S14E4: Why Usage-Based Billing Is Inevitable with Metronome Co-Founder Scott Woody

Everyone admitted it was a huge problem. Everyone thought it was an unsolvable problem. Everyone knew it was hard, but they're like, yeah, it's so hard that you can't actually solve it as an external party. You have to build it yourself. What we decided we needed to do was go super narrow to find a version of the problem that was so hard and so gnarly that no one would even pretend to try to solve it. And that was usage billing.

Welcome back to The Room Podcast Season 14. Hi, Mads.

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Perkins Coie supports the most innovative entrepreneurs and investors in fast-moving and high-growth sectors, addressing their myriad of legal needs. But the firm doesn't just provide end-to-end legal and business counseling to its startup clients. It also facilitates introductions to key advisors and sources of capital. Perkins Coie's interactive website, Startup Percolator offers access to programs, resources, and rich dynamic content designed to assist entrepreneurs on their startup journey. To learn more, go to startuppercolator.com and perkinscoie.com. On today's episode of The Room Podcast, we sit down with Scott Woody, the co-founder and CEO of Metronome. Growing up in Bishop, California, a town of 3,000 people and 6 hours from every airport, Scott taught himself to code in the library before anyone around him cared about computers. That self-reliance became the engine behind everything that had followed. A startup that ultimately was acquired by Dropbox, then 6 years leading modernization engineering at one of the then Valley's hottest companies, and ultimately an insight that would define his next decade. At Dropbox, Scott watched billing be the long pole in every product launch. He left convinced that fixing it at the foundational level could unlock something much bigger. The ability for software companies to price to actual value and simply move faster. That conviction became Metronome, which grew to serve OpenAI, Anthropic, NVIDIA, and Databricks, just to name a few, raising over $120 million from Andreessen Horowitz, NEA, and General Catalyst. Ultimately, it was acquired just 3 months ago by Stripe for a reported billion dollars. 3 key insights and themes we we explore in this episode are betting on second-order effects, not just the obvious wave, the importance of pricing to value, and the relationships that can feel optional with calls with competitors and ecosystem partners that often end up being where the most important outcomes are built. In an era where usage-based billing is at the forefront of every leader's minds, this conversation is a critical one. Let's open the door. Scott, thank you so much for joining us today here in the room.

Thanks for having me. I'm very excited.

Where did you grow up and how has that shaped your view of the world?

I grew up in the 3-mile border of Nevada, basically on the California-Nevada border. So I grew up in California, but if you've heard of the Eastern Sierra, I'm from a town called Bishop, which is known for bouldering and skiing and fishing. And so I grew up in like a town of about 3,000 people in the middle of rural California, 6 hours from every airport. It meant that if you were like technic— technical or math focused. It was very weird to be there because you're alone on an island. And I also grew up before the internet had broad penetration. I was the kid who was just like lived in the library, spent all my time there. And then because the libraries eventually had computers, got into computers way before it made any sense and became an autodidact, which I think has been like a pretty constant theme in my life, which is just like, how do you learn as much as you can with the information you have at your fingertips? And how do you use that to learn at the maximum possible rate? So that was a big part of it. And then also just every entrepreneur needs some kind a chip on their shoulder. And so definitely being a nerd in a very small town fits the bill for me.

An East Californian who had no access to Starlink because there was no Starlink at the time. I resonate with the nerd allegations. I would often bring my latest book to recess and would be reading that on the wood chips. That totally did not make me a ton of friends, but I did learn a lot, to your point. In that vein of early identity, I'm curious if you always thought you would become a founder.

I was very convinced I wanted to become a professor. I think my dad is a professor of physics, so very familial, I guess. But I quickly realized I was too impatient or not smart enough. I still can't tell which. I was like good at school. I was bad at research. And even though I went to school and did really well, we would come to the research lab and I would just sit there and I would just be bored to tears. And then I was at Stanford at the time and I realized actually there's something that's more interesting here. It's like the startup thing. Everyone is starting companies everywhere around me. and that started to pull on my curiosity, and I started to lean into that curiosity and like where I was getting excited, and I was definitively not in grad school.

The waters in which we wade often do inform what is our version of success, and definitely going to Stanford would have brought this idea of being a founder to the forefront. And of course, you've had a really exciting year with your current startup Metronome, which was acquired by Stripe. We're gonna get to that later. That was not your first startup. You started something called Foundry Hiring. Tell us a little bit about that startup and what you learned from it.

