Carta’s Path to $500M ARR, Raising $1B, & Why PE is The Future | Henry Ward, CEO

Henry Ward, CEO of Carta, joins Sourcery to share how the company scaled to nearly $500M in ARR, raised $1B across seven rounds, and evolved from a startup serving cap tables to a platform targeting massive markets like private equity and private credit. Ward discusses the Peter Thiel-inspired strategy of dominating small markets before expanding, the importance of focusing on inputs over outputs, the challenges of selling to both hoodie-wearing founders and Midtown CFOs, and Carta’s AI-driven future. This wide-ranging conversation dives into scaling lessons, product innovation, network effects, and why private equity is the future. Carta was a classic 3x, 3x, 2x, 2x, to $100M in Revenue & are now growing 20%+ at scale. Highlights • Carta has raised $1B to date & is approaching $500M in ARR, growing 20%+ annually. • Strategic shift from venture into larger asset classes like private equity & private credit. • Peter Thiel’s “competition is for losers” philosophy shapes Carta’s market-entry strategy. • AI as both a customer-facing differentiator & an internal productivity engine. • Scaling up to delivering million-dollar enterprise solutions for institutional private equity & private credit Connect with us: 1. Henry Ward: https://www.linkedin.com/in/heward/ 2. Molly O’Shea: https://x.com/MollySOShea 3. Sourcery: https://x.com/sourceryvc Brought to you by: • Brex—The modern finance platform, combining the world’s smartest corporate card with integrated expense management, banking, bill pay, and travel. As a Sourcery Listener you get: 75,000 points after spending $3,000 on Brex card(s), white-glove onboarding, $5,000 in AWS credits, $2,500 in OpenAI credits, & access to $180k+ in SaaS discounts. On top of $500 toward Brex travel, $300 in cashback, plus exclusive perks (like billboards..) visit → https://brex.com/sourcery • Turing—Turing delivers top-tier talent, data, and tools to help AI labs improve model performance—and enables enterprises to turn those models into powerful, production-ready systems. Visit: turing.com/sourcery • Kalshi—The largest prediction market and the only legal platform in the US where people can trade directly on the outcomes of future events: https://kalshi.com/sourcery • Fourthwall—The #1 way to sell merch online — Fourthwall is the easiest way to launch a fully branded merch store—used by big brands like MKBHD, Acquired, & even the Smithsonian. 100+ products. No upfront cost. Visit Fourthwall to start today: https://fourthwall.com/ Follow Sourcery for the latest updates! https://www.sourcery.vc/ Chapters: (00:00) Competition is for Losers (01:07) Carta’s Growth: Approaching Half a Billion ARR (02:51) $1B Funding Journey & Board Evolution (05:30) Measuring Success: Inputs vs Outputs (07:55) Product Portfolio & Power Law in Software (10:58) Peter Thiel’s Influence: “Competition is for Losers” & Growth Strategy (12:02) Expanding from Small Markets to Big Impact (14:00) Entering Private Equity & Credit (15:59) Network Effects: Global vs Local (18:02) Product Market Fit & Building a 10X Product (20:30) Relationship with Mark Andreessen & Board Insights (23:10) Company Building vs Product Building (25:58) AI at Carta: Internal & Customer-Facing Innovations (31:29) The Impact of AI on Jobs & Workflow (34:33) Personal Motivation & Performance (35:44) Looking Forward: New AI Products & Excitement for the Year

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

• 0:00Speaker 00

  When boards generally get involved in product, that's usually a sign the company's going down.

• 0:05Molly O'Shea?

  Yeah.

• 0:05Speaker 00

  Carta is good at two things. One is entering services industries and turning them into software industries. The second is we love doing things that people today do in spreadsheets that they shouldn't be doing. Service industries dominated with spreadsheets. That's like perfect for us. We've turned them all into software industries. So we love doing that. We're big fans of Peter Thiel's competition is for losers. If a lot of people are doing something, don't do it. Do the thing that nobody else is doing. Or the corollary of that is.

• 0:29Molly O'Shea?

  You're the CEO of Carta. I hear you're getting really close to half a billion dollars in ARR. It's really exciting.

• 0:34Speaker 00

  Yeah, it's fantastic. It took us 10 years to get here. Hopefully, the next half billion won't take 10 years.

