Decomposing How Ramp Stole AmEx Customers: Dark Matter Moats from Selling Money to Selling Time

(Illustration: As an amateur photographer, I’m always drawn to light and shadow, like reflections. The reflections you only catch after the rain, or the light, or the dark matter we think we can’t see or touch, but maybe it’s been there all along. Taken during an evening walk before a business dinner in 2016, at the Royal Palace of Madrid. Image source: Ernest.)

[How Ramp Took Customers from American Express: Building Dark Matter Moats for Enterprise Software in the AI Era by Shifting from Selling Money to Selling Time]

A few days ago while putting together Breaking Down Keith Rabois on Barrels, Ugly Babies, and AI-Era Teams, Keith recommended checking out a talk by Ramp CEO Eric. Plus, he led Ramp’s seed round in May 2019 and locked in the Series A with a term sheet as early as September, so I wanted to see how the founder Keith bet on so early actually thinks. I dug up this February 2026 episode with Eric Glyman on the Stripe channel and excerpted three short sections to get a feel for it.

⌬ Dark Matter Moats: The Layer That Makes Companies Truly Hard to Replicate

• Eric borrows the cosmological metaphor of dark matter to describe the hidden assets of software companies.
• If we ask Claude Code to clone a Ramp, we can replicate the surface-level UI, but not the nine million edge cases buried below the iceberg.
• San Francisco’s recent blackout caught the Waymo fleet with a scenario nobody had coded for — you only find out where the obstacles and utility poles are by actually going outside.
• Eric says tech debt sounds like a bad thing, but the truth is that it accumulates the defensive logic left behind by every hole the company has stepped into. .
• He pointed to vLex, a 25-year-old Spanish company whose founder Alex bought up Spanish legal records going back to 1492. They ran a bootstrapped $20M/year SaaS for years, then jumped to $100M in one year.
• Why? Because today’s ChatGPT can’t do that — that data simply isn’t in the LLM training set.
• DomainTools, another example, runs a cron job to record WHOIS history across the internet every single day. These time-stacked datasets only become more valuable in the AI age.

(That said, our team has been stacking its own iceberg in the fitness equipment domain, and we’re getting ready to stack the next one :)

⌬ A Dollar Saved Equals Twelve Dollars Earned

• US businesses average roughly 8% profit margin. Eric lays out the math:
• Cutting one dollar of spending is equivalent to earning twelve dollars of revenue.
• Ramp helps customers cut 5% of spending on average, and last year their customers grew revenue by 16%, versus a US national average of just 5%. .
• Traditional banks compete with lower interest rates and reward points. Eric calls that selling money. What Ramp is doing is selling time.
• The time customers save goes back into their core business. The leverage is on a completely different order of magnitude.

(When we work with electronics manufacturers and traditional industry clients to re-explore their ERP data, what actually gets saved usually isn’t one specific procurement amount — it’s helping customers save human time. Management watches the financial statements, but only workflows that are actually moving, traceable, and visualized in a positive direction can create positive revenue growth.)

⌬ The Marginal Cost of Arguing Has Gone to Zero

• Eric shared an example: his wife got into a dispute with a company using ChatGPT, they used AI to argue back, and after some back-and-forth his wife won.
• The abstraction behind this scene is that in the past we couldn’t be bothered to call customer service and fight over 5 or 20 bucks — not because the money didn’t matter, but because the phone cost, emotional cost, and time cost all added up to far more than what we’d fight back. .
• But the AI era drives certain costs, which we used to consider costs, toward zero.
• Every small price difference that was previously written off now has a chance to be reclaimed.
• It gets even more obvious in enterprise contexts: automated chargeback disputes, a competitor quote dropping in 90 days before renewal, cross-customer comparisons showing your per-seat SaaS price is 20% higher than the market — all the same concept. .
• Ramp is already doing the last one. Their data collection pool can see the per-seat price every customer pays to Salesforce.
• Once information asymmetry is broken, the negotiation structure gets rewritten.

(。)

📷 Caption 👉 As an amateur photographer, I’m always drawn to light and shadow, like reflections. The reflections you only catch after the rain, or the light, or the dark matter we think we can’t see or touch, but maybe it’s been there all along. Taken during an evening walk before a business dinner in 2016, at the Royal Palace of Madrid.

Hitting “👍” or “❤️” as you pass by every day sounds like a big deal, and also like a tiny thing. Like a miracle, yet also like a given.

#Ramp #FinTech #EricGlyman #KeithRabois

✳️ Further Reading

• Breaking Down Keith Rabois on Barrels, Ugly Babies, and AI-Era Teams
• Decomposing ElevenLabs’ Growth Engine: From 2 to 300 with a Research-Product Flywheel
• Before Playing with Claude Managed Agents: Breaking Down Palantir’s Five-Layer Framework for Production AI Agents
• Why Enterprise AI Deployment Gets Stuck: Lessons from Mistral AI’s Approach
• Decomposing Family Office Fee Structures: What Does Your 1% Actually Buy?

✳️ Knowledge Graph

(More about Knowledge Graph…)

graph LR
    %% Concept classes - Orange
    classDef concept fill:#FF8000,stroke:#333,stroke-width:2px,color:#fff;
    %% Instances - Blue
    classDef instance fill:#0080FF,stroke:#333,stroke-width:2px,color:#fff;

    CGov[Corporate Governance]:::concept
    CEng[Software Engineering]:::concept
    CArch[System Architecture]:::concept
    CLiq[Liquidity Management]:::concept
    CProc[Procurement Strategy]:::concept
    CRisk[Risk Underwriting]:::concept
    CPay[Payment Rails]:::concept

    IRamp[Ramp Platform]:::instance
    IAgent[Agentic AI Review]:::instance
    ITechDebt[Tech Debt and Edge Cases]:::instance
    ITreasury[Treasury Yield Products]:::instance
    IGPO[Group Purchasing Power]:::instance
    IIBS[Information Based Strategy]:::instance
    IStable[Stablecoin Integration]:::instance

    IRamp -->|revolutionizes| CLiq
    IAgent -->|automates| CGov
    ITechDebt -->|fortifies| CArch
    ITreasury -->|optimizes| CLiq
    IRamp -->|develops| IAgent
    IRamp -.->|initiates| IGPO
    IGPO -->|empowers| CProc
    IIBS -->|transforms| CRisk
    IStable -->|modernizes| CPay
    CEng -->|accumulates| ITechDebt

graph TD
    classDef phase fill:#0080FF,stroke:#333,stroke-width:2px,color:#fff;
    classDef advantage fill:#FF8000,stroke:#333,stroke-width:2px,color:#fff;
    classDef outcome fill:#4CAF50,stroke:#333,stroke-width:2px,color:#fff;

    A[Phase 1 Startup Entry]:::phase --> B[Phase 2 Scale and Expansion]:::phase
    B --> C[Phase 3 Digital Brain Platform]:::phase

    A -.-> D[Core Focus Product Velocity]:::advantage
    D --> E[Outcome Fast Card Issuance and UX]:::outcome

    B -.-> F[Core Focus Time vs Money]:::advantage
    F --> G[Outcome Automated Expense and Bill Pay]:::outcome
    F --> H[Outcome Cutting 5 percent Average Spend]:::outcome

    C -.-> I[Core Focus Ecosystem Leverage]:::advantage
    I --> J[Outcome Agentic AI Policy Review]:::outcome
    I --> K[Outcome GPO Discount Negotiation]:::outcome
    I --> L[Outcome Automated Treasury Yield]:::outcome

✳️ Transcripts

Introduction and Initial Questions

• I don’t know if we need, if we want to do this, but— I already look like that naturally, so.
• Oh, this is Kevin from “The Office.”
• Yeah, yeah.
• Eric Glyman is the co-founder and CEO of Ramp, the corporate card and finance automation platform.
• Founded in 2019, Ramp has taken the industry by storm.
• Oh, cheers.
• Cheers.
• Can you describe maybe a good framing, just the Ramp business today?
• What’s the biggest part of the business in terms of where you make money?
• What are the new growth lines?
• Any metrics you can share on the scale?
• Alex and I have a million questions, but maybe you can start by just framing it up for us.