I didn't like the idea of my parents paying for school. It wasn't that they— we didn't have money or whatever. They were middle class. It was fine. But I was just like, I want to pay for myself. I looked for jobs, and one of the jobs I found was advertising, paying like $60 an hour, which at the time was 7 times minimum wage or something like that. And I was like, what is this job? And it was essentially being a headhunter for a hedge fund. What you did is you basically like talent scout your entire university. This is at Berkeley. And find the list of the top 100 best people in every department. You interview them. Think of it like you're a mole on the inside as an undergrad mapping the market of Berkeley talent and then feeding it to the hedge fund. And then they would try to recruit them. Flash forward 4 years, I'm in grad school and I'm like, I need to get out of grad school. This isn't for me. I need to start a company. That's the only way to get out. And I was like, what problem have I personally had? And the problem I had was when I was a talent scout, the CRM problem, which is, you know, the applicant tracking system problem in recruiting, was really a huge pain in the butt. And I'm like, what would you do if you built an applicant tracking system that much more data-focused, analytic-focused, that actually helped you try to hire faster. And so that was what Foundry was about, was exploring that space. And today there's companies like Greenhouse or whatever. Those companies hadn't been started. All of the companies that are like the kind of current leaders in talent management were all started within a 3-month period of when I started Foundry. In fact, I met those founders very early and almost merged with them. But the idea was leaning into something I knew, which was How do you find talent? How do you source them? How do you make them successful? And then tried to apply it to the real world. Now, I'd never worked in a company, so I had no idea what an ATS was or anything like that. First principled my way to an ATS. It was an awful idea, totally terrible. And then eventually we got an acquisition offer from Dropbox and that's how that journey ended. But yeah, that first startup was like born of a desperation to leave grad school and then, okay, you should build something that you understand at least somewhat. And so that was how I random walked my way into that idea.

First pancakes are powerful tools for learning, and certainly landing at Dropbox was not a bad place to end up at the time. You spent 6 years from there leading engineering groups at Dropbox. Tell us just a little bit more about that time. That was an incredibly hot startup in the space, ultimately went public itself. Really curious just to hear about some of the insights you gleaned from working in those waters.

At the time, we had acquisition offers from Dropbox and Palantir, which was like pretty, pretty good. Of those though, I think Palantir was where my heart was and Dropbox was where my wallet was. In retrospect, not true, not correct.

Claudia, unfamiliar sounding?

Dropbox, aside from like Uber and Airbnb, it was like those were the 3 hottest companies in the Valley at that point in time. I felt like when they made an offer to us, I was like, you guys realize I'm an idiot. What are you doing? I literally walked in every day and I felt like grateful that I somehow tricked my way into that company. And in retrospect, I think what they saw was essentially what I would call founder energy, which is just this like irrational belief that you can go move the system. The system isn't going to move you. And then also just like a raw creativity applied to, in this case, it was like what I had done at Foundry, just that initiative and that kind of raw energy, I think was just super rare, even at Dropbox. And so they're looking for that, I'll call it like really talented folks or people they believe were really talented and they didn't really care about pedigree, like at all. While I was there, I kind of had a very simple algorithm for what I did, which was find the most important problem and work on it. And what I realized was that in a large company, there's a lot of important problems that already have a bunch of people working on them. And then if you look hard enough, there are probably problems that are really important that no one wants to work on for whatever reason. Maybe it's just like unsexy or maybe it's just really hard. And so I just found my way to what we called at the time monetization, which was the team that was responsible for making money at Dropbox because it was a self-serve PLG type motion. And so it was like an engineering product team whose job was to say, own the first 30 days of user experience and get those users from, I don't know anything about Dropbox, to I'm paying money to Dropbox. And if you remember that period of time, making money for these companies was kind of like lame. It was like, well, who cares? Like, just let's grow. And I was like, the only reason a business exists is to make money. Not to be crass about it, but like, that is what defines a business, right? I was like flabbergasted because they offered the job to like 15 people before me and they eventually offered me that and everyone said no. And I was like, Okay. Yeah, of course I'm going to go do this. And that was one of the best business decisions I've ever made in my life. I just went and that team went from 2 people to 70 in 2 years. My product partner on that team is now the CBO at OpenAI. It collected elite talent and I just got to be front row center to a business line that went from $200 million to $1.3 billion in 3 years. I got to be the engineering backbone of that thing. And so, you know, was it sexy? Was it cool technologically? No, but was it super impactful to the business? Yes. And therefore, was it good for my career? Yes. So it was great.

You pulled that thread of monetization with your next gig. So soon after Dropbox, you started Metronome, really to power usage-based billing at a time when most companies were still defaulting to subscriptions. Tell us a little bit more about the core insight that made you believe usage-based billing would become inevitable, especially before the AI boom, and what made you so excited to start a business in the space.

