The New CFO: How AI Is Rewriting the Finance Function | Figma CFO Praveer Melwani

AI is moving finance from reconciling what happened last month to helping decide what the business should do next. Figma CFO Praveer Melwani argues that the best finance teams are becoming builders themselves, automating repetitive work so they can spend more time understanding customers, running experiments, and shaping strategy. Praveer joins a16z’s Seema Amble and Ivan Makarov to share what that shift looks like inside Figma, from collections and expense analysis to M&A diligence, where the corp dev team now uses AI to prototype products and simulate how Figma leaders might challenge an investment memo. They discuss why AI “slop” is a real risk, how Figma decides what to build versus buy, and why successful internal experiments eventually need a centralized systems layer to turn one-off agents into reliable infrastructure. They also get into what this means for hiring the next generation of finance leaders. Praveer’s bar isn’t simply whether someone can use AI. It’s whether they can understand the business, interrogate the output, communicate clearly, and use automation without outsourcing their thinking.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  I think we're going to be able to attract and build the world's best finance organization because so much what people want is the ability to learn and feel like they're being invested in and surrounded by people that want to go and become the best at their craft.

• 0:11Seema Amble?

  We'd love to hear a little bit about what made someone a great hire on your team, a great person.

• 0:17Speaker 00

  I want folks that feel extremely intellectually curious. You're coming in and trying to solve and try to understand the business really well. You want to use AI as a tool to help you and empower you, but it's really, really critical to still be that thinker.

• 0:29Speaker 02

  We're in the era right now where a lot of slop is being called out. I've heard one CFO talk about how using AI just led to unlimited amount of docs that are being created every day.

• 0:38Speaker 00

  Anything that you're putting out there that you're asking someone to consume, it's going to take them time, effort and energy. 95% of the challenge there is just like getting your data in the right spot.

• 0:45Seema Amble?

  What do we think changes in the next 12 to 18 months?

• 0:49Speaker 00

  If our business complexity was staying the same, I think we probably wouldn't need the same number of people a year from now.

• 0:57Erik Torenberg?

  For decades, finance teams spent enormous amounts of time figuring out what already happened. AI is starting to give them more time to decide what should happen next. In this episode, A16Z partner Seema Amble and Ivan Makarov sit down with Figma CFO Praveer Melwani to talk about what an AI-native finance organization actually looks like. Praveer joined Figma in 2017 as its first business operations hire, years before becoming CFO and helping take the company public. Back then, automation meant writing hundreds of lines of SQL, waiting for queries to run, and stitching financial and product data together by hand. Today, his team is building very differently. Collections workflows are automated. Corporate finance can reconcile messy data across multiple systems in minutes.

• 1:41Erik Torenberg?

  And the corp dev team can use AI to prototype an acquisition targets product and run investment demos against simulated versions of Figma's own leadership team before presenting them. But Praveer argues the real shift isn't simply about doing the old work faster. It's about changing what finance people spend their time doing in the first place and turning the CFO organization from what he calls a traffic cop into a business enabler. They also discuss what should never be outsourced to AI, why Excel isn't going anywhere yet, and what founders should actually look for in the next generation of CFOs.

• 2:16Seema Amble?

  Welcome to the A16Z podcast. I'm Seema Amble. I'm joined here by my partner, Ivan Makarov. We recently wrote a piece called "You Need a New CFO." Our argument was that AI takes finance to the next level and the CFO's job increasingly includes building and automation and really designing the systems and the team to do that. Today, we're joined by Praveer Melwani, who's the CFO at Figma, and we'd love to explore what you have seen over the course of your career and what you and your team are doing now. Praveer, thanks for joining us.

• 2:48Speaker 00

  Yeah, thanks for having me. Excited.

• 2:49Seema Amble?

  Maybe to kick things off, both Ivan and Praveer, we'd love to hear a little bit over the course of both your careers, how automation has changed the role in finance and what the team does.

• 3:01Speaker 00

  Yeah, I've always felt like the role of a finance individual should be this operational leader. And when I joined Figma, none of the automation pieces were in place at all. And I felt like in order for me to be effective at the time that I joined, a lot of my work needed to be living in SQL, building the data tables, really understanding how I could orchestrate the financial information to drive the conversations I wanted then have across the company. And I continue to kind of go back to that initial days that I had in that seat and what I was doing as the force multiplier, the piece that actually gave me the ability to have the scaled impact across the organization. And if anything, I think what I was building way back then is that much more possible and plausible and accessible to individuals by the tools available to them today. So I hope that more and more folks feel like they can be empowered to take that operational sort of

• 3:46Speaker 00

  lens to the way that they actually go and position and work with their counterparts across the business. Because I do think that's the magic of shifting this role from what can be viewed as like a traffic cop sort of finance-y type function to one that's a business enabler and a true change agent within the organization.

• 4:00Seema Amble?

  And to double click on what you were using for automation, pre-AI, maybe explain to people what exactly you were doing. Was it macros in Excel? Was it using OCR for documents?

• 4:13Speaker 00

  Yeah, honestly, it was like everything under the sun. So like, it started like living in SQL, looking at all of our product metric and utilization data, mapping it to all the financial information we had in Stripe. I'd go and create these 400 or 500 lines of SQL that I'd want to then use to create the golden tables that I'd go and pass off to someone, or then be able to pass to different go-to-market systems that we'd be using. So I felt I spent my day living in that query editor. I'd then go and-

• 4:35Seema Amble?

  And of course, waiting for the query to run for-

• 4:38Speaker 00

  Totally. And then, yeah, and you hope you got it right the first time.

