00:28:17 · David Senra, Mati Staniszewski
[00:28:17] S0: And you're doing this with FTEs? [00:28:19] S1: Yes. We do all that with FTEs, then we deploy, and then of course we scale over time. [00:28:24] S0: When did you realize that a huge path to greatly increasing your revenue was doing FTEs? [00:28:29] S1: And before I answer this, and of course, the last part is, as you deploy, the job isn't done, you still want to continue, evaluate, monitor, refine the behavior over time. And that applies across all of the use cases. NFDs for that are great too. I used to be at Palantir, so it always felt like a big thing of how we want to work with customers. It's almost I don't like the word customers because in many ways I feel like all of them are partners where you are working together on the same problem and trying to solve that. So a lot of the philosophy of the FDEs was there from the start to make it specific, working with the partners side by side on their problem [00:29:09] S0: and This their is really interesting. Tell me what you observed that was working at Palantir. You were like, Oh, if I start my company, I want to do that too, and why?
00:29:19 · Mati Staniszewski
[00:29:19] S1: I think the most incredible thing was that you were meant to be on the same side of customer obsessed of their problem and try to understand them deeply from the beginning. So I used to work at BlackRock before Palantir. And BlackRock, when I joined, given the compliance security, the first month or two, when you send an email, it gets verified by your team, it gets trained before you send it externally. It's a pretty detailed flow of making sure that it's good. In Palantir, when I joined after the onboarding in the first month, I'm like, Okay, you now need to work and understand a customer. You're flying to Aberdeen, to North Sea, to work side by side with them, understand what's happening, and then bring it back. That was a complete shock for me and the approach and culture of I have never almost interacted with a customer on the BlackRock side. Now here I am in the first weeks, I meant to go there and be next to them, which was crazy. I thought it great. I thought it was that mentality and every time you are going to be there on the, I'll call it, front line loosely on the front line to work with them and bring that knowledge back, understand what is actually a problem, what's fixable problem, and then actually fix it. And that mentality is so true now at ElevenLabs too, where all of our FTEs, our go to market team too, is going to obsess of like, how can I actually be there with the customer, understand the problem and work with that? There was other components that I think were great. The small teams, they had usually small deployment teams that worked on a lot of that. The best idea wins. 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. Define small. About five people is considered in Palantir big and in ElevenLabs is going to be also relatively big. Will tell you something more though on the FDE side because of course now you probably see 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 are deeply embedded on understanding what's the roadmap of the product.
00:31:36 · Mati Staniszewski, David Senra
But there's a second reason, which is one, you want all the FD's 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 for the next generation of companies building on top of it. And I feel like the second part is frequently missed. It's like first, okay, if these are doing effectively a lot of the hard integration work to solve the problem. But if you don't do the second step of how you actually learn the expertise and bring it back to the product, then it's effectively just services or just the [00:32:15] S0: Wait, say more about that second part. So you're gleaning information through trial and error, working closely with them. Then you can take that back and spread that knowledge across the other tens of thousands of customers that you have. Is that what you're talking [00:32:27] S1: about? Exactly. [00:32:28] S0: Okay. [00:32:28] S1: Exactly. And it's a product knowledge of like how you operate with, you know, there are simple things. Let's say you build an integration. How do I have that integration available to everyone? That's a simpler version of that. But let's say you are working in healthcare space. In healthcare space, if you deploy the work, then you want to optimize the product experience for the right... If you are not studying as a second customer, you want to make sure that you have Exactly. [00:32:58] S0: You're using your customer base as almost like R and D, another form of R and D.
00:32:58 · David Senra, Mati Staniszewski
[00:32:58] S0: You're using your customer base as almost like R and D, another form of R and D. [00:33:03] S1: You are definitely accelerating your R and D through understanding the domain that you're working with. It's, because [00:33:09] S0: And their problems are not very rarely a company's problems is unique to that company. [00:33:13] S1: That's right. 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. You learn with another one, you learn, you bring it back to the product experience. Both of those customers benefited from having the product optimized for the better work. The domain expertise they have is still there as they 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. [00:33:39] S0: What else did you learn working at Palantir? [00:33:41] S1: They also were very much of no title organization, we carry over at ElevenLabs, which does help in that best idea wins approach where people do feel, I feel like mimicking you on that church. [00:33:56] S0: I thought the same thing. Was like, you don't have to if [00:33:58] S1: you don't want to. No, it's a complete coincidence. Change of course. [00:34:03] S0: We're leaving that part in.
00:34:03 · David Senra, Mati Staniszewski
[00:34:03] S0: We're leaving that part in. [00:34:05] S1: No titles, relatively flat organization, very few layers. It's like, between me and the C suites, I worked there before the DPO, it was four, five steps or less. So you always felt like a proximity between, think it was like four or three actually. So it was a good proximity of being able to work together. At ElevenLabs, we have a couple of five today, like maximum depth of how many layers there should be. Hopefully over time, actually there will be fewer, no more layers, if AI helps you run the organization the [00:34:41] S0: way we would like to run. Well, say more about that. What can you not do today in the way you run your organization that you hope AI can change in the future?
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.