When I left Dropbox, the thing I knew was that billing systems are completely busted. Like, they're just awful. Like, it was the long pole for every product launch at Dropbox was getting billing right and getting monetization right. And so I knew something was like deeply wrong with that part of the world. But I also knew that there were companies like Recurly and there are companies like, um, Zora and big companies, and they hadn't really taken off in tech. And so there was something confusing to me. I was like, why? This is a problem. Dropbox has 70 people working on it. It's horrible. Like, why hasn't any vendor come in? The thing I knew was that doing monetization billing right was a really hard problem, both technically and from a product perspective and from a distribution problem perspective. Everyone admitted it was a huge problem. Everyone thought it was an unsolvable problem. Everyone knew it was hard, but they're like, yeah, it's so hard that you can't actually solve it as an external party. You have to build it yourself. What we decided we needed to do was go super narrow. To find a version of the problem that was so hard and so gnarly that no one would even pretend to try to solve it. And that was usage billing. And so early on met up with Confluent, which is now a customer of ours, 2 or 3 that had usage billing and they were all like, this is the worst. You have to do this really hard data management problem. You essentially have to invent Datadog and do the billing system. And if you could solve it, it would be something we would pay real money for. And so it was like, Yes, there's a general pain of billing, but there's this acute pain and these people are literally staffing huge teams to go solve this and they're generating inaccurate bills. Like you can find these articles of Twilio having to restate earnings because they misbilled customers because their usage tracking system wasn't correct. It was so catastrophic. And so we needed an acute pain because trusting a 3-person startup to do your billing is like fundamentally an irrational thing. Like no company should ever make that decision. And so we needed to work on a space that was so hard and so gnarly that they had no choice. That was That's what led us to the usage billing flavor of things. And then obviously usage took off. For me as an engineer, from first principles, that made sense is like, if you read pricing theory, everyone is like, do not price on costs, do not price flat fee, it's just terrible. Price to value, like that is the best kind of pricing. It's like the Platonic ideal of pricing. And yet all of software was priced on seats, which did not correlate with value at all. And so there's this like fundamental received wisdom from thousands of years of pricing is price to value, and yet no one is doing it. Maybe it's a technology problem and maybe it's a maturity problem and maybe it's a problem that we can go help solve. And so from first principles, usage billing, outcome billing, all that stuff was the most obvious business model and yet no one was doing it. And so I had to dig in and say, why is this? Can we help accelerate that trend? And then I think AI has kind of made this inevitable. And that's why everyone's doing it today, including Forcel.

What surprised you most about how customers actually wanted to use Metronome once you were live and they were onboarded to the product?

If you do billing right, it should enable other parts of the business to move faster. That was like my initial insight, because I didn't own the billing system at Dropbox. I was a consumer of it. And I was like, oh God, we could move so much faster if this billing system actually worked. One of the things that's been most surprising was how true that has been. If you remove billing as the long pole, then suddenly the data in the billing system is very useful to the rest of the company. But if it's the long pole, it means the data is always lagging and always really hard to get access to. And so if you are a sales rep and you're selling dollar-based commits, like I'm going to spend $5,000 this year, as a sales rep, you are essentially selling a contract that says, give me $5,000 upfront, maybe pay quarterly, whatever, and you're going to get credits that get to burn down. Now, if you have a system like Metronome, what you can do is you can watch that customer use your product in real time and you can catch them when they have that weekend where someone just goes crazy and builds this cool integration that consumes all their credits. And you can have that conversation on Monday and be like, yo, like, what's going on? Are you finding value in this product? You can find product market fit really fast. If you don't use Metronome, if you build it yourself or you do it async, what you do is you discover that use case like 30 to 60 days after it already happened, maybe 6 months after it already happened. And so what it does is it means the cycle time of iteration on product market fit is always slower. And so one of the most surprising things has been by actually making this data available to companies, they just use it in a lot of places. We sell to like some of the large labs and some of the large labs, they'll have 50 different teams looking at Metronome data on a weekly basis. And that was the theory of the business from day one. It just turns out that there's like the first time where I'm like, oh, the theory actually tracked with reality. And in fact, it taught me the feeling of what market pull is because instead of trying to build things and hoping people care, it's more like they're like ripping the data out of you and they're like, give me this data faster, lower latency. How do you give me more? How do I use this data for running sales or for fixing margin or all this stuff. And so that's been the most surprising thing is like how true the theory is to the actual product experience. And so now our job is running as hard as we can to keep up with the demands. And it's like, honestly, product at Metronome is one of the more, not boring things, but it's the most straightforward things because you're just like, customers want to give you money for these things. And it's like uncreative is maybe the best way to put it. It's like you just have to choose which of these many things that customers want do you actually go build?

It really resonates when you say like the ability to rip out data is a thing that customers are demanding. Like I remember one of my first 2 AM phone calls on a weekend from one of our customers was that our like dashboard was lagging, the data export button wasn't working. That was a whole thing, but a good sign that people actually care. And so that leads me to the labs getting really excited. Metronome attracted customers like OpenAI, Anthropic, NVIDIA, Databricks very early on, and they have incredibly complex usage patterns. Tell us, who was the first customer that truly validated you were onto something big?

