00:34:50 · Mati Staniszewski
[00:34:50] S1: I think there is always you want information from the person working as closely to the problem. So let's say you're developing the product, you want you want to to speak with the engineer that actually develops that product rather than their manager. 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. 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 forth. Second, I think that in general, roughly at ElevenLabs, most people will have close to 10 direct reports. So a pretty wide blight set which helps us build that small team approach that we have. And that too only works if you can amplify a lot of what's happening across all the teams, all the people that you work with, to summarize information of what's happening in the teams, how this is performing, what are some of the gaps. That definitely helps and helps shift it from reactive to proactive, I think too. What I mean by this is frequently in the past I think you would rely on specific individuals surfacing the information to you. Now, as we think about ElevenLabs and how we run, you can summarize all what's happening, all the data of what's working, what's not, get that signal, I get that signal, I can proactively engage on where I think it's not working, which helps. It helps, of course, everybody across the company because you have that same ability wherever you are. I think that maybe the last part, which is very related to those two, why it's even possible today. We took a choice to be extremely transparent with a lot of the data that we have, a lot of the docs that we write. So everybody has almost access to all the docs that are there in the company, which ultimately helps you create that system where you can actually tap into that knowledge.
00:36:51 · David Senra
[00:36:51] S0: Okay. 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 because you're relatively young. This is your first company. Your first company you built, you got into AI right away, and then you were perfectly positioned for this huge explosion. Obviously, people have been talking about AI for eighty years or whatever, but you're the right place, right time with, I think, the right set of skills based on what the company built so far. So how different do you think in the future the way you run your organization can be than what it is today?
00:37:19 · Mati Staniszewski
[00:37:19] S1: I think the small teams approach will definitely be there across many of the companies that I believe will be created in the future. It also helps with a 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 relatively small and independent, people bottoms up adopt what they think is best and are unable to run with it straight away. That helped a lot in that sense. I'll give it to others which we believe strongly on. One, in all the small teams that we have, in all the teams that we have, we bring even non technical teams, we bring engineering talent in those teams. 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 how they are using AI. I think that will be a bigger pattern in the future across the companies too, where I think increasingly some of the biggest and smallest companies will try to infuse all teams with engineering resources so they can get smarter.
00:38:27 · David Senra
[00:38:27] S0: Is there any function that is centralized at ElevenLabs that then all these small individual teams can then access? I spent some time with Luca Ferrari of Bending Spoons. And he had this wild idea to me where he's just like, well, HR is actually really important. He thinks the fact that tech people are dismissive of it is ridiculous. And he's like, but my HR is like 50 people and they're all engineers. And then it's like one centralized HR that every single other, because he owns I don't know how many companies, 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 tap into that for that resource.
00:39:08 · Mati Staniszewski
[00:39:08] S1: Of course, there are centralized functions. Legal is a good example 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 learning the craft of how to sell ElevenLabs. As you said, there's so many different products. You need to be very particular about how you deliver that to the specific customer So it's not confusing the customer and what we are offering or what we do. Yes, so there's a good amount of those functions, but they all too similar to Luca's approach, all of them will have a good amount of engineering in them and figuring out how you scale that operation. It's not becoming hundreds of people in all locations, but how you can use the few people that you have and really bring that knowledge everywhere. One of the biggest ones for us is probably around rev ops of how you are like the revenue engineering effectively function. We have so many tools that help you get the knowledge whether it's code during the conversations, transcribe, bring it back, make it easier for you to fill on a field so you capture that knowledge and then don't have to spend manual time. And then of course increasingly we dogfood a lot of our own work so trying to figure out how we can create AI agents to help replace part of that work but still operate within the team. A good example is AISDR. People going on the website today on ElevenLabs, you can fill in the dropdown form and leave information about your company, but you can also speak with voice agent and leave that in a quicker and different way. We've seen a lot of people go for that flow. And then interestingly, two things happen. One, people are both making their things easier. They enjoy it more. But two, they leave a lot more information than they ever would for the dropdown form. They tell us so many about the problems, about the wider set of use cases so we can connect them better.
00:41:00 · David Senra, Mati Staniszewski
[00:41:00] S0: That's really interesting. So because they're speaking and not typing, you get more information? [00:41:04] S1: 100%. Mean, it's of course a quicker way of doing it, but also people just feel more at ease instead of going for this manual dropdown forum. It's just better way on leaving the information. But now, because 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 want it to help everybody across wherever you are. We are a global company. So it's central and then deployed to each local team. So each local team can refine it for the local new ones, but developed, of course, centrally.