• 0:39Molly O'Shea?

  A lot of people want AI right now. How are you thinking about involving AI with Carta?

• 0:54Molly O'Shea?

  Henry Ward, welcome to Sorcery.

• 0:57Speaker 00

  Thanks for having me. Great to be here.

• 0:58Molly O'Shea?

  I'm so excited to have you on and also shout out to Tess. Thank you so much for the introduction and helping hooking this up. To start, you're the CEO of Carta. So I hear you're getting really close to half a billion dollars in ARR. How are you thinking about the growth of the business?

• 1:13Speaker 00

  Yeah, it's fantastic. It took us 10 years to get here. Super excited. You know, we were one of those classic, back in the old days, you would call it a triple, triple, double, double to 100 million. And we did that. And now we're, you know, 20% plus grower at scale. Hopefully, the next half billion won't take 10 years. So, you know, we'll see. Every company has sort of these S-curves that they're going through. And we're on the second half of an S-curve in venture, but the beginning of an S-curve in private equity and private credit. And that's driving a lot of the, I think, the next two to five years of growth. You know, if we get to a billion bucks, I think it's because we caught fire in private equity. If we get to two to three billion bucks, it means we've gotten into other asset classes.

• 1:56Speaker 00

  So, yeah, so it's just the beginning for us.

• 2:00Molly O'Shea?

  I think because Carta has scaled so large, people might forget that you guys were once a startup. I want to know, who are some of your investors? And what kind of funding have you reached to date?

• 2:11Speaker 00

  So we've raised, shockingly, about a billion bucks in total across, I think, seven rounds. So Union Square Ventures did our Series A, Spark Capital did our B,

• 2:25Speaker 00

  Menlo did our C, Meritech did our D, Tribe did our E with Andreessen Horowitz, Lightspeed did the next one, and Silver Lake Premier did our last one. So we just, as we keep moving further up into the stack of private capital, we went from small seed funds to large venture funds to growth equity funds, and then, most recently, private equity. We've got a board of seven. We've got people from, like Will from Lightspeed, we've got Matt from Menlo, Mark from Andreessen Horowitz, Joe from Silver Lake, Barbara, who is the first female vice chair at Lehman, and then RBS. So we've

• 3:08Speaker 00

  got a great board. It's been a fantastic, you know, the evolution of a board over a company's growth is something I learned, you don't get to do very often. And it's pretty amazing when you look at the board at an early stage and the board at late stage and pre-IPO, it's a very different dynamic. It's a different group of people to work with. And it's been fantastic. I've learned so much from this generation of the board.

• 3:32Molly O'Shea?

  How do you think about the metrics to determine success in the business? So what are you measuring? I think you have over 2,500 venture funds?

• 3:40Speaker 00

  Yeah, about 2,500 venture funds, about 35,000 startups. We talk a lot about inputs. So, you know, the normal way to measure a business like ours is growth, you know, net new, expansion revenue, margins, or of all the traditional stuff. And internally, I try never to talk about those things because those are the outputs of the business. We spend all our time talking about the inputs of the business and what are the various flywheels of Carta. So When we go into these internal meetings in our monthly business reviews, we have a network flywheel for the business and it's basically the more securities, card of securities, electronic securities that get accepted by investors,

• 4:23Speaker 00

  the more investors come on the platform, the more startups they refer to the platform, the more investors they bring and that flywheel spins. We have a similar thesis on funds and LPs. The more funds that we manage on the platform, the more LPs get on the platform, the more they like the service, they bring more funds and we have this flywheel that spins. So everything we do at Carta is about how do we build more of these flywheels? So even all the way down to, you know, sub-product of cap tables with a small team, they have a flywheel that they're trying to drive and spin. So all of our internal KPIs are flywheel driven. So it's things like number of securities accepted, numbers of cap tables shared, number of capital commitments that we've processed, how much money we've moved for a particular customer.

• 5:06Speaker 00

  And our thesis is if you just keep driving those things, the outputs will come. And that's traditionally been true for us. I think when we get into trouble or most companies get in trouble is when they focus on the outputs. They're looking, they're trying to drive the numbers that are really outputs of something else. And what happens is they lose sight of what that something else is. And that's when the business starts to slow.

• 5:31Molly O'Shea?

