This Week in Startups - What Ramp’s data tells us about AI, unemployment and more with CEO Eric Glyman | E2192

Episode Date: October 13, 2025

Today’s show:*Eric Glyman of Ramp joins us to share the fintech unicorn’s growth secrets AND their Lab full of research data.On TWiST, Jason and Alex chat with Eric about Ramp’s counter-intuitiv...e mission — helping startups spend LESS money — PLUS they take a deep dive into the company’s treasure trove of startup trend data. Why is there a huge spike in unemployed recent college trends? Is “static team size” as a big a story as Jason and Alex think? What does it actually take to get companies to adopt AI Agents? The answers all might be in these Ramp numbers.PLUS Eric joins us for some hot Founder Q’s, and what’s going on with all this Y Combinator drama? We’re sifting through the angriest tweets for the inside scoop.FINALLY, Jason recommends some of his favorite startup accelerators of the moment (aside from his own) including…PearXArc from SequoiaAntlerSpeedrun from a16zTimestamps:(00:02:18) The 72-hour rule strikes again: Trump’s China’s tariff reversal(00:03:10) Why crypto got hit even HARDER than the stock market post-Trump announcement(00:07:32) Market manipulation “at a scale we’ve never seen before…”; what does this mean for everyday investors?(10:05) Squarespace - Use offer code TWIST to save 10% off your first purchase of a website or domain at https://www.Squarespace.com/TWIST(00:12:55) Ramp CEO Eric Glyman swings by to update us on his fintech unicorn’s growth and their “Lab” for research data(20:09) Netsuite - Download the ebook CFO’s Guide to AI and Machine Learning for free at https://www.netsuite.com/twist(00:21:40) Is “static team size” a real trend? What the Ramp data shows…(00:26:25) Ramp’s “counter-intuitive” mission: to help companies spend LESS money, not more.(30:24) Paper OS offers the largest library of AI-driven Workflows for both founders & fund managers. Claim your $10K credit at paperos.com/twist(00:38:07) WHY the huge spike in unemployed recent college grads? Especially among the guys?(00:49:16) What it actually takes to get companies to adopt AI agents into their processes(00:52:25) Why Jason thinks Eric is a top-tier TWiST guest. We’re going through the metrics…(00:54:05) There’s YC drama on social media now… we’re spilling the tea.Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisThank you to our partners:Squarespace - Use offer code TWIST to save 10% off your first purchase of a website or domain at https://www.Squarespace.com/TWISTNetsuite - Download the ebook CFO’s Guide to AI and Machine Learning for free at https://www.netsuite.com/twistPAPER OS - Building an empire? PaperOS offers the largest library of AI-driven Workflows for both founders & fund managers. Whether you’re raising capital, launching a fund, or wading through diligence, PaperOS unlocks simplicity and scale for your ever-growing empire. Claim your $10K credit at paperos.com/twistGreat TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason’s suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.comSubscribe to the Founder University Podcast: https://www.youtube.com/@founderuniversity1916

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Starting point is 00:00:00 30 minutes before Trump dropped the news and sent the markets into chaos, someone took a very large, short position, about $700 million, Jason, in notional value. And then after the crypto market took an enormous dump, they closed the position. And they between $160 and $200 million reports vary a little bit. Now, they have highlighted the person they think this is, a hedge fund manager out of Hong Kong.