Ramp Business Overview and Evolution

• Yeah, of course.
• So, first, just the pace that this has come together has been pretty remarkable.
• Seven years, yeah.
• You know?
• I think by the time we were, six years and change, the company had passed over a billion a year in revenue.
• The largest portion of that is card.
• And so, that might be a classic kind of interchange-based model.
• But behind it— So this is people, in their business they have spend cards, everyone walking around the company has a Ramp card.
• And you run interchange on those.
• That’s right.
• Next, you can think about bill payments and software.
• Software, it’s a two-something-year-old business line, just about two years and some months.
• That’s over 100 million a year business line in and of itself.
• And that can be advanced functionality to maybe manage lots of entities, to automate aspects of accounting, maybe aspects of procurement, bill payments.
• So, this can be sending checks, wires, ACH and that’s predominantly a float as well in some cases foreign exchange transaction business.
• Treasury.
• That’s a product that is about a year old, several billion dollars of deposits.
• Some of that is checking-like products.
• Some of that is more of an investment and money ladder type product.
• And then the last, the other ones are procurement and then travel, which is a bit of an in-kind.
• And what’s been so interesting is that if you break down and look towards maybe let’s say contribution profit, gross profit of the business, a few years ago it would’ve been 90 plus percent card.
• I think by the end of this year, the second, third, fourth, fifth lines of business will comprise and aggregate the majority of Ramp’s business.
• And so, it's evolved into this platform by which if you're trying to operate your company, it's just a lot more efficient.
• You spend less.
• I think people know Ramp for, we help the average company cut their expenses by about 5% per year.
• The thing that’s been really fascinating is people are starting to use these products in aggregate.
• Not only are they not paying for five, six sets of point solutions, but they’re also not wasting time.
• They’re growing faster.
• The average customer last year on Ramp grew their revenue by, I think it was 16%, which compared to, in the United States, the average business— Much higher than that.
• Yeah, I think it’s 5% in the US.
• And so, in some sense, what we're trying to do is be not just a better platform, but a better, almost kind of digital brain for organizations to allocate resources and make sure spend is not wasted.
• Yeah.
• So, you start by selling, say, spend cards into a business.

Ramp’s Multi-Product Entry Points

• The CFO likes it, the employees like it, and then that gives you permission to go sell some of this other functionality.
• And so, it’s kind of a classic multi-product cross-sell.
• Is it always starting with spend cards or do you now have multiple front doors into the business?
• It’s been the big story of the past year.
• I think there were, over the last quarter, thousands of businesses that came in just for bill payments.
• There’s accounting firms that are becoming into, they say, “We’re a Ramp shop here if you want to work with us.
• We’ll bring in bill payments, treasury…” We use Ramp to go power that and they can manage 10, 100, 200 clients all through one platform.
• And we’re excited.
• I mean, probably the fastest growing line of business is procurement.
• Or, they’re single clients that are looking to kind of bring in and do full-scale purchase orders across, whether it’s single or a dozen plus entities, all the way through.
• And so, that’s been the really fun story of the past year.

AI-Powered Expense Policy Enforcement

• Do you have a view on what the right policy is for employee spend within a business?
• I love that you ask this, yeah.
• 37signals or someone will say, “Companies are so lame.
• You just give everyone a credit card and trust people and it’s fine.”
• And then meanwhile, large companies are like, “Well, this hotel is in a Tier 2 city and therefore there’s this dollar limit and it must be booked 14 days in advance.”
• And so, you see companies operate at really two ends of the spectrum in terms of how much flexibility they give people.
• What is correct for a company, or does it just vary by size?
• I love this question.
• And the interesting part, if you really kind of dig into Ramp’s businesses, we have ways of back-testing and actually understanding based on how strict your policy is, how things are running.
• Does that have an impact on how much time your employees are, let’s say doing expenses, how quickly you’re growing?
• And you can start to actually compare based off of the operating hygiene of the company… What are end margins?
• What is a pace of growth that occurs at the company?
• And I bring this back to what— So you can do a correlational study between expense policies and company growth.
• And look, it’s pretty interesting.
• I mean, the first, there's an aspect of, in most companies, particularly high-growth companies, it tends to resemble something closer to the "no rules rules" Netflix approach of, we're going to trust but verify and shine a light on it.
• Spend tends to be reasonably permissive.
• But then part of the breakthrough of the past year is you could basically take an expense policy, let’s say it’s written in plain English.
• “If the flight is more than five hours, you can take business.
• If it’s under…” Things that would’ve been horrible to go and have your managers go and verify this stuff, now you can run that through an LLM.
• I think that we’re processing over 100,000 expenses a day that are being reviewed agentically.
• This is a very fast-growing subset of the business.
• So you give the Ramp agent this company’s expense policy, and then it applies it to the transactions that are coming through.
• Exactly.
• And so you can start to do things like, I think about the episode you’d had with Susan Li.
• It was incredibly instructive where, she sort of says, it would feel so silly and it's not a great use of my time in some sense to be a very expensive machine learning algorithm to do, to review expenses.
• But yet, somehow, a lot of people in companies are reduced to that, thanks to Sarbanes-Oxley and the rules around it.
• Now you can have an agent functionally that does that, that takes that aspect of the job.
• And so, it has access to the full set of data that you would, all the transaction-related metadata, the receipt data, the timing data, the policy data.
• It then can go in real-time review.
• Was this in or out?
• Can have the full audit trail explaining its reasoning.
• And today, it's over 99% accurate, which turns out it's much more accurate than people are.

The Challenge of Imposing a Moral Code

• So, people don’t know the expense policy and expenses are pretty automated.
• And I find this thing super interesting, in part because I don’t think it should be anyone’s job to go and review people’s expenses, but somehow, while it’s in no one’s JD, the law kind of requires everyone to waste an hour of their time every month, if you’re a manager.
• And does the law allow for it to be reviewed agentically and then just signed off on by the human?
• It does, yeah.
• The goal of this is separation of duties.
• That you yourself are not reviewing your own expenses.
• There needs to be a set of procedures that govern and actually are effective through the action of, okay, the rule says this.
• Did you take some steps to do this?
• It can be a system— Yeah, you can’t self-certify.
• The funny thing is that, I mean, one way of doing this, actually, we used to do this, is why not just post your expense reports in the public eye, right?
• So, and the reason to do this is actually it could go wrong.
• You could say, “I’m going to spend, you stay at the Four Seasons, I’m going to stay at the Five Seasons.”
• You could go that direction.
• But what you actually want is a moral code.

Balancing Trust, Verification, and Culture

• It’s like, if you were the owner of the business, it is your own money.
• Yes.
• So, if you were staying at the Five Seasons, I’ve just made that hotel chain up, it’s like, you’re— Sounds pretty nice.
• You’re stealing from yourself.
• Why would you do that?
• The problem is that once you get to tens of thousands of people, how do you impose that moral code?
• And actually, like the two tent poles that you just mentioned, they’re both bad.
• Because if you have to stay at a crappy hotel, and you’re about to sign a two million dollar contract and you didn’t get any sleep, it’s the Motel 6, and you take a two-hour taxi.
• It’s like, all right, you saved the company money.
• That does not make sense.
• Stay at the Four Seasons.
• But you can't really embody that in, "if this, then that."
• Because what you want is this moral code.
• Like, that’s what you want.
• And like, how do you actually instill that?
• And there’s almost a behavioral psychology way, which is like, we’ll just show what people are spending.
• If you’re at the top of the leaderboard, we might trust but verify, and verify a lot more.

Instilling Company Culture in Policies

• But that’s the hard thing to do and actually preserve as the company goes from the founder to the founder plus the founder’s brother to many, many more people.
• How do you keep that same esprit de corps or this informal code?
• I think it comes back to… What was the name of the movie?
• “12 Angry Men,” I think it was, where, as you’re watching the film, you get some level of detail and someone seems very guilty.
• It’s a dead shut case.
• And as more evidence emerges, you realize actually, this may be different.
• And you need more context in order to arrive at maybe a moral conclusion.
• Did it relate to closing a project?
• How does it relate to an outcome that maybe you’ll see emerge one month, two months after you stayed at the Five Seasons and closed the deal that changed the company, whatever the example is.
• I would argue in favor of tools that have more context, that do more jobs of work.
• Because not only can you do the narrow job better, but you can start to get at the answer of what actually is right for shareholders.
• Where should we be allocating capital?
• It’s so interesting to hear, because every company approaches this differently.
• Like, I’m on the board of Wise, and you know, Kristo flies coach everywhere, everybody flies.
• That’s just the policy, but it might be penny-wise, pound-foolish.
• Again, not for me to say, but I also really admire the corporate code.
• It’s just like, you, actually, that is cultural.
• It’s kind of weird to say expenses are cultural, but they are.
• For sure.
• Yeah.
• It's shared— Shared belief system.
• It’s a shared belief system.
• It’s like, what is the culture of the company?

