00:22:38 · Praveer Melwani, Ivan Makarov
[00:22:38] S0: Yeah. I I think, like, you know, I think we've always had... I think having specialists come up with the ideas and iterate, they know what good looks like. They know what they want. They know the process that they're that they're trying to make look right. Like, they're fantastic in going... At going about building these initial prototypes. But do I want that same individual to be the individual that has to go and make sure that they're checking for all upstream dependencies and making sure that, like, you know, if they were ever to leave that, like, this thing is hosted in the right way. And, hey, does anyone else across the organization have the same need? Probably not. This is where I think, like, you know, a world class CIO org can can come in and really show some magic here. Yeah. I'm really excited. We just had a new CIO join yesterday, a guy named Casper Sorensen who joined over from Coinbase. And a lot of what we talked about a lot in the interview process is how do you create these centralized PM type functions within the CIO organization that can partner with the rest of the business teams, find the things that are really working, and then build these foundations that others can build on top of, which is not too dissimilar from how a systems organization would have functioned otherwise, but the pace that you can iterate on, and then how you can empower others to build on top is what is changing right now. Is it centralized right now within the company? [00:23:55] S2: Do you see that changing? Would eventually Yeah.
00:23:55 · Ivan Makarov, Praveer Melwani, Seema Amble
[00:23:55] S2: Do you see that changing? Would eventually Yeah. [00:23:58] S0: So as is all things at Figma, I think we've grown faster than we've built, you know, the tools to support it. And, you know, it's on me to always empower the organization to build, and then I'll... I don't want to slow people down by creating the infrastructure on top of it, and so I think we're chasing a little bit of that right now. I think with some teams, we've done a better job centralizing that. And with other teams, I think, you know, they've they've built far far quicker, and I think we're now having the process of saying, okay. Well, how can we go and help? So I think we're in the messy middle right now. [00:24:27] S1: Mhmm. I think that resonates with a lot of what we're hearing from our companies, whether it's a go to market engineer, a talent engineer, this concept of the finance engineer. It's a decentralized set of builders across teams. It could have different profiles. Sometimes it's someone who has an engineering background on finance who's good at kind of thinking about what workflows need to be automated. Other times, it's... We borrowed someone from us, a product engineer from another team to go build. But, you know, I think I think everyone's in this messy middle right now in terms of of what what that profile of person looks like.
00:25:04 · Praveer Melwani
[00:25:04] S0: A lot of it reminds me of data science teams and how they partner with other parts of the organization as well. And you as a data science partner are like, you know, the deeper you get into understanding the context of the team that you're working with, like, the better I think you you operate as a as a... As an individual. So, you know, we've got data science individuals that are partnering with our product team. They build as much, if not more product intuition than our than our product managers and engineers, and they're viewed as part of that core team that can go and help ideate and push change, and they're just leveraging a different tool in order to enable that. Similarly, we've got folks on, you know, the data science side that are supporting our finance organization. It's actually really interesting. Like, the folks that I think have been devoted there actually come from accounting backgrounds, a couple of them. And they understand that, like, hey. This stuff has gotta be, like, really, really hard and can't... And always correct. They understand the nuances that we're describing on, like, checks and balances. What is a refund? What is it, you know, uncollectible? All that all that kind of all all that kind of nomenclature, and so it actually enables them to be better builders. And, similarly, I could see that translate to, like, you know, the the, you know, the finance engineer that you're describing. You have some shared understanding of what is necessary. You could build that context over time, but at least, like, you... It's important to at least, like, build that major so that you can also go and push other people's frame of thinking as well.
00:26:20 · Ivan Makarov
[00:26:20] S2: Who owns the definitions? Like, the reason why I'm asking this question, especially we see it in an early stage, where it could be a team of 20 people, just founders, and no finance or business people, and then eventually they bring in them on. But they're building definitions of key metrics that serve reporting, that serve investors, and really business decisions. And eventually finance gets hired. Where the definitions, how often would you... It feels like in the past, we used to revisit them maybe every couple of years, where now, because you can access the code or you can access the Stripe logic much easier with AI, has that changed much? How often do you visit it? I mean Yeah.
00:26:57 · Praveer Melwani, Seema Amble
[00:26:57] S0: My my team owns the outputs there. Maybe I'm maybe I'm a little... We're we're a little bit later than some of those early... Earlier businesses. We have, you know, more controls in how and how we wanna talk about it. It's always been really important to me to have consistency in how we talk about our business. You know, it's one of the things that I felt has always been empowering to like how I can show up with our board, with our leadership team, with other folks broadly is that they know that what I'm putting out there is the same thing that I would have put out there a month ago, and the historicals never change, and I'm not trying to hide anything. And I, you know, I would just wanna make sure that, you know, as we grow and as we give ourselves the ability to iterate, and, you know, we constantly have this conversation on different sets of disclosure as we go through earnings, we wanna be consistent, and we wanna have the decisions that we make be things that we can look back on and feel good about, and have longevity further beyond. And so I think it's great if people finding different ways to think about their business, if it's empowering them to go and build their business better. But I do think that there's some value and consistency as well. [00:28:02] S1: Who is it on your team that's automated the most? What role?
00:28:02 · Seema Amble, Praveer Melwani
[00:28:02] S1: Who is it on your team that's automated the most? What role? [00:28:09] S0: You know, I I could say someone, but I'm I'm assuming that that someone else is probably coming up with something different really quickly. But, you know, very, very honestly, it's like all... Like, individuals who are owning certain parts of our forecast model all the way through to, you know, individuals on our biz ops team that are automating their day to day sort of like, you know, they're actually going and running, you know, competitive benchmarking and pricing studies. So it's like, I actually think that, you know, it's the it's the one upping of each other that actually enables you to create an organization that wants to better one another. So, you know, I I would feel uncomfortable saying there's one individual because I truly do think that this is like a team that's trying to do this together. [00:28:52] S1: You think it tends to be people who are more expert... Like, who have more expertise or experience in an area, or is it really across the board? And and how much is it coming from you and the role that you've automated yourself?