  Are there any kind of instances or examples that you've seen throughout your time as CEO of other companies doing that and focusing on the wrong things like outputs?

• 5:41Speaker 00

  We see it all the time. I see it in other companies and other startups. But I'll speak more to us. We make the mistake all the time, you know, because it's super easy to get excited about the outputs. We call it alpha versus beta. So we talk a lot, alpha is what we consider things that we have control over and beta is things that we don't. So beta is like market, you know, if we lose a customer because they're going out of business or, you know, the market's down, that's beta, you know, it affects our outputs, but it's not something we can control. But if a customer leaves because they're unhappy or we made a mistake, that's alpha. You know, if we sell a customer and convince them to come to Carta. That that's alpha. We were doing something that wouldn't have happened if we didn't put in the effort.

• 6:24Speaker 00

  And so all of our, where we get into a lot of mistakes is when we start thinking about beta. We're like, oh, we had a good quarter. Was it alpha or beta, right? Did we have a good quarter because the market had a good quarter? Or do we have a good quarter because we did the work? And sometimes the inverse is true. We had a bad quarter. Well, maybe we had a bad quarter in the vanity metrics because the market was down. But if you actually look at the stuff we had control over, we did a really good job. And having that discipline, it's too, it's so easy for executives, I think, for companies to start worrying about the outputs that you lose sight of the inputs. And we've made that mistake and we keep coming back and fixing it.

• 7:05Molly O'Shea?

  Yeah, and Carta has evolved through many different products now. So like, I think you now have three different kinds of main product suites. Could you break those down? I think most people know Carta most from cap tables, getting in with startups. So where does that lead you to now?

• 7:23Speaker 00

  So it's really funny. If you go back to the early days, our first product wasn't even cap tables. It was electronic stock certificates. And the innovation back then was you had to mail these paper stock certificates. And our idea was instead of FedExing a paper stock certificate or putting it in the post, we would email it. It would be electronic. That was our big innovation.

• 7:47Speaker 00

  Which sounds silly now, but that at the time was considered crazy. People thought it was illegal. And we're like, no, it's like PayPal, but for equity. And then the problem, of course, with that was, well, we were competing with FedEx. That was the competition. And everybody was like, how big's the market for emailing a stock certificate? And the answer was not very big. And then we got into cap tables and the criticism there was how big's the market for cap tables? And very similar, it's bigger than people thought, but it's not enormous. And we just grew up with every product we launched had a fairly limited market size. And so I call us an innovation company. I think there's like two types of startups. There's innovation startups and execution startups.

• 8:31Speaker 00

  So an execution startup is like a Rippling or a MongoDB, where it's just like, if you build a better database or a better HRIS system, you have line of sight to billions in revenue. Like, you don't have to worry. You just have to do better than the incumbents. You have to out-execute everybody else. In our world, We didn't have that luxury. Any one product, we didn't have line of sight to billions in revenue. And so we had to constantly build new products to expand the TAM, expand the market size. And so now it's true, we have three main business lines, cap tables for startups, fund accounting for private funds and cap tables for private equity. And those are the main business lines, but we probably have 40 products. Because I say it's similar to music, there's a lot of like one-hit wonders, you know,

• 9:15Speaker 00

  they did one song and disappeared. There's some people that can put together an album. And there's very few people that can put together album after album after album. And what, everybody listens to the song they love. Nobody knows about the 30 songs the artist released that nobody pays attention to. And that's like us. We built a lot of products. Three of them work really, really well. I think product portfolio management in companies is much like Venture Life.

• 9:40Molly O'Shea?

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• 10:25Molly O'Shea?

  Companies like Scale AI, DoorDash, ServiceTitan, Hims, Anthropic, Flexport, Robinhood, and Plaid. Trust and use Brex. Start today at brex.com/sorcery. That's B-R-E-X dot com slash sorcery. Given that you started with that initial wedge and maybe the market wasn't that small, how do you think about growing through those markets and getting multi-billion dollars in revenue?

• 10:50Speaker 00

  Yeah. So we're big fans of the Peter Thiel's competition is for losers. And if a lot of people are doing something, don't do it. Do the thing that nobody else is doing. And that implicit or the corollary of that is if nobody else is doing it, it's probably because people think it's a bad idea or the TAM is not big enough to be interesting. So by definition, anything we go after, because nobody else is interested in it, everybody thinks it's a bad idea. That is the curse of card. Everyone's like, that is a stupid idea. Everything we do, people think is stupid. And so the way you get around that is you start with these small markets that you can quickly dominate. So cap tables was one, small market. Nobody cared about it, stupid idea.