Antiquated Bill Payment Systems

• You talked about your expansion into Bill Pay.
• It seems like bill payment has proven, over the past 40 years, uniquely resistant to automation and modernization.
• If you look at how a typical business pays their rent, or if you order a keg of Guinness, you’ll get a PDF emailed to you by some person who has a relationship with you.
• And there will be bank account details which hopefully are correct.
• And you send a payment to those.
• And even bill payment products, you guys have a bunch of technology here, but it’s like, we scan the PDF in an automated way, or we ensure that the bank account details weren’t mistyped or something.
• But it's kind of "putting a little bit of lipstick on the pig" of the whole system being super antiquated.
• Why is the system so antiquated when it comes to bill payment in particular?
• I think this is some of what Alex was bringing up.
• It's the constraints of programming things in an "if this, then that" kind of world are very heavy.

Complexity of Spending Decisions

• There’s a lot of complexity.
• And when you think about the nuance and algorithms that govern why do companies spend money under some circumstances, how hard it can be to record.
• I wouldn’t overlook…
• Let's say that you're a manufacturer and you're buying some asset which you're going to use for five years and it's going to depreciate.
• It's a very different accounting treatment versus I'm buying a pay-as-you-go SaaS app.
• All the complexities around that might govern whether or not you decide to spend.
• And then finally, once you get all this detail, how do you review this and decide where to allocate your next marginal dollar is very complicated.
• But many systems are in place upgraded despite the fact that that’s pretty complex.

Historical Upgrades of Payment Systems

• So credit cards started with no real-time authorization system, which is crazy.
• And you just hoped that they were good for— Carbon copy.
• Exactly.
• The machine with the pleasing sound.
• They’d do great in the current ASMR environment.
• That’s true.
• But then they added, you could call up and get an authorization and then they obviously added to the current systems we know where— The modem, you forgot the modem.
• Exactly.
• And then the modem.
• And so, in place credit cards were upgraded with much better capabilities.
• And similarly, if you look at checks and how they work, even though we think of checks as antiquated, it used to be the case that physical checks had to be flown all around the country to be physically settled.
• And then there was the Check 21 Act in, what was it, the year 2000?
• Where they said a scan of a check is good enough and so they could be digitized by the banks and then shredded.
• And then there was the, you can take a photo of a check with your phone.
• And so we’ve managed to take this super old-timey check system and despite the fact it’s super old-timey, in some ways it has actually been meaningfully upgraded.

Need for Centralized Payment Networks

• And if you looked at the bill pay system from the outside, you would say we should have DNS for companies.
• So rather than a company like sending you their bank account details, you should look them up in some central clearinghouse.
• And that way you confirm that you’re not being phished.
• A lot of spear-phishing attacks work that way.
• Although you referenced this.
• So there’s actually an indifference point that you can graph.
• If interest rates go up high enough, if I send you a check, which is like a paper mail check and that takes five days and hopefully the USPS goes on strike for two more weeks so I’ve got the postmark.
• I actually benefit… It’s actually cheaper for me.
• You legally paid, right?
• It’s crazy.
• No, it’s crazy.
• This is the problem.

Adversarial Nature of AR/AP

• Like credit cards, everybody…
• I am in the store, I want the TV.
• You want to sell me the TV.
• We both want this done right away.
• And in the knuckle-crunching, ASMR, carbon-copy days, they might not have been willing to sell that to me because they didn’t know if I was good for the money.
• They’d never seen me before.
• And the interesting thing is that AR and AP are almost an adversarial process.
• You mentioned this.
• What do you want to do as a controller?
• Well, you want to pay as late as possible and you want to collect as early as possible.
• And then you have this weird thing where checks, it’s not just an accident that they stick around for a long time.
• It’s like there’s a financial incentive for one party.
• So that’s true on payment timing, I agree with that but there are some things that are just a dead weight loss, like the ability to fat-finger a bank account.
• No one benefits from that.
• Everyone has a horrible time if that happens.
• No, that Nigerian guy.
• There’s some people that benefit.
• Nigerian princes.
• Let’s think of everyone.
• I will posit that many networks have been upgraded in place.
• But somehow the loose network of businesses paying each other via PDF invoices has proven very resistant to in-place upgrades.
• Also, I love your notion of DNS for payments or for expenses.
• So, I don’t know if you saw this, Google wanted to issue a 100-year bond.

Google’s 100-Year Bond and Financing

• Yes.
• So, why is that interesting?
• Imagine that I am owed money by Google.
• I am one of the small businesses that you reference.
• Their job is to pay me as late as possible.
• They can borrow money for a hundred years at like 3% or whatever it is, cheaper than the US government probably.
• T plus a hundred, yeah.
• I mean it’s a little more expensive than the US government, but they are borrowing…
• That’s crazy.
• I can borrow money at 20%, but why do I need to borrow money?
• Because Google’s paying me late.
• Those jerks.
• So, I should be able to borrow money kind of at the rate at which Google is borrowing money because my AR…
• My AR is their AP.
• But the problem is, unless you put all this together, you would just look at me and you’re like, “Well, you’re just a little schmuck.
• I’m going to charge you 18%.”
• It’s like, yeah, but it’s Google.
• They could borrow money at T plus whatever, you know, SOFR plus a hundred.
• 100%.
• That’s not fair.
• But the only way to really solve that is with more data and actually entangling...
• Not entangling, but just kind of connecting these things together.

Shifting Software Development Landscape

• What's your vision for once AI is doing a lot of software engineering, what does that look like in three or four years time?
• Is the competitive equilibrium similar, but the expectations for the amount of software and functionality businesses are shipping is much higher?
• Are software teams similar looking, different looking?
• Again, you’re doing a lot of AI engineering.
• What does the future hold?
• It's all blurring.
• It's totally crazy.
• There's a designer shipping code.
• Marketing at Ramp reports into our CTO Karim, my co-founder who's doing some of like the best marketing I've ever experienced and seen.
• We have customer support agents like shipping code to production too.
• I just think that the half-life of you see a problem to how long it takes for you to go fix it and do something about it is shrinking immensely.
• Or if you want to change a color of a button, you can just say, “Hey at Ramp Inspect, can you change the color of this button?”
• And it goes and spins it up and it does it within minutes.
• It verifies and validates it.
• And so, I actually think in some sense, these classic barriers that software businesses had are clearly going to erode.
• Yes but, there’s the old joke of “It’s much more fun to write code than read code,” which explains a lot of software engineer’s behavior.
• And it becomes easier to change the button.
• Is that another instance of it being more fun to write code than read code?
• Where lines of code are a liability and not an asset because they're something you have to reckon with.
• And so, are companies at some level incurring some tech debt now where they're adding a bunch of code, which will maybe be harder to reason with later?
• Or do you just get bailed out by the models getting better?
• It’s really interesting.

AI-Driven Code Generation and Rewriting

• And by the way, one of the other interesting sub-conversations I’m hearing a lot, too, is when you think about where tech debt comes from, there’s a set of conditions and trade-offs you make, you write things in a discreet and deterministic way.
• Under these circumstances, follow this code path.
• Under this circumstance, follow this other one.
• In a world where there’s LLMs and the models themselves are improving, I think it’s entirely possible that the way that code is written is you say, “Here’s what I’m solving for.
• Under these kinds of conditions, here’s what I want to occur.
• Go write the code that drives this outcome.”
• And maybe with the models such as they are today can get it done in sort of a spaghetti code written fashion.
• But it kind of works even though it’s some kind of Rube Goldberg machine underneath the hood.
• But as these models get much smarter, you might write your code base in such a way where you say, “Every year, rewrite the underlying code, but here’s the outcome I can drive.”
• And today you accomplish my outcome 90% of the time, 95, 98, 99, 100.
• And do you just have kind of self-healing and writing code all the way through?
• And this notion of like underlying code does goes away because we're writing things in this different manner.

Impact on Cognitive Work and Infrastructure

• Obviously, there’s real conditions in which that’s not going to…
• That won’t occur.
• Like, if you're writing code that needs to have four nines of accuracy and uptime, like that's probably not the methods you're using.
• But if you're like a growth engineering team, that's probably what you're doing today if you're kind of on the leading edge of this stuff.
• And so, I find this stuff very fascinating.
• And when I think about the deeper implications of this stuff, I think that if you are completing this small amount of cognitive work...
• Let’s say you are an expense app.
• The spend has occurred, it needs to go get the…
• write it down somewhere and get someone’s approval.
• And that's all the knowledge work that you're doing.
• That's very few tokens in order to accomplish that, both to create the infrastructure in order to facilitate it, like that probably evaporates.
• Anyone can probably custom write that kind of app.
• Whereas if you're doing much deeper kind of work, such to underwrite a company, provide financing, automate areas of accounting, I think the fitness function for companies becomes, can you actually do things in such a way where even if you could spend tokens on it, it would take more tokens to create the thing or do that work than the system maybe that you've built to kind of drive that outcome.
• I just think the rules of what it means to be a software company are changing.

