The Exchanges

Q Can you, um, can you effectively, are you thinking of, like, fine-tuning a model against certain accounting terms, or doing, you know, like, I'm sort of curious anything about problem solving, or is it just wait for future generations of models to come out, or?

A We did spend some time fine-tuning in many places, and then we very quickly found out that our time was worth way more, uh, and that we should just, like, wait, wait for, like, other generations of model. What we've gotten really good at, though, is hardening our infrastructure so that we can easily switch when we need to, and we can quickly evaluate The different models on the, on the sub-tasks that we care about. Like, I was asked this question by, by, by one of our investors recently. It was like, with, like, the GPT, GPT-Forum Mini, how, how has that changed things for us? Has it brought costs down, and how are we thinking about it? And my answer is like, oh yeah, it's, it's already in production, and for like, 90% of tasks that we're running, it's good enough, so that was a quick switch. And within a day, we can know very quickly, like, that, yes, this is, like, good enough, and we have the right evals.

AI assessment note: “we should just, like, wait, wait for, like, other generations of model.”

Q about are like, as you said, for organizations. And I remember talking to you guys when you were just getting started, you were like kind of discovering that there was all this value in businesses and how businesses spend instead of like your first company was more consumer oriented. Like, how'd you decide to like make that shift and like how, you know, learning about that audience, investing in it?

A I'd say, I'd say a lot of the like really ideation phase of, of ramp. We were, um, Talking to a lot of our friends, people in our community, and it just so happens that a lot of them were either starting early stage companies or joining early stage companies. Um, and a lot of the, the, the problems that we're facing at a larger scale were some of the ones that we're trying to solve for consumers first. Um, and the, the, the funny thing with, with, uh, businesses is the, the, the better they got, and the larger they got, they actually, the more wasteful they would get, and the less they would know about their Not only is it, like, a more interesting, uh, uh, and in some cases, like, bigger problem to solve, it just, like, scales with success in some ways, so, like, the better companies were even more interesting opportunities for us, so, uh we,, we went after that, and there was, I'd say, like, another realization we had early, um, around, uh, like, you look at the user experiences of, of different products out there, and the ones we use As consumers on a day-to-day, like, they obsess over every single interaction, every single flow, like, Instagram's amazing. Robinhood did that very, very well for trading stocks and investing, and then those same people who use these apps in their daily lives show up at work and are expected to use tools that were built in the eighties and are …

AI assessment note: “we saw an opportunity to really bring a lot of consumer thinking around like UI UX”

Q more about how you're starting to use it, both for internal purposes? I mean, you mentioned marketing is now a technical function, which is amazing. How you're starting to implement it for customers, or where does that matter? How you think about that as a regulated entity? So I would just love to hear how you started thinking about using AI and then what that's led into for you all.

A A hundred percent. I mean, one of the early, uh, really, thesis of, of RAMP is if we really want to help you, uh, save time and money, we need context, right? So one of the things we obsessed, uh, uh, a lot over in the early days is We have some amount of information from the card statement. We have more information from the things that we see in your inbox. We can get even more information if we're connected, we're connected to your ERP and you get to a point where like, okay, there's a lot of it. It's very unstructured. How do you structure it and really help companies build and automate the workflows? So, and that's kind of how a lot of the like internal ways that AI, uh, shows up in our product really work. And that like, They tend to, like, we really focus on the job to be done, so in, like, you want to close your books, and there are different workflows that are part of this, and, uh, we're able to work on them a lot faster and really customize them without having to think about every company individually because we're able to just, like, apply a high-level generic, like, um, AI algo with some constraints and, and just make sure that those repetitive tasks, uh, become a lot faster. Uh, so there's a lot of that that we do also on Uh, helping you figure out, uh, what bills to pay and when. There's often a right answer, right? You want to pay the bill at the most optimal tim…

AI assessment note: “that's kind of how a lot of the like internal ways that AI, uh, shows up in our product”

Q on marketing? Has, um, the use of AI or other technologies constrained how many people that you bring in? Does it give them enormous leverage? Is it, you divide it in traditional, like, brand and digital and performance-based marketing and all that? Like, I'm just sort of curious, has it changed a normal marketing department structure? Or is it roughly the same structure if you provide a lot of tooling?

A The structure that we have today is, is, is roughly the same, and we're, like, primarily focused on, on giving them more leverage. Um, I, I think what, uh, what we're trying to do is, like, make sure that they're able to, like, match, um, the speed at which, uh, we wanna, like, continue to build product, and I think a lot of companies, when faced with that, will tend to slow down. It's great. We're gonna stop shipping every week or shipping every month. Instead, we're gonna do Quarterly, quarterly releases and yearly releases, and the problem with that is, uh, you kind of, like, cap yourself, and generally, like, you do that to give more, uh, breathing rooms or more, to have more control over, like, the things you're putting out in the world, and the way we want to do that is by giving those teams more, more leverage and better tooling without compromising on speed.

AI assessment note: “The structure that we have today is, is, is roughly the same”

Q Maybe if you zoom out from that, um, idea of like, oh, like, well, we could have testing like we have in software and sharing, but on copy to, uh, it's weird in general for a technology leader to own marketing, like, you know, project out several years. What does marketing look like?

A Uh, uh, well, the, the one thing that I think will remain for a very long time is, is having good taste. Uh, and, uh, at like at the end of the day, like if you are, even if you are working with the eyes and machines at, Someone needs to decide, like, is, is this good or not? And, and there's this element of taste that you're not going to be able to replace. But what if you could get, like, the, the marketing teams and professionals to just really, really focus on that and remove a lot of the mundane, repetitive. And that's really, like, what I'm, like, obsessing about now is, like, how do we give the people in our marketing more time to focus on the things that are true differentiators and not have to reinvent the wheel on, uh, just really, like, processes that could be Um, hardened and, and, and improved with, with AI. And it starts with, there are different job families within marketing, probably a lot more than there are in engineering. The skill sets are very disparate and very often they need to work together effectively. Those interfaces between different teams are not always, uh, very clear. So like the first, uh, step for me is we really looking at, at, uh, marketing as any other system. It has, Bottlenecks. It has things that you could run in parallel. It has dependencies, and I guess the first step is, like, trying to identify where those bottlenecks are and building…

AI assessment note: “the one thing that I think will remain for a very long time is, is having good taste”

Q with that volume. So they started building internal tooling early for it. So I think it's kind of a common theme for companies that are very thoughtful about this. How did you all think about what to build versus buy? Have you ever thought about actually spinning this out or offering it as a product to your customers? I'm sort of curious how you think about those dimensions of this.

A So I, I think that question gets asked a lot and like you generally get with a nuanced, like it depends answer, which is generally right. But the one thing that doesn't get talked about is, um, we can kind of assess generally whether if you decide to build, if you've done a good job building or bad job building, it's very hard to assess when you, Do, uh, when you decide to buy, whether you did a good job buying or not buying, and it's not something that really comes up in, uh, say, I don't know, a performance review or in the way, like, people get evaluated internally, which is kind of crazy when you think about it. Like, we talk about people being great in organizations because they're great at hiring and recruiting, and, but you never hear anyone talk about, oh, this person, like, picks the right vendors.

AI assessment note: “I think that question gets asked a lot and like you generally get with a nuanced”