn't do any events and then I realized that it's like actually you can do them well you do need to prepare you need to pre-arrange a lot of the one ones you want to do during the conference everybody is there at that time you don't want to do too many of them because a lot of the there's like some repeating crowd across those events. So

1:09:37

So you want to do the ones which is kind of different.

1:09:41

[clears throat] Um and of course you want to be pretty explicit to the other side too that they know what they are like you know that you are not you're pitching them and they are relaxing that's like a bad recipe for disaster.

1:09:50

Uh but uh but many people want that too.

1:09:52

They are there to that do exactly the same thing do business and figure it out.

1:09:56

So so now it works really well for me like I do good prep.

1:09:59

We pre-arrange a lot of time.

1:10:01

might never go and like try to be there for just the sessions or just the content or when of course I speak frequently on those conferences but the main the main thing is is is trying to grab time with the people that are there and that has been working really well.

1:10:15

>> Are you still drinking?

1:10:16

>> No, on the weddings but apart from that it's it's a >> every time I go to Europe I have the same thought when I get back I should drink more.

1:10:22

[laughter] >> So much fun.

1:10:26

>> It's like they just know how to have fun.

1:10:28

[laughter] There are social circumstances where I would drink.

1:10:31

They're just so infrequent now that that there's that I wouldn't do it. >> Okay.

1:10:35

Next time we are at one of these rare conferences together, let's make sure we have a drink. [laughter] >> All right. Deal. >> Deal. Deal. >> All right. Thanks for doing this.

1:10:44

>> I hope you enjoyed this episode.

1:10:44

Please remember to subscribe wherever you're listening and leave a review.

1:10:47

And make sure you listen to my other podcast, Founders.

1:10:50

For almost a decade, I've obsessively read over 400 biographies of history's greatest entrepreneurs, searching for ideas that you can use in your work.

1:10:58

Most of the guests you hear on this show first found me through Founders.