Invest Like the Best with Patrick O'Shaughnessy - Karim Atiyeh - Building Ramp - [Invest Like the Best, EP.445]

Episode Date: October 21, 2025

My guest today is Karim Atiyeh. Karim is the co-founder and CTO of Ramp, the fastest-growing finance automation platform in history, reaching over $1 billion in revenue in just over five years. Ramp is, of course, also our presenting sponsor, so I’m obviously very biased in how highly I think about Ramp and about Karim. But, this interview was not part of that sponsorship, I simply view Karim as one of the best operators active today. Ramp is building what Karim calls "self-driving finance"—using AI agents to automate everything from expense policy enforcement to invoice processing, eliminating the bureaucratic waste that plagues modern businesses. Karim shares his framework for moving from using AI as a productivity tool to programming AI as your actual product, with policy agents that understand context better than humans and improve continuously. Our discussion captures the relentless iteration speed and technical depth required to build generational companies in the age of AI. We explore his systematic approach to building consumer-grade experiences for business software, the psychology behind his "divinely discontent" management style, and why he believes technical founders will dominate this era because they can see possibilities others miss. Please enjoy my conversation with Karim Atiyeh. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠.⁠⁠⁠⁠⁠⁠⁠⁠ ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ramp⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ramp’s mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ramp.com/invest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to sign up for free and get a $250 welcome bonus. – This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ridgeline⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ridgeline has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Head to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ridgelineapps.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to learn more about the platform. – This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ AlphaSense⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. AlphaSense has completely transformed the research process with cutting-edge AI technology and a vast collection of top-tier, reliable business content. Invest Like the Best listeners can get a free trial now at⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Alpha-Sense.com/Invest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and experience firsthand how AlphaSense and Tegus help you make smarter decisions faster. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Show Notes: (00:00:00) Welcome to Invest Like the Best (00:05:09) The Competitive Landscape and AI Advancements (00:07:27) Building Self-Driving Finance with AI (00:08:28) Policy Agents and Automation (00:12:14) Ramp's User Experience and Design Philosophy (00:23:10) Kareem's Background and Entrepreneurial Journey (00:28:06) Founding Paribus and Lessons Learned (00:41:57) The Birth of Ramp and Early Challenges (00:54:30) Nurturing Investor Relationships (00:57:10) Challenges in Fundraising (00:58:23) Customer Adoption and Product Evolution (01:01:55) Transition to SaaS Revenue Model (01:06:37) Marketing Innovations and Experiments (01:24:16) Recruiting for Spikiness and Speed (01:31:29) Future of Payments and Business Models (01:39:06) The Kindest Thing

Most software companies try to maximize your time on their app to juice engagement. Ramp does the exact opposite. Ramp understands that no one wants to spend hours chasing receipts, reviewing expense reports, and checking for policy violations. So they built their tools to give that time back, using AI to automate 85% of expense reviews with 99% accuracy. And since Ramp saves companies 5%, it's no wonder that Shopify runs on Ramp, Stripe runs on Ramp, and my business does too.

To see what happens when you eliminate the busy work, check out Ramp.com slash Inverc. Hello and welcome everyone. I'm Patrick O'Shaughnessy and this is Invest like the Best. This show is an open-ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money. If you enjoy these conversations and want to go deeper, check out Colossus Review, our quarterly publication with in-depth profiles of the people shaping business and investing. You can find Colossus Review along with all of our podcasts at join colossus.com. Patrick O'Shaughnessy is the CEO of Positive Sum. All opinions. expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion

of positive sum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of positive sum may maintain positions in the securities discussed in this podcast. To learn more, visit psum.vc. My guest today is Kareem Artia. Kareem is the co-founder and CTO of Ramp, the fastest growing finance automation platform in history, reaching over a billion in revenue in just over five years. Ramp is, of course, also our presenting sponsor, so I'm obviously very biased in how highly I think about Ramp and about Kareem. But this interview was not a part of that sponsorship. I simply view Kareem as one of the best operators active today.

Ramp is building what Kareem calls self-driving finance, using AI agents to automate everything from expense policy enforcement to invoice processing, eliminating the bureaucratic waste that plagues modern businesses. Kreme shares his framework for moving from using AI as a productivity tool to programming AI as your actual product, with policy agents that understand contexts better than humans and improve continuously. Our discussion captures the relentless iteration speed and technical depth required to build generational companies in the age of AI. We explore his systematic approach to building consumer-grade experiences for business software, the psychology behind his divinely discontent management style, and why he believes technical founders will dominate

this era because they can see the possibilities that others miss. Please enjoy my conversation with Karim and Tia. Kareem, we're going to start this conversation at the very end, which is today, because you have one of the most unique perspectives on what's going on in the world as this technology paradigm is shifting, where you're not an upstart anymore. You're a big established company, but at the same time, you run the company like an upstart, like it's day one, and you're up against massive incumbents. And so the reason I'm interested in this cocktail is this is going to happen in every industry,

where there's big, stodgy incumbents that have been doing things a certain way for a long time. There's going to be fast, talented young companies that challenge them. And so I'm curious for you to detail what it's like to be in that position right now, where you're past a billion in revenue, you're one of the fastest companies ever to go to that size in five, six years. And you're up against Amex and companies like this. What does that feel like? What does the competitive battlefield feel like to you today?

It's very exciting. but even when you are describing us as no longer an upstart, I still haven't internalized this, to be honest with you. The most exciting aspect of being a startup is that you get to grow very fast, make decisions quickly and move quickly. So we are trying to maintain that as much as we can. And we do this by essentially breaking up

all the different problems we're trying to go after and give small teams full autonomy over these problems. So every time I spent some time with a small part of the company it does feel like they have full autonomy over the problem they're going after and the way they're building. And I'd say with what's going on with AI advancements and the different ways that companies are starting to build is that every company is trying to figure out how to adopt those new technologies and benefit from them. And you're still in the phase where you have these articles coming out every couple of weeks that are mixed. Some will say like, oh, companies

are adopting AI but not seeing any benefit. In another week, you have an article from someone you think highly of or you trust saying that their company has adopted AI in some part of the organization. It's had an immense impact on them. So it's still early. It's obvious to me that the impact of adopting the technology are transformative, but a lot of companies are still stuck in the very early phases. And I would describe the first very early phase as you are using those LLMs to do the same work that you were doing before, maybe a little bit faster or more efficiently. So if you're a developer, for example, you are using AI to help you write a little bit more code. So you're not sure on how to write the next couple of lines to codes.

You go to a chat GPT, you go to an LLM, and have it give you advice. You get some code. You copy it, you paste it. Maybe you go a little bit further and you start using these agents where you describe your problem in English and you use a cognition or a cursor and then you get a lot more code written for you and then you're reviewing it. And that's cool. But I think that next phase that we're entering and the one that I'm seeing in our company is one where you start thinking about these LLMs really as part of your product and you're

programming them. So you're no longer writing the same old code that you used to write with the help of LLMs. Your code is the LLM now. Your code is the LLM plus instructions and an infinite loop. So you're essentially writing those agents. We're in the middle of that right now. Do you have a favorite example of that so far that you've actually deployed in this work. Yeah, of course. I'd say the most obvious one is what we call internally the policy agents.

So most companies have a travel expense management policy. It's generally a document. Sometimes it's well written and clear and sometimes it's not. But that's essentially a document that you write to drive the behaviors of people in the company and how they manage their expenses. In the old world, people make transactions. And before they make the transactions, sometimes they'll go and check the expense report. Sometimes they try to remember it from memory. they'll make a transaction, they'll file an expense report, and some manager will try to make sure that some manager or someone on the finance team will try to make sure

that the expense that was made by the employee actually abides by the rules of the expense policy. It's very manual. Generally, the transactions are missing context. So there's a lot of back and forth between the people enforcing the policy and the people who made the transaction. It takes a lot of time.

So we've built our policy agents in a way that it has more context about the transaction than most people reviewing those transactions today. So it's integrated with your calendar. It's integrated with your email. It knows your expense policy, et cetera. And more context about the policy than any employee. So it can run 24-7 as transactions come in and apply the logic of the expense policy

against these transactions and decide whether something is in policy or not. And do that a lot more efficiently than any human. So you have a 24-7 live enforcement of your policy. And not only that, but as it runs over time, it gets better. better at advising how to make the policy a little bit clearer or easier to interpret and your policy becomes better and better over time. Maybe to make that a little bit simpler, instead of having deterministic codes tell software what transactions are in policy or not, you essentially have this living, breathing text document that can evolve over time that's guiding an agent that has

access to tools like your calendar, email, et cetera, on how to classify transactions. And that same principle applies in so many different parts of the company. Now, the good thing about expense policies is most company have them, but companies do all sorts of things that sometimes are not written down that can be very easily automated by agents. So for example, when you receive an invoice as a company, what do you do? It's like, well, you do a couple things. One, you make sure that the invoice is not fraudulent, maybe. You make sure that you're being invoiced for a that you've actually ordered, the product that you've actually received.

You make sure that the price matches what you had negotiated. So there's a lot of steps that actually happen before and after any payment that a company makes. And most of the time, they're not very well documented. A lot of work that we're doing right now is because we have so many interesting customers and they're using the product to run their finances, we can infer a lot of these policies through their behavior. And a lot of those policies that we're inferring are driving the next generation of agents that we're building. I was with an old friend last week who was in town for, I think Visa had some sort of big conference in New York last week.