• 11:33Speaker 00

  But we could quickly win because nobody cared about it. We're the only ones that cared about it, literally in the world. If you, if you are a great engineer that got passionate about cap tables in 2015, there was one company you could work for and it was us. That was it. So, but there were only like three of those engineers. You know, so, but we got them all. We had a monopoly on engineers that wanted to do cap tables. And so you win this small market, but you win it very quickly. And then you concentrically grow out of it. And it's the, Peter Thiel uses the Facebook example. You know, Facebook started on college campuses. Worst market, students don't have any money. Nobody cares, it's college, like all this kind of stuff. But he just won these campuses really quickly. And he went, he did it at Harvard, then he went to Stanford, then he went to Berkeley.

• 12:18Speaker 00

  And then he started to concentrically grow out of the campuses and, and get into the alumni groups and connect the campuses and so on. And that's always been our thesis is start in small markets, win something that nobody else cares about and then concentrically grow. The challenge, of course, is the risk of doing something that's got a big market that everybody cares about is you're one of many. You're, we call it a one of N market. The risk for us is you can win these small markets, but can you expand out of them? And we call them N of, N of one markets, where there's one and only one winner, but then can use that as a base to expand the TAM. And we've done that with cap tables, fund administration, private equity, private credit. That, that's been our playbook and so far it's worked.

• 12:59Molly O'Shea?

  And you've expanded now into private equity, private credit. Those categories might've not been served before, but now you're serving them a product. Why did you get so excited about the opportunity there?

• 13:10Speaker 00

  I would say card is good at two things. One is entering services industries and turning them to software industries. We cap tables was a service industry before we got into it. 49A was a service industry. Fund administration was a service industry. We're we've turned them all into software industry. So we love doing that. The second is we love doing things that people today do in spreadsheets that they shouldn't be doing. And if you look, cap tables is a spreadsheet problem. Value at 49A was a spreadsheet problem. Fund accounting is a spreadsheet problem. Private credit is a spreadsheet problem. Private equity is a spreadsheet problem. And all we do is we take those spreadsheets and we move them into the cloud. And so when we saw these other problem sets that they were seeing in private equity and private credit, we're like, service industries dominated with spreadsheets. That's like, perfect for us.

• 13:55Speaker 00

  We are the best in the world at taking on those those kinds of problems. And what's really exciting is the market size of private equity is six to eight times the size of venture. And then it's another three or four times private equity and private credit. And then you can go to infrastructure and real estate. You just start knocking down these dominos. It's really interesting in my small market to concentrically grow out. You know, we thought the small market was cap tables. The small market was actually venture. Venture is a very small market when you look at alternatives as a as an asset class. And this was a great market for us to learn because it's a hard, hard market. It's small, high velocity, a lot of change, high transaction volumes. If you can build a software company selling to startups,

• 14:39Speaker 00

  you can build a software company selling to anybody.

• 14:42Molly O'Shea?

  I was gonna say, I mean, I've read a couple of your recent reports. There was one on the LP market for VCs. And that's pretty much cut in half in the last year or so. That industry is just volatile by nature. It's driven by a lot of market tailwinds and different kinds of market constraints. Of course, you would go to private equity. Of course, you would go to private credit. It's much more of a sound business. Do you still put a lot of emphasis on venture? Like, how is that evolving with so much volatility?

• 15:11Speaker 00

  Venture is very volatile as an asset class because it's the it's the tail end of the whip. It's the last asset class allocator's alley. So they they start with bonds, then they go to public equities, then they'll go to real estate. You know, then they'll go to credit, private credit, then they'll go to private equity. And they have any more money left, then they'll add some torque and venture. And then it's last and you know, first out, it's like as soon as it's LIFO, as soon as they want to pull back. The first thing they pull back is venture and then private equity and they work their way back. So venture has always been super volatile. We don't mind that because we we enjoy the highs and I think we've done quite well. Even even when the market turns, we we continue to grow. So we find ways to to create value.