There was a constellation of customers that came online within the same 2-month period. I think in retrospect, that was the product-market fit signal. It took us like a year to realize it, but it was like in retrospect. So it was Cribble, this company called Cockroach Labs, which is a database company based in New York, and then dbt. All 3 of them bought without it was like a 4-week sales cycle in a product that didn't even exist. We showed them like a working API call. I was like, oh wow. And they all bought like instantly. And again, we were like not even— we were pre-Series A. It took us a long time to fulfill the value prop, get them live, and then also prove that it was working. But like in retrospect, I think a smarter or maybe a better entrepreneur, more tuned to this stuff, would have been like, that was product-market fit. That was the point where you should have gone fucking all in. And instead We were very slow to invest. By the time we were acquired, we still hadn't spent any of our Series B money. And that was because we've been relatively slow to invest, I think, because we were very worried about getting ahead of our skis on any of our, like, headcount. And that was the moment where, in retrospect, I'm like, God, I wish we had just thrown fuel on the fire. And this was like 3 or 4 years ago at this point.

I mean, it's a tricky balance. Like, it was the 2021 people were lighting cash on fire pullback where everyone said, okay, wait, actually we need you need to have a business plan, to your point earlier about making revenue. And so a lot of startups like yourself who had obviously had amazing traction and found product-market fit kind of getting told different narratives around when and how and where to invest VC dollars.

We were just inherently very conservative. That's why we picked billing in part, because if you choose a billing vendor, you want them to be there next year and 3 years and 5 years from now, right? Conservative is actually like a good thing, right? Is if you're building a bank, you probably want someone who's fairly conservative, not some super yolo risk taker. Our nature was to build for the long term and that kind of aligned to customer values. And yet, if we had been more aggressive, I think we would have grown faster and created more market momentum. I am like not complaining, of course, but it was one of those situations where you look back and you're like, actually, the market was telling me something. I just was a little too in my own head to see it. Yeah.

Yeah, you did go on to raise an incredible amount of venture dollars from tier 1 investors, over $120 million from NEA, Andreessen, General Catalyst, incredible names. On the side of the capital providers, who was the first person to say yes to investing in you and believing in Metronome?

All 3 of our major institutionals kind of have different versions of a similar story. So in 2019, when we were raising money, again, billing was a toxic category. Literally the number of people who were just like, like, do not do this. This is the worst idea. This is not a real business. There's no business here. Stop. It was just like ridiculous. We were second-time founders, had done this before, had a pretty good track record at Dropbox. By most measures, should have been able to easily raise money. And ultimately, the only person who would give us money was the former CTO of Dropbox, Quentin, over at General Catalyst. He had just moved there. He hadn't even moved yet. He was still a CTO of Dropbox, but he wrote his first check into Metronome. Told him all his own crew, like, gotta take a bet. We were his literal first check in GC. It turned out well for him. He was the first person to believe. He was just like, I don't know about the space, the first principles make sense, but I trust Scott and Kevin, you guys can get this done. And he bet big. He also been the CTO at SAP, so he had seen the kind of ERP part of the equation and had a fundamental belief that if you do this billing stuff really well, you'd be able to eat value away from the ERP, which I strongly believe in. And so he had a really strong conviction. And then the second person I would call out is Martin over at Andreessen, who led our A. What he saw was signs of product-market fit. And then secondarily, he's a big infrastructure guy. Now he's a big AI guy, and he just saw every single infrastructure as a service company was going to become usage-based. And so by the time we came along, he'd been of a prepared mind for about a year. He was the second person who was like, took a major swing. I think they invested really early and went really hard. And can't see.

That's a powerful investor who is actually backing your customers, is not necessarily a classical fintech guy, if you will, and sees value in how business models are shifting and the need of the actual financial infrastructure, if you will, to create and empower this AI wave of usage-based billing.

He's incredibly smart, and when he sees a trend, That's hard.

We're about to chat a little bit more about some of the lessons as you've scaled Metronome and also the lessons through the acquisition. But before we get there, we know founder journeys are never linear. Things don't always go as planned. So Scott, maybe tell us about a time where something just went completely wrong and what advice you would have for founders that are maybe feeling stuck currently as they're building. At my startup, Pryve, Rippling helped us avoid a lot of the operational drag that comes with scaling a team. With most tools, something as simple as onboarding a new hire involves multiple systems, payroll apps, hardware, and it can take weeks, quite frankly. With Rippling, those workflows happen automatically in one place. That means fewer distractions and more time focused on building. Over 15,000 startups rely on Rippling to scale fast without adding additional ops and HR headcount. So if you or your startup wanna move as quickly as you can and focus on what really matters, like your product and your customers, you need Rippling. Right now, venture-backed startups can get 6 months of Rippling's startup stack for free. Head to rippling.com/theroom and sign up today. That's R-I-P-P-L-I-N-G.com/T-H-E-R-O-O-M to sign up for 6 months free today. Focus on what you're building, leave the rest to Rippling. rippling.com/theroom.