• 4:41Seema Amble?

  Exactly.

• 4:41Speaker 00

  And then we eventually hired data scientists and I'd go and tap them and say, "Hey, I have this thing I went and built. Can you go and add it to our ETL process?" So it goes and there's a recurring job that I can then use that same information and pass it to Salesforce or Marketo, whatever systems that we were using at the time. And that was like the initial sort of unlock for me of, oh my gosh, if I can get consistent in our definitions, in the way that we're talking about things, no longer are we ever debating like what's true and what's fact. And we can just get past that and really focus on how are we actually going to go and drive the business?

• 5:09Seema Amble?

  I was talking to someone who was in their early twenties, who was complaining about how long a prompt takes to run. And I was explaining to them, "You've not lived the pain of hours on hours of waiting for a SQL query to run and then only to come back and be like, shit, it didn't totally work?" And so, yeah, it is just an order of magnitude.

• 5:27Speaker 00

  Totally.

• 5:28Speaker 02

  Yeah, the time is really interesting, right? Especially the era that we've lived through. When I was a wet flow at Figma, we saw, for example, a huge spike in usage in COVID that I could not believe in the beginning. I don't know if you've experienced it this way too, where I thought our data was broken or something else was broken, but it took us weeks to figure it out.

• 5:45Speaker 00

  Yeah.

• 5:45Speaker 02

  And I feel like today, in this day and age, we live in the day where you could figure it out to an hour. There was some of the spikes, some of the usage revenue as well. This is a very different world we live in. Did you experience that as well?

• 5:55Speaker 00

  I mean, yeah, I mean, our business, during the early days of the pandemic, I think that was actually the time where we started to partner with the folks at Andreessen, it was like right at the early stages over there. But yeah, I mean, I wake up every day. I mean, I have the ability to go and rebuild my context on what's happening. And then at any moment during the day, the team loves it when I'm, I don't know if they love it, but they know that I'm constantly in there going and taking a look at, you know, hourly dashboards or sort of daily metrics on things to make sure that I'm also sourcing things that I think maybe look like anomalies or asking the right questions. And I think they view me similarly to how they view their role within the organization as, you know, a counterpart who has ideas, who wants to come to them and truly build the best business possible, all using and having access to the same data available to each other.

• 6:33Speaker 02

  Yeah, what's interesting, like when you and I went to college around that time, that was a more of a monthly or quarterly cadence. And then it became a weekly cadence. I remember maybe, especially with data moving more into the cloud, it became like, let's have a big weekly dashboard to where now what's possible is daily. Has that changed your habits, the way you even just look at, think about data, how often you think about it all?

• 6:53Speaker 00

  Honestly, I view data and having access to it as the key unlock to how I can run my day effectively. And so throughout my time at Figma, it was the thing that I would wake up every day and I, I remember there'd be like 30 people that would sign up for a paid plan in those first few days when I joined. And I'd go through line by line, who are they? Are they personal addresses? Are they business addresses? Are there people that we can reach out to? What can I learn from this to help us inform what we eventually built, which was our organization's product? And I think early days, it's extremely important. And then now, I just understand the repercussions of movement in any one direction. And if you catch something before it becomes a big deal, it can actually save the business like hundreds, thousands of dollars. But if you catch it in the other direction, you can really put more juice behind it and really seek to unlock in the other way. So

• 7:38Speaker 00

  if anything, like I view this as like a daily, if not more than that rhythm. And I think the goal for me is how do I empower other folks on my team and across the business to similarly feel the accountability to those same metrics and truly act as business owners and want to go and triage things and not say like, "Hey, I can wait till next week." Like you do need to solve it sooner rather than later because I do think the rhythms here are moving really rapidly.

• 7:58Seema Amble?

  And before we get into what you've automated, we'd love to hear a little bit about what made someone a great hire on your team, a great person in the leadership role, maybe pre-AI.

• 8:10Speaker 00

  I think, I mean, honestly, a lot of similar things today, but I think that you'd apply them slightly differently. I want folks that feel extremely intellectually curious. You're coming in and trying to solve and try to understand the business really well and then seek to problem solve in a way that was trying to drive the right outcome. I don't think that necessarily has changed today. Like, I still very much value that. I do think that you can make a lot of the tedious tasks or the repetitive nature of things feel like they take less and less of your time so that you can spend more and more of your time really trying to seek how you can find the places of magic within the business that you can go and supercharge. So intellectual curiosity, fluency with data, ability to ask really solid questions, and then structure your thoughts in ways where

• 8:52Speaker 00

  you can actually make sense of the data that's being given back to you and then thoughtfully communicate it on the other side of it.

• 8:58Speaker 02

  How do you interview for that?

• 9:00Speaker 00

  It's interesting. Right now, I'm hiring for a VP Finance, and the case study part of the process for me is so, so sacred. I want to both test for like, how are you using the tools available to you? So yes, I fully expect folks to, I don't give them a lot of information as part of this case study. We're a public company, so I can get the benefit of a lot of data out there. But how you actually piece those puzzle pieces together in a way that actually makes sense, the model output makes sense, you have the ability not just to go and create that output, but you truly understand how it works. So then I focus the case study conversation on, have you really, really understood the structure that you've created? Have you molded it in a way where you've tested what are the highest, what are the pieces of that model that are the, the most sensitive to

• 9:42Speaker 00

  any change? Do you have a strong intuition on how the business is actually working using the tool that you've created? And then, like we were just talking about, can you effectively communicate that? Because yes, I think anyone can go and create like a model sitting in, pick your favorite LM, you can go and do that really easily. But are you using it as an effective tool that like actually is enabling you to think? And I think you don't want to outsource your thinking today. Like, I think you want to use AI as a tool to help you and empower you. But it's really, really critical to still be that thinker.