• 15:56Speaker 00

  What's really exciting about the the other asset classes is venture is unique in a lot of ways, but it's really just an extension of private equity. Like it's not, you know, from investing in startups and the culture is very different. But in terms of building infrastructure for how to run a startup, running a venture fund, not that different from running a private equity fund when you think about core infrastructure. So what we've been very fortunate is all of the work that we've done in venture is now exportable into these other asset classes. And that's why that's why we spent the last two years becoming private equity experts. My expectation, my hope is in three to five years, how card is sort of synonymous with infrastructure for venture in three to five years will be synonymous with infrastructure for PE.

• 16:39Molly O'Shea?

  Are there like, do you have to go after different approaches for those industries? I'm sure because you mentioned, and I know this too, but like because venture is such a wonky asset class. And internally, they act like startups. Private equity is more institutional. So do you adapt your approach for servicing these companies throughout that? Or is the product pretty linear?

• 17:00Speaker 00

  The product is not that different. What's really different is the go to market motion. We started with a sales team that sold, you know, $6,000 cap tables to 24 year old founders in hoodies. You know, in Soma, and and now we're selling million dollar accounting solutions to middle aged CFOs in Midtown. Like it's just a very different sales motion. So that's been the biggest probably challenge for us to to adapt to to a new industry. Another way of thinking about our business is we're very much a network business. And we try, we try to build networks directly into the product. And so obviously, our first network was cap table to investor. Our second network is investor to LP or fund to LP.

• 17:46Speaker 00

  What makes venture unique as an asset class for us is that it has what I'll call a global topology. You know, you bring a company on to Carta because all the investors are minority holders, they bring a bunch of investors, they bring 20 investors and then those 20 investors hopefully recommend some startups which bring more investors and you get this very complex web of a global topology. In private equity, it's different. A KKR portfolio company that buys Carta cap table software doesn't help us with a Carlyle portfolio company. They're just completely separate. A KKR portfolio company that we sell helps us get another KKR portfolio company. There is what we call a local network effect versus global network effect. And the way

• 18:26Speaker 00

  that the analogy we use is Airbnb versus Uber. So Airbnb, we look at as a global topology. So an apartment in Paris helps me in San Francisco. A car in Paris doesn't really help me in San Francisco. And so Airbnb has to kind of protect this global network effect. Uber has a different problem where they have to protect these local cities, right? Each city is a network effect and that's, that's why Lyft and Uber and Didi and all these other ride sharing companies competed at a city level. What's interesting about venture versus private equity is we have very strong global network effect in venture, which I think has helped with our durability there. But now when we go to market in private equity, it's a local network. We have to win firm

• 19:09Speaker 00

  by firm by firm. We can't just win the market and it's a very different go to market and product strategy in these local topologies.

• 19:17Molly O'Shea?

  From your experience, maybe this is more philosophical, but how do you think about product market fit?

• 19:23Molly O'Shea?

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• 19:59Speaker 00

  I love the you can't get people to move if it's if you have a 2x better product, it's got to be a 10x better product, however you define that, that's another Thiel thing or Andreessen thing. And so we think a lot about how do we make a 10x better product? If it's not going to be 10x better, it's not worth doing. And once you get to a 10x better product, how you know you've got it is it just sells itself. Like you don't need to train salespeople. It just people just want it and they they they take it, you know, they'll find a way to buy it. I remember in the early days of cap tables, people used to buy over the phone back then. And somehow we messed up the phone system so that we'd

• 20:40Speaker 00

  just hang up on people if they tried to press two for sales. And we didn't know for a month because people were just finding another way to buy it. The only way we found is somebody came through the support channel and was like, I've been trying to give you money for three weeks, but nobody will take it. And that's when you knew like you had something. And so the the best thing, you know, I spent a lot of time on with the sales teams and go to market. But arguably, that's a that's actually means I don't have a great enough product. Because if I had a really good enough product, I wouldn't need to spend time with sales like and I should be spending all my time building a 10x better product.

• 21:13Molly O'Shea?

  Do you think sales and go to market can sometimes give us a false impression that you have product market fit?