In the early days, we knew we wanted to work in billing and we thought usage was gonna be the initial wedge, but we were like very early to that market. So it was actually really hard to find companies that had that business model. What it meant was that you would talk to companies and you'd hear things like, yeah, we want to move to that. When we move from on-prem to cloud, how the hell is that going to happen? And it was different than this isn't an interesting idea. This is a second order problem. The bigger problem is we need to launch our new cloud-based product or something like that. Let's say you're moving from on-prem to cloud, you need usage billing. In the on-prem era, you don't. It's like you're selling flat fees. It does not— you don't need anything that Metro provides. And then as soon as you move into that new world, you're going to need this infrastructure. And they all intellectually knew it. They were just all in the middle of building their cloud offering. So it was kind of presented this like existential question where you're like, do we believe that they're actually going to come to the cloud? Do we believe in this long-term trend? It was very stressful because you're like, I know there's a wave coming. I can feel it. But it's not here yet, and I'm just early. Do we believe that the cloud is coming? By first principles, the answer is obviously yes. And if you believe that, then infrastructure SaaS would adopt usage-based pricing. That was a second-order consequence of this first-order belief. But the reason it was stressful is because the data was not available to you in the market yet. And yet the first principles chain was, if cloud is real, then usage billing is real. It's super obvious, but you had to make a structured bet. And so we had this like very real talk conversation. Where we're like, we have to pick a bet and how much do we believe in this cloud thing? If we believe cloud is real, then usage billing has to be real and therefore we have to bet now and be ahead of it. And it was like going to that level of atomic, just like first principles thinking and then just saying, okay, and then let's just be out here long enough for the wave to break. And so that's why we ran on a very low burn mode. Like we were like cash flow positive actually very early in the business. We wanted to wait for this wave to break. We just didn't know if it was going to be this year or next year or 5 years from now. The advice I would give to folks is find your convictions. If you're not making a strong bet on something speculative, then probably your idea is obvious or it's really bad, one of the two. But like, if this is true, then this thing is true. I think of it like a second-order effect of a major wave. The way I now think about it when I'm advising folks is there's like a big wave that's coming. Let's say in this case AI. What is a second-order effect of if AI is real, then Training data matters more than anything. That's why Scale is like a good business to invest in. Find your obvious first-order effect and then do the non-obvious second-order if this, then that logic chain, and then bet on that second thing because AI is obviously here. So like figure out ahead of whenever that is, what is the next wave that is coming? Maybe it's agents or something like, I'm going to build a business that only works if agents are real, but if agents are real, then they're definitely going to need Molt book or whatever it is, you know what I mean? Like I'm making a joke, but that kind of logic, reducing it to that way actually helped. And then we said, look, we're betting on infrastructure as a service. We are betting that this trend is real and we may not be right. If we are wrong, then we're dead, which is the default state. But if we are right, then we will be ahead of the market and we will win. By the way, this also allowed us to find investors who also believed that infrastructure as a service was a real thing. And then they tended to have portfolios that were correlated with customers. And that's how we found Martine. We kind of put on our venture investor theory hat and then just bet hard on a thing.

That's a really helpful framework for thinking through living in the future, but building a company in the now. One of my favorite analogies of this right now, that's totally unrelated, but just as you were talking, made me think of is this whole Ozempic second order effects for infrastructure in our society. The one that is a meme of sorts is the reduce in airplane gas, because if the planes weigh less, that means less carbon emissions. What else does this mean about how we build planes. And an insane kind of absurdity example, if you will, for the sake of argument, which is to say things change when these factors happen and there will be businesses to be built as a result.

Well, I exactly— actually using that exact same thing, I think you can predict the rise of non-alcoholic drinks because Ozempic suppresses all those kind of hedonistic tendencies. And alcohol, they look for like ways of having fun while out without having a ton of calories, and therefore non-alcoholic drinks. As someone who been on GLP-1s, I know, like, I know this viscerally. I am very much a fan of the efficient markets. You have to take risk. If you don't take risk, how are you going to grow?

Good little Easter egg on the non-alcoholic beverages for a future guest, the Recess founder we're having on this season. And we've had others like DeSoir, which is Katy Perry's non-alcoholic brand. So we love that space too. We have a range of conversations and guests. They often overlap. I think also you're getting to the heart of the evolution of the end user experience with billing itself. Previously, perhaps one would not think about their software usage relative to billing if you just are paying these flat fees, team-based pricing, et cetera. But as you're becoming more embedded into the workflows of the end buyer and user of software, people are becoming more familiar with their spend relative to their usage. The token— I don't even know what to call it— the token phenomenon, or like the rise of tokens as the way we think about our workflows with AI. AI has of course really impacted this. So this has bred a really complex ecosystem of trust, predictability, and ultimately like customer anxiety. So I'm curious about how you thought ultimately with the end Metronome user, thinking through your relationship with them and how you thought about building out a holistic product experience.