• 10:11Seema Amble?

  Yeah, a lot of what you're describing applies to a good hire with or without AI. I think if anything, AI just, you need more of the accountability and thoroughness to know that the thinking is there behind it as you receive a work product. Let's dive in a little bit on, or to understand what you've automated, and we can talk a little about what we've been seeing with our corporate companies. But maybe walk us through a couple of workflows at Figma that you've automated. And how did you decide what to focus on and what did you, what did you do to automate them?

• 10:44Speaker 00

  Yeah, I, you know, they're so broad. And so I, you know, maybe I could pick a few that, to me, have been fun to see. I think- I think we've like moved really quickly even over the last, over the last year to say, you know, how do I go and try to coach people to embrace new tools and new ways of working to now one where I feel like I'm, you know, constantly being, constantly, constantly being like hit in the face with a lot of these really cool ideas. We do a segment at the, at the company All Hands, we, our All Hands is called Fig Nation where we show folks how others have built with AI and consistently our team shows up as, as a team that's, that's there. So it's things with, you know, Kajal and our, our credit and collections team. He's gone and rebuilt his entire workflow,

• 11:28Speaker 00

  everything from invoice tracking, cash collections, making sure that we can reconcile everything to, to NetSuite. And he's done it in a way where it's like a homegrown system where, you know, it's, it's tied to the various systems that we use. It then has freed him up to say, okay, well, I can go and continue to drive down my day's receivable by folks focusing on the, on the things that really matter. And then focusing on what are the other sort of tedious tasks that I can go and build automation for. And so he's then gone and say, well, I can go and like rebuild the way that I want to run our credit checks. And I can go and stitch together the data sets in interesting ways that allow me not to have to go and, you know, manually go and into them. And it's a singular way where he can now go to anyone to, to say, hey, go and leverage the tools

• 12:09Speaker 00

  that I've created to, to, to go and, and really drive, and drive change there. On our, on our corp dev team, it's, it's been really fun to see like how they, you know, both will, you know, can you vibe code a product is one of the, one of the checks that we use in diligence now, which is actually really fun to see. Like how, how deep is your moat? How interesting is the technology there? And I think, you know, everyone should be able to-

• 12:32Seema Amble?

  You'll try to recreate the product. Wow, okay.

• 12:34Speaker 00

  Yeah. And you can act, I mean, I think our team's gotten really damn good at, at some of this. And so you can get through some of the, you know, is this a real thing? Is it not? Like, how, how difficult is it or not? And, you know, there's obviously nuances to, to a whole bunch of these ideas, but it gives you like a solid intuition there.

• 12:48Seema Amble?

  And before, would you have had to go to the product team to do that part of the diligence?

• 12:53Speaker 00

  Yeah. I mean, we still partner with the product team, but you can take a lot more of like, hey, this is what I built. This is what I've seen. And it builds a lot of credibility there.

• 13:00Speaker 02

  I can do pause on that. Those are some of the corp dev people, right? Not product people.

• 13:05Speaker 00

  Yeah.

• 13:06Speaker 02

  Their finance background, right?

• 13:07Speaker 00

  Yeah. Yeah. Totally. And they, we're like a very document oriented culture. So they write investment MOs, they write, you know, M and A MOs, whatever it may be. And, you know, amongst them, the end, the end readers are the, the, the folks that are digesting it are going to be folks on our leadership team or other product leaders. And, you know, more often than not, there are themes, there are similar questions, there, there are ways that we all as leaders tend to have a way of looking at problems. And what's, what's been interesting is they've gone and created unique personalities for each of us as leaders. As, you know, a set of skills that they can go and run their investment memos by, to actually improve the process.

• 13:48Seema Amble?

  Do you have like an investment committee that exists, like the interaction between all of them?

• 13:53Speaker 00

  Yeah, exactly. So that's exactly what they'll end up demoing. Or rather, they'll, they'll sit there kind of going back and forth and saying, okay, this is what Previa would say, and this is what Dylan would say, and this is what like, you know, Sean would say, our CRO. And so you kind of get, you get, you get like the areas of the document that you either want to go and plus up, do more diligence on, what are common sets of feedback that I need to go and make sure I ask the questions over. And then it reduces the cycle time that we're all sitting together on. So, you know, I, there's a lot of these areas where, you know, we're both feeling like it's, it's a tool that helps you augment. It's this tool that helps you go and replace workflow. And then it's this tool that helps you seek to understand and learn. And I, you know, I'm constantly surprised at like how, you know, quickly we've been able to riff on things. And, you know, for me, it's,

• 14:35Speaker 00

  it's actually put me in this really optimistic spot of saying like, I'm gonna, I think we're gonna be able to attract and build the world's best finance organization because so much what people want is the ability to learn and feel like they're being invested in and surrounded by people that want to go and, you know, become the best at their craft. And as much as I can do to go and affect and enable that change, the better I think we're going to be able to go at retaining and growing and grooming that talent over time, too.

• 14:59Seema Amble?

  And are all those tools, did you build those right with the LM directly? Or are you guys also looking at off the shelf AI tools that you can partner with? And would you rather build or buy?

