00:16:59 · Praveer Melwani
[00:16:59] S0: of the stuff that's being created right now with AI? Sometimes. Yeah. Yeah. I I think, like, you know, I think we... We've also done a good job internally about building policies around, like, branding when you've written something with AI. I think, like, you know, one of the things that's really important, I think I was sharing it earlier, like, you should not be outsourcing your thinking. You know, anything that you're putting out there that you're asking someone to consume, it's gonna take them time, effort, and energy. And so I think you wanna make sure that, you know, you put a similar bar to go and review, read, summarize, make it simple. You can start in a different place. I'm totally cool with that. But I do think it's on all of us to make sure that we're, you know, being really thoughtful about how we we use each other's time as well. So, yeah, I mean, I've been in instances where I, you know, things look a little bit half baked and you really poke around, you're like, do you do you really understand what's going on over here? But I've been... Also been in instances where I'm like, oh my gosh. Like, your speed of iteration here is, like, pretty damn incredible by virtue of how you set it up. Like, a couple weeks ago, was sitting in a... We're going through 27 planning. I was sitting in a T and E review. We're looking, you know, we're looking at our T and E portfolio and saying, okay, where where do we have the opportunity to go and make changes to policy? Or maybe where where are we not upholding policy where we should? And our corporate finance team, they did a really good job about stitching together information that lived in different data sources. We used Navan. We used SIP. We used RAMP. And there's a lot of fuzzy match that you have to go through in order to, like, really get that information working. Like, was someone actually traveling for for an off-site? What if they lived in San Francisco and were just visiting? Like, how do you actually wanna go and, like, tag and treat that data? Like, 95% of the challenge there is just, like, getting your data in the right spot. And these models are good at making at making these assumptions for you. And I I didn't need something a 100% perfect. I just wanted something that was directionally, you know, in the right...
00:18:43 · Praveer Melwani
You know, in the similar vein for where I'm going that gave me enough information to understand, you know, what are the areas I really need to crank the dial on. It was really interesting. They both, like, outputted a set of suggested changes that we needed we needed to... We could make. I gave... I remember giving feedback that morning. Thirty minutes later on, like, some of the construction of how I actually wanted things to look like, like, it was all visualized for me when we got in the meeting. Was like, holy shit. This is, a really fantastic use case here. And they did it in a way that, like, you know, I don't think they would have been able to do it by hand. So, you know, as as much of that slop, you know, I think can happen. I also think some magic can really get unlocked if you if you if you kind of, like, use the right tool for the right purpose and understand, you know, what is what is good enough and what needs to be, like, really, really picture perfect.
00:19:27 · Seema Amble
[00:19:27] S1: A couple of comments to that. I mean, a key unlock is the data. Right? Now with AI, you can consume all these sources of data and quickly do the fuzzy match, get a a directionally correct or precise, you know, reconciliation across these sources. Whereas before, right, you had to run the SQL query and had to... You had to wait and then and see it... And and then and then essentially, you had to be your own BI analyst on on top of it. The second piece is there's this muscle that's being developed around the automation. Right? And so even if there is slop... Like, for example, I was talking to one of our growth stage c... CFOs who was saying that in an... I think a month or two, have been, you know, 40 or 50 agents created by their team, which obviously are not all being used. But it was getting everyone in this motion of of, okay, if I don't... If I'm doing something manual or tedious, I don't have a great tool for it. Let me build. And so a lot of those, maybe 90%, I'm... I would guess, of those tools and agents are not being used anymore. But it got people to think, okay. Instead of doing this manually, let me think automation first around it, which I think is almost as important as getting the, like, the the agent built.
00:20:41 · Praveer Melwani
[00:20:41] S0: Yeah. I 100% agree with you. I also think, like, how you share it, how you get other people to understand what other people are building, and then you end up in these scenarios where where, you know, our internal audit team is like, I... They spend a ton of time going and, like, following up with individuals to make sure that they're adding information, you know, on the tickets that they needed so it could be trackable for our SOC... Our SOX audit. And then you're like, well, you know, that internal audit team is not the only team that does that. You know, our GRCs team is doing the same thing as they go through, like, all of our ISO and SOC two audits as well. You know, you have a bunch of this back and forth on the AP side when they're going and writing accruals. Like, you you wanted to go and build this motion of going and triaging, pulling information in, reconciling it, and why not go and build a singular platform that does that? This is actually where I think, like, you know, a systems team is really, really interesting to come in and then harmonize some of the things that you see are happening, really productize it so that you don't have all these individuals going and building similar things. That, I think, is like the evolution of what a CIO function should or could be. It's like how do you go and you take a lot of these bottoms up things that people have crafted and you have it you have it be rebuilt and repurposed in a way that can live on beyond the creator and the and the initial builder. So I I I, you know, I think that that that cross org sharing, we're doing some of it at our at our, you know, at our all... Company all hands, but we're also doing a lot of it internally across our teams.
00:21:55 · Seema Amble
[00:21:55] S1: I was also talking to another one of our growth stage companies. The head of customer success was saying every one of his reps had a different dashboard that they had vibe coded and they had different numbers. Yeah. And so I think to your point, there has to be some reconciling function, which was a great segue to hear from you guys around what are people doing in terms of the teams that should be building this? And who's taking the agency? Is it, you know, someone initially builds an agent from your team and then you're taking it to an engineering team sent... Live test centrally. And we talked a lot about this idea of the finance engineer, which we can unpack further, but we'd love to hear a little bit about.
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.