I think you're exactly hitting on like a second order effect of a second order effect. So if usage billing is real, it literally cuts against one of the fundamental human psychological problems. Why hasn't usage billing? It's like value-aligned. Why hasn't it ever taken off before? And the answer is that in its purest sense, usage billing forces consumers to make continuous decisions, which if you study consumer buying behavior, you do not want to overwhelm a consumer with decisions. The more decisions you make them make, they just will make fewer decisions. They just won't do it. It causes stress. It's painful. I'm sure you've had this experience. The main problem with usage billing as a concept is that if the pricing is too front of mind, as you're going into ChatGPT, you're like, should I send this query? Is it worth the 0.2 cents? It forces this kind of continuous decision-making apparatus. And so that was the meme, and that was why subscriptions took off, because you make one decision once, and then you just use the product, and it's great, and everyone's happy. The thing that we realized, though, was that while consumers don't like making a decision, they will make decisions and they will choose usage billing if you can give them what we call tools for visibility and control. And the way we learned this, we spent time with our friends over at OpenAI and they built this feature that allows you to sign up and create a new project and then put a budget around it. Like essentially say, I don't want to spend more than $100 on this project. And what this did was it turned this fundamental uncertainty of how much am I going to spend into a like definite certainty. I'm never going to spend more than this amount. And so what you've what you've done is you've given the customers enough control over how they're spending money that it actually is empowering to them and it actually makes AI accessible. And what it does is it makes them hate usage billing less. Now, it doesn't mean that it's not harder than a subscription. It is, but it meets the user need for control and visibility, which allows the technology to be taken up in a way that otherwise it would never have been. So that exact same company without a budget tool, what it's gonna find is that customers are just gonna be constantly complaining about accidentally overspending, and they're gonna be really mad at you, and your NPS is gonna suffer. That same company with a budget tool, now the CFO loves you, now the teams love you. It gets to these like completely different product behaviors that you otherwise wouldn't have. And so by studying the problem from first principles, you actually get to a different place. And so that's why we've invested so much in real-time budget tools, visibility, and control. What we realized was if you do that well enough, consumers will actually embrace like a continuous spend mindset and they will embrace a much more usage-based paradigm. And yes, subscriptions are easier to understand and therefore better, but the truth is you have to have a usage model with these AI products because the fundamental cost is a factor in your ability to run a business going forward. And so that was our realization, was just like studying the customer and And then taking this kind of fundamental assumption, which is everything needs to be flat fee or subscription, and questioning it, and then say, what would need to be true in order for consumers to be okay with token spending or something like that? And that's where this budget tools and this visibility and control comes from. Consumers have been doing usage-based pricing forever. Telecom, cell phones, all this stuff. And actually, if you study the history of cell phones, there's times where pay-as-you-go is the dominant business model, and there are times where family plans and all-you-can-eat are the dominant business model. And if you study that in some depth, you realize that especially for this weird esoteric business model that is now becoming de rigueur, you can kind of learn from the history of what happened and why those trends happened and connect it back to what does the consumer actually want. We're all very used to consumption-based pricing. Like you could argue credit cards are consumption-based pricing. Every time you buy something, you swipe a credit card and you get charged a fee. And what makes those successful? Why do subscriptions exist in a world where most people are familiar with credit cards? Cards. By studying these things as like an intellectual thing, you get to very interesting product spaces that kind of like, oh, okay, well, what if you built software that made it so that a consumer could consume all the tokens they want and never run into the error case of accidentally spending $10,000 over a weekend on OpenAI?

So important constraints to have in this generation of building product and selling product. Metronome was recently acquired by Stripe for a reported billion dollars. Stripe was already building billing products, but clearly saw something so differentiated in what you built even after its team acquisition of Octane. What made this partnership feel like the right next chapter rather than continuing independently?