• 15:12Speaker 00

  Yeah. The ones I was describing, you know, it's a mix. Like some, like some of them folks were sitting in codex. And, you know, I think that's what the team is doing on the, on the corporate development team. They're sitting in codex and trying to, you know, work their way through something. We've also seen folks like sitting within, you know, some of the workflow automation pieces and building skills around agency using chat GPT. And so that's, you know, how some of the credit and collections pieces were, were being built. And we also started to see folks being able to embrace it and build it on our tooling as well. So we, you know, we have a tool called Figma Make, which allows folks to be able to prompt through natural, natural language and create, you know, an application, a website. You can then host it. You have like a, you know, backend behind it. And so, you know, some of those instances are starting to crop up, too. So I'm actually excited about that because then we can, then we can ideally flip into this

• 15:56Speaker 00

  world where we can give product feedback as well, which, you know, I, I know everyone would love.

• 16:03Speaker 02

  I think we're in the era right now, in the period, in the cycle where a lot of slop is being called out. There's been a lot of conversation too, where we went from unlimited token to people just calling it slop in meetings. Or I've heard one CFO talk about how using AI just led to unlimited amount of docs that are being created every day. And you just can't find anything because everybody can write a doc now or 10 docs in, in, in a few minutes that it took, it would take you a week or two. Well, there's some of the areas where, and then naturally created also the conversation around hiring. Do you hire younger people that are more versed in these tools? Do you hire people more experienced that may be both? Or do you hire more senior people that know what the world class looks like? And that's what worries me a little bit is that we will

• 16:44Speaker 02

  forget what the world class looked like. Just like in the pre-AI era, you know where a really good model looks like. Like especially with some experience and having created models. Where do you think this is going? Like have you had to call slop on some of the stuff that's being created right now with AI?

• 17:01Speaker 00

  Sometimes. Yeah. 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. Anything that you're putting out there that you're asking someone to consume, it's going to take them time, effort and energy. And so I think you want to 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, how we use each other's time as well. So yeah, I mean, I've been in, I've been in instances where,

• 17:43Speaker 00

  you know, things look a little bit half baked and you really poke around. You're like, did 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 up. Like a couple of weeks ago, I 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 are we not like upholding policy where we should? In our corporate finance team, they did a really good job about stitching together information that lived in different data sources. We use Nirvan, we use Sip, we use 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 offsite? What if they lived in San Francisco and were just

• 18:28Speaker 00

  visiting? Like, how do you actually want to go and like tag and treat that data? Like 95% of the challenge there is like getting your data in the right spot. And these models are good at making, at making these assumptions for you. And I didn't need something 100% perfect. I just wanted something that was directionally, you know, in the right, 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. 30 minutes later on, like some of the construction of how I actually wanted things to look, look like, like it was all visualized for me when we got in the meeting. I was like, holy shit, this is like a really fantastic use case here. And they did it in a

• 19:09Speaker 00

  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.

• 19:27Seema Amble?

  A couple of comments to that. I mean, a key unlock is the data, right? Now with AI, you can consume all of these sources of data and quickly do the fuzzy match, get a directionally correct or precise, you know, reconciliation across these sources. Whereas before, right? You had to run the SQL query, you had to, you had to wait and then, and see it. 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 CEO, CFOs who was saying that in, I think a month or two, there have been, you know, 40 or 50 agents created by

• 20:12Seema Amble?

  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 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.

• 20:41Speaker 00

  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, 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 to be trackable for our stock, our stocks audit. And then you're like, well, You know, that internal audit team is not the only team that does that. You know, our GRC team is doing the same thing as they go through like all of our ISO and SOC 2 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, is really, really

• 21:24Speaker 00

  interesting to come in and then harmonize some of the things that you see are happening, really productize it, um, 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 need, 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, you know, I think that that cross org sharing, we're doing some of it at our, at our, you know, um, at our company all hands, but we're also doing a lot of it internally across our teams.

• 21:55Seema Amble?

  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.

• 22:07Speaker 00

  Yeah.

• 22:08Seema Amble?

  And so I think to your point, uh, there has to be some reconciling function, um, which would, it was a great segue to hear from you guys around, uh, what are people doing in terms of the teams that should be building this? Are, and who is, who's taking the agency? Is it, you know, you, someone initially builds an agent from your team and then you're taking it to, um, you're taking it to an engineering team centrally. And we talked a lot about this idea of the finance engineer, which we can unpack further, but would love to hear a little bit about.

• 22:38Speaker 00

  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, um, they know the process that they're, that they're trying to make look right. Like they're fantastic in going, uh, going about building these initial prototypes.

• 22:56Speaker 00

  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.

• 23:17Speaker 00

  Um, 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 like what, you know, we talked about a lot in, in the interview process is like, how do you, how do you create these like, you know, 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 like, um, foundations that other can, others can build on top of, which is not too dissimilar from like how a systems organization would have functioned otherwise, but the pace that you can, you can, um, you can iterate on and then how you can empower others to build on top, um, is what is changing right now.

• 23:52Speaker 02

  Is it centralized right now within the company? Just, would they see that changing or eventually?

• 23:57Speaker 00

  So, um, as is all things at Figma, I think we've grown faster than we 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, um, centralizing that. And with other teams, I think, um, you know, they, they built far, far quicker. And I think we're now having the process of saying, okay, well, how can we go and help? So, um, I think we're in the messy middle right now.

• 24:27Seema Amble?

  I think that resonates with a lot of what we're hearing from, uh, our companies, whether it's a go-to-market engineer, a talent engineer, this concept of the finance engineer, it's a decentralized, um, set of builders across teams. It could have different profiles. You know, some, 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, you borrowed someone from us, a, a product engineer from another team, um, 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.

• 25:04Speaker 00

  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, um, 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.

