00:49:28 · John Collison, Mati Staniszewski
[00:49:28] S0: Yeah. For for example, you know, Eleven is a huge company, and yet A 100%. You started on Stripe on a self [00:49:33] S1: serve kind like initially, Ed, it's like, you know, we were two of us at the at the beginning. You try to see what's working in the industry, but you try to think from first principle. So you wanna try it out. You want to understand how it works. So the more friction elements before you're trying it out, the less you trust whether it's available, whether there'll be additional payment that's hidden behind some of those steps, so you don't want to go through them. So it's so much. [00:49:55] S0: Speaking of Stripe, do you have any Stripe feedback for us? Anything you want us to fix? [00:49:59] S1: My most common feedback until recently is like, why don't you give us pay as you go user base billing type version? But one of our finance lead, Mati, I know I was speaking with your team, and and that was day before. Yeah. He was, like, thinking about it for a long time. He's great. Was it like you said, like, [00:50:18] S0: you guys should buy Metronome? [00:50:19] S1: You should buy Metronome. [00:50:20] S0: And then [00:50:20] S1: the next day, Metronome acquisition was announced. So now you have it. So that's that was my most common feedback, and we'll be launching.
00:50:20 · Mati Staniszewski, John Collison
[00:50:20] S1: the next day, Metronome acquisition was announced. So now you have it. So that's that was my most common feedback, and we'll be launching. [00:50:56] S0: Directly. Going back to self serve, I think a new thing in AI is that all self serve products should have pay as you go as an option. Maybe you wanna have, like, a subscription with some unlimited tiers, but I don't know if you had the experience of, like, you're using Claude and, like, you're typing away your queries and eventually you hit some rate limit and it's like, sorry, you've hit your usage limit, and you want to be able to do the thing that you can do at Claude Code, which is just pay per API. It's like, fine. I'll pay for it. And it's kind of very funny as a consumer to not have the option to pay more to use the product more. And so, yeah, I think every AI product will need... Know, they probably want to have some all you can need... Most of what you can use subscription with limits and then the ability to pay for overages. So it sounds like that's what you're... [00:51:37] S1: Yeah. Exactly. That's what that's what we that's what we... What we're doing.
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?