Competitive Moats and AI Engineering Teams

• I think network effects and what you're building is more important than ever.
• Like, if you think about the classic set of moats that are there, I think that this question of where are their moats in a world where...
• I like Dario’s way of putting this.
• If you have a country of geniuses, data center, yeah, living somewhere and they’re writing code and they’re incentivized to compete with you, too.
• If you’re not really following what are the classic four moats and building towards that, like, I think life gets a lot harder.
• Do you guys have a house view on the new competitive equilibrium with a lot of AI engineering really working?
• Well, I think there are a couple things.
• I think Marc talked about this a little while ago, but what is an EPD team?
• Engineering, product, design team.
• Product development team.
• You normally have one product manager, maybe you have five to eight engineers and one designer.
• And now everybody has Cursor and Claude Code.
• So the designer is like, “I don’t need any of these bozos.”
• The product manager says, “I don’t need any of those bozos.”
• Each of the engineers are like, “I don’t need any of these bozos.”
• And they’re all— it’s like the start of The Dark Knight.
• And they’re all right.
• It really is.
• It’s… Exactly.
• It's like they're all wearing the Joker mask.

Evolving Business Moats and Competitive Landscape

• Or, the Joker mask is Claude Code or Cursor.
• But the problem is, because I was talking to one of my CEOs, this is a pretty scaled company, lots of revenue.
• And they use all these tools, they're not more efficient.
• And he is like, "Why aren't we more efficient?"
• And it’s two things.
• Number one, it's a real company, they have real customers.
• They can’t just push things and hope for the best.
• But it’s like you actually have an HR problem.
• In that if you’re building from scratch, granted you have nothing, you have no tech debt, you don’t really have to worry about customers, you don’t have any, but you wouldn’t have an eight-person EPD team.
• You would probably just have each person…
• we have eight different product managers, slash engineers, slash whatever.
• Each one is a pod unto themselves.
• So that’s one thing.
• I totally agree on the data moats where that has become more important.
• I’ll tell you a story that you might like.
• I met this company, vLex.
• It’s a 25-year-old company.
• This guy Alex bought up every legal record in Spain, like probably going back to 1492.
• Buys the Ferdinand and Isabella…
• Here’s the document, I’m going to take a picture of that, I’ll sell it to every law firm.
• And he built like a $20 million a year SaaS business, bootstrapped for 25 years.
• And then it went to like a hundred million in one year.
• Now why is that?
• Because he used to sell this document or he used to sell a subscription to Kirkland & Ellis and Latham & Watkins and all these big law firms.
• And a paralegal would take that, they would turn it into a document.
• They’d charge the client $10,000 and ChatGPT can’t do that.
• GenAI can’t do that.
• But you know who can do that is vLex.
• Another good example of this, of who has proprietary data?
• A lot of times, the data's free.
• This is the really cool thing.
• Or it’s sitting, I wouldn’t call your data free, but it’s not like for-sale data sets.
• Do you know domaintools.com?
• It’s my favorite business.
• So DomainTools runs a cron job every day on every single internet website.
• They do a WHOIS lookup every single day.
• And they build a historical record of that which no one has.
• So if you want to see who owned stripe.com in 1999, well, it was free in 1999.
• If you invented time machine, go run that WHOIS query in your terminal but you can’t do that.
• So you have to pay them.
• But all that data is free or FlightAware with ADS-B data.
• So you have a lot of these weird businesses.
• And of course this is not a new idea, like FactSet, Bloomberg…
• You have aggregators of data, but that becomes so much more valuable.
• Totally.
• Because your 10,000 geniuses cannot do that.
• You always experience this if you hire someone extraordinarily talented, like top of the class at MIT and you say, “All right, join the engineering team and go ship the code.”
• And they ship something kind of crazy on the first day.
• And it’s sort of slow.
• And it’s like, you can have someone who is intellectually an absolute giant, but learning kind of how a company does things the way it does.
• Learning the procedures and nuances of an organization takes time.
• It’s part of what makes working with interns or junior engineers fun.
• I think the learning curve is obviously immensely steep.
• And I think that the speed at which, with sufficient access to the data and the procedures of a company, they're going to get there very, very fast.
• But these moats are real, you know?

Dark Matter Moats and Tech Debt Value

• Well, the other moat I would argue is the dark-mattered moat.
• Yes.
• And what I mean is you know, like the Milky Way, nobody could figure out why the mass is the mass because it's like all the observed stars and planets and everything else.
• It's, no, actually the vast majority of the matter, or energy, because they're the same thing, is dark matter, dark energy.
• And what does that mean?
• Nobody the hell knows.
• But it’s just like, we don’t know it.
• And for products, it’s like you built, if I tell Claude, “Go clone Ramp.”
• Because this is the SaaSpocalypse that’s happening right now.
• It’s like, oh, of course.
• Well, I just went to the website and now I have a website that looks like Ramp.
• No, no, no.
• There are like nine million edge cases.
• The tech debt sounds bad because it's a pejorative, debt = bad.
• But actually it's good because what you've done is you've uncovered every single problem that can go wrong.
• The fact that, I mean, a great example, remember when the power went out in San Francisco a month and a half ago?
• So we have this amazing thing called Waymo.
• Waymo had not figured out this corner case of what if the power goes out?
• It was a thundering herd problem with the customer, or the human overrides, yeah.
• But they had no idea.
• And it’s actually great that that happened.
• You need these problems to happen.
• And just because my background, I used to write shareware, this try-before-you-buy software.
• Shareware was a big thing.
• That’s a blast from the past.
• It’s a blast from the past.
• So there’s a website that’s part of CNET— That might come back, you know?
• Well, but it’s freemium.
• This is where I’m going with this story and you’ll like this.
• So Download.com was the preeminent site for downloading shareware.
• It was like…
• CNET was one of the most popular properties in 1999, 2000.
• So, all of the top downloadable software products were there— Download.com sounds like a company that had a Super Bowl ad.
• They would’ve.
• I bet they did, actually.
• They probably had two.
• I’d be shocked.
• They probably had five.
• Right between Pets.com and something else.
• So Download.com had all the popular products and then this site called Elance shows up and Elance is now called Upwork.
• This connected you with work that you would want done by very smart people, basically in the developing world.
• So I want a software product built.
• Here’s everybody in Romania and Russia and India.
• I want translation, I want graphics.
• So what ended up happening is people would look at the Download.com top list because before it was a very cottage industry of who wrote shareware and it was very profitable.
• Like ID software shareware company, McAfee shareware company.
• Actually Cybersource started off processing payments for shareware companies.
• That’s how they got McAfee.
• That’s funny.
• Very interesting history to this we can talk about some other time, but basically what happened is people found Elance, like, “Oh, I could pay anybody $500 to clone anything on this list.
• Everything on this list makes tens of millions of dollars a year.
• Let’s go.”
• And the cloning never worked.
• It functionally worked.
• Because if I say “I’m going to clone Eric.”
• I might not know that you have a pancreas.
• Right?
• I’m sure you do.
• I might not know that you have two kidneys.
• So the problem is that cloning just, it goes skin deep and like that’s the embedded advantage of these companies.
• Do you then think the SaaSpocalypse is kind of irrational?
• I think it depends.

SaaSpocalypse Rationality and Enterprise Software

• I think some of it is very rational.
• Because if I want, if I have a feature that became a company, and I know this sounds like a very negative thing to say, but I want to get paged if my server goes down.
• It’s a very logical reason to build a company called PagerDuty.
• That now has a lot of stuff around it but I might just say, “Hey, whenever my servers…” There are corner cases, there is the proverbial the power goes out in San Francisco, do something differently.
• That's very, very different than NetSuite, which is, I have a saying that I like, which is the best companies have hostages, not customers, at least in enterprise software.
• Not for you because you actually have INPS.
• But that they’re much harder to go rip that out and a lot of it is like the “Goldilocks zone” that you operate in.
• If you're too expensive, of course I'm going to try to rip that thing out.
• If it's so cheap then I forgot nobody even used it.
• So you have to be in this Goldilocks zone, you have to have enough complexity.
• And ideally the front end is different than the back end.
• So, Workday I think is…
• Nobody’s going to get rid of Workday.
• And I actually credit David Ricardo with this.
• Like, comparative advantage.
• Sure, you could grow your own food.
• You could plumb your own plumbing.
• But you’re not going to do that.
• And somebody could do your own HR system.
• The one maybe pitch for Stripe and others that I would say here is, I do think that that is right.
• And there is a lot of complexity and local tax law for payments and things that make Workday an extraordinary business.
• There was this overarching macro question of how does work get done?
• If you believe that.
• You know, work can get done through tokens and models.
• And presumably it doesn’t go through payroll, probably goes through a credit card or check to these types of companies.
• And so, the share of, it’s almost this sort of simple math that if you X-rayed the P&L of most companies, the majority of it classically, at least for asset-light firms, is payroll.
• You’re paying for people to do things and SaaS is maybe a small percentage of a company’s income or a company’s cost base.
• Does suddenly that share grow to high single digits, low double digits, significant double digits?
• And does the share actually move where, the payroll economy itself, even though maybe it grows, becomes less relevant?
• I think this is the really funny part of even as this has been going on.
• What do I know as a private company other than seeing our own payment data?
• But you start to see these companies beating their earnings in a way they never have before, where the terminal value perhaps is falling out.
• But they’re saying, “Shareholders, we’re reaccelerating.
• We haven’t seen this since 2021.
• We’re going faster and you’re going to have multiple progressive quarters of this actually occurring for certain types of businesses.”
• And so, it’s a really interesting time to… I very violently agree with your view is like, yeah, it depends.
• But it’s doing really well.
• That’s my brilliant comment.
• It depends.