• 25:48Speaker 00

  Uh, and they understand that like, hey, this stuff has got to be like really, really hard and can, and, and always correct. Uh, 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, um, uh, 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, 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.

• 26:20Speaker 02

  Who owns the definitions? Like the, the reason why I asked this question, especially we see it at an early stage where it could be a team of 20 people and just, uh, founders and no finance or business people. And eventually they bring in them on, um, but they're building, uh, definitions of key metrics that serve reporting, that serve, um, 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.

• 26:57Speaker 00

  Yeah, my, my team owns the outputs there. Um, maybe, um, maybe I'm a little, we're a little bit later than some of those early, earlier businesses. We have, you know, more controls in how, in how we want to talk about it. It's always been really important to me to have consistency in how we talk about our business. Um, you know, it's one of the things that I felt has always been empowering that like how I can show up for, with our board, with our leadership team, with, you know, 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, you know, the historical has never changed and, you know, I'm, I'm not trying to hide anything. And I, um, you know, I, I would just want to 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, different sets of disclosure as we go through earnings.

• 27:40Speaker 00

  We want to be consistent and we, we want to have the decisions that we make, um, be things that we can look back on and feel, um, uh, feel good about, um, and have longevity further beyond. And so I, I, you know, I think it's, 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 in consistency as well.

• 28:02Seema Amble?

  Who is it on your team that's automated the most? What role?

• 28:10Speaker 00

  You know, I, 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, uh, individuals on our biz ops team that are automating their day-to-day, um, sort of like, you know, how they're actually going and running, um, uh, you know, competitive benchmarking and pricing studies. So it's like, uh, 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, um, because I truly do think that this is like a, a team that's, um, uh, trying to do this together.

• 28:52Seema Amble?

  Do 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?

• 29:04Speaker 00

  Yeah. I, I mean, I think like early days, it was helpful for me to go and show folks like, hey, if I, if I'm coming and trying to do things in a different way, like, hey, that should be your signal to you that, you know, my expectation is that you are as well.

• 29:20Speaker 00

  But I think, you know, in large part, um, I think the things that are important is have a solid understanding of the data sets that you're trying to pull from. And the folks that have been able to move more quickly have like an understanding of like how these things are stitched together. And when you understand things that, and how they're architected, you can better think as like an architect of like, okay, how do I actually bridge these things in a way that's logical? Where do I know where the model is actually making a determinative decision versus inferring? And what tasks, like, is it okay for that to happen? What tasks is it not okay? And I think then, you know, others kind of pick up and learn from that. But, uh, you know, I, I do think that like the, the rhythm that we've created, the show and tell rhythm, the, you know, the internal hackathons, this ability to bring in other

• 30:04Speaker 00

  experts, we do a lot of like, I do a lot of conversations with other finance leaders and I try to bring in some of that intel internally so that it can get disseminated. And I think my leaders are also doing that too, which is really cool to see. Um, I think everyone right now is trying to learn from one another, which is, which is really cool to see.

• 30:18Seema Amble?

  Nice.

• 30:19Speaker 02

  Yeah, I feel like one of the common themes that coming up in my conversations with CFOs or directors of finance, or even just individual contributors, is that they're finding it's really fun to be working again. Because before it was like you're reconciling something for two weeks or three weeks, and you're closing the books for two or three weeks continuously. And now, it just feels like people are really turning their eyes towards the business and are able to surface insights, business, and all of that. There's just a lot of excitement around what's possible with AI, what's possible with vertical solutions. One of the things I'm curious to go back on the buy scenario. I was talking to one of our hyper growth companies the other day, and they said, we just have to buy everything off the shelf. We're moving so fast. Do you ever

• 31:03Speaker 02

  feel that way? Like, maybe billing is a longer path than just buying one of the solutions out there?

• 31:08Speaker 00

  I think for like, the core systems or record solutions, and like, the things that like, we just can't mess up, like, yes, we're going and buying solutions for that. The areas where I think our team is having a lot of fun, it's the, you know, it's kind of where you're going. It's like, the workflow automation. Like, what are the areas where, if I think about my day, like, I'm almost like, not thinking. And how can I go and augment my day to day so I can, you know, go and reorchestrate how I want to spend my time? I like, I also, you know, fully, fully agree with the sentiment that you're sharing, that like, the work has gotten, you know, the work, the work is always going to be interesting, but the work has gotten more fun, because you can explore things more quickly. I've had folks on my team come up to me being like, holy shit,

• 31:49Speaker 00

  like, I actually am like, having a ton of fun. And I actually think that like, the policies that we created and the freedom we've given folks to explore are the reasons why like, some folks are like, I want to stay here. I really, really like what I'm doing. And I think, you know, I don't know if folks are actually treating access technology as like, a recruiting vehicle as much as they could or should. You know, I at least started to do that in the recruiting conversations, since I started to hear that from the team. Especially when you're trying to pull from folks who are not necessarily in technology, they're like, oh, my gosh, this is like, my, my front end, or my front entrance into like, an entirely new world. And if I'm empowered to learn, like, this is really cool. So, you know, I actually would be, I mean, I know other people are maybe going to steal this now, but like, for me, that was actually one of the really fun things to do.

• 32:30Speaker 02

  I agree. I actually, I had this idea too, that I think we need to start talking about this, like, we talk about perks and benefits. You get X, Y, and Z if you come to work here, that might, your former employee, the employer doesn't let you available, and now you also get access to all these models or other tools.