• 21:19Speaker 00

  100%. And it's the one of the biggest mistakes that startups and CEOs when they launch new products make is they have such a great sales motion, they can push a product out to market that doesn't have a strong product market fit. But it it feels like it does initially. And then it'll go up, and then it'll stop. And we've had a couple products like that. The product wasn't 10x better, it was just the sales execution was good. We've always been a chart our own way. So when everybody was going left, we'd go right. I don't think we ever really got pulled by by external height, market hype. We definitely distracted ourselves. We'd have, oh, this is a great product idea, let's try it. And it didn't work. Oh, let's try this, let's try that. We have, we have tons of ideas.

• 22:04Speaker 00

  The nice thing about our business is we have a lot of optionality. Once you own the cap table, you can do a lot of different things. Once you own Fun accounting, you can do a lot of different things. And so our challenge is always like, it's always been, how do we pick ideas? And then how much, how much effort do you put behind one before you, you give up? And that's the consummate challenge is, you know, we think it's a good idea. Do you work on it for a month? Do you work on it for a year? Do you work on it with two engineers? Do you work on it with 50? You know, trying to figure out that that balance is the, is always the trick. In general, we'll try lots of ideas and we're really good at sort of the poker of knowing when to, when to draw the next card.

• 22:45Speaker 00

  And then, you know, pay, pay another dollar to draw the next card. And knowing when to fold them. I think that's something we do quite well.

• 22:54Molly O'Shea?

  I was listening to this A16Z podcast where you were talking about your relationship with Mark Andreessen. Could you share a little bit more on that?

• 23:02Speaker 00

  He's, he's on our board. He's been there since 2019 and he's great. You know, I usually get an hour, a quarter with him. I go have breakfast with him. And talk to him about what's going on in the company and it's one of the best, best hours I spend each quarter. I, I, I learn a ton from him. I've never met somebody that's understood the founder journey better than, better than he does. Almost every problem I have, he's like, oh, here's what they did over at Facebook or here or whatever. He's, he's seen it all. So he's been a phenomenal person on the board. Another one is Joe at Silver Lake. So like, I'm, I'm just a tech CEO.

• 23:45Speaker 00

  But now we're doing so much more than tech. We're doing fintech. We're doing services. We're doing this, that, we're doing M and A. We're just doing a million other things that you don't learn to do as an early stage founder. I'm, I'm learning as I go. And nobody does institutionalization of a company and M and A better than the PE people. And so I learned a ton from him and Silver Lake on, on, on how to do M and A. Cause you know, we'll probably do two or three deals this year, another two or three next year. And then how to, how to institutionalize the, the company. That's, that's been super helpful too.

• 24:19Molly O'Shea?

  How has your mindset shifted throughout time?

• 24:24Speaker 00

  You know, I think one of the big inflection points for me was, as an early-stage founder, your job is build a product and sell it. That's great. And so you spend a lot of time building and then you try to sell it, and that's the right playbook. When you get to this stage, what you realize is your job is still to build products and sell them. That is the most important thing you do. But your job is also to build a company that can do it for you. And that's actually really hard. It's hard enough to build a product that people want. It's really hard enough to build an institution that can build a product that people want. Like, Apple, you know, does it so well. It's amazing how good. They just institutionalize it, you know. They just know how to do it. It doesn't take one person over

• 25:07Speaker 00

  there, like it used to with Steve. But that's where I try to spend a lot of my time is, how do you do company building versus product building? You can also make the same mistake, which is, you know, you also get a lot of founders that just love being a founder, but building a company. They love the hiring and the events and the marketing and the, you know, and they lose sight of the only thing you need to do is build something people want. That's it. Everything takes care of itself after that. But once you forget to build something people want, that's usually the beginning of the end.

• 25:43Molly O'Shea?

  A lot of people want AI right now. How are you thinking about involving AI with Carta?

• 25:49Speaker 00

  We're all in. I actually just came from two internal AI meetings. AI is interesting. What does it mean to be an AI company? And some people think of it as, oh, you're building AI products. You're building a product that does AI or uses AI or some AI enablement product. Another is you could be an AI company, building traditional non-AI products, but your internal stacks all AI. You are building a new type of company based on AI. We're both. So today, I spend half my time on product and the other half on AI projects at Carta. And the AI projects come in two forms. One is, how do we use AI to build differentiated user experiences for our customers? So it's all in the product side.