Ramp’s Global Spend Management with Stablecoins

• Yeah, you mentioned… Very Howard Marks of you.
• As you’re hearing from Eric, Ramp has become the default way a lot of American companies manage spend.
• Stablecoins allowed that functionality to work in many countries all at once.
• With Ramp's stablecoin-backed corporate cards, businesses can fund a balance with stablecoins, issue cards against those balances instantly, and allow employees to spend anywhere cards are accepted without the business having to think about stablecoins all the time.
• Same card experience, same controls, just a much more global set of rails underneath.
• This is one of the many practical ways we’re seeing businesses on Stripe use stablecoins by launching card programs in many more countries and doing so in much less time than it would’ve taken otherwise.
• If you’re thinking about using stablecoins to expand, Stripe can help.

Economic Strength and AI Adoption

• You mentioned your spend data.
• What does the spend data that Ramp sees tell us about the economy?
• I think it is stronger than many people understand in lots of ways.
• I mean, first, I’ll go back to one of the things that perplexed our team for a long time.
• Our economists on the team saw this data even as recently as last year, where the Census Bureau would do these periodic surveys.
• They'd go out and ask, "How much is your business using AI to produce goods or services?"
• A very refined economic way of wording the questions.
• And they would come back with these pronouncements saying a single digit percent of businesses in the US have adopted AI.
• And we looked at our data and we support over 55,000 businesses.
• We lean a little bit towards tech, but not heavily.
• It kind of resembles the distribution of businesses you would see in the States.
• And well, the majority of businesses have used AI.
• You look at businesses whether they’re paying for— As in they subscribe to ChatGPT or Anthropic or something like that?
• Exactly.
• Or maybe a business that is a true agentic… Cognition or a Cursor, something like that, where this is kind of a vertical application.
• And so, one, there is this disconnect between the use of tools if you look at how quickly businesses are adopting and responding to these new tools versus what maybe people report on.
• Next: growth.

US Economic Reacceleration and Business Savvy

• I think it’s been clear over the last few quarters is the US itself is reaccelerating.
• GDP growth has gone from maybe the one to 2% area to four to five.
• And you could argue how much of this is, a little artificial with subsidies, but it’s been pretty significant.
• But subsidized by what?
• Some of the Big Beautiful Bill as well as some of the tariffs.
• And where that’s been reallocated, I think some people, I would argue on the whole, maybe unfairly said this.
• I think that there's more durable growth inside of the businesses.
• But I would say overall business health is much stronger.
• And I think that the really interesting thing and again, some of this is specific to the data that we see, but I think that businesses are generally getting more and more savvy about finding tools that help them be more efficient.
• And I think what skews our data is maybe the savings we drive for people.
• Seems the way of explaining it is like, people know the… Ben Franklin would say this phrase of “a penny saved is a penny earned.”
• And this is an awesome aphorism, but the average American business has an 8% profit margin.
• And so mathematically speaking, a penny saved is equivalent to 12 pennies of revenue earned.
• And so if you save businesses a lot, you end up with these outcomes of the average Ramp bases materially outgrowing the regular US average.
• And we can clearly see this and demonstrate this for our own set of customers.
• I suspect these types of things are occurring at businesses adopting these new sets of technologies, I would argue probably faster, very clearly, than what the US is maybe, the classic sources are seeing.
• So I think it’s much healthier.

Cost Savings and Operational Efficiencies

• When a business saves money on Ramp, what happens?
• The CFO comes in and says, “Oh my god, we’re spending— confetti.
• Way too much money, on confetti.
• We don’t need this much confetti.”
• Who’s buying the confetti?
• “We have huge stockpiles that we don’t need.”
• What happens when a business saves 5%?
• What are they actually cutting?
• So there’s two pieces of it primarily.
• One is like these hard-dollar cost savings and then some of this is time, and I'll start with the time because it's the squishy one, but I think that it's, in some cases, actually much more important.
• Oh, sure.
• They save time on their expense reconciliation.
• That makes sense.
• So they're no longer going through line by line and therefore there's one person who is freed up to go do something else.
• And I think one of the classic biases that people forget is people chronically undervalue their own time.
• As a principle of business, everyone has an hourly rate.
• Within a business, human time is incredibly expensive.
• I think the lean companies got this right and eliminated the bottlenecks there.
• So, okay, that’s one form.
• What else?
• Next, all right, when you start to have these fine-tuned kind of controls.
• This part has been I think probably the biggest lion’s share of this.
• Let’s go back to one of the earlier conversations of why do people use checks, this horrible system and purchase orders?
• Well, one of the advantages of checks is unless you mail it to someone and you sign it, no money can leave your company.
• And what every person knows who's ever had a credit card and gone to a gym once and had a good New Year's resolution.
• But is you go a couple times and you’re like, “Goddammit, this gym is charging me.”
• The difficulty of sending a check is a feature, not a bug.
• Yeah, exactly.
• But it’s part of what Ramp was the first to build.
• One-time use cards.
• Single-use cards, but also more than that, merchant blocking.
• So you can, whether it’s on one card or 10,000 cards at once, build in a kill switch to say, “Okay, we’ve signed this new deal with this merchant.
• We are only on Uber, we are no longer taking Lyfts.
• And anytime someone goes and tries to go on merchant A or B, you can do this.”
• Or you sign a new contract and you say, “I’m gonna spend $10,000 only with Salesforce and on the $10,001st dollar they try to charge you, it declines.”
• And what gets to happen, you get to have a conversation with their sales team who really wants to make their budget.
• And if you look at this mathematically, for most companies that come over a low end, maybe a very hygienic company that is giving out a few cards and the old world could durably cut their expenses about 2% a year by doing this.
• Some of these very laissez-faire businesses are saving just 10%, just through these things.
• Next, you start ending up with these more fine-tuned kind of controls where you can say under these circumstances I want to go and have kind of charges occur.
• Maybe you have an engineer stay till 8:00 PM at night, you can go and buy a meal.
• But if you take an Uber on a Saturday, that should turn off.
• And so you have the cards, if it’s like an Uber on a Saturday auto-decline, but you can text and say actually it’s for work.
• You send back a yes, it turns on.
• And so it's all these little tiny paper cuts that actually start to go into run.
• Next, it's vendor data.
• One of the unique assets of Ramp is anytime you spend money, you upload a receipt, maybe you upload an invoice or an MSA.
• This takes us back to the Paribus days.
• We know across hundreds of millions of purchases every year, not just that you spent money at a software vendor, but what did you spend per seat?
• And so if you’re a customer on Ramp and you’re about to go and pay this large bill on a random SaaS vendor, we can show you in real-time before you send the funds, you are paying 20% more than the rest of the market.
• Here’s kind of the cost curve of what others are paying.
• And actually by going and empowering your procurement team— do you have enough data to do that?
• Because my AWS bill is not like your AWS bill.
• And so, don’t you need to know how many instances we’re running to know if this is a good deal or not?
• You can, but you can still kind of get down to the level of, is there a bulk discount or not?
• And start to know of, is there a negotiated aspect?
• There’s other types of things where I’d argue maybe a lot of classic software-as-a-service ends up in this way.
• It’s like your pricing is really dependent on, you know, did you sign that deal on January 1st or on December 31st when the sales team really needs to hit the quota?
• And you can actually see down to the seat level, you’re paying $30 per seat.
• It’s a great time to be signing a Salesforce contract.
• And so you can actually get down to the seat level and say, okay, you’re about to auto-renew.
• The market price has actually moved for the set of service.
• And so it can be very, very useful to procurement teams to know where they compare with the market.
• That was actually my question for you, which is, so if you remember Groupon?
• Yes.
• The much beleaguered Groupon, but Groupon started off as a site called ThePoint.com/groupon because originally it was like, “I don’t like the fact that Starbucks uses paper cups.
• If I get 10,000 other people to donate a dollar, we’ll fly a plane in front of Howard Schultz’s house,” which also emits carbon, a bad example.
• But you only want, it’s a collective action thing.
• So, and then because I met Andrew Mason and Brad Keywell when they were first starting this business, it was like eight people.
• It was ThePoint and downstairs there was a pizza restaurant or something like, “Oh, if I get like 50 people to agree to buy pizza, maybe they’ll give us a lower price.”
• The cause became discounts.
• Yes.