• 32:44Speaker 00

  Yeah. Yeah. And I think it's not just that, but then it's also like, if you, if you have folks understand what are other people building around them. And so much of what you're going to learn is through osmosis of what others have built to. And so if you get this feeling that like, you're joining an organization, that's not just saying that they're, that they give access to these things, but they're actually building and that you can see it, and you can feel it through the interview process, those are the places I'd gravitate to.

• 33:06Seema Amble?

  So, in 2020, my partner Angela and I wrote this piece on how CFOs needed modern tools. We had this pyramid diagram in there, which was essentially saying that the finance team was spending all their time on this like, data reconciliation layer. And at the top, which was the smallest amount of time, was being spent on strategic finance, or like, strategy questions. I'm curious if your time, you've, you know, actually seen your time and your team's time unlock, not just on doing things they enjoy more, but like, being more strategic, or being able to weigh in on more decisions, or like, how has that changed your your role?

• 33:43Speaker 00

  I feel fortunate that like, you know, as I've grown within the company, that like, that has taken up more and more of my role. And then, as I then think about like, what, what is exciting for others, like, I also recognize like, for me to have, that there's benefit in me creating that same space for other people within the organization. So yes, there are things that like, we'll have to do as daily rhythms or weekly rhythms. But in the same breath, like, if I can get, like, take our, take our, we have a finance organization that's split, and one of the, one of the pillars is go to market. If I can take the team that's focused on our self-serve business, and immediately get them out of reconciling last, last week, or last month, or whatever it is, and then very much more focused on what are the experiments we're running, what are the trends that we're seeing, where are the dollars that we should, like, what are the additional dollars that we should be spending on? Like, that is way

• 34:28Speaker 00

  more engaging to them. And I think they're actually able to do more of that now. Like, it's like such, it's, some of the little things here matter so much. It's like, how can I go and automate the creation of a set of materials that I know it's going to look and feel the exact same way, and, you know, then focus my time on the annotation, the discovery, the understanding. And we've seen, we've seen that start to get a lot, a lot faster. And the quality of that improved. And, you know, we even had one of, like, I was actually the leader of that team get up and talk about like, how he had gone and created a set of plugins to go and, you know, in Figma to go and ideate on this stuff really quickly. So, you know, I, I would hope that my team is telling me that they're spending a growing share of their, their time on that, on that bucket of things. But you're always going to have to chase, you know, the complexity in your business, and managing the complexity with like, how much

• 35:12Speaker 00

  time you're able to reserve for, for the other pieces.

• 35:15Seema Amble?

  Totally. One of the things that we're seeing in the CFO tools that we've invested in is, the product is moving away from, you know, tracking workflow towards providing a result. And then part of the product is the, the audit trail. So, obviously, finance needs to make sure everything's correct. You need to be able to track where, you know, how the, the product came to a particular reconciliation, for example. But then, it's done for you. So it's that balance of both having the audit trail and the, and the result. But we are definitely seeing our team spend more time doing things like, running experiments, and doing things that used to take like, a month-long research study. You had to pull in some from

• 35:59Seema Amble?

  data science, and like, chase down a bunch of people over email, get everyone in a room. And now you can quickly iterate on this, because you can, yeah, you can, you have agents running in the background.

• 36:09Speaker 00

  And it could even, and it's even things on like, the accounting side, like flux analysis, right? Like, you know, you're spending time as an accountant, going through and trying to reviewing the GL accounts for like, period over period. If you can leverage a tool, and I know there's a whole bunch of tools now out there that give you that initial sort of like, stab at what has changed. That gives them like, a set of things that they can go and chase. It gives them like, an additional set of things. And maybe it's right, right away. And I'd love for that to be more and more true. And then they focus their time elsewhere. And so I, I fully expect that, like, the spirit of where you're going, like, that, that like, initial draft, the initial sort of set of expectation, that initial sort of idea of what to go and, and pull the thread on, can be surfaced via tools. It's kind of where I was going when I was talking about that T and E piece, right? Like, it was giving our team sets of threads that they can go and pull. And then us enough got to go and chase it too.

• 36:54Seema Amble?

  Right. You have the, the data, and then now the time to go, you know, address those second order questions, and see what, what's behind, what's, what's going on.

• 37:02Speaker 02

  Yeah, I was thinking, how, when we grew up, the word reconciliation was a very negative word. It was associated with a lot of bad memories, and a lot of weeks and months spent on trying to chase something. Where now, it's just something you do, or maybe it's even a positive word, because you can, you can solve it much easier, quicker with the modern tools and with AI. And, and find, maybe not exactly where the errors are, but just get there so much quicker. And then you still need, obviously, to go talk to people, as FPNA will always continue to be there. The people, the people discipline.

• 37:31Speaker 00

  Yeah, I, you know, it's one of those things, I think I underplayed, or I under, I didn't realize how important communication, you know, relationship building, your ability to, you know, go and influence was to this role. You know, I, I probably walked in feeling like I could, you know, be the smartest person in the room and figure it all out. But then I realized, like, you know, it's a team sport, regardless. And you can only go and affect so much change. And you then really do have to go and get other people to be on the same page with you. And if you can do that effectively, I think you can be a really effective leader. But, you know, those are sort of like, the, I think, the true skills of, I can tell, you were, you were asking earlier about, like, you know, what am I screening for? If I, if

• 38:13Speaker 00

  I can test and get a sense that you're like, you have this ability to build really solid followership, you have this ability to go and build trust with others, like, that's so invaluable.

• 38:22Seema Amble?

  That's a, a good segue into what I wanted to chat about next, which is, what do we think changes in the next 12 to 18 months for the team, and the role, and the function overall? I don't know if you guys have any points of view on, on what might change. Maybe let's start off talking about how your team even is organized.

