00:51:37 · Mati Staniszewski, John Collison
[00:51:37] S1: Yeah. Exactly. That's what that's what we that's what we... What we're doing. [00:51:41] S0: The other thing I wanted to ask you about is I feel like all CEOs of larger companies today are trying to figure out how do all these AI advancements change the nature of the organization, and how do you redesign your organization a bit around all this new intelligence? And so that could be about what the scaling factor is of, like, the number of people you need to do the work, But it also should be like, do you need more senior people because they're better able to direct the AIs, and the AIs are maybe kind of doing the work of what previously would have been junior people? Do you need more junior people because they're gonna be more AI native in how they work? Do you want smaller teams? Do you want bigger teams? How do you actually go do the process engineering of, you know, your finance team should be using Claude extensively? But, like, finance teams did not historically, you know, have a lot of home built software. And so there's all these questions that are floating around. And you have very rapidly built a much more AI native company. And so I'm curious what lessons we should all be learning from ElevenLabs as a large business recently built. And so without the baggage of decades of, you know, how we've always done it.
00:52:52 · Mati Staniszewski, John Collison
[00:52:52] S1: Yeah. Yeah. We started 2022, which is a year when the two topics of the day were crypto and metaverse. So just before... And then, of course, AI first scaled. Started. Exactly. Exactly. But we could, like, had the privilege of, like, kind of scaling through the world when it was all happening. For us, Woodworks, and and we, like, really believe in that being the the the big part of the future. The first is small teams. [00:53:14] S0: Mhmm. [00:53:14] S1: Like, keeping the teams small and super flat. So, like, can you have... Both me and my cofounder will have over 15 direct reports each that that we'll work with. And most of those people will have that same scale of direct reports and... [00:53:28] S0: Okay. So your spam and control is way larger than the traditional company. Normally, Ace, you have double that, and obviously, that's an exponential. [00:53:34] S1: Exactly. And and, course, you know, there are some teams where... Which which in the short term might not do that, but ultimately, that's where we think it's going to be headed. It's, roughly 10 team size within each of those of those work items. [00:53:45] S0: And then start ups Pretty close. No offense. But, like, startups often have pretty wacko management ideas. Like, there was a funny tweet, Laura Grant me the confidence of a, you know, early stage startup founder blogging about their management theories. But, like, you think this is not a start effect? This is an AI effect where basically...
00:53:45 · John Collison, Mati Staniszewski
[00:53:45] S0: And then start ups Pretty close. No offense. But, like, startups often have pretty wacko management ideas. Like, there was a funny tweet, Laura Grant me the confidence of a, you know, early stage startup founder blogging about their management theories. But, like, you think this is not a start effect? This is an AI effect where basically... [00:54:01] S1: No. It's definitely a little bit of start effect, Yeah. Yeah. I think it's, hindsight benefit. I'm canceling our Stripe changes. Yeah. No. No. It's like, I need to preempt that I'm not going to be... Know, it's... The hindsight of this may be working. We'll see in the next five to ten years. [00:54:19] S0: Their Much org. [00:54:20] S1: Much flatter org. Yeah. So it works for us. Might not work for all the companies. And there are some parts where, like, go to market, we still are trying to figure out what's the best way. Yes. But smaller teams, flatter org... And I I think there are two paradigms, but, like, generally people being more technical [00:54:33] S0: Mhmm. [00:54:33] S1: Or if not technical, even in nontechnical teams, having a technical resource. So, you know, we will have a person in ops or in talent that will... We have effectively a tech lead for that team [00:54:45] S0: Yes. [00:54:45] S1: That helps them automate a lot of that that that work and helps up level the rest of the team too. Yes. So there are kind of two parts that are helping. Okay.
00:54:45 · Mati Staniszewski, John Collison
[00:54:45] S1: That helps them automate a lot of that that that work and helps up level the rest of the team too. Yes. So there are kind of two parts that are helping. Okay. [00:54:52] S0: So talk this... Talk me through this in talent or something like that. Is it that you are building your own software where other companies might have bought software, like a Workday or a Greenhouse or something? Is it that they are using the existing software you have better? Is the process that will be spreadsheets in a traditional company are built with software? How do you kinda use the software in these sorts of organizations?
00:55:16 · Mati Staniszewski
[00:55:16] S1: Yeah. Look, there are... Sometimes, but we still use a lot of, like, the the traditional vendors. Like, one pattern is, of course, elevenifying everything, like making the the data explorable for you to be able to interact with it of, like, who's in the pipeline, what worked, who does the best references, like, all of that all of that works, so you can double down on that. But two, it's frequently things that you manually do that a lot of the car... Like, there's a gap between where where where the agents are today versus what you could do if you have the technical skill set. And a good example is, like, how do you scrape all the right profiles to be able to reach out to the right candidates? So you, like, analyze whether it's, you know, don't know how much I should want to say, but try to detect specific things that we know worked. So you bring that across to the people. On go to market side, there's just so many things you can do with with with additional amplifiers. You know, it goes from understanding what case studies are relevant and creating a good preread for you before you go to the meeting through creating the AI SDR experience that we spoke about to creating an entire deck experience. So you have, like, a prepopulated deck with the right numbers that is customized to that customer, which you want still the person to go through and and and develop, but ultimately is is in there. So there's plenty of those additional things that you know will amplify the work of the people around, potentially replace some of those easier tasks that are done. And then there's like, you know, we wanted for people to explore the culture at ElevenLabs. We created a voice agent that people can speak with and see what's the culture, but also get prepped for the interviews. I think across many of those teams, like, additional benefit of of what they can do. Interesting piece. So, of course, in Ukraine, with ongoing work, they need to rethink a lot of how their development, their systems, their support works for the citizens across the country. And people are in the war zone. They don't have the same access to the information. They cannot rely on the same phone lines. They cannot rely on the same physical services around the country. So they've developed effectively a central And your
00:57:22 · John Collison, Mati Staniszewski
[00:57:22] S0: employees in the Ukraine? [00:57:24] S1: We we we had a few, but they reached out because they were developing their central map called Diia. They developed it over the years, but now before they were double dawning of how this can... Doubling down on how this can be a a way of supporting the citizens. And, course, there's a easy part of, like, how you create a first agenda government where you have help with the benefits and what's happening on the frontline or education, so that's delivered to everyone, health care so you can book your checkup or appointment. How you create all of that, and of course, we traveled to Kyiv. We worked with them on bringing that and making that available for voice so everybody can access it. But the thing we've learned while being there was that model of what we speak about, where you have technical resources in each of the teams, they actually have the same in every of the ministries. So every ministry had technical resources working on creating that agentic version of their work. And then it was like a central digital transformation team that would assemble this all together to deliver that for the central citizen support, which I thought was brilliant. [00:58:25] S0: That's very