Collective Bargaining Power and Discounts

• And then, but then the thing is, Groupon wasn’t known for this, “it has to tip” because they always had the demand.
• So they never had to worry about it, because before it’s like you’ve got supply, you’ve got demand.
• I guess my question for you is, can you be the arbiter of pricing?
• Can you aggregate the demand?
• And the same way that like Costco, who shops at Costco?
• Every small restaurant shops at Costco.
• And Costco uses that collective bargaining power, if you will, to say, "Hey Coca-Cola, give us a very, very low price."
• They take very, very little of that because right now I’m using Ramp to buy stuff.
• But I would imagine if you could say, “Hey, I have $100 billion.”
• I didn’t know it was that high, that’s amazing.
• “I have a hundred billion dollars of spend.
• I can hopefully direct it this way or that way.
• Please give me a 20% discount.”
• Can you do that?
• Or is that further in the funnel of the purchase process?

Group Purchasing Organizations and Demand Aggregation

• There is this large swath of businesses that I've been fascinated by called group purchasing organizations.
• A lot of these came out of the healthcare world where it’s a very small set of— APMs?
• Yeah.
• Yeah, exactly, supplier.
• But if you can go and aggregate demand, you could say, okay, for these type of purchases, you’re going to offer this procedure at this account for this type of equipment, you’re going to give this level bulk kind of discount.
• And you’ve gone and you’ve done that.
• And I think these are very popular now in the private equity world.
• Even when I look at Ramp data today, there are dozens of, and more and more every year, of merchants where, you know, we were sending billions of dollars.
• It is truly, it is the client’s money, they are going where they’re going.
• But we have a sense of actually, okay, where is this actually going?
• And can you go and say, you know, across the Ramp buyer base over the next 12 months, this is how many dollars will go towards you.
• Can we negotiate a discount?
• The other way which maybe starts to…
• Sometimes these businesses veer closer to advertising, but where it gets really interesting is we see the fastest-growing businesses.
• What are the businesses that people are getting really excited and are adopting really quickly?
• And we might have a signal of these are actually good businesses and good tools and actually most businesses should move towards that.
• Could you go and actually start to say, “Hey, your renewal is coming up in 90 days.
• Have you considered this other business who has provided a 20% complimentary welcome lower price to you?”
• And so, there’s multiple forms that can take place.
• But the short version of it is, I think one, it’s yes, I think you can offer a bulk discount.
• But two, you end up almost getting closer to, back to this other theme of can you start to go and maybe show businesses that directing their next marginal dollar will lead to this outcome.
• Well, it feels like there’s even like a third thing.

Merchant-Specific Balances and Vendor Loyalty

• Which is, I would call it merchant-specific balance.
• So imagine that it’s December 31st, I’m buying something at Whole Foods.
• And then I see an offer, not donate a dollar to the, you know, whatever charity they’re pushing.
• But it’s like, why don’t you commit $2,000 of spend for 2026 for $1,800?
• And the nice thing there is that they lock in that spend for me.
• They actually collect it.
• I mean I know there’s a stupid law and all this complicated stuff.
• But the key thing is it's almost a risk management and a loyalty play for them at once.
• Because the problem is that they don’t know how much celery to buy.
• They don’t know how many…
• So, it kind goes back to the AR/AP thing that we were talking about earlier.
• You nailed it, yeah.
• Because the other thing is not just saying, “Hey, I’m going to group bargain on behalf of all the different customers that I work with.”
• But it’s an ancillary thing, which is you might want to just pre-commit your spend to a particular vendor.
• And that vendor would love to have that spend pre-committed, even if they’re Amazon and their cost of capital is very low.
• Because they know they don’t have to worry when they’re planning their budget for the next year.
• That you’re going to churn in month nine.
• And that seems like another, like the closest that you can get to that is gift cards.
• Strangely enough which I’m sure you know well from your— It’s gift cards for business.
• Yeah because it’s like you go to Costco, this is actually a big business at Costco.
• You go to Costco, they sell gift cards.
• We were just talking about this.
• So they sell gift cards.
• You can buy $100 of Starbucks gift cards for 80 bucks.
• Is Starbucks dumb?
• Like why are they, if they’re worth $100?
• No, because they basically have, in the ecosystem, money that is going to be spent at Starbucks.
• And yeah, there’s breakage and other stuff, but it’s actually a quite, it’s quite a valuable value proposition for the receiving merchant because they know that you’re going to spend your money with them.
• But I want to go back to your previous idea where McDonald’s every five years or whatever does a big bake-off between Coke and Pepsi and they always renew with Coke and they have a long-time… Maybe a movie theater chain is better example.
• All the big chains, like they don’t serve Coke and Pepsi, they only serve one and they do a big bake-off between the brands every five years.
• And you have lots of small businesses that are buying from Coke or buying from Pepsi.
• And so, it feels like you could just do a bake-off between them saying Ramp is going to have a preferred vendor and you can obviously use a Ramp card on either, it’ll work, but we have preferred rates with Pepsi.
• Is that a thing Ramp should do?
• It’s a really interesting question.
• The short is I think over the long duration of time.
• Like I’m kind of bit of a crazy person.
• We should try everything is my actual answer.
• Claude Code.
• Yeah, Claude Code.
• Let’s go, let’s do it, build it.
• Pepsi.
• Make money from Pepsi.
• Go and negotiate.
• The cost of a phone call, a negotiation has never been lower, but… And there’s this almost philosophical question of like, all right, where is the differentiation?

Ramp’s Differentiation: Selling Time vs. Money

• What makes Ramp different?
• But isn't that increasingly the scale?
• It is, and I think that you’re right in that at the very beginning of the company, the answer was very easy of like, look, our cost of capital is nowhere close to a bank’s.
• The interchange that we could make is nowhere close to it.
• We have all the disadvantages of scale and kind of the only thing that we could do to compete with these people was we could… Everything was slow at the bank that I worked at before, it was hard to ship things.
• We need to move fast.
• We need to kind of have this emphasis around velocity to ship product and just kind of blitzkrieg faster than maybe others could respond.
• What it's evolved into and I think is today probably the largest point of differentiation at the meta level between Ramp and maybe the financial service providers that we compete with is they sell money and we sell time.
• They’ll sell you a lower, like a loan at a lower cost of capital, rewards at wherever they set it.
• We will sell your expenses, done.
• And so, are you naturally skeptical of this idea because it’s selling money rather than selling time?
• I wouldn’t say I’m naturally skeptical.
• I would say that— It’s okay.
• We’re not precious.
• We have lots more ideas.
• No, no, no.
• It’s good.
• There is this question of, I think back to our roots, like, I don't know.
• How do you build a product that is 10 times better than other folks?
• And I think when you get really large, actually just a line drive is good and a 2x or a 3x is better kind of thing is actually good.
• But how do you find these sets of things that other your product offering is so different than what you can find elsewhere?
• And I think that we can conceivably, and I know this, you can negotiate with the large logistics companies.
• A deal with FedEx that would be better than what most companies are paying and I think that that’s interesting.
• Then you have all the sublevels of how do you get people to know about the offer, to sign in to the offer, to deal with all these sub things.
• Or you could just go and spend that next marginal hour to go and say like, let’s just automate all of accounting for these customers.
• Let’s go and start doing financial work for these customers.
• No financial institution is able to compete on that kind of vector.
• And so, I would say it in the fullness of time, we want to do both.
• Like I think that you want to save people the maximum amount of time, the maximum amount of money that you can, but I think part of what makes us so different in this kind of world that we operate in is we have this obsession of sources of drag of the things that slow down purchases that lead you to overspend versus other companies.
• But just to push on that, I feel like the differentiation for companies often has to change as time goes on because they start in one competitive equilibrium.