• 38:41Speaker 00

  Yeah. I mean, I would love to be in a spot where, you know, we're only adding individuals if like, the complexity of the business is growing faster than, than the, than the needs to support it. I do think that we're in a spot now where like, you know, a lot of the, the regular sort of business rhythm pieces, I think you can start to move in the reverse direction versus needing to add people in order to keep up with it. You know, I think for us, we're going to continue to fight it, because we're, you know, adding new products, we're acquiring teams and businesses, we're, you know, continuing to evolve what, what we're doing. And so it's always more, I think, in that world, the complexity there is still outpacing, you know, where we're, where we're able to truly drive, you know, if, you know, complete efficiency. But we're definitely like, we're definitely getting more efficient,

• 39:26Speaker 00

  you know, period over period.

• 39:28Seema Amble?

  Do you think that the efficiency, do you think it'll like, plateau? Like, you've got the tools to do what you need to do? Or do you think that this, more of these processes will just completely get automated end to end?

• 39:39Speaker 00

  I would hope that more and more can get completely automated. I think maybe I'd start with the pieces that are like, truly deterministic, and like, how can I feed it with enough information so that I can feel that the output there, you know, is completely, completely trustworthy? I think getting something to that, like, audit-ready output piece for, for a system that's like, truly business critical is extremely high. I think it's also going to be, you know, an interesting sort of conversation with the auditors, and we'll get some comfortable. But I don't, I don't kind of take it out of the picture. I do think we'll get there over time. I think, you know, like I was sharing, you know, as long as our business, if our business complexity was like, staying the same, I think we probably wouldn't need the same number of people a year from now. But, you know, I, and I think

• 40:23Speaker 00

  you only get there because you're doing a better job of finding these places and rhythms where you can, you can build more consistency in, in the way that you're operating.

• 40:30Speaker 02

  Is Excel under threat?

• 40:33Speaker 00

  No, it's like my love language, dude. Like, I think in the same way I was describing how I, you know, I still think that case study is so important because like you use it as a tool, right? Like you use it, you use it to build intuition. A lot of the output people are still creating is a model. I mean, that model could be, you know, you could host it somewhere. It could be something else, but like, I think you want this tool to give you this ability to refine your understanding and play with things with your hands. And it's kind of like the magic that we see with Figma, right? Like we can give people the ability to go and, you know, have an initial stab in the first draft through, you know, prompting and through natural language. But like, sometimes it's so much easier to go and riff and make changes on your hand. Take a color wheel as an example. You've got like a screen that you've designed and you're like, hey, I want to go and change the background. You could sit there and an agent prompt it, right?

• 41:17Speaker 00

  Like go change the background from red to green. Or I could take the color wheel and you get all the different shades of it and you get the real feel of what's going on. Similarly, I think about that with Excel. It's the way I build trust, the way I build understanding. There may be something better in the future, but for me, I think it'd be really, really hard to rip away from me.

• 41:32Seema Amble?

  I also grew up in Excel and I still use Excel to like organize my thoughts. Like if I'm trying to run an analysis, I'll, it's, yeah, it's just even like the spatial organization of it. And, and I think the, the models aren't quite good enough to like create a forecast or a model quite yet, but I think that organization is still valuable. I don't know if you feel similarly.

• 41:55Speaker 00

  Totally. And I also think, you know, part of the things that I've tried to experiment with now is like, how can I use, you know, how can I use, how can I use one of these models to help me better understand the output that the team is putting together? Like if you give me like a, you know, a 20 tap model, it's going to be really challenging for me to go and like tap through and thumb through everything. But if I can, you know, pass that same context through, through, through a model to help me understand, you know, what are the things that really are the needle movers? Or what are the areas that are more sensitive? It's actually given me like a better starting spot to go and orchestrate and understand things, which I've actually found really, really helpful and effective.

• 42:32Speaker 02

  The world we're living in is also challenging too. I was talking to university professor the other day and I was asking him, how do they teach AI at the universities? Well, they don't right now. And one of the challenges is that they, they said they had a course and within the semester, they've changed the syllabus several times because new models have dropped. And they just have to completely change how they do it though. So they just sort of give up. So they're going back to fundamentals again, teaching people analytical thinking and Excel and all of that. Because I imagine you're in a similar world where if you were relying in AI too heavily, you're going to have to redo how you do your earnings.

• 43:06Speaker 00

  A lot has changed, but a lot hasn't changed. And I think maybe that's the spirit of where you're going. I, you know, I think that the core capabilities of what makes a great finance person are still there.

• 43:18Speaker 00

  How you actually, you know, leverage the tools at your disposal to make, you know, better, better decisions is, you know, always going to be this like moving target for you.

• 43:28Speaker 00

  Like the unlock that sequel was for me is, you know, now, you know, net new unlock with like AI as a tool and capability driver for me. So I, you know, I think a great finance person has longevity if they continue to adapt.

• 43:43Seema Amble?

  Which, you know, we wrote this piece, we said, it was titled, "You Need A New CFO." The main point was that the, there's a mindset shift. So whether the individual actually has changed, it's the, that they have to think more automation first, either build or buy the tools, depending on what's, what's available and what makes sense, but it's really automation first. I'm curious if you think the profile, either of you, of a CFO in the next year or two is going to change in any way, or to your point, it's kind of the same, the same dimensions that are important, but maybe just the mindset continues to evolve.