And all the various players from your competitors and people in your industry were there. And he told me that he had no affiliation with you or with me that everyone there was bitching about ramp taking all their customers. And I'm curious, what you think the most common reasons are for that? when you're beating whoever it is, what are the most common attribution reasons when you study why a given customer is picking you over somebody else because it seems a little bit like

slowly than suddenly thing is happening with Ramp. You and I have talked about this offline. And I'm curious why it feels that way to you. I think it relates to the speed of product and everything else, but I want to hear it from you. I still go back to the early days and why a lot of people even picked us when we didn't have that much credibility

or social proofing. I'd say a lot of it was our obsession over wanting to build consumer grade user experience for a business product. You think about a lot of the business products that were built in the previous generation. They were essentially built for decision makers. So you think about building an HR tool or anything. It's like, well, who's a decision maker? It's like, well, that person on the team, great. It's like, we're going to build it for them.

We're going to pitch it to them and we're just going to convince them to switch to us. And once they do, we're going to care a lot less about them. And then you end up with these business software that is used at a company that maybe solves the problem of the one decision maker but makes everyone else at the company very miserable. So you solve one person's problem, but you give everyone else of the company just a small paper cut every day. And we wanted to reverse that. I would challenge you to find anyone who enjoys using concur, for example. There's a lot of business software that was built in that way. No care for the user experience.

And when we set out to build ramp, we wanted the user experience. of an Instagram, but applied to business software. Design obsession has helped us a lot and just polishing every single interaction, making sure that we only ask questions that are absolutely necessary, that we can pre-fill any form that can be pre-filled so that you have as little work to do as a user of the product.

And over time, we got even better at this because we get even more data about how people wanna use the product and we can skip even more steps. And that obsession over design really turned into an obsession over minimizing the amount of time people spend in our app. I was going to ask what the process is to make that possible. So someone else listening wants to build a consumer grade app and some other business area.

What is the actual practice of doing that over and over and over again? You keep looking at every interaction that you have with a customer, right? It could be an email. It could be a form. And then you ask yourself, how can I figure out the answer to that question myself without asking the customer or if I'm telling the customer to do X, why can't I do it for them? So for example, I'm sure you've gotten one of those error messages from a product that you've used that will tell you, hey, Patrick, you tried to do X. It didn't work. You might want to try one retrying the payment or the transaction, two, changing your bank account details or something like this. Well, instead of doing this, we could retry it ourselves, for example. And if we are asking you to change your banking details or to submit a piece of information, instead of just telling you an email, like go to our website and submit your information, we could have. have a form right there that allows you to submit your information in the email. So there's always

a way to skip a step and make it a little bit faster. We're essentially always obsessing over that. Can you talk about, I feel like this is rooted in your personal psychology. I was talking to our friend David before this and he uses the phrase all the time, divinely discontent. He told me the story of the day that you announced the $13 billion valuation round, which of course is an exciting moment in the company's history, that he was with you and all you were. were doing was screaming about problems in the product and the team and things not moving fast enough and like zero enjoyment on a day that you would have had a good excuse to be a little bit more relaxed and instead just pissed off about something in the product not being good enough.

Can you talk about where that comes from for you? How long it's been like that? There are probably two reasons for it. One is I forgot the exact quote from Jeff Bezos in one of his letters. I really believe that a lot of the results that you are seeing today at R&RD efforts that we put in in solving the problems six months to a year ago. So the current quarter was baked in a couple months ago. So I always find it a little bit weird to celebrate lagging indicators today. And I don't know.

I often think that they put at risk some of the very important work that we are trying to do today and solving the problems that we have today because people might feel like, oh, things are going amazingly. well, we don't really have any problems, and that's not true. There are always problems and always ways to make things better, faster, more efficient, et cetera. So it's the assignment of like, hey, we're working on such important things. And if we don't realize that they're really important, we might mess up the next six months and the next year. So that's part of it. The other one is, I feel like if things were good and we didn't really have problems,

I wouldn't know what to do with myself. Like, what are we doing here? if the job's actually done. And the good thing is the job's never done. We could always push it further, do better. There's always more time that could be shaved off of every single user interaction experience. As I'm talking, I'm visualizing these charts

that I'm sure you've seen. Every time I look at them, I get a bit frustrated of amounts spent in the U.S. on healthcare in total or on education. And you see these charts that have been going up every decade for the past couple decades It's where we spend more and more, and a lot of people would say that the outcomes are not necessarily, they're probably better, but not as much as you would expect given the spending.

If you dig in a little bit deeper, it's like, where's all that spending going? It's very obvious that it's just being wasted on administrative PS and things that don't move the needle. It's not being spent on more training for doctors or healthcare providers. It's not being spent on more training for teachers and better educational outcomes. It's being spent on a lot of bureaucracy and BS that doesn't move. the needle. And I think a lot of that is what we are trying very hard to reduce. At the end of the day, we serve the companies that are our customers. And I'm sure they have a lot of, they feel a lot of drag and they might feel like things are moving slower than they would like to. And we want to

play a big part in accelerating that. I want to learn more about how you bake this into the culture. It seems like this is maybe the central tenant of the ramp culture. There's a funny story. I heard the day or another, actually it's just literally right over here, another founder was telling me about the experience of selling his product to Ramp, which is a customer now, and that the last thing that happened was, whoever was buying it, it was some random person at Ramp said, we'd like to do it, but we won't do it until you've confirmed that you are a Ramp customer for your business. And so it seems like there's this bite at the edge of the spear at all parts of Ramp, and obviously you're hammering this into people. How do you do that? Describe the process of keeping the

culture focused on that tenant. What I like about this is from the very start at ramp, we tried to create a culture where people have mutual accountability to each other as opposed to this tab down culture where you have accountability to your manager. And people want to do well because their peers, their colleagues and other teams depend on them. So that creates a culture where sales cares a lot about product and product cares a lot about sales and marketing cares about finance and vice versa. That's probably where this comes from. We all need to be selling our products. We all need to be making the customer experience better.

We all need to be advising our product builders and what we're hearing from customers so that we can take their feedback into consideration. I just think it works. If I go back to the early days of Ramp, the way I look at it is my most important filter for the interviews I used to do early and still do to this day is if this person was starting a company

and I was looking to join a company, would I join them? or would I start a company with that person if circumstances were different? That is the only bar. If I had to summarize my interview, it would just be that. And that comes from the ability

to persevere in the face of challenge and continuously solve hard problems because at the end of the day, a company is just a collection of people solving problems together, one after the next, and they keep getting more difficult and bigger. And the question is,

how much can you endure for how long? And the best way to do that very well is to be on that journey with people who are very aligned, aligned on the values, the mission, and this is the journey that they're on. There are always going to be more problems. The job is never going to be done. Hopefully we're enjoying solving these problems together for a very, very, very long time. You and I start talking and we very quickly get in the weeds. And sometimes I forget that people don't know every little inside nook and cranny of ramp like I'm lucky to. maybe just describe for people how you think about the business today, what it is, what it does, who it's for. I don't want to presume everyone out there knows what the answers to those questions. So maybe just give us a little bit of extra context on what your model of the business is today as one of its leaders.

Yeah, of course. So at Remp, we're building a finance automation platform. It's for finance teams of companies of all size from startups to large 100,000 plus employee companies that helps those finance teams run everything from expenses, procurement workflows, account payable workflows, accounting automation, reporting as it relates to the way that they are spending money in their company. And a lot of our focus is in building systems and product that automate a lot of the busy work away. And we've tried to essentially stitch together a lot of the workflows that today are very disparate, can live on 10 or

20 different systems and as a result, result in incredible inefficiencies for most businesses that are now closing their books in weeks and month instead of essentially having a live view of what's going on in their business. So if I were to think about a developer and the way they orient towards AWS or something, we've got this massive menu of stuff that makes it possible for me to build like a serverless application and not have to worry about any of the underlying stuff. Is it a clean enough analogy that effectively you're doing that for the finance part of a business? Yeah. Over time, I mean, I would say that part of the intent is to make it a lot easier to build and run companies without having to be a finance operations experts. You can worry about

your company, your mission, whether it's a restaurant or a soccer team or really whatever it is without having to be a finance expert. It can run on autopilot. What's the scope of this? How much money do businesses spend a year or something? Oh my God, so much. It is on the order of hundred plus billion dollars per year. If anything, I think there's something interesting happening today where I'd argue that probably most primary thing that businesses spend on is payroll for a lot of businesses. But as the world is shifting towards using more and more and more agents that are built by other companies, it's very likely that more of that payroll spend will essentially become software spin.

I think it's only growing. To rewind the clock a little bit, if we were writing the book, Karim's entrepreneurial journey or something, what do you think would be the prolog? What would be the opening scene of that story? It would certainly have to start in Lebanon and Beirut, which is where I grew up.

And I grew up in a very, I guess, interesting period of Lebanon's history because I was born right at the end of the Civil War. And if you rewind the clock a lot in Lebanon, You'll see that it's always been periods of peace followed by some form of conflict and war. And I was born in 89, 90, and I spent the first 16, 17 years of my life there. And it was a relatively calm period. Always spurts of conflict, but nothing really major.

But you could tell growing up there that a lot of the previous generation was scarred from the war and everyone was kind of living on edge. So in other words, I'd say a sense that things are very ephemeral and could disappear very quickly was there and the air. And or in a sense for my parents of, hey, you're going to have to do the best you can so that you maximize your chances of getting out of here and getting into the best school that you can so that you can get a visa and build a better life for yourself abroad is very important. I was living with that stress, maybe hanging over my head in a country that was constantly exposed. to all sorts of risks that I've learned to live with external risk very well, I would say. It doesn't really phase me. Okay, so you're 16-ish.