• 26:34Speaker 00

  And then how do we use AI internally to be a better, faster, smarter organization? And I split time on both. And so much of the AI stuff I'm learning, it's like programming. Like it's like being an engineer, but instead of programming using Python, you're programming using the English language. But most people aren't trained programmers. And so much of changing the culture of Carta to be an AI-first company is teaching people to think differently, just to think about. Like I was just in a meeting where a team was manipulating. We do a lot of spreadsheet work. We have a lot of spreadsheet whizzes at Carta, a bunch of Excel people. And they're just manipulating Excel.

• 27:18Speaker 00

  But what I told them is you guys should never touch Excel. The AI should do everything for you. You should just tell the LLM what you need. Or, hey, I need this report in this format and just have the LLM do it for you. And nobody thinks that way, right? Because we've been trained our entire career. Open up a macro, write a formula.

• 27:37Molly O'Shea?

  Yeah.

• 27:38Speaker 00

  And so so much of it is just changing how people think about this stuff.

• 27:42Molly O'Shea?

  I love how you take it from two perspectives, the internal side and the customer side. On the customer side, how are you thinking about what kind of effects you'll have on their experience?

• 27:53Speaker 00

  So internally, what I tell the team about how to build AI products is you got to follow two rules. One is differentiated customer experience that we couldn't do before AI existed. Like you do something for the customer that literally we could not have done a year ago. Just we didn't have the technology. It just wasn't there. So that's part one. And then part two is you can't use a prompt. Because that's what everybody does is they put in another prompt. Like we have this incredible new technology with AI and the world is littered with, nobody has any good ideas with it. They're just like, I wrote another prompt. It's just a better prompt than the other prompts, right? Or a specialist prompt or whatever. It's a health prompt or a finance prompt. So if you reduce the solution set of or solution space of ideas to.

• 28:41Speaker 00

  Differentiate user experience that couldn't exist. And you're not allowed to use a prompt. It actually gets hard to come up with good ideas. Some of the best ones we have are really good. So for example, one of the experiments we're doing with our customers is as they our product's complex, you gotta, you know, you have to understand fund accounting and workflows and treasury and money. And there's a lot of stuff to figure out. And so there's training. So we now have a chat, an AI bot that every time you you load into the page, we directly inject context of the page that you're on and what you're doing. So we can predict what you're what you want to do. So you go in and you click on a capital call link and you load the capital call page. We now know you want to do a capital call.

• 29:25Speaker 00

  We see you now typing in $10 million. We now know you're doing a $10 million cap call. And then the bot AI agent can just go, oh, hey, last time you did this $10 million cap call, these are the three things that you needed to do. And then, and then also you forgot to do the fourth last time and you had to correct something. So instead of correcting it, let's just do it now. You don't never have to ask it a question, right? No questions. It just knows exactly what you're doing at all times during while you're in the application and just helps you do it. That's like one example. We have another example where all of the errors today, most errors are found by humans, unfortunately, which is crazy. Like they click on a button and there's an error, you know, the money didn't move or something didn't happen that was supposed to.

• 30:08Speaker 00

  So now we have agents all night going through, testing all the different possible things that a customer might do the next morning when they wake up. And then we catch the errors before they do. Differentiate user experience that couldn't exist before LLMs. So that's the type of stuff we're working on.

• 30:23Molly O'Shea?

  That's so exciting.

• 30:24Speaker 00

  Yeah, yeah, it's so cool. Like, I feel like a kid again. I'm having so much fun with the AI stuff. It's really incredible.

• 30:30Molly O'Shea?

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• 31:14Molly O'Shea?

  There's another side to AI where people are concerned about how it's going to affect organizations, jobs, that sort of thing. How do you think about this?

• 31:23Speaker 00

  You know, if you look at the history of technology, every time there's a new technology, everybody thinks it's going to eliminate jobs. You know, automobile came about and then, you know, there'd be no more horse drawn carriage people. The calculator came out and then all these people using abacus's would be, you know, out of jobs. It's just never happened in history. You know, the tractor, right? All these farmers would go, like, it's just never happened in history that a great new technology came out and it reduced jobs. Like, we don't have an epidemic of homeless, you know, protractor users. Like, it just doesn't, you know, calculator created more jobs, not less. The same will be true of AI. That doesn't mean the jobs will be the same.