• 44:16Speaker 00

  If I were to give advice to anyone, it's like hire someone who feels a similar amount of business ownership and wants to be the, you know, an operational rigor as you as the CEO does. They want to win, they want to win no matter which way possible. They have a set of tools that they're going to use and an understanding of a P and L to go and orchestrate that change. But you truly want like a business leader versus like, you know, someone who, you know, like I was sharing earlier, like a traffic cop, right? Like that, that is just not, and yes, I think there's a lot of, there's a lot of things that you're going to need to have as like commonplace and solid understanding of, like all the accounting fundamentals, like, you know, your, your, your ability to actually go and orchestrate a planning process. But like, I actually think the things that like make people truly unique in this role, it's like, do you understand the business?

• 45:01Speaker 00

  Can you go and make, make change happen? And can you get, can you simplify the understanding of how the business model works? So that others are all running in the same direction.

• 45:09Speaker 02

  Yeah, and I think it's true, whether we're talking about a public company like Figma, or we're talking about a seed stage or a series A startup that's starting to scale to go to market and getting traction, is that that's what the founders and the CEOs really need from finance is that extra business opinion, opinion on the business and insights that are easier to get, but also still you go back to the basics like customers. Do you understand the customers? Do you understand the behaviors? Do you understand the metrics that come from that? Inputs, outputs. I think that's, that's will always be the same in what we expect.

• 45:42Speaker 00

  Yeah, maybe the thing I'd add, like, I, I, I do think like, you know,

• 45:48Speaker 00

  creativity is important, not like, you know, go and create like a funky set of metrics creative, but like, how can you actually go and think about your business in a slightly different light? And use that as like the way that you go and drive change and be opinionated. And I, you know, I actually don't know how, you know, I try to do, I try to do this. I don't know if I'm doing it as much as I, you know, could. But if I come up with these ideas, if I can come up with different ways of thinking about things, I actually think that, I think some great ideas can come from your finance organization. And if you really set them up well and right, they can be, they can be this like layer within your organization that's just as impactful and really driving a lot of the internal strategy as well.

• 46:33Seema Amble?

  I will say at the investor and board level, we are seeing a much deeper set of analysis come through or the rapid iteration. You know, before it used to be, oh, we have all these questions at the board meeting or before, and then it's a, you know, the team needs to run and cycle through that. That process has just short circuited and hopefully is less painful on the finance team's side.

• 46:55Seema Amble?

  Last question for you, Yvonne. As our portfolio companies or just companies in general come to you and say, where do I start in terms of automation? What do you give them as advice?

• 47:05Speaker 02

  I think it's kind of the same place where we always started. You start with the integrity of data. You have to figure out if you actually have a good access to data, if you're tracking things. Many, many of the times, especially early stage companies, they don't even track anything. And so you have to set that up. And that often goes in against the priorities that maybe the first finance hire has, like, I gotta close my book sometime, gotta send the board update. All of that actually, no, like you can't even do that until you're on the solid foundation. You might sometimes have to set it, you might have to rebuild it, you might have to change things. We've had a number of people that came in, especially now, very quickly you can realize within several weeks that maybe the revenue is calculated in a way that's not how it should be calculated for that business model.

• 47:44Seema Amble?

  More, more creative error at the early stage than I've ever seen before.

• 47:49Speaker 02

  For sure, for sure. It's changing fast too. But, but it starts with data and then based on that, you really kind of create the reporting rigor, you create the metrics and then you create the story. I think one of the things too, Prevar, was especially you've been on that journey as a CFO, like storytelling becomes a really, really important once you have your eyes set on the IPO and you have to be all telling the same story. I feel like that has moved to earlier and earlier stages because you expect to tell the story now in fundraising for series A, series B. And not just the story of what the product vision could be, but story with the numbers and what the, what the business could really be like. And that's gotten easier, but it's also gotten harder because I think a lot of people overthink that with AI.

• 48:33Seema Amble?

  And, well, you know, Yvonne and I have been hosting these CFO and controller dinners for, I don't know, a couple of years now. And we saw this real market change, I'd say maybe nine months ago, when it went from people saying, oh yeah, I'm generating this tax memo or this onboarding doc with AI to saying, okay, yeah, I can actually, I'm doing the core, the data reconciliation and automating many of the workflows. And it's really been a step, function change. And if anything, the leaders are saying, I'm, I need to do this, otherwise I'll be perceived within my organization as behind everyone else. This goes back to your point around you winning the hackathons. Like finance was never the one that was going to be winning the automation hackathons, you know, I don't know, a couple of years ago.

• 49:17Seema Amble?

  And it's, it's pretty cool to see that's totally changed.

• 49:19Speaker 00

  Yeah, I love this part of it. And I, I would, we have like an internal maker week and it's our internally branded like hackathon. And, you know, I would always sit there early days and not really know how to participate. And now I'm like, if I had like a spare minute, I think I have a million different ideas and I'm sure my team has, feels very similarly.

• 49:37Seema Amble?

  Well, Prevar, thank you so much for joining us. This was really fun to talk about and understand directly from someone who's gone through this journey of automation over, over your career. And thanks, Yvonne, and this was a really fun conversation.

• 49:50Speaker 00

  Yeah, thanks for having me.

• 49:51Seema Amble?

  Yeah.

• 49:54Erik Torenberg?

  Thanks for listening to this episode of the A16Z Podcast. If you liked this episode, be sure to like, comment, subscribe, leave us a rating or review and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts and Spotify. Follow us on X at A16Z and subscribe to our Substack at A16Z.substack.com. Thanks again for listening and I'll see you in the next episode.

• 50:20Erik Torenberg?

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