Maybe tell the first story of coming here, what you were doing, who you met. I love your personal story. So what happened when you're around 16? Even before coming, I would trap myself in libraries in Lebanon and just find books and magazines that I was interested in. And I still remember just opening up a bunch of science magazines in particular. and just looking at the latest advancements, discoveries, and every time I'd look at a new discovery that was made,

it was scientists at MIT or researchers at MIT, and just the name MIT just kept coming up as a place where a lot of incredible engineering discoveries were made. As a result, I was just fascinated by MIT as a school. And then I look around, I guess, my high school, and there was one person a couple years ahead of me who had gone to study MIT, so I reached out to them and asked them, what is it like? What's a good way for me to, I guess, expose myself to type of work being done at MIT? Do they offer any summer science programs? And that's when I hear about a summer science program that was hosted at MIT called the Research Science Institute, RSI. So I ended up looking into that program and applying and coming a year and a half before college in 2000. to MIT for the Research Science Institute, which was very transformative experience. It was my first time in the U.S. by myself for an extended period of time.

I had come as a tourist with my parents, but I think I'd come to Disneyland once. RSI was dead. I was on my own with another 60, 70 or so students, all brilliant, incredibly talented. And even before coming for the program, we had to pick what our research. subject or topic would be. And I had picked computer science at the time thinking that it's great, I'm going to learn a lot more about it. And it turns out that the expectation was that I would do computer science research and not

learn about computer science. That's where I was essentially put under, I guess a lot of stress that are great. I not only need to do some research, but I also need to teach myself a lot more in a very, very short period of time. It was a fascinating experience where I ended up working. at this small startup off of Kendall subway stop in Boston, the Kendall T-stop, called Virage. And at the time, what Verage was doing was buying lots of video news feeds from all over the country. So they'd buy like the news feeds of the local ABC station in small town in Texas all over the U.S.

So they'd buy all those TV news feeds, convert the speech to text, and then classify the text using Markov chains. And a lot of techniques that we're using are essentially like the ancestors of what LLMs rely on. It's a lot of the best technology available for doing natural language processing at the time. And my research project involved training these models that they were using a lot more efficiently than they were. So very interesting. At the time, the technology was very nascent, but it was a very cool experience. And I guess the best part about it all is the friends I've made along the way.

Some of my best friends to this day I've met through RSI. It was a very fun experience. Maybe you can zoom forward to starting paribus, why you started it, and what the original idea was. In the ramp story that will be written about one day in some book, it'll be a key chapter, I think, because of the people that come into your life, working together with them in a more formal capacity for the first time, the business lessons that you're learning. So my interest in Paribus is especially,

what are the key lessons that you learned in that chapter? Yeah, of course. Well, Paribus was an interesting one. So I started Paribus with Eric, so same co-founder as Ramp, obviously. Eric and I at the time were both fresh college graduates in New York, working at our first jobs, both incredibly busy at work. We were buying a lot of our supplies on Amazon, online,

and we were essentially doing a lot of online shopping. And Eric notices after a trip that the price that he had paid for a flight for his girlfriend at the time was very different than the price that someone else paid, and he notices that there's a discrepancy in the way items are priced online. And we were very lucky in a sense because that was around the same time that data science was starting to become

that function that is very key for really everyone, but online retailers in particular, we're starting to employ data teams and dynamically pricing their items to try and maximize their revenue. I was in consulting at a time, a little discontent as well. I guess that's maybe the recurring theme.

It was like I kept feeling that we were put on these projects, really smart, very ambitious people, to do a lot of manual work that could be done a lot more efficiently with software. And every time I would try to suggest that we write a little bit of software, I would get maybe a nod and yeah, that makes sense. But the incentive just weren't aligned because the consulting firms are pricing for a number of people spending time on projects. So no one really had the incentives.

incentive to minimize the time spent on projects and just maximize the value. But even then, I find myself running quite a bit of software during my consulting days, which is probably why the first version of Paribus that we built was essentially me writing VBA macros in Excel to track prices. So the very first version of Paribus was an Excel spreadsheet that had a set of SKUs and a job running in the background that would check the price of every single one of those. items every day on Amazon. And you could do this with VBA. The programming language really doesn't matter. You can open a web browser, get to the right page, and pull the price, and do it in a loop.

And that was the first version of Paribus. When we're trying to figure out, is there a business there? Are prices changing quickly enough that there's enough money to be saved for customers, that there's a business model there? And clearly there was. Even in the first month, we were tracking prices, we not only noticed that, yes, prices were changing, but the rate at which those changes was happening in that one month in 2014 was increasing over the course of a month. And that trend essentially never stopped. So we quickly realized that there was a business there. Prices were changing incredibly quickly. And at the same time, all online retailers had some form of promise to their customers that if prices were to drop and to change, there was a best

price guarantee or a price match guarantee. And the reason they do this is because they want to give their customers the confidence to just... Chop with them by default. Exactly. Click that button, just do it. If something changes, we'll get it back for you. But they're also banking on the fact that no one really checks the prices of the items they buy after they bought them. With purpose, we just automated all of it. The idea was like, well, all these retailers have armies of data scientists working for them to price discriminate. To price discriminate. And we're going to arm the rebels, essentially. We're going to build a technology for consumers, the best technology possible to try and minimize the amount of pain in their online shopping experience and maximize the amount of money

that can recoup after the fact by holding retailers accountable to their guarantees. And we did that incredibly effectively, and it was very popular. As you can imagine, like if you're a customer or a consumer and you see a value prop of click a button, save money, it's free, but it's pretty great value prop. So it grew incredibly quickly. I think within the span of a year where we're like approaching a million users is growing very fast. And the experience of building it was incredibly challenging because unlike ramp or unlike every most tech companies, you're building. a product on top of a very unpredictable foundation. We are building products on top of the websites of retailers

who, one, don't want us there, two are changing their pages all the time. And three are heavily incentivized to make it harder for us over time. And when we started building Paribus around that time, Amazon still used to send receipts to your inbox. I don't know if you remember this, but you used to get a full itemized receipt with the price of every single item that you bought.

You don't anymore. You now get a link that says, thanks for shopping at Amazon. If you would like to see your receipt, please click here. And you have to go to Amazon.com, log in, press a couple buttons, and eventually you make it to your receipt.

So they made it harder over time to get those receipts. Pretty sure that we were running one of the largest scraping operations in the U.S. at the time going through at some point billions of emails per day and tens of millions of receipts per day. So what did that teach you? Both strengths and weaknesses,

things that you would bring with you to ramp, but also things that you would leave behind. I would say a lot of pragmatism in engineering systems, this idea that you're never going to really build the perfect system, so you're better off building something quickly that will break in very predictable ways, and you are able to recover from incredibly quickly. So the idea with Parabas was you start with the assumption that things will break,

that you are trying to speed up the process of fixing them quickly when they break, as opposed to building the system that will never break. And it is very different from how, I'd say, most experienced engineers learn how to do engineering at larger companies, where you are trying to build like a great system that will not break and they will withstand the test of time. And there's a beauty to that as well, but that's very different from the way we built things at Parabas. So the name of the game at Parabas is build it very quickly and make sure that it breaks predictably. And a lot of these lessons we certainly brought with us to ramp with some

nuances, obviously. I would say like the first big split that we made that ramp and the way we built product is there are parts of ramp that we should build in a way that they will never break. And we've got to be very careful. The way we built them and experience in building those systems is very valuable. And there are other parts of ramp where we need to iterate very quickly, assume that it's going to break very quickly. Well, that it's going to break, but we need to improve incredibly fast. And we split the product and engineering teams along that boundary relatively quickly. So anything that touched money, money movement, risk falls in the category of you need to build it right and make sure it doesn't break and assume that you're not going to have

to innovate that much, frankly, on it. It's like, you just need to. You just need to build it. You just to build that system really well. And there are a lot of parts of ramp where we've innovated a ton, pulling receipts from a mailbox and trying to match them as best you can to the right transaction, it's like, well, if it works, it's amazing. If it doesn't work, it's whatever. No one's going to feel it. No one's going to see it.

It's just that a receipt was a match. That's fine. No other company is able to match receipts nearly as good as we are. So it's okay. If you are, let's say, optimizing any form or experience. on the website, like, well, the button is non-functional for a couple minutes, or the colors change, or the font is not correct, that's fine. Someone will complain about it and you'll fix it very quickly. It's okay. And to this day, there are little parts of ramp that are probably

breaking 10 times a day and we're fixing them like 20 times a day and no one's really noticing. Especially early on, I think when you have customers that already perceive you as a small startup up in a small company and may have some doubts about your capabilities. I often find it a much better way to build credibility with them and trust if things break and you fix them very quickly as opposed to if they just don't care and don't notice anything by the products. One of my favorite things to do is just be very quick to respond when a customer brings up something that's broken or we notice a subpar experience in the product and we see it

as a personal challenge. How quickly can we notice and how quickly we can fix it? If I take that lesson away, in parts of the business when you're building a product that have minimal downside and high upside, you actually want things to be breaking. Otherwise, you're not taking enough risk. Is that the... A hundred percent. I think it's very easy to fall into the trap of, well, we want to make sure that there are no bugs. It's like, you know what's one great way to make sure that you have no bugs? Don't chip anything. Don't write any code. You will have no bugs. And that's the problem with that approach. So I think if you are solving for great outcome and great impact, you want things to be breaking.

What was the craziest moment in the history of Paribus? Oof, there was a period of time, I think it was a couple weeks where we were getting angry letters and cease and desist from multiple retailers. and we're getting these letters from notorious law firms that we had heard of and we're a team of 12, 13 engineers fresh out of college and trying to Google the name of the person sending us a letter or the name of their firm is like, oh my God, this is a multi-thousand people law firm that represents the largest corporations. And my hunch would be to send them a I'm sorry response.