It's all about how do we build as quickly as possible to the end state? Why are we building billing software? Not because I love billing, even though it's fine, but what I love is I love helping businesses grow at maximum possible rate. That's exciting. How do you build tools that help you price and package? How do you build tools that make a great user experience inevitable, not like something you have to go spend hundreds of engineers to go build? I believe fundamentally, if you build the right infrastructure around monetization, you allow companies like a Vercel or an OpenAI to build really great products around the monetization information and the monetization engine. That was the idea of what we were trying to do. Now you have to start by doing billing, like billing Billing is a necessary step. If you don't do billing, you don't earn the right to help companies grow faster. But billing is the starting point, not the endpoint. And so we had a working billing system, but what we don't have is we don't yet have a machine learning model that is helping you price better. We don't yet have all this pricing recommendation stuff. We don't yet have a BI tool built into Metro. We have to like work with third parties to provide that. And so by working with Stripe, what we realized is like actually their ambition is the same as ours. Like literally their mission broadly is grow the GDP of the internet. And I'm like, yeah, I just want to do that by making it frictionless and easy for software businesses to deploy whatever pricing model they want in seconds and then build a great product experiences around that. And that completely fit within their larger mission, but also represented kind of a few steps ahead of where they currently were. And so that was what gave me the excitement was like, actually this company and our mission is exactly the same. We're approaching it from a billing-centric point of view. They're approaching it from a payment-centric point of view. What if you combine these two entities and you just went and did the whole thing? And then we also just had this really strong belief that if we did this, we could provide a lot more software, a lot cheaper for every single company on earth. The way I like to analogize it, it's like you're playing the game Chutes and Ladders and someone gives you a ladder to the last row. Do you climb the ladder? I'm like, fuck yes, I climb the ladder. Like, I want to get there as fast as I possibly can. And I want to make sure that consumers get the maximum value. To do. And broadly, I just looked at it like, this shortens our time to end state by like 10 years. What would I do for that? I would do anything for that. And I think our customers would agree, like, it's a much better together story than it is keeping us apart. And also, we were one of their top customers as well. Almost all of our largest customers use both of us already. And so it was like this, like, really great, like, synergistic partnership already. And so it just made perfect technical sense too.

This acquisition certainly is like a textbook example of like a strategic, mission-aligned find merging that is better for the mission and vision, but also the customers, a very great ladder, so to speak. A lot of founders, especially in this current environment, often come to me and say, how did your acquisition happen? What advice would you have? What can you tell us about how your deal came together? And then what advice you would have for founders that either may be gearing up for M&A or are wanting to plant the seeds for M&A to be an option later on in their journey?

Up until a year ago, I never thought about this. I mean, it's not that I never thought about M&A as a possibility. It was more like I hadn't thought about the question you just asked. How do you build yourself so that you can be acquired is maybe the way to think about it. And I met this CEO of a public company and had his company get taken private. And I was like, what do you wish you had done differently? And his number one advice, he's like, look, the thing I wish I had done more than anything in this 15-year journey was I wish I had spent more time with competitors in the early days. And I was like, that's weird. You spend all this time thinking about like your competitors, the ecosystem as enemies, but the reality is you all are both fighting against irrelevance in a very literal sense. Like most of the market doesn't give a crap about what you do and how you conflict or don't conflict with each other. And you can create this boogeyman image of the people in your ecosystem, but that if you just spend time with them, you'll realize is that there are humans on the other side and that there are potentials for working together. And that if you never take that first call and you don't develop that relationship, you will never have that outcome. It will just never happen. And you will never find that partnership. And so what I realized from that conversation was I just started spending more time in the ecosystem. Up until that point, I'd been entirely focused on our customers and internal stuff. And then his advice was spend 20% of your time with partners competitors. I was like, 20% is insane. I'm never going to do that, but I could probably do 5%, 10%, maybe one day a month. And I started making that change. That's how I met Patrick and Will. They were both surprised because they were like, oh wow, no one ever takes these phone calls. Turns out that's not true, but they were surprised. And I was like, yeah, I don't know. I'm taking this advice very literally. Makes sense. The other thing that I thought about is, and this is just like a startup thing, is that let's say I exchange information with a large company and we both exchange like 10 bytes of information. Information. My leverage on that information is infinitely higher than that large company's. I can get a lot more from a lot more information. My company can move faster. My company has way less sunk costs. And so I was just like, when I have these conversations, I'm going to be like pretty upfront. What's our vision? Where are we going? Why are we going there? Show that I'm like highly competent and highly confident in where I'm going. For founders I would ever want to work with, that would be an appealing thing. You must be lying to us or whatever. Ever. That's not a place I want to work. And so I was basically just like kind of pre-flighting my, here's how I am, here's who I am, do you like this person? If so, then maybe we could have a conversation in a year. More or less, I just encourage folks to take the meetings, be yourself, figure out what you want, and be true to who you are as a person. I met a lot of people that I hated, and then I just stopped talking to them, and I just focused on the ones that I liked.

Scott, that's just like such incredible advice. I'd also love to touch on what life has like post-acquisition and going through the acquisition. You know, it's not only incredibly tiresome from like a due diligence standpoint, but they can also be incredibly emotionally complex for founders. What was the hardest part of letting go of complete independence and also been the most energizing part of this transition?