Starting point is 00:00:22 He has gone on to Twitter and say, hey, guys, I know inside information. I don't know the Trump family. But that's pretty speculative. I don't think we've locked down 100% that it was him, but people are just saying, hey, if you make such a strong trade so quickly before an enormous news event and close it, it seems like you had inside information. This Weekend Startups is brought to you by PaperOS. Building an empire, PaperOS offers the largest
Starting point is 00:00:47 library of AI-driven workflows for both founders and fund managers. Whether you're raising capital, launching a fund, or wading through diligence, PaperOS unlock simplicity and scale for your ever-growing empire. Claim your $10,000 credit at paperOS.com slash twist. NetSweet. The business landscape is very chaotic right now. That's why you need NetSuite by Oracle. Download the CFO's guide to AI and machine learning for free at netsuite.com slash twist. And Squarespace, turn your idea into a beautiful website. Go to Squarespace.com slash twist for a free trial. When you're ready to launch, use offer code twist to save 10% off your first purchase of a website or domain. All right, everybody, welcome back to this week in startups. I'm your host
Starting point is 00:01:44 Jason Gallaghanis with me my co-host. Alex Wilhelm is back. I'm back. You're back. Friday, you had a little bit of sick nanny, sick kids, the whole thing. Yeah, it happens three times a year when you get kids. Yeah, it was brutal. We're like 90% healed. We're over the hump and I'm stoked because Gosh, Jason, it's a busy news day. We've got a great guest. It's going to be a great show. Awesome. Well, let's just kick off with this first show, the first story here,
Starting point is 00:02:09 because it's been another 72 hours of chaos. Good time to review our rules of Trump, number one. Trump says a lot of stuff. And rule number two, wait 72 hours. So here we are. There was a big announcement on Friday that Chinese tariffs were going to be insane. What's happened since?
Starting point is 00:02:28 Well, after Trump said Chinese tariffs, we're going to go up 100% in addition to the prior levels. We have seen stock market come back a little bit. About $2 trillion in market cap was wiped off the U.S. stock market on Friday. That's an enormous amount of money, Jason. People were very worried. The crypto market also took a pretty big hit. Since then, things have come back today, taking a look at where things are.
Starting point is 00:02:50 The NASDAQ's up 2%. The S&P 500 is up about 1.5%. So a nice recovery bounce, not all the way. But I think it goes to show that the fear that we saw on Friday has come down. pretty much materially. I don't think we're out of the woods yet on the Chinese tariffs issue, where Earth's issue and everything else. But traders seem to be breathing a bit easier today,
Starting point is 00:03:08 and that's good for everyone's portfolio. Yeah, the Earth's rare earth metals is a key issue here. As we talked about on Friday, you know, like 60, 70% of rare earths come out of China, but they only have a third of the known deposits, and we keep finding more of them. So although they have a lock on it, in terms of distributing them right now, the truth is it's just because most countries
Starting point is 00:03:35 don't want to rip up the earth and take out rare earth metals because it would cost more than China can provide them for. So if you can get your wheat from a farm in the middle of America, you probably don't want to stand up a grain field in your yard, even if you could. You just buy it from the cheapest person that's called capitalism, globalism.
Starting point is 00:03:56 So it's really not going to be that big of an issue. and I think most countries are going to, because China keeps yanking this chain on rare earth metals, they're going to start becoming more independent. Just like China, because we won't sell them certain chipsets are going to make their own chipsets. So this is how the markets work. If you don't sell stuff to the other party, they're going to find ways to route around you. Market, yeah, took a real dive.
Starting point is 00:04:25 Crypto got creamed because you can see. still trade it when the market closes. So it fell from 122 to 103. The interesting part of that was that somebody made $200 million, placing a trade 30 minutes before Trump's tariff announcement, send prices falling, which is perplexing but not unexpected. Lots to unpack there. Have we figured anything out or maybe just explain to the audience what technically happened?
Starting point is 00:05:03 So 30 minutes before Trump dropped the news and sent the markets into chaos, someone took a very large short position, about $700 million, Jason, in notional value. And then after the crypto market took an enormous dump, they closed the position. And they between $160 and $200 million reports vary a little bit. Now, they have highlighted the person they think this is a hedge fund manager out of Hong Kong. He has gone on to Twitter and say, hey, guys, I know inside information. I don't know the Trump family. But that's pretty speculative.