And I'm like, okay, we can't really do this. What do we have to do here? And the way we responded to it is just trying to explain in very logical terms what we were doing and why it was good for consumers and why they should care, which was really funny. But one of those crazy experience was we'd get a letter from Amazon around how we were supposedly compromising the security of the accounts of their users. And I thought it was really funny at the time because a lot of the product that we had built was, one on AWS and two with the help of a lot of AWS architects

in order to make sure that it was built as well as possible and as secure as possible for the users. So our response was great. We'd be happy to get out of call with your team that is helping us build this in the most secure way possible. And we got on a call with, I think it was either Andy Jassy or someone very senior on his team at the time when he was running AWS

to just go through our architecture and how we were building this. It seemed to me on the call that they were actually very excited about what we're building. It was like, this is really cool. We liked this. And we ended up the call with this understanding that AWS was actually really happy with us and that our problem was with Amazon retail. It ended up getting resolved, but just as a really tiny company being attacked or

attacked by the legal teams of really massive companies feels really, really scary at the time, but in a way, like also validating. Is that helpful to be scared early? Because then you just get less scared in each subsequent time that there's something major breaking. Does it just not phase you anymore? If you solve really scary, small problems,

their reward is scary, bigger problems and it never stops. There's always this line, people talk about product market fit as a stage. It seems like a more interesting stage is when is the first time that someone tries to kill you? Like the story you just described. Do you agree with that?

Oh, for sure. You were analyzing a company, like almost better to invest right after someone's trying to kill them and they survived. Oh, 100%. If you're doing anything that's correct or right, people are going to try to kill you multiple times. What's the key to not being killed? Perseverance. There are a lot of nuances there, but... Tell me.

I think it's just to never give up to some extent. I never see the possibility of us. being killed as an option, to be honest with you. Like, I'm constantly looking for the multiple ways that we can withstand a challenge and how we survive. And I see the risk when that happens as us endlessly talking about the options

and not maybe taking enough action. So I try to get into gear really quickly so that we could just start acting on the ways that we will survive and not get killed. So when a challenge happens, I tend to look through all the ways that we succeed and maximize the chances that we do. And I think the companies that don't do that well tend to die. Die because spent a lot of time thinking and talking and not enough time doing as opposed to

because they don't see the options, frankly. What did you learn at the end of Paribus's story? So you sold the business to Capital One. Why did you sell it? Lessons are learned in selling a business. You make good money doing it. Yeah, I guess we should go back to that. The Parabas story was very, instrumental in us wanting to start ramp, to be honest, because at the time that we sold Parabas, we weren't really looking to sell the business. We were looking for partners that would help us grow. And we thought about it in that way. It was like, well, we know Paribus is really great. It drives a lot of value to people who have shopped online in very predictable ways. And we're looking for partners who could help us figure out who shopped online recently so that we can get in front of

them, make a compelling pitch, and hopefully convert them into a user. And who better for that than the credit card companies? They know exactly who made a purchase at Amazon or Walmart or Jet.com at the time recently. We got to meet the team at Capital One and really enjoyed working with that one. They're a lot more tech savvy than most of the other bank, and that's the reputation they have, which is great. And we were in partnership conversations with them, frankly. they were interested in building differentiations for the card product because, I mean, at the time, and frankly, to this day, a lot of the consumer card products still fail, like, different versions of the same product just marketed differently.

So they were interested in differentiating through product and partnerships, and we're interested in figuring out who had recently purchased something at Amazon or Walmart. So during partnership conversations with Capital One and around the same time, we're getting a lot of these league. challenges it's clear that we needed more fire or power whether in the form of partnerships or in the form of capital just to withstand the storm and quickly those partnership conversations with Capital One turn into acquisition conversations we get really interested because our visions were clearly very aligned with the Capital One team they wanted to give us the capital to support the funding to essentially turn the antagonistic relationships with the retailers into more

friendly relationships, and they had a lot of great relationships with those retailers. So that was very interesting. But the most interesting part about those acquisition conversations is we got to learn a lot more about the credit card industry, how it worked, where the revenue came from. And it was fascinating to see that product that you essentially, the card business, they essentially put in the hand of customers. There's no contract that anyone needs to sign. it's like the more they use it, the more revenue you make,

and you can just focus on making the product as good as possible so that they use it as much as possible. And it was refreshing. It was like, great. Like you just put this card in the hands of a person and the more useful it is to them, the more they use it, the more revenue you make. So we started understanding that fascinating business model,

and it felt very powerful to, at Capital One, combine that card with the Paribus offering. So it just felt like a great natural fit. Two years into our journey, so after spending about two years at Capital One and growing the Parabas product, which is now called Capital One Shopping, and includes some other features that I think are very valuable. We started thinking, what's next for us? Both Eric and I were clearly not done with our entrepreneurial journey. We wanted a bigger challenge. And a lot of the idea for Ramp early on was what if we built something like Paribis for businesses.

Specifically, what if we built technology to help businesses save as much money as possible? And that later turned into how can we build technology that helps businesses save as much time and money as possible because businesses, as we both know, tend to waste a lot more time than they do money and those are generally interchangeable. So we set out to build ramp

and just like it was the case for Paribus, really the card early on was a way to, to know what businesses we're spending time and money on. If you know what tools they use and how much money they're spending on them, you get a sense of how the business functions, what kind of business they are, and you eventually get a sense of where they are wasting both time and money and how you can help them save as much of it as possible. And this is still true to this day about RAMP.

I'd say the biggest difference is the scope of our ambition has gotten a lot bigger. We're not only helping businesses with the money and the time they spend on, let's say, like, card purchases, but it's really all the spend that is happening across their business and all the workflow associated with it, starting with procurement, right, which you could describe as the workflows that dictate how a business makes decisions on what to buy and how to buy it, how to negotiate for it, et cetera, all the way to accounting for those transactions. and reporting on it. So the scope of our ambition has gone from the mode of transaction, the card, to all the workflows happening before, all the workflows happening after, and all the time wasted as that is happening. So if I go back to day one of Ramp and this notion that you need a way to know what's being spent where and how and why by whom, talks through like the very first version of the product.

A dumb investor at the time might have said, what the hell do we need another credit card for lots of business credit cards. And Amex had a great brand. Yeah, exactly. Just to pick one. There were more than just Amex, but people loved Amex. It had a pretty sterling brand. Amex for business. It was a huge business. Why do I need another card? So bring us into the

room of you're talking about what literally to take as a first step and who did send it to and why. Just the first couple days are always so interesting. And who raised money from? Like, how you figured that out is the deep detail. It's so fascinating. I agree with you. They still have a really good brand, but at the time, that's all they had.

They have a good brand, and yeah, I guess you could log in and check your statement, but that's about it. Funny enough, our pitch in the early days before we had officially launched as we were looking for design partners and people to give us feedback on the product, it wasn't like this is amazing and going to change your life. It was, this is not worse than Amex. And you might as well give it a try. So it's like, it's a card, it works.

It does all the things, the Amex card or any other business. guard will do. And because we have built maybe direct trust with you, you better trust that we will make it better for you over time. What a pitch. It was a terrible pitch. But we went and essentially sold us to, yeah, friends and family, people who trusted us, not because of the product we had built, but just because of their belief in our capability to improve the product over time. So these were people that we had gone through a Y Combinator in 2015 with Peribus. These were my brother who was also starting his company. A lot of our friends who were entrepreneurs in New York and in the startup ecosystem in New York.

Those were our early customers. They were partners more than they were customers, frankly. They were design partners. Because the first differentiation we really built and we pulled from some of the skill set we had acquired at Paribus was a very robust integration. with your email. You make card transactions. A lot of the receipts go to your email. How do we tie these two things together as effectively as possible? And we're really, really good at parsing emails while preserving the privacy of your business emails. We built some tech that would identify the emails that are very likely to be receipts, extracting those, identifying purchases,

and tying them to your card transaction. And that step alone actually, saves a lot of time from the workflow of submitting expenses. You'd look at your statement as like, oh, man, where's the receipt for debt thing? And we got very, very good at mapping receipts in your inbox to the transaction. The next step is we got very, very good at essentially transforming the merchant acceptor identifier into a human readable text. You often look at these credit card statements, like, what is debt thing? It makes no sense.

What is MCDX? It's like, oh, that's a McDonald's identifier. Okay, good. Why don't we just call that thing McDonald's? So we built the tech to clean up the merchant names. We built the tech to map the receipts in your inbox to receipts in your statement. And then we just kept improving the product one step at a time and taking it further and further and further. But that was the very first version of Ramp.

It's just like really good mapping of receipts. In terms of how we thought about investors, Eric and I did not. really want to raise at the beginning. Part of the reason we wanted to start Ramp as well is it's one of those things that we could do because we had the right to do because we were second time founders. We had some capital set aside and building a business like Ramp required capital because you need to fund the receivables of your customers. We're like, great, we have more capital than we did as first time founders.

We have more credibility. We don't really need investors. The first investor that we got connected with was because around that time I was playing Fortnite with my brother and some of his friends and turns out that there were a lot of other founders and people in the startup ecosystem that we were playing with.

And one of them was Dalian Asparov at Founders Fund. He was pretty sure on some sort of garden leave because he had left Kostla with Keith Rubei and was about to join Founders Fund. And I was still at Capital One, still thinking about ramp exactly how it was going to look like

and when we were going to leave capital one to start the company. And I remember telling Delian, it was like, oh, I think we had put in our notice. I remember telling Delianz, I think I'm going to stop playing Fortnite. I need to start getting serious because Eric and I are starting another company. And he got very curious.

And he tells me that he and Keith had just started, I think, at Founders Fund. And they were essentially looking to fund an idea just like this one. And I think he tells me something along and I was, oh, I'm going to be in San Francisco next week. Why don't you come and pitch us on ramp? I then call Eric is like, what do you think should we do this?