Evolution of Competitive Advantages

• And then as time goes on, they're in another competitive equilibrium because it's dynamic.
• That’s fair.
• And it feels to me that Ramp got its start with very fast product velocity and having this great product experience.
• And as you grow up, you can just build a scale into the product and scale… Scale-derived product advantages.
• Not just like we’re big, but like Costco, the advantage comes from the scale and they really passed it on to the customer.
• And it feels like there could be a second stage to this rocket where you get going with faster product velocity.
• But then there’s actually a pretty different set of product differentiations as you scale up.
• I think it’s true.
• I think it’s well said.
• And there’s this almost question of like, in every line of business that we’re building, where are we in the S-curve?
• How far are we?
• Is this a product that is serving these tinkerers, early adopters?
• Are we in the early majority?
• Are we in the late, where we need to shift the business to kind of harvesting contribution, optimize price, not quantity in it, or towards the end?
• And the thing which is so shocking and I think maybe as part of why I love this business, and I think even, I think about Stripe and many of the great businesses in payments that have been built.
• I believe today Ramp powers more than 2% of all corporate and small business card transactions in the United States.
• Which is amazing for a business that, the product, you couldn’t even sign up for it six years ago.
• And yet that’s a really fancy way of saying 98% of spend is not on us.
• On Ramp?
• Yeah.
• And let’s say we do it again.

Evolving Differentiation and S-Curve

• We grew faster last year than we did the year before.
• I feel very good about the way this year is starting off and maybe it’s closer to four.
• 96% is still big.
• 92% is still big.
• It is so large.
• And by the way, there’s more ways to buy things than just cards.
• You think about bill payments.
• And so, I think that there is an aspect of, for most people, there’s so much drudgery around, I think people are doing artisanal expense reports.
• You know, it’s fun to be like a hipster and spend an hour making coffee, but like, it’s a little crazy that this is the Blue Bottle of expense reports.
• You know, but unfortunately, you’re in Concur and you have like this spinning wheel.
• It’s a pour-over expense report.
• It’s a pour, we love it that way.
• Single origin.
• You try it.
• It’s the experience.
• You’re the Nespresso.
• It’s much more efficient.
• But like, what I would say is this aspect of time is most people have not experienced this thing, you know, is just a fact of life for building a business that’s been hard doesn’t need to be hard.
• Doing your books doesn’t need to be hard.
• And so, I still think in some sense, in where we are on the S-curves of our business, I lean that way.
• But you’re totally right when you’re at this level where in the not too distant future, I mean, you’re there processing trillions of dollars per year in economic activity.
• And we aspire to be there in the not too distant future.
• Sounds like you’ll be there pretty soon.
• We’re working our hardest.
• Exponential growth is a powerful thing.
• Yes, it’s definitely given me good things to think about and work towards.

Impact of AI on Negotiation and Costs

• So I was thinking about when we met, when you were running Paribus.
• And it kind of feels like one of the first or second or third order effects of AI is the marginal cost of arguing has gone down to zero.
• I’m serious.
• It’s true.
• It’s just like, I mean, my wife got into an argument with some company and it’s like she used ChatGPT to argue with them, they used it to argue back with her.
• And it’s like, I just saw the future.
• This is incredible.
• And like, we won, which is great.
• Your agent will talk to my agent, yeah.
• But you think about this from a chargeback where it’s like, “Hey, this price went down.”
• I mean, this is how we, I remember like, this is such a good idea.
• It’s like the price went down, you have these breakage models that the card networks had.
• And Best Buy has to write you a check, or Visa has to write you a check because that TV fell by 20%.
• But nobody does that.
• And now everybody’s going to do that.
• Or it’s like, you do a chargeback for $5, it’s just not worth it.
• I thought it was Pepsi that I was buying at McDonald’s.
• It was Coke.
• Chargeback, right?
• Nobody’s going to dispute that because the cost is too high, but now the cost goes to zero.
• So I’m just, what do you think?
• I mean, it’s hard to picture five years from now what the actual full effects of this are.
• But if you kind of think about that as the macro abstraction of it's like marginal cost of arguing goes to zero.
• What changes?
• I think to be really explicit, I think what's happening is the marginal cost of time, of knowledge.
• Yes.
• That is a much better abstraction.
• Is what’s going down so rapidly.
• And I think about our customer base.
• Most of our customers don’t have a single software engineer, let alone a software engineer for their finance team.
• And if what we are very good at doing is selling functionally sets of work, maybe it’s embedded in a financial operating platform, but expenses done, accounting done, some type of knowledge work done, and you can deliver that.
• That is immense high-leverage value for these customers.
• Let’s say it costs $5 before, they didn’t do it, now they can get $5 of value.
• But maybe the cost of… It’s a software type cost, maybe it’s pennies of tokens to actually go and do that.
• That is a great business to be in because it’s very high customer value.
• We can capture just a small amount of that and build this business.
• And when you go back to kind of the original insight of Ramp, we entered into this industry where it was very profitable, but not only was it misaligned, but people were fighting over like basis points.
• Every last dollar that went into rewards could have meant like tens or hundreds of millions of dollars in profit for the business, for them.
• But if you think about for a customer, let’s say that in order to make one extra basis point as a business, you would try to incent them to spend a hundred more dollars.
• For that customer and let’s say they buy something that gym membership they didn’t need, or that subscription keeps going, they have lost $100, it’s gone out the door and maybe they go to the gym, maybe they don’t.
• But that is out of their bank account.
• And if you just try to say, I’m going to have a better rewards program, sure, maybe you can get that customer a dollar or $1.10 back or some amount.
• That pales in comparison to helping them just not spend that $100, cancel the subscription.
• The economic leverage of that activity is much higher.
• You sold your last business Paribus to Capital One.

Lessons from Capital One’s Founding

• Capital One is one of the biggest founder-run financial firms that people in Silicon Valley don't talk about.
• What should we all be…
• And has been extraordinarily successful.
• What should we all be learning from Capital One in their success?
• Actually, I should say, how did they?
• What product really broke out for them?
• Just what is Capital One success?
• I think there’s a lot that makes them amazing as a company.
• Both the founders are excellent.
• Rich Fairbank, Nigel Morris.
• I think it's worth people reading up on their stories.
• It was founded in ’90s, is that right?
• So, not quite.
• From a legal standpoint— I’m very wooly on my Capital One history.
• I think that legally the incorporation in some sense for Capital One, it was, I think it was in 1994, but the actual start traces back to the ’80s.
• At the time Rich and Nigel had met, they were consultants and they had this insight that the business of credit cards was… While it was lucrative, was not serving most of the country.
• The way you could kind of think about credit cards back then, you know Diners Club, maybe others have heard of it.
• It was was a way for rich business people to get together and have lunch.
• And like they put the card down and the restaurant would pick up the tab and they could go and pay the restaurant back later.
• And they had kind of navigated that and the simplification is if you had a very high credit score, you could get one of these cards with the benefits that it had.
• And if you didn’t have a credit score that met that, you could have a debit card.
• And that was basically it.
• It was a very linear cutoff.
• And what Rich and Nigel… The insight that they had had is there must be some curve.
• We should be able to test this.
• Maybe we give people cards that have above an 800 credit score or something like that then.
• But what about 790?
• There might be people there that can go and pay for this.
• If and the way we could go and take on the cost of this, maybe we charge them a somewhat higher interest rate until they prove their efficacy.
• If 790 works, let’s go to 780.
• So, it's kind of the BNPL of its day.
• There is a population who are, for whatever reason, just below the threshold where banks are giving them good access to credit, where you can actually very profitably lend to them.
• This is right.
• Exactly.
• And so, they, in the ’80s, were functionally pitching all these different banks to say, “We should go on this exploration.
• We’ll even run this for you.
• Let us go and run this.”
• And they went door to door to door to door to door.
• The banks didn’t buy it.
• They didn’t buy it.