Starting point is 00:05:32 I don't think we've locked down 100% that it was him. But people are just saying, hey, if you make such a strong trade so quickly before an enormous news event and close it, it seems like you had inside information. And I think we have seen in the crypto world over time that the traditional financial world rules don't always apply. And this is one of those times which people are saying, hey, maybe someone here was acting unfairly with information that the market didn't have. And I think it was Joshua DeVos of Coin Desk. He said, the timing and scale of the positions opened on October 10th, Friday, immediately prior
Starting point is 00:06:05 to the market-wide liquidation, does raise suspicion of information asymmetry, which is a very understated way of saying that someone might have cheated the market. Yeah. And it's important for people to note, although people are now putting crypto regulation in place and we didn't have new regulation for crypto. for the past, I don't know, well, for the whole existence of crypto. We really haven't had new regulations. The regulations have been, see the old regulations, which obviously sometimes apply, sometimes don't apply.
Starting point is 00:06:36 What all this means is if you're playing in a global casino with anonymity and every jurisdiction in the world participating to some extent, that's never existed before in the history of humanity. What that means is groups of people can manipulate markets at a scale we've not. never seen before. You want to place bets and try to move markets around stocks. You have to have brokers. Some countries allow you to buy shares. Some don't. There's so much regulatory framework in the stock market, in bonds, even in gambling. You know, you go to a casino and you count cards. They've got an eye in the sky. They watch you. Well, we created a global casino. And the global casino
Starting point is 00:07:20 still has no rules. And one of the rules that people perceive the market has in many cases, but it doesn't, is trading on insider information in crypto, on prediction markets. They're kind of predicated on the concept that some people will have information, information asymmetry is kind of like saying, I have information you don't have. I have an edge on you. I know that, I don't know, the quarterback was out all night in a strip club drinking, and I saw him stumble into his hotel at 6 a.m. with a whole gaggle of partiers and the game is, you know, tip-offs at 1 p.m., you kind of have inside
Starting point is 00:08:02 information. You can trade on that. You can bet on the jets or do something stupid like that. Here, you could bet on crypto. So just know, if you're not running the project, you are the sucker at the table. The people running the projects are the casino, the people running the markets and the marketplaces, the market makers. they're kind of the equivalent of the casino, the bookies, the sports book. You really should
Starting point is 00:08:29 be thoughtful about what percentage of money you put into crypto and what your expectation is for that return. I would say, I've always said, low single digits of Bitcoin or the most known stable projects. If you can afford to lose it, you'll make it up if you do. And if it goes 100x, well, wow, you know, it's 5% of your portfolio. Now your portfolio is 5x. It's great. So be thoughtful folks. And it is what it is. I'll just throw in that later on, Donald Trump did post again that, you know, don't worry about China.
Starting point is 00:08:59 We'll sort this out. And that led to CoffeeZill, one of our favorite friends of the show. We've had them on the podcast said, imagine getting liquidated because of tariff fears on Friday only to have it called off two days later. People took a lot of financial hits, Jason. I saw people posting on social media that they were leveraged and lost all their assets. So if you're going to trade in crypto, maybe don't. don't use leverage as well. That seems like an additional risk that you don't need if you're
Starting point is 00:09:23 going to dabble in exotics. I'm just glad that, you know, AMD was off 8% and Tesla fell 5% and Vivida lost 5%. I'm glad that we're kind of coming back from those concerns. Though I do think that it shows how brittle the market is, Jason, that things fell so quickly over a Trump tweet this far into his administration. That was my takeaway. Yeah. And producer Claude made us a little table here. We'll pull up on the screen. As you just mentioned, AMD, Tesla, Invidia, broadcom, Apple, and Oracle, are these the top declines or amongst the top declines? These are amongst the top declines.
Starting point is 00:09:59 Some were a little bit sharper, but we looked at market cap and percentage decline to try to find the most interesting declines. As my friends at Squarespace like to say, a website makes it real. So like the sort of thing you need to hire a huge team to do, right? Well, it's actually easier than ever before with Squarespace. They have everything you need to get your domain name,
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Starting point is 00:10:59 go to Squarespace.com slash twist to get 10% off your first website or domain purchase. That's Squarespace.com slash twist. Got it. Okay, so we took two variables into account here. And if you look at them, some of them are directly impacted by China. Apple makes iPhones and their laptops and everything mostly in China to this day. And then you got Nvidia and AMD, who are very fully, very large companies now. So one might even say Tesla falls into that as well. Robust valuation club seems to get hit a little bit more because anytime your valuation gets disconnected from fundamentals in some way, some people might call it a meme stock,
Starting point is 00:11:47 momentum stock, or just visionary founders with incredible potential. and people get excited about owning it and or they have a brand name that makes retail want to own more of it. Yeah, when there's a pullback or a downtraft, they might lose double what the market does. And thank you to producer Claude from our friends over to Anthropic.