Like we don't really need the investment. And both got really excited, particularly because Keith himself was a legendary investor and had had a legendary run and was particularly knowledgeable about that space. He had helped start Square, was early at PayPal. He was uniquely positioned to understand exactly what we were trying to do. and we felt like he would be the perfect investor for our kind of business. We're interested to talk to him more for the advice

than the money, which is, I guess, the best way to meet investors. What have you learned about investors since? Ramp has been, I would call it, extremely successful at raising capital, but from the right people, like your cap table is an extremely impressive list of investors. How are you so good at it?

The framework that I have for it is we don't think, of investors very differently than we think of our employees. The difference is you can't buy ramp stock on the open market. You can be a private investor in ramp or you can come work at ramp and these are the two ways that you are able to get ramp equity. Employees investor time and their effort and investors investor capital or their piece capital, they're not that different. And in the same way that we like to select for employees that we think bring something to the table and can help us differentiate and push the envelope further. That's how we think about our investors as well.

It's like, what do we think of it as a long-term partnership and we think about what they can bring to the table as well. And it's very different for every investor. Some investors have expertise that they can help us with and a lot of them have networks and great portfolio companies that we think can be great partners to us, et cetera. So we've always thought about it very similarly that we think about interviewing great employees.

So in the same way that think of employees, you could bring the best person into the company, but if you don't spend time with them to onboard them and figure out what you exactly want them to do and what their skill set is and empower them to do the best work that they can, if you bring investors on board and not nurture that relationship

and actually get to know them better and understand what they're really good at and how they can help you, you're not going to get a lot out of it. So we do spend a lot of time obsessing over how to keep our investors, aware of the business, how it's going, what challenges we're facing, and how they're best positioned to help us. We spend a lot of time educating them about the business and its challenges. And I think it's a lot more powerful to do that over a long period of time so that

they see the evolution as opposed to just reach out to your investor once in a while when you need something. It seems like historically there's been more demand for it than supply of it. How much are you using that to drive them helping you between rounds in order to gain access to future supply of ramp equity? Deliberate about that? Of course, a lot. I realized that we're very lucky to be in a position where it almost every round there was a lot more demand from investors than there was supply. But I see it as a great opportunity to make sure that a lot of investors that we're excited about can often get maybe a starting position in ramp and build up the position that they're really excited to get over. time and we make that very obvious. We go into the relationship one step at a time and a lot of

investors get some allocation in one round and as we build a relationship and they get more excited about the business. We get more excited about working with them. They have an opportunity to invest in subsequent rounds and there's been a dynamic that really has started our seed round and still hasn't ended. Most of our investors have, maybe all of them have participated in multiple rounds. What was the hardest round you ever raised? I would say I might have been 2022.

You had a little bit of a down market that started in maybe Chen or Feb or of 2021 if I'm getting my dates right. 22 is the bad year, yeah. 22 is the bad year, right? So it was end of 2021 might have been the peak

and 22 was the bad year. So that round was somewhere towards the end of 22 or 23 or something like that. Not because it was hard to raise the round. It was more because it was hard for me to make peace with the fact that the valuations had gone down.

But not so much that, but more of a, why the hell would be raised? Because we don't really need the cash and the valuations are done. So what the hell is the point of that? It's hard to say. Part of me thinks that, yeah, I was wrong. And part of me was like, we'll never know. But the reason it was so interesting is because when things like that happen, especially in the private markets, a lot of external observers,

might have the perception of, well, the last mark that that company had was at a time where valuations were not really anchored in reality. So what really is the mark today? No one really knows. So it ends up creating that uncertainty for investors, for employees, for everybody. And there's an element of, hey, the valuation is what it is. Who cares? Like the active raising a round only just makes it known. It doesn't change anything about the valuation. It's just like a price discovery mechanism. So that round, I think of a lot more as great. Just discover what the price really is and where the market really is.

So we could set a checkpoint and start building from that checkpoint, which in retrospect, yeah, it was a hard round to get aligned on the need to raise. But the end of the day, we also saw it as, look, at the end of the day, we get great people on board and great investors on board who are excited about the journey ahead is like, who really cares where the checkpoint is. We're never really trying to maximize what the valuation is that every single. single rent. That doesn't really matter. It's about what the ultimate enterprise value that we can create is. And I think that just comes from the sum total value we're creating for our customers.

To do that, to create that enterprise value, I'm coming back to this original algorithm that you laid out, which is this neat model that if you do a better job and make a thing easier to use, they spend more and you make more money. Exactly. This incredibly highly aligned thing. What were the next couple turns of that crank? So originally you were really good at receipts and something basic to save some time. What's your memory of the earliest explosive moment of customer adoption? And what was going on? What were you building?

Just give us the next couple turns of that algorithm. Yeah, I mean, really, once we got in, then the algorithm became, let's try to get our best estimate on how much total time is being wasted by customers and get that time down as much as possible. So we think a lot about the value that we create for customers in terms of minimizing time waste. To look at time and money wasted, money wasted on track. transactions that shouldn't have happened, time wasted on reviewing transactions or adding information related to transactions so they can be reviewed.

And you get the sum total of that time, and you start building products that minimize the time spent. Can you predict what that transaction was for instead of asking the user for a memo? Can you get price benchmarks about what products cost so that person doing procurement doesn't have to go spend a lot of time doing research? Can you extract the information from an invoice? that was received and account for it properly so that you don't have to spend a lot of time figuring out what accounting category does a transaction fall into.

And we kept essentially mapping out the total amount of time wasted in all parts of a finance team that we touched. And we look at that as like the total addressable market. And as we build products, you get more adoption. You get more customers excited to use more of ramp and the total value that we deliver for them as higher. And I'd say there were points early on where you get customers that just don't want to hear the pitch at all.

They're like, I'm really only interested in the card part. I'm really only interested in cashback I'm going to get and maybe the API that you offer. I remember the one early customer that I'm sure you're familiar with that sadly cannot mention and just broadly in aerospace engineering. Famous for wanting to build everything in house, a lot of their software in house. healthy skepticism of external vendors. Well, they weren't going to build their card product, but as a result, their perspective when they want to use Ramp

was like, we're really only interested in the card, all the other software, we want to build ourselves. It's like, great. We're excited that we offered an API because they're like fantastic. We can plug into the card that you've built, and we can map it to our internal ERP and extract all the data we need and we'll build our software. The first six months roll around is like, oh, we really like what you built there over the past couple months.

We want to try it. And they tried that. It's like, oh, we really like what you've built around like AP automation. We really want to try it. And before you know it, they're actually trying more and more of the product, driving a lot more value. And they're very excited to roll it out, not only to more users in their business, but frankly, to more of the finance workflows that they're experiencing. So that land and expand motion really started to become real, I would say, like two and a half or three years into the company, where it was no longer this cool looking card with a nice U.X that integrated it with your receipts. But we actually were building AP automation software, accounting automation software, etc.

How do you think about the transition from a business that's like a total payment volume business where you're basically making more money as more spent on the cards to something that, looks more like a blended TPV and SaaS business. So I know your SaaS revenue is exploding. Talk about that transition. Why go that direction? Why not just try to push it all through TPV? As we were saying earlier, it's a beautiful and very simple business model

to be able to just put the cards in the hands of somebody. The more they use it, the more revenue you get. And you're just essentially focused on building great software so that they're incentivized to use it. We actually want businesses to spend less. unlike most other card companies, we're not here to put rewards in front of them that will incentivize them to spend more.

Our view is built software that helps them spend less, and as a result, they'll use your card and you get more share of wallet, but they're saving money. They're saving money. The best ways to help them save money is to help them not make transactions

that they should have never made as opposed to giving them points and rewards. That's a beautiful model. The limits of that model, though, is that the amount of money that businesses spend on card does not scale linearly with the complexity of that business. So small businesses tend to run everything through card. So it works well for small businesses. But as you mature, the larger businesses tend to move a lot more of their purchasing and spending through essentially bill payments and procurement systems. And not as

much through cards. If you try to visualize what does card spend look in a business as a, let's say, in one dimension you have card spend on the other dimension. You have either complexity of the business or number of employees or however you want to chart it, it starts to plateau at some point. When you really think about what a real skill is at Ramp, is like we're really good at, let's say reducing the bureaucracy, complexity, time waste in a system, a company and building software to do that. And that has a lot of value for really large businesses. So what this means is

our mechanism for capturing value, which is small percentage of car transaction, breaks for large businesses because we drive a lot of value for them. We built a lot of great software for them, but we're not able to capture any of that value for really, really large businesses because our revenue mechanism is not scaling. So that's when we started thinking about, okay, great, What is the right value capture mechanism when most of our product and engineering teams are focused on driving value for these complex businesses? And you're like, well, we need to be able to charge for software. And frankly, if we are charging for software, we'll also guide us better towards the right things to do. You get a feedback signal from the market that they are willing to pay for certain products because they get value from them.

And that's when we decided to transition. There was a lot of fear when we did, I'd say internally, because you have just like beautiful. business model that's working really well and everyone's a little freaked out. Are people going to be willing to pay for it? Is it going to hurt our conversion? Is it going to hurt our growth? And it turns out that not only did it not do that, in many ways, it's accelerated that growth because it's incentivized our sales team to mention those products, talk about them. And it incentivized our customers to be a lot more demanding and responsive. And as a result, they helped us essentially guide our roadmap a lot better than if product was free.

and no one cared about it. A lot of our focus on our engineering teams right now is on continuing to build these products that drive value for customers and capture value through software pricing and software revenue. And in many ways, I mean,

we're still trying to figure out the right way to monetize and price for some of the agents that we're working on and building that drive more value. And I think a lot of companies are really trying to figure out how do you charge for work? Like how do you price for work? Do you have a theory? You want to charge for complexity of the task that the agent's been able to solve,

and you're starting to see more and more business models where you're essentially charging for the time that the agent is spending on a task or the number of tokens that they're using, which is fine. I worry a little bit about that model sometimes incentivizing the engineering team to not be as efficient as possible with their use of AI. If you're a company charging for how much time the agent is spending on the task, or you're not incentivized to just use lots of CPU cycles and not make it super efficient? So I worry about that a lot.