Capital One’s Growth and Strategy Evolution

• And then finally, there was a bank in Virginia, Signet Bank, that said, "Fine, we'll let you run it.
• You can come join.
• We’ll give you this group and some resources to go build this."
• So, they built this as this division inside of it.
• And it started to work.
• As this was going on, the computer revolution was taking off and it was sort of an unfortunate acronym, but they called it IBS.
• Irritable something something.
• No, it’s Information-Based Strategy.
• And they said, “We could use different pockets of data and run these.”
• It was before there was big data, there was this kind of data of we could go and test.
• You know, maybe this person has a balance of $8,000 at this bank.
• We could send them an offer at this interest rate or this kind of, you don’t need to pay back interest for six months or 12 months.
• And they could start to go and see the mathematical return against this.
• And this division started really working and it got so profitable it became a problem for the business and they convinced them to spin it out.
• And so, in 1994, that is the founding as people know Capital One today.
• But it actually was, I think, almost a decade in building to actually go and do this.
• I think that there was a lot that they got really right.
• One, I think that they took much more of a first-principles view of the business.
• Whereas others said, “This is a profitable product.
• I’m going to do it like the other person and use scale and distribution advantages.”
• They said, "Well, let's think about the product nature itself."
• There’s different, everyone’s making money on interchange.
• Maybe there’s lending could work and you could kind of have different strategies for different types of populations.
• They did this so large where I think at one point they were the largest customer of the US Postal Service.
• They would send out so many offers, I think until Amazon took them over.
• There was a period of time that they did this.
• So, it’s incredibly experimental.
• They kind of carved the path and showed how do you go from credit facilities for fintech founders, eventually maybe you become a bank or buy a bank and carve that path.
• So, there’s some tactical lessons.
• I also think they’ve done a great job of building a great and durable brand.
• One of the things that Capital One has done very, very well, I think, has focused on like, what is the consistent visual message?
• What is the aesthetic and how do you stand out in this busy and different world?
• And so, there’s a lot of pieces to what’s made that company work, but— And they’ve also remained focused, which a lot of banks haven’t.
• I would say so.
• Well, I think that is a rewrite of history.
• They were doing like cell-phone financing, healthcare financing.
• They were a part of this thing.
• They have come back to focus after wandering in the woods.
• They had some JV, it was like America One, I think it was called, to compete with Amazon.
• They were actually the most experimental business ever in a lot of ways.
• In, I think it was Hibernia Bank in Louisiana.
• And this was after Hurricane Katrina.
• I think it was maybe during it or just after they were able to buy.
• And it was like, it was an existential question for them.
• And I think that many people worried about, you knew this like, well, too from the BNPL businesses where if you’re kind of a lending-based business, and it’s fine when interest rates are low, but if there’s a crisis and people don’t want to lend to you, it can just break your business.
• And so they had these kind of scares, and they said, “We need a stable kind of cost base.”
• Eventually, they bought a bank, which was, in a lot of ways, very good.
• They had, kind of, the deposits as this durable, stable, low-cost or consistent capital base.
• But the flip side of buying it was they had to reconcile their culture of like, crazy experimentation of trying everything, to, “We’re a regulated bank now.
• We’ve got to be bank people.”
• And it’s more than just an attitude thing.
• If you are a nationally chartered bank, it’s real strictures, yeah.
• You know, look, it’s to a level of, let’s say, the bank fails on Monday night.
• There is personnel.
• These guys in windbreakers in your office the next day.
• And they’ve probably been working there for some time before.
• You know, and so it’s… I think there was a change.
• In some sense, there is experimentation, I think, within certain constraints, would be how I would describe the Capital One post-buying a bank versus before, would be my read of it.
• But when you look at them in the ’90s and 2000s, it was like them, and in some ways, like, name the high-flying tech company.

Talent Pool and Hiring Philosophy

• They were right up there in terms of share price growth.
• They started re-achieving it, I think, in the late 2010s.
• But it’s a fascinating company.
• I mean, I think the talent pool.
• So at Affirm, our first, like, really good risk person, but this is true for every fintech company.
• It’s just like, “Actually, this is kind of cool.”
• Billy Alvarado, our first COO, grew up at Capital One.
• I had played the piano, and my teacher was taught by somebody who was taught by somebody.
• There was actually a chart.
• You can look this up.
• Czerny and Beethoven taught everybody who ever taught anybody.
• So like Lang Lang or Yuja Wang, like, pick any famous pianist today.
• They can always trace their lineage 100% of the time to Czerny, Carl Czerny or Beethoven.
• Capital One is like the Czerny.
• Our Head of Risk, Srinath Srinivasan, he's amazing, came from Capital.
• We had the same boss 10 years apart, actually, in some sense.
• And all the heads of risk for all modern fintechs came from Capital One.
• Well, because it’s one of these things where you know that you don’t want to just hire for intercept, you want to hire for slope.
• And this is the problem.
• It’s like, you find, not to pick on Bank of America or Chase or somebody, but it’s like, “All right, this person clearly knows how to do their job.
• The bank that they work in is worth a lot of money.”
• But they don’t necessarily have, how do I put this delicately, the slope.
• They won’t know what that means because they don’t know what slope means.
• But seriously, the guy that we hired, just so… He was very, very smart.
• And that was the key thing about Capital One, is that they didn't hire banking people, they just hired smart people.
• And it became known as the place where smart people went.
• And actually, the fact that companies would poach people from Capital One actually added to the allure.
• It’s like, “I want to work at McKinsey because at the end of McKinsey, I’m going to get a better job somewhere else.”
• Capital One job market.
• Capital One actually had, it did have that imprimatur.
• And I think part of it is it’s the only founder-led institution.

Future of Business Treasury and Banking

• Last question, Eric.
• We’re talking about banking here.
• You have a treasury product.
• In five years, where do businesses keep their money?
• Is it with, I mean, statistically mostly, you mentioned 2% on Ramp, it’s even higher today in traditional banks like a Chase or a Bank of America?
• There’s also neobanks, you know, I mean, kind of bank-like entities like Mercury or Revolut or Monzo or things like that.
• There are companies like Ramp where you started in spend cards, but maybe moving more into treasury.
• How do you think that shakes out as a market?
• So, as a macro point, I think there is an incredible amount of money made by institutions who are enjoying the profit pool and sharing very little with their end customers.
• You know, if you think about the implications of like the federal overnight funds rate.
• This is basically saying, hey, if you want to go and— Just it’s insane that there’s so little yield sharing in the current market.
• I think that the national average for businesses, right, these are sophisticated entities with personnel.
• They’re supposed to be able to manage and put their funds in some place that’s more high yield.
• I think the national average on checking accounts is 0.07% in the US.
• And so I’m guessing you don’t believe that Bank of America and JP Morgan and all these folks will wake up more altruistic one day.
• And so, what is the competitive process by which you think we’ll get there?
• I think that new businesses, whether it’s they have their own charter or they work with banks too that, this is not a monopoly.
• Like they have, everyone has competitors and it is a market that evolves.
• I think that that rate will go up, that the easier it is for people to, whether it's to create depository institutions, create accounts at these institutions, or create stores of value maybe even outside of these systems, maybe in a stable currency.
• And so, I think that rate goes up.
• I think part of what’s driven the extremely rapid growth of Ramp Treasury is it’s just a vastly better deal for customers.
• Maybe you keep three months of just walking around money in your checking account, but if you know the funds you’re going to receive and what you’re paying out, well, we can move funds on the day payroll is coming due into that account and then every other day make sure the funds are earning the highest rate possible.
• And so, I think from a macro perspective, these things tend to go up in terms of the relative yield.
• I think there’s another question of slack in the system.
• If you have more and more…
• Money can think, right?
• If the dollars in your company have some level of intelligence like it’s able to kind of determine when can it be spent, under what circumstances?
• It’s increasingly recorded in real time and there’s some reasoning around this, some ability to kind of opine of where should the next marginal dollar go?
• And you have systems that are able to think infinitely about these things even at 3:00 AM in the morning when most of your team is asleep.
• Well, once you determine, like maybe you’ll determine I should keep the funds in some level in like a 2% or a 4% yielding account.
• But I think more of those dollars will go in flight actually to go spend to, if you have a business that makes an 8% profit margin a year, that's a lot higher than what you can earn in the overnight rate.
• And so in some sense, I think you have the dual effect.
• Smarter capital allocation.
• I think more dollars will be put to work.
• I agree with Alex's macro point of if you kind of understand counterparties, you understand more information.
• I think that one, the cost of financing should go down and I think more dollars should be in the system in some sense.
• It’s actually a waste for everyone to have your dollars just sitting in a bank account.
• Who does that benefit?
• But it goes back to your time point.
• And it’s like the reason why I got mad at Chase a while ago, and I still have a Chase account.
• And like why is that?
• It’s like I have a life insurance policy.
• I don’t remember the login for it.
• It’s just too much work.
• I wrote, this is a true story.
• Isn’t this an issue if you die?
• Yeah, I mean.
• Well, but they’ll pay my wife.
• I just don’t know how to log in and change the bank account.
• So, they’ll send her a nice letter I’m sure, some flowers.
• But, you know, why…
• Well actually, this is a true story.
• I wrote a check for somebody’s bar mitzvah.
• Mazel tov.
• Has not been deposited.
• Do I want to be the schmuck who has the bounced check?
• No, I don’t.
• So it’s like I have to— This kid is keeping you at Chase.
• Well, great to see you.
• You too.
• Eric, thank you.
• Thanks for the Guinness.
• It was a great time.