• 32:05Speaker 00

  Just like if you were an abacus, you know, professional and the calculator came out, you had to do something else. But there are way more jobs for all these people because of the calculator. That will be true of AI. The question is, will people learn it? How quickly will they learn it? What will, how will the jobs shift? But this idea that AI is going to create massive unemployment is, everybody thinks that it's just, it's just, if you look at history, it's just never been true. And maybe this is the moment that it's right, but it just doesn't seem that way. It just seems like the potential is just going to create so many more opportunities to find things to do.

• 32:40Molly O'Shea?

  How do you use it? Your workflow.

• 32:41Speaker 00

  I use it for a lot of kind of the basic stuff of like reading stuff, transcribing stuff for me. Especially I can, I can dictate really quickly and turn it into, to written stuff. So there's like all these like little kind of productivity hacks that are helpful. Where I find it most useful though, is actually for other teams. Because I don't do a lot of things that are repetitive. I don't do a lot of things at scale. You know, I, most of my day is eight hours of listening and then I make one or two decisions at the end of the day. Whereas other people that are actually producing things, you know, they're producing reports, they're writing code, they're creating spreadsheets. Like the people that are actually doing production at scale, that's where I think it's been super helpful.

• 33:23Speaker 00

  And so I spend most of my time actually helping them learn to use AI to do their jobs better. And that's, that's been incredibly high leverage for us.

• 33:32Molly O'Shea?

  Performance driven.

• 33:33Speaker 00

  A hundred percent. What's really fascinating about the, the AI stuff is because the reasoning models are getting so good. It's not just that the, the AI is like doing things faster, better. They're so much easier to debug. So one of the things everybody says is like, well, AI makes mistakes. Well, I mean, people make mistakes all the time. The difference is you can ask the AI why they made a mistake and it's very hard to ask a person. Like, why'd you make that mistake? They don't know. They're just like, I just made a mistake, leave me alone. AI, you're like, show me the chain of thought that made you make the mistake. And then you can fix it and they'll never make that mistake again. I think the biggest feature of AI is not that it's smart, it's that it's debuggable.

• 34:16Molly O'Shea?

  And that's more of like work operational performance. I want to get into more of like your personal professional performance. So Sorcery is really proud to be sponsored by Brex. They're all about spending smarter, moving faster. From your perspective, what keeps you going? Like, how do you maintain this high level of performance?

• 34:36Speaker 00

  I love what I do. You know, I often say it's like to be a good founder, it's got to be, I think, for the love of the game. Like, you just love playing. It's like, why didn't Tom Brady retire? Because he just wanted to keep playing for as long as he can. People ask me, like, why don't you retire? I'm like, I just love, I would do this for free. Like, I just love what I do. And if you don't, I always tell people, don't, don't do startups for the, for the money, because if you're doing it for the money, most of the time, you're poor. You know, you're early stage or four, and you're grinding, and it's miserable. So you quit, because you don't make any money. And then, and then if you're one of the very few lucky people that makes it, then you're rich. And then you still wouldn't do it for the money, because you're rich,

• 35:18Speaker 00

  you don't need it anymore. And so you just have to, the love of the game. And I, every day, I just love coming and building products that customers like. Like, that's, that's what I do.

• 35:28Molly O'Shea?

  That's amazing. As we close out, I usually end on one question. What are you most looking forward to this year?

• 35:34Speaker 00

  We have a couple of products that are in the chute right now on the AI side that I think, you know, I think our product and venture and private equity is a 5X better product than what exists today. I think with some of the stuff that's in the, in the hopper, it's going to be a 15X better experience for customers. So I can't wait for that. It's a little bit like, you know, giving a toy to a child, when you, when you build like a really great product, like, your customers' eyes light up. There's no better feeling than seeing that. So I, I can't wait to, to put some customers on some of the new stuff that we're building.

• 36:11Molly O'Shea?

  So exciting. Massive growth, new energy into the company, a lot of things to look forward to. Thank you so much, Henry.

• 36:18Speaker 00

  Thank you. Thanks for having me.

• 36:19Molly O'Shea?

  Hey, it's Molly. If you enjoy our interviews, check out our newsletter, sorcery.vc, where we deliver a once a week top deals and tech headlines email, and also go deeper on our podcast interviews. Subscribe to Sorcery today. And don't forget to subscribe to the podcast on YouTube, Spotify, Apple, or wherever you listen. Link in description to sign up.