That's why I don't really love that model. I'm not quite sure exactly how it's going to look like. I'd love to ask you about a few of your kind of general views of company building and the future. One of them that you and I have talked about before is this view that a lot of the best company builders will be very technical in this era. Say more about that. So I think we're at an interesting junction right now. And the best analogy that I can give is the Ford one where like if you had asked people before cars what they wanted, they would have said faster horses or probably at the juncture right now where you ask customers what they want from your products and they'll say like,

oh, I want an additional widget here, an additional button there. They don't realize that the car to their faster horse is possible. We as a company should be obsessing over what do customers really want. Well, they want to get from point A to point B. And what is the best way to get them there is like, well, it's to build a car for them. And she asked the question, is like, who even realizes that that car is something that is possible and what it might look like is like, well, the people who came up with the technology for how an engine functions and what it's capable of doing and what is possible.

And these tend to be more technical people in general. I think the technical folks are more likely to see the possibilities in terms of product than non-technical folks. So as a result, particularly right now, technical folks can be very impactful in other disciplines because they see the possibilities better than other experts might. And the other side of it is the gap between not having subject matter expertise in a domain, I can say in marketing or healthcare or education, and having it is the smallest it's ever been. The only thing stopping you from getting that knowledge is your ability to learn and to ask the right questions of an LLM that can help you become an expert a lot quicker than you would otherwise be. I like to

joke now that I'm a better doctor than I've ever been, but I'm not a doctor. I'm a better lawyer than I've ever been, but I'm not a lawyer. And in practice, that means that when I'm having a conversation with my doctor, I'm a lot more knowledgeable and I know to ask the right questions. When I'm having conversations with a lawyer, they're a lot more efficient than I'm asking the right questions. And as a result, I think like engineers that know what is possible can help us build the future of our product much better for our customers, even though they have not done procurement before. They have not done AP before. They have not done accounting before, et cetera. You've extended that even to marketing. Can you maybe tell this story? So rewind time, I don't know,

a year and a half or two years ago or something, you and I were talking about this. And you decided to go take over marketing as the CTO. And you've had this experience since, which I find really interesting of what it's like to bring an engineer and an engineering team to a problem without domain expertise in the same way you're just describing. What did you do and walk us through that? Because it feels like that playbook might be usable by others in different parts of their business. Yeah, of course. The funny thing about that is I think that was a time where all the lagging indicators were going extremely well. Like a lot of people were asking me at a time, it's like, what do you think is broken? I mean, things seem to be going quite well. There's no need.

for a change there. And I was looking at the early leading indicators and starting to see things like, well, we've made our conversion really good. In a lot of segments, we were converting at more than 50%. That meant that if a customer had a conversation with a salesperson, there was a 50 plus percent chance that there will be a customer within 30 to 60 days, which is incredible.

And you're like, okay, conversion is getting really good. We've gotten better at monetization, but conversion can't get better than 100%. There's some kind of upward limit. There's some kind of upward limit to monetization as well, some percentage of the value that we're driving. Okay. There is no upward limit or the upward limit to how big our time is, is a lot further because we're still to this day sub 2% of corporate card alone.

And it just felt like we were starting to slow down maybe a little bit in our ability to generate leads. And while these two other things in terms of conversion and monetization were going really, really well, there's an upward limit to them. And if we didn't figure out how to re-accelerate

our ability to generate leads, we would be in trouble today. That was a year, year and a half ago. And I started obsessing over that problem, and I guess I turned to some sense of paranoia when everyone else around me feels like things are going great.

It's like, okay, why does the problem? And for me at a time, that was the problem. how do we make that better? And around that time, there was maybe an attitude in marketing broadly of we would try things. And if they didn't work, we would maybe assume that I was like, well, those things don't really work for us as opposed to, no, they have to work. We just haven't figured out how to make them work. What's an example of that?

So let's say we would try to, I don't know, run an ad on a podcast or partner up with a podcast. and it doesn't work. We're like, well, podcasting doesn't work for us. My attitude would be is like, no, you picked a wrong person to partner with, or you picked the wrong format of an ad. Why is the thing broken? It's not that the thing doesn't work, is you haven't figured out how to make it work. It's like, clearly all these forms of advertising do work, otherwise other good companies

wouldn't be doing it. We just need to figure out what works for us and how to make it work for us. That was the lens that we brought to really everything, the right. mail, paid advertising, brand advertising, all the different things in marketing, product marketing and how we launch products. So I went into it with the attitude of we're going to fix the experimentation mechanism and the system through which we do work. And in many ways, like, apply the Elon algorithm to it. So in a lot of parts of marketing, you need to work with the brand team to, say, generate an image or an asset, whether it's for a product launch or an ad.

It's like you want an image, an asset, some copy. And as part of marketing, you tend to work with the brand team on those. So the way you used to run before is for every single piece of content that you wanted to generate, you had to write a brief. So you would write a brief to explain to the brand team what you're trying to do. That brief would get reviewed by the brand team about once a week. The brand team would decide who to assign to it, based on skill set, and then you would get some output two weeks later, or maybe a week later.

So that meant that no matter what you wanted to do in marketing, if you're working with a brand team, it would at the very least take about two weeks, which is kind of crazy. What if you need to work on something that, I don't know, should take 10 minutes or 20 minutes. It doesn't matter. It'll take two weeks for it to be in front of somebody, and then they'll do to work for 10 minutes. And with that kind of clock speed, it's impossible to get anything done. And while a lot of people would have gone into marketing with like, okay, great, the way to fix this is let's come up with a better campaign idea.

I went into it with the, let's just like look at the actual system that generates work and focus on how we can make that system as efficient as possible. I didn't go into it with like, oh, I have better creative ideas than the people on those teams because we have amazing people. I just want to put their ideas in front of the world as quickly and as efficiently as possible. That's what I'm focused on. We have great creative people. They'll still come up with the ideas. But when they have an idea and I want to put it in front of someone, I wanted to take 10 minutes, not two weeks. And if we do that, we can take a lot more shots on goal. We can take a lot more risk with

the things that we do because we know that if it doesn't work out, we could try something else tomorrow. And that's really the type of attitude that we went into it with. And I think that's helped us a ton. I actually have another example that I love. You could think about billboard advertising. If you want to put a billboard in New York, let's say it costs you $100,000. The funny thing with billboards is you don't really get that much economy of scale. If you want to put another billboard, it costs you $200,000. You put three billboards at $300,000. But if you want to change a billboard that you've already bought, it only costs you $1,000. So that means that if you have one billboard, you have one billboard, in Union Square and you want to change it tomorrow that costs you another $1,000.

You want to change it after tomorrow. That's another $1,000. So you can essentially have a billboard in Union Square that changes seven times in a week, and that's $107,000, or you can have two static billboards for $200,000. I would argue that one billboard changing seven times in a week is a much more powerful way to drive a message and get a story out than two billboards. And it's a lot cheaper. So a lot of the attitude that we brought in is like, how can we find these hacks and ways to get more out of the systems that exist?

The creative is not really changing. I'm not trying to influence that, but like the system through which we are doing marketing work is a lot more inquisitive and experimentation driven. I love that. One side of the system is getting more at-bats, let's call it. The other side of the system is where are you getting hits? that feels also very complicated, especially when it's, like we've talked about, it's just to break the fourth wall, like ramps our biggest sponsor, Senra's biggest sponsor, we've worked together very closely.

Typically, what we found in podcasts is the values, you just hear the name four million times and then eventually you need to solve the problem. You're like, oh, yeah, ramp. That feels harder to measure than an ad in Facebook or something where it's incredibly tight the feedback loop. You're an engineer. I know you like tight feedback loops. How do you balance stuff that's harder to measure?

assigned value to it. You could either figure out what the exact value is, or you could think about it comparatively. So the way we've thought about it in working with you, which has been amazing versus, I'd say working with another random podcast. I listen to your podcast a lot. I love it.

I think a lot of people like me listen to your podcast. I think a lot of our audiences, people like me, who are building businesses and obsessing over businesses. If we decided that we wanted to work with podcasters, who are the best in the world that we can work with, that have the right audience for us. And that's the lens.

It's more about targeting the right audience than it is, let's say, a higher level metric like how many clicks am I getting or how many views am I getting? It's about getting the right views. And that's the way to think about it for us. If you were a step back and describe once more like holistically the system that you installed,

how would you describe it? There was a diagram of the system that you came and installed in marketing to do everything you just described. What does the diagram look like? It's more about principles. It's fast iteration cycles. It's scientific where there's experimentation and feedback loop.