When you're a founder and you're first starting, what you're saying in the world is you're the lunatic in the woods that's just like yelling, this matters so much. And like, in reality, none of it's true and you just feel kind kind of like a lot of, at least I felt, a lot of self-doubt. Maybe I'm wrong, maybe I'm not. And working at Stripe is the first time where I'm like, actually, there are other people who believe the same things that I believe. And it's this like extreme feeling of like, I would call it like mission alignment or kindred feeling of like, oh, like maybe we are wrong, maybe we are crazy, but at least there's this other 12,000-person company that also believes this, one of the most successful companies in the world. And so that part has been incredibly normalizing and this kind of belief that, like, in myself and what our mission had always been. That part has been by far the most energizing and just like this realization that, oh wow, it's not that we were misfits. I mean, maybe we are, but there's an entire island of misfits and we could have been a part of it. And so I was like a really cool part. And I've just honestly loved everyone that I've met in the journey there. Hardest part, honestly, for me, you spend, in my case, 6 years like building this thing and you build an identity around we metronome. We are gnomes. We are silly. Here's our culture. We are railing against the universe. And yes, we're probably wrong, but maybe we're right and we'll move the world. And so that kind of creates this, I would say, like internal culture that's like super tight and super well-knit. Then you spend months in diligence. You, the CEO, are like mind-melded with the other company. You're like, oh my God, this is the best opportunity in the but you have months to process this change, and then your company finds out about it on a Tuesday, and then they have to sign employment letters in 2 weeks or whatever the timeline is, and they have to go through that entire thing that you got months to spend. And by the way, you spent months with some of the most charismatic, smartest people on the freaking earth. And this company, they have to do it on their own with you as the person who's helping lead them through that. I would say that couple-week period was just incredibly emotionally challenging. People are stressed, people are excited. For some people, this is a generational outcome and it's just great for them. But some people, it's like they joined 3 weeks ago when they thought they were joining a startup and now they're joining a large company and you're having to like migrate all these people through that kind of change. I would say that was just really a lot of emotional energy and you got to keep your business running and you got to actually get the deal done. And so I would say that that point was by far the hardest. And I think in our case, in the end, I think it was a great outcome for everyone. And I think they almost all understand that now, but it took a long time and it took a lot of like very careful management. And I'm not going to pretend like I did it perfectly. I'm sure there's some things I said that were like not the best. And no matter how much you prepare for it, it's like a singular experience. You're bound to make mistakes. And then it's also like, there's some amount of you're losing your old identity. I haven't really experienced that as much, because we are keeping our identity, we're merging with a very similar culture. And so I haven't had that culture shock yet, but it's a lot of emotional weight to bear on you and also the other people that you lean on. And I just think that's been a challenge, but, but one that ultimately we've gotten through.

It's funny how even while you're going through all of it, the deal could just fall through at the very last second. And most people just don't realize that, which is so crazy.

The level of existential stress is incredibly high. MJ, you know it. Until literally the money hits the bank, I was just like, oh God, what's going to happen? What's going to happen? What's going to happen? And yeah.

Tell us a little bit about something you're excited for personally in 2026.

It's very top of mind for me, but Stripe has a large user conference called Sessions in the end of April. And so we're going to participate in that. And I think we're like in the run-up to Sessions. I've never been a part of one of these before, but I think it's like a chance to bring our message to the mainstream in a way that like we've never had. Had. And I'm just incredibly excited about that opportunity and the chance to put our message into the world at a stage that, just say, we've never even had a fraction of that size. And so that's just inherently really cool. And we're going to do it on stage with some of our largest customers, so that's like very awesome for me.

Who is a woman in your professional life who has had a profound impact on you and your career?

First, my wife Amelia. She's worked in tech for a very long time. She gives me incredibly really great humanizing advice about how to balance the stress of being a founder, but also being an executive and how to do that well. And I find that she's a very strong emotional intelligence that sometimes I can be accused of not having. And I think she helps me get to good outcomes and helps me understand times when maybe my psychology doesn't true up with another person's. And I think she's been incredibly helpful on that front and also just my wife. So that's been great. Second would be our board member, Hillary at NEA. She was like head of sales at Salesforce and SAP. She just has been like one of the most amazing sales leaders ever in Silicon Valley and her just super pragmatic advice on how to run and build a scaling sales org. That's not something I'm a technical founder. I've never had to do that. And her advice there has been incredible. And then the third person I'll call out is a woman who now works at OpenAI. Her name is Emma. She is one of the literally smartest people I've ever met. Met in my life. And she chose to work for us at one of her first tech jobs. I'm incredibly grateful for the opportunity to have worked with her, but she just showed me what, like, raw intelligence, drive, and fucking pure learning rate gets you in startups. And it's helped me double down on horsepower and learning rate and drive will get you anywhere. And she's a perfect testament to that and helped, like, land that lesson with me. So incredibly grateful that we got to spend several years working together.

Scott, thank you so much for the time today. This was such a pleasure, so interesting, and we're so excited for this next chapter for you.

Thank you. See ya.

Thank you so much for joining us at The Room Podcast. If you want more from The Room every week, subscribe to our newsletter at theroompodcast.com/newsletter. We'll be back next week with a new episode an inspirational guest Tuesday, 10:00 AM Eastern, 7:00 AM Pacific. See you in the room.

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