Starting point is 00:12:11 Hey, man, if you want to do really great, real-time, deep research, research like this, get a producer like Claude. head to clod.a.ai slash twist and you'll get 50% off your first three months of Claude Pro, which is what we use and we pay for here at the show. It's claw.com.A.I. slash twist.
Starting point is 00:12:31 Yep. All right. Jason, shall we move over and talk to our guest? Absolutely. All right. So next up on the docket is someone that I've known for a long time, Eric Gleiman, the co-founder and CEO of Ramp. If you don't know Ramp,
Starting point is 00:12:43 they started off their life in the realm of corporate cards. They've expanded quite a lot since then bringing AI agents to the, fintech use case for all companies out there. Jason, they're a mega unicorn. They're doing incredibly well. Eric, welcome to the show. Alex, Jason, it's great to see you both, and thanks for having me today. Of course. Of course. I have a lot of these heavy, heavy ramp cards in my little man purse, also known as a satchel. Don't judge me. Indiana Jones had a satchel. But, you know, it's great for corporate spend and expense management. I don't know if we have a promo code, but I do
Starting point is 00:13:18 love the product. It's a great product. And you've been doing a lot of work around taking the aggregate payments that startup spend. And you're able to, without invading anybody's privacy, putting that out there very clearly, tell us what's going on in the space. Who's spending on what products, huh? Absolutely. And well, first, just thank you for giving us a shot and believing us and letting us serve you and your team. It means a lot to me. And, and all, all of us and you're exactly right. We're now RAMP customers over 50,000 organizations, are spending more than $100 billion per year across the platform. And through that, it turns out it's an incredible index in an aggregated and anonymized way to get a sense of what's
Starting point is 00:14:09 actually happening in the economy. You can see this at any point. Just go to ramp.com slash data and you can dive into and see, you know, spend increasing, decreasing where people say, you know, growth is happening in the AI market. How is it happening at the model layer and dig in any way? But that's been a really fun project, open source. All right. Let's leave that up for a second here, Alex, because we can review it and explain it to the audience, if it was listening primarily.
Starting point is 00:14:40 If you're listening and you want to watch the show, we have video up on Spotify and you can go to YouTube.com and search for us. So, well, we had that chart of the leaderboard. I think the leaderboard was kind of interesting. If we can go back to that one, Alex. Absolutely. Here you go. Perfect.
Starting point is 00:14:55 I may get two times bigger if you don't mind. New customer count, open AI in the number one spot. Intuit, which makes QuickBooks, I believe, Anthropic, which makes Claude, Canva, which makes an Adobe, which made creative software. And then by new spend, you got HubSpot card, Avanta, Pipe 17, and Avaler. I don't know if I know Avalara, but Carta, obviously, for CapTables, Vanta for your SOC2. And by new spend, that's interesting. So these are the top SaaS vendors from last month across all of your customer base, which is startups, right?
Starting point is 00:15:30 Or mostly startups. It's, you know, that's how we started about it. But actually, it's really not anymore. You know, technology where it's a little over-indexed in, but, you know, this is everything, consumer goods, health care, manufacturing, you name it. And some of these are temporal. So Avalara, for example, is sales tax automation software. And there's a big tax deadline, I think, actually, on Wednesday of this week. And so folks kind of bolstering all that side of it.