It's led the person who came up with the, let's say, creative idea, be accountable to that idea. It's not done by committee. You don't get to ask 10 people what they think and come up with a watered down idea. You just do it. And if you do it well, you get credit for it. If you don't do it well enough times, eventually you will no longer be at the company that needs to be known. People have more skin in the game when they're making those decisions and making

sure that the tools that team has access to are not getting in the way but are empowering you. We make a lot more use of AI tooling now in marketing than we used to. And today, if you want to put together an article on Ramp and you are, let's say, on the SEO team or on the content marketing team and you want to generate an image for that article, we have a tool that was built internally that allows you to generate an image that is on brand within seconds. So it's quick experimentation, accountability with the person coming up with the creative and tools that don't get in the way, but allow you to get

your work very quickly with as little dependency as possible. Through this process, I love the billboard example. So I'm curious what the next three are like that. What are the most surprising things you discovered about different channels or different ways of doing things. Anything else come to mind from your marketing adventure? Yeah. There are things that have always been true, let's say, in paid marketing or what happens in social media. You get a lot of these concepts and patterns that work incredibly, effectively in paid

advertising for a very short period of time and stop working. So it's very important to always be at the forefront of what is happening there and why it's working until all the alpha starts being taken away and it stops working. And I'll give you actually an example from the paribus days because I don't want to give away all our secret sauce either because I think it was like a very powerful one. But when Facebook introduced video ads in the news feed, I think in 2014 or 15, that was a new thing at that time. When they first introduced it, you used to scroll through your news feed and the videos would just play immediately with the sound. and people were really annoyed and I guess bothered

and Facebook then decided to make those video ads not play the sound by default. And when that happened, the effectiveness of video ads on Facebook dropped drastically. So they got cheaper as a result. But the videos that became really effective were the ones where you could tell

what was happening essentially without the sound. So one of our most effective video ads at Parabas, we ran like very early when that was, starting to happen when Facebook had made that change, where Eric and I were dressed in banana costumes holding signs with text on them. It's a great silent video because you look at that image is like, what are these people doing dressed in banana costumes? And you're holding signs with text on them. So you can actually tell what's happening without having to listen because you can read. And that ad became very effective. And it worked very, very well for three or four months and

and it stopped working. And that is very true in online advertising. It's moving so quickly and the platforms that you're doing ads on top of are changing so quickly. So like being at the forefront of what's happening and how you can get alpha is super important. So we want to hire people who are obsessed aware of the changes happening with those systems, et cetera. That's also true in SEO. Like Google every once in a while will publish articles about how they're changing the way that they prioritize SEO to say, for example, reward websites that load a good. incredibly fast or reward websites that are very mobile friendly. And they do that every couple of months. So being aware of what's happening and moving very quickly, super important. Speed, super important.

So this is happening everywhere. There's so much buying for our attention that I'm really curious what you've learned about getting people's attention and the, like what things, what are the principles of getting attention? Something that comes to mind is our friend Scott Wu at Cognition and his team did this amazing launch video when Cognition first came out. And there really weren't many launch videos at the time. So everyone watched it and had this incredible reach. Now like literally anything that gets $10,000 of funding has a launch video. And so there's 10 million of them. And as a result, I personally literally did not watch a single one, no matter how big the company is, because it's just this sea of slop of launch videos. And so I don't care anymore.

So I'm curious what you've learned about the principles for getting attention in the first place. It's funny. I was re-listening to one of Senra's episodes on Dyson recently. I actually found a lot of the same principles we try to apply for this in the way that Dyson ran his business, which is seeking differentiation for differentiation's sake. We are always looking for ways to be different. And the very first way in which we've done that really well, a lot of credit goes to Diego and our team, who runs the design team. how they think about design.

In the very early days, we were thinking about what the right color for RAMP should be. And we're working with brand partners on it, and I remember this color wheel that you look at. And you see all these companies that we aspire to be like and where they are on the color wheel and all the finance-related apps are somewhere in blue or green.

It's like green for money, blue as trust. And there's no one in yellow. The only thing in yellow was Snapchat. Consumer company, Snapchat. Snapchat. And the primary reason why we chose the yellow was because it was different. That's it. And you could have argued at the time. And certainly some people did that, oh, well, if you go yellow, you're not going to get anyone's trust and you want to start with things that they associate. It was like, no, like, we are going to change that. We're going to be different. And if we do that

really well, it's going to pay dividends for a very long time. And I think it does. You see a very yellow ad or boss? You assume it's ramp. You assume it's ramp. That is. what brand is, ultimately, when you think about what is brand, is like, well, if you're watching a movie and you see a rat can in the distance, you might not be able to read Coca-Cola, but you know it's a Coca-Cola can. That's very, very powerful. So I think one way to grab attention is to seek differentiation and with enough repetition. Eventually, you're like, well, okay, I see the pattern here. You're a man attracted to extremes and differentiation. Talk about that same concept in recruiting and recruiting for what you would call spikiness. I love this framework of hiring for slope and for spikiness as opposed to, let's say, people who check the box on 10 different things. And we've applied that since very, very early. Even at Parabas, like, I remember one of the early things that Parabas was like, well, we were a small company with very limited resources competing for talent with the Facebooks and Googles of the world. It's like we can pay them less money.

We have less of a brand. We have in many ways less large-scale problems to work on. It's like, how do we really differentiate? And there are a couple of things. One is I'm going to look for very spiky people in areas where I have asymmetric information. We were recent college graduates in some way we knew a lot about the people who had gone to the school that we had gone to or the schools that we had experienced

with, so namely, yes, Harvard and MIT for Eric and I. And not only that, we knew about a lot of the hardest classes that students were taking. So we could go and look at, let's say, a freshman in college and the classes they're taking and the level of extreme talent in one area and recognize that very quickly. So it was less about like what is your total GPA and your total sum of experiences and other interviews you've done throughout your four years in college. But I know that in year one of school, if you're taking that class and got a really good grade in that one class, it must mean that you are extremely talented at math or computer science, whatever it is. So we're looking for these spikes, like,

very, very early. So a couple of ways that we're looking for extremes. We're looking for freshmen where other companies were trying to hire juniors. We're looking for people who had maybe taken and excelled in very specific classes. And in my case, having gone to RSI and knowing how hard it was to get into RSI and the level of talented RSI, I was looking for seeking programs like it that gave you an early signal that someone was very spiky, even before college in many ways. One of the people we hired very early on at Ramp was Calvin Lee, who had interned with us at Paribus in January for one month. Like, not a lot of companies offer one month internships, had less than one year in college, but clearly even then looked incredibly spiky. He had left high school early to prepare for the Informatics Olympiad.

He ended up finishing college in two and a half years. And we met Calvin very early on and built a very strong relationship. So by the time that he was graduating, we were actually starting Ramp and he was one of our very first hires. And to this day, Calvin, I think, has his hands in so many different things that Ramp and has gone from being an engineer to being on the sales team for a bit to running our forward deployed engineering organization. And while he's incredibly spiky, it turned out to be also very versatile in the company and one of my favorite people to work with. but that pattern certainly extended to a lot of the ways we've done recruiting early on. When I look at someone's resume, I don't have a checklist of 10 things I'm trying to check the box on.

I'm generally looking for what they're telling me in their resume they're really good at, brushing up on that topic if this is a topic that I'm not an expert on, and interviewing them specifically on that one topic. If you're telling me you're great at something, I'm going to see how great you actually are, and you better be a lot more knowledgeable about it than me after doing a couple hours of research. And I get two very strong signals from this. It's like, well, how good of a judge are you and how good you are at that actual thing? Okay, you're saying you're a great at poker, for example.

Are you great poker players? Like, how good you actually are? Are you a good judge of yourself? Are you aware of the spectrum of talent in that field? And two, how far have you been able to take that thing? I'm a lot more interested in essentially assembling the Avengers at the company where everyone has a clear superpower than a lot of people who just check the box on 10 things. The more things you are looking to vet someone on, the more likely you are to get average people, essentially. Another thing you and I have talked a lot about is that pure raw speed, which has been a theme of our conversation today, is probably the most important thing, especially for young companies.

maybe you develop more structural visa-like moats over time. But to earn that right, you just need to go ridiculously fast in the early days and iterate really fast in all the ways that you're describing. If you were giving advice to companies on practical, tactical things they can do to make their business go faster, what are your favorite things? I mean, you want to shorten the cycle as much as possible between idea and putting the thing in front of a customer. And there's just so many ways to do that.

You could simply just focus on great. I'm writing code. How long does it take to get to production? And in that, there's like, well, how fast do your test run? How quickly can you actually deploy? I'll share a store on that, which is quite funny. It's like the first time we hired a product manager at Ramp was Jeff. He was like he came into the organization.

He had some experience being a PM at another organization. And he looks at the way we are prioritizing work and cutting up chunks of work. And he's a little bit appalled that we are not sizing the different levels of effort for the different tasks. A lot of company will do this. Oh, there are 10 things we want to do. Like, this one is five points and we'll take five hours. And this one is one point and we'll take one hour and whatever. And it's like freaking out that we're not really measuring how long we think things will take.

And he's trying to introduce that. And I get freaked out. I'm like, why are you doing this, Jeff? He's like, well, so that we can know how fast we're actually moving. And I was like, wait, you don't think we're moving fast enough? He's like, no, I think we're moving incredibly fast, like faster than any place I've seen, but I just want to measure it. And I believe that there's a little bit of a Schrodinger's principle there where it's like

you can get a lot of precision on how long things take or you could do them very fast. It's hard to get both because if you start to put a lot of importance on measuring in advance, how long you think things will take and estimating that long. Exactly. You end up rewarding and punishing people who make the right estimates. so you incentivize estimates that are longer than they should take so that they can hit those estimates. So it's a very simple tactical thing that you could do. But it's hard because you need a natural ability to understand how quickly it is to actually develop things.

And it's hard to do that without expertise in the thing that you're building. It's hard for non-engineers to know how long an engineering task can take if you're really good at it. It's hard for designers to know how long a design task should take, et cetera. So not following a lot of the. the processes that other company follow because very often process gets in the way. I think process are a good way to move you to average in a discipline if you feel like you're below average, but often some of the people who are most extreme on how fast I move or on any dimension that you're trying to measure tend to do things in a very odd, non-standard

way. So avoiding standards is probably one way we do this. What's your commentary on the base level players and infrastructure in and around this business where people have talked about Visa and MasterCard as the best business model of all time or something like this. The introduction of stable coins and what Stripes doing there, things that Visa or MasterCard might be trying to do themselves. What are the interesting shifting sands to you that might affect how you build the business, what opportunities might become opportunities that haven't been in a long time? The worst idea you could have had for the last 50 years is try to beat Visa at its own game. network effects too strong. What shifting sands loosen some opportunity in your perspective?

This is an interesting one. I think a big misconception is that the reason payments are maybe more expensive than some merchants would like them to be online is because visa takes such a bit cut. That's not true at all. One of the reasons that maybe card payments might be a little bit more expensive for merchants in the U.S. is a lot of debt expense comes in the form of rewards for consumers and American consumers are very, very attached to their rewards. It's going to be interesting to see in what areas people are willing to give up any of their rewards in order to, I don't know, maybe get a differentiated experience in some way and the merchants get cheaper payments. But the stable coin promise as it stands today,

for merchants is one where payments are maybe faster and cheaper. But it's still not very clear what it is for consumers or the people paying. Because at the end of the day, if you want to buy something, you just care about the price and how quickly it's going to ship to you and the quality and things like that. Do you really care how you're paying or what is happening behind the scenes? Not really. So in a way, I think a lot of the shifting sense around what is the underlying technology

through which money is moving, I'd say that's very irrelevant to the people making payments. But what may become interesting is if you believe in a world where individuals themselves are less involved in making the payments and you have agents doing that on their behalf, it's okay, help me buy that thing. Those agents might not care about rewards

as much as you do or may help you make more optimal decisions. You could see a world where, agents are deciding to optimize the rails and pick different lays based on some different maximization function that's not related to reward. So in other words, if the decision makers are shifting, the path that they take to make the payment might shift. So it is interesting. I mean, stable coins are certainly very interesting. It's kind of crazy that today payments cannot settle on a weekend or outside of business hours in certain cases. There's no reason why payments shouldn't be selling live 24-7 all the time and be very cheap.

So I think that will change. But to be honest, from our perspective at ramp, we are in the business of optimizing and speeding up the workflows of our customers. And in many ways, like, I couldn't care less whether that runs on TACH rails or the card rails or the stable corn rails. You'll be the beneficiary of whatever positive change. Exactly. It's exciting. Let's say we did this again in five years.

We have every five-year tradition. And at that next increment, we have the benefit of telling the most exciting possible version of the story that happened between 2025 and 2030. What do you think that looks like for ramp? It's going to be a pretty funny one. But my hope is that people don't have to log into ramp at all,

basically, is the way to think about it. If you're really obsessed over minimizing the amount of time that things take, And today you're having to log in to ramp and it's taking five seconds and then it'll take four. And eventually it'll take zero. And you have a lot of your finances that are essentially self-driving. One of the analogies I like is like what's happening with cars. You've gone from very mechanical cars where you have to do everything and fix everything.

And you have things like lane assist and park assist and early signs that the car can assist you and do a little bit more. And we're getting very close to the way most like you could just. sit in the back and press a button and you go from point A to point B. I think something very similar is happening in many areas of business. And the one we're focused on is all the workflows and decisions that happen before money is moved, after money is moved and how you optimize these decisions over time. There's this endless cycle and loop between you spend on something. Something happens in your business.

It's good, great. You don't do more of it. It's bad. Maybe you should minimize that. So you end up having the infinite cycle of making just best. decisions with your money and not wasting a lot of time in bureaucracy. So I will love RAM to be as self-driving as possible and for people not to have to log into ramp at all.

For that vision to come to reality, is most of it the infusion, I'll call it of intelligence, AI basically, building the chain, as you've described, doing so many times as an engineer, you're always thinking in terms of what are the increments here and then just attacking each one with intelligence, for lack of a better term? I think that's right. I would also add that there are indirect benefits of the models getting better that we benefit from ourselves as well. And the accumulation of more artifacts and data about how customers are using our product every day and for what reasons. This allows us to infer a lot of what their intent is from their actions and the way they decide to fill forms and what they approve and not approve.

So it's like the more our customers are using the product and deriving positive outcomes, the more we can learn. And as those models get better about reasoning over like more complex tasks, we benefit from it either. Very exciting place to be in. Can you tell the story about constraints that led you to become a good manager? Oh, God, yeah. There were some funny ones, but the most on the nose one is one of the early days of Paribis. Eric and I were the only two people working on Paribus. And Eric, while having studied a little bit of computer science, wasn't really a software engineer himself.

So 100% of the engineering capability of the company was just me. And then I go on a random skin trip one day and you do unfortunate circumstances come back with a broken arm. And I remember Eric looking at me and having that reaction is like, oh, great. Like, we're fucked now. what the hell are we going to do? And luckily, we had started working with a few junior engineers around that time. And that was the first time that I was forced to try to get better at maybe delegating, managing, explaining concepts, explaining architecture, and focusing less on the direct

output that I can have myself and focusing a little bit more about how I can maximize the sum total of the output of the team as a whole. And it was very constraining to do that without an arm. I'm trying to type as much as I can with my left arm, but I need to be as specific as I can with as few words as possible and drawing diagrams and writing down some concepts. So that was a very funny experience where I had to very quickly figure out how to delegate well. Back to our book on the story of Karim's entrepreneurship journey. We're just at a mile marker now. You're only six years into ramp, which is kind of crazy to imagine how fast you guys have scaled.

But if I think back, maybe I'll go all the way back to the startup paravis and encompass the entirety of company building that you've had so far, so a bit longer. How have your views on company building leadership management most changed across that period of time? I used to go into challenges with the assumption that there was a reward at the end and that the reward would feel great. And that was the intent and goal. And I think the more challenges we've gone through and succeeded at conquering or surpassing, the more I realized that the reward is just a journey, to be honest.

So it's made me a lot more intentional about doing the things that will help me enjoy the journey over time and enjoy all the challenges that come along the way because the reward for solving challenges is just more complicated challenges over time. So you might as well just put yourself in a position where you are enjoying these challenges, as much as possible. And for me in particular, I think that has to do with more than anything else, the people I'm doing it with.

I still meet a lot of young, very talented designers, engineers, builders in general. And they always have different answers to questions like, what are you excited about, what you want to do? And there's some people who really talk about the complexity of the technical challenge and some that talk about the mission itself.

And there are like different ways to answer that question. But the one for me that I just continue to go back too is really about the people that I work with. And I feel very lucky that Ramp has such a multifaceted company in some ways where we have to not only be really good at the engineering parts of it, but also the design parts of it, the marketing and the sales and the risk and capital markets and fundraising. And you get to work as a result with very spiky people and very different areas that are brilliant that I love learning from consistently. So I want to put to together. Great teams solve that challenge and win and more the team that will help us consistently

win forever because I would like to build something that hopefully outlives us. Last question for you. What are you most proud of at Ramp? Calibre of people we've been able to attract and the sum total of not just Ramp, but I think the great companies that will come out of Ramp and the diaspora of amazing people who have spent some time at Ramp and in some cases have decided to go on to start other companies. I mean, I still tell people who join us that I would love for Ramp to be the last job that they ever have to apply for. And that's been very true for a lot of people.

And that can mean a lot of things. They can mean that people left and right will just try to approach them because they've been at Ramp. And it's very easy to want to try to avoid that by hiring people who are purely incredibly loyal and I don't think that's a good idea. I see it as a sign that we're hiring the right people if we keep doing that. So I'm excited to see the sum total of amazing things that the people who have ever set foot at Ramp or worked with us will do over their lifetime. Incredibly in awe, talent that we have.

I mean, even this past summer, one of our interns while he was interning at the company won a cold metal at the International Physics Olympiad. It's just incredible what some of people at Ramp have been able to achieve. So talent, very proud of that. I think you know my traditional closing question. What's the kindest thing that anyone's ever done for you? The one that's been most impactful on the rest of my life probably happened early on when I was going through the research science institute at MIT, and I was 16. And first time in the U.S. away from my family, war breaks out in Lebanon. The airport's closed.

and I had become really close with my best friend today that I had met at that camp. Zach, who, you know quite well, were together at Research Science Institute, and he just immediately tells me, oh, don't worry about it at all. Camp is ending in a week. You could just come with me and be in New York,

and my family's amazing. I already told them about you. They're very excited to meet you. This is going to be great. And little did I know that that same day, I heard that a couple of years later from Zach's mom. I think he called his mom and was like, Mom, don't ask any questions.

My friend Kareem is going to come live in New York with us as soon as the camp is done. And I think his mom couldn't even be in New York around that time. And Zach had something else to do. And the day I met his mom, it was like, welcome me with open arms and everything. He told me that she would make sure that I had a great experience staying with them. And I show up at their house in the city. And I remember the experience being amazing.

I was just like opened the door. I had hidden the key for me because they couldn't be there. And I opened the door and I go into the kitchen. And they're like meals labeled for every day of the week. There's pocket money on the side in case I needed for transportation, enlist with all the numbers that I could call if I needed any help. I was like, wow, like this is amazing. I don't even know these people.

And they're already treating me like family. And to this day, I think of Zach and his family as my second family in the U.S. and spend a lot of the holidays together and has really become part of my family in many ways. But the fact that they were willing and able to do this very quickly for someone who was a stranger in retrospect is kind of crazy. Pretty amazing story about a person who may be or probably is the best investor of his generation. Pretty wild, amazing closing story. Kareem, thanks so much for your time. Thank you, Patrick.

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