Starting point is 00:16:01 But it's an interesting look, even at just what AI adoption is or software adoption, even outside of typical software world. Yeah. And this information, people used to trade on information like this at hedge funds, where it was available for purchase. So there would be companies that would aggregate credit card data. They would pay the credit card companies
Starting point is 00:16:23 for the aggregate data. They would clean it up and they would sell it to hedge funds. You know, just like satellite companies sometimes would look at the number of cars in a Walmart. And then they would literally, back in the day, Alex, count them.
Starting point is 00:16:34 And then they would show the trend of how many people are in the Walmart parking lot and for how long or whatever they could. And then you could maybe make some trades on how Walmart versus Target are doing and make a couple of basis points. again, back to that information asymmetry we talked about earlier. Yep.
Starting point is 00:16:52 I think you raise a really good point, Jason, that a lot of this data was out there, but it was the highest bidder to go and get this. And a big part of why we publish this at the same time every month, we make it available to everyone is, you know, it turns out for most people, just, you know, small business owners, finance teams, people, you know, just trying to, you know, make improvements have very little visibility. both into what are others doing to improve their business. And so we just try to open source this and let people see what are, you know, right or wrong.
Starting point is 00:17:24 What are people moving their businesses to? So you can have the latest sense of what actually might be creating value, not just who's marketing, but what are people buying? And then more interestingly, you can, this is even broken down in a product I love in the, in Ramps product called Price Intelligence and then accounting automation where you can see, you know, maybe you get a quote from a vendor like Salesforce. they tell you it'll be $300 per seat. You can upload that contract and see here's what the rest of the market is paying.
Starting point is 00:17:51 And so just as you can go on Zillow and see what your home might be worth, you can figure out if you're paying market rate or getting charged a little too much and make your business a little bit better. And so we love just making data available to people building businesses. Well, and this is just such a great startup tip. If you can create data that comes out on a regular basis and people cite it on podcasts or our journalists do. That's how Zillow with this estimate.
Starting point is 00:18:17 And we've had the founder of Zill on here a couple of times. And I've actually had the CMO who created it on. And it infuriated people. When they launched it, they did an estimate, which then forced everybody to talk about and how it was wrong. And so then everybody engaged with it, which then created more press because people are like, my home's worth $2 million.
Starting point is 00:18:37 You're saying it's worth $1 million. This is terrible. It's like, okay, well, we can fix it. Just tell us what it's worth. And we'll adjust it. And they did that even on a very granular level, Alex. They would do it by market. So then they created a marketing strategy
Starting point is 00:18:51 and the 2.0 of that to go after the local newspapers, go after the local news programs, go after the local radio shows. And this is what's called earned media in the space. Paid is you're paid for Google ads or TikTok ads. Earned media means you created something of quality content that gets you on a podcast like this and we talk about it. And there's an implied,
Starting point is 00:19:12 Oh, well, this person, Eric is smart because he has data, and here you are. Now people know Ram to get a couple more customers. So well played and, you know, Carter does this. Everybody does. But you got to actually have a thoughtful good data set. And I always appreciate Eric when you tip me off on which trades I should make with this data before in our group chat. So I do appreciate that. Everybody gets access to it after we make our trades and play some.
Starting point is 00:19:33 Eric shaking his head. We don't do that. We don't do that. We don't do that. But you know what? I will tell you, it would not. there's not financial advice. But I don't believe, and I'll have a lawyer, vet it with us.
Starting point is 00:19:47 But it's not actually inside information, knowing processing data or whatever. That's not inside information. Inside information is inside the company or with their partners. I don't think this would fall into that. But hey, if you're a ramp employer partner or you build the website, don't do it. Don't do it. Don't do it. Yeah, don't risk insider trade.
Starting point is 00:20:06 That's a terrible, terrible thing. My social media feed is filled. With all these experts giving me stock tips, investment advice, but we know nobody's got the crystal ball. Everyone is just guessing. They're making their best guesstimate. But now you can take the guesswork out of your business planning and strategy when you use NetSuite by Oracle. NetSuite is the number one, AI Cloud Enterprise Resource Planning Software on the market today. That means every facet of your business comes together in a single, easy-to-use, fluid platform, giving you a single source of truth.
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Starting point is 00:21:13 Plus, our friends at NetSuite want to give you a free gift. Download the CFO's Guide to AI and Machine Learning for free at netsuite.com slash twist. That's netsweet.com slash twist. But you also know how the economy is going, I think, Eric. So there's been a lot of discussion, and we came up with a term here for it. What's our term for? Oh, static team size.
Starting point is 00:21:41 So we was talking, Alex and I about this trend. for the past four years, Uber, Airbnb, Google, Meta, Microsoft, all having the same number of employees this year as they likely did four years ago or modestly up or modestly down. So static team size. The team size does not change. You probably know when team size has changed because they would issue more ramp cards. So what is the data saying there? Are companies hiring or not?
Starting point is 00:22:06 And then what does that say about the impact of AI? Because you're seeing a lot more AI spend. So we got really two interesting points here. let's just go at the first. What are you seeing in terms of the size of companies that are already large? Are they staying the same, getting bigger? So first of all, you're exactly right. The revenue scale and also the valuation, the market cap scale of companies per employee
Starting point is 00:22:31 has gone either just up generally for these mega cap companies to even, you know, you look at companies like, you know, cursor, which are maybe these, extremes. A couple years ago, we're bringing on their first customers to today. I believe they have something like, you know, 50 employees, you know, ballpark for, you know, a 20 to rumor, you know, 30 billion valuation. I think that the sheer leverage per employee, you know, events in particular industries or not, I think has gone up. And while this is going on, the backdrop of this, I think unemployment in the U.S. for the labor force was something like 4.1%, which I believe below 5%, I think, is the target that the Federal Reserve keeps as a target when they kind of make
Starting point is 00:23:25 their estimates for, you know, is inflation low or not. And so it's both these companies are getting smaller. Well, unemployment is actually within target and even below. And so I think to me, this is both interesting. I think sometimes people focus on the fears of, like, do you need as many people to build companies? I think the other way to look at this is actually maybe there's going to be more companies. Maybe there's going to be more people who are not stuck in, you know, mid-level health working at these giant organizations. But instead, whether it's at startups or more lean and highly leveraged companies, people can just get more done with every dollar an hour. And so I tend to be fairly hopeful in the year and midterm around this. Just for everyone's information, the natural rate of unemployment or the Fed target is between
Starting point is 00:24:14 4 and 5%. And currently we're at 4.2. So Eric, you're dead on. Yeah. And this is the 50-year low for our lifetime. And if you look at recent college graduates, however, they're having a heck of a time getting jobs, which I attribute to entry-level jobs are being taken by AI because they're easy to automate. Now, Eric, you make such a great point. Whenever a complex system, has some unique variable introduced to it, things can get weird and you have reactions. And then you have second order effects. So if you look up the broad concept of, you know, cognitive biases and systems thinking, you can jump into a rabbit hole where a bunch of, you know, Malcolm Gladwell type people
Starting point is 00:25:00 spent a lot of time thinking about thinking. But the truth is, if there's no jobs for graduates and they're smart, then what three or four of them will do is apply to I Combinator or launch accelerator, found a university, if I try to find something to do with their time, because they'll be frustrated, which is what we did. When I was a kid, we graduated school in the early 90s, there were no jobs. It was a huge recession. I think we were probably amongst young people mid-teens.
Starting point is 00:25:28 I think in that time period, it was mid-teen. So most of your friends had jobs, but probably one in five didn't. One in six didn't. And what happened then was people started zines, or they started bands, or they started bands, or or they became freelance photographers and they joined what was called in Wired magazine, freelance nation. It was really interesting, this concept that you didn't have to have a full-time job and stay somewhere.
Starting point is 00:25:50 Let's go to the next piece, which is you are a SaaS-based business and it's got a per-employee component to it because each employee gets a ramp card. So some amount of your revenue is based on headcount. So how does this impact you if you're the land and expand comes? as a SaaS company doesn't work. Do you have to spend more time trying to find new companies? I love that she asked this. And so even, you know, SaaS apart, we started the company about 2,400 and I guess one day ago with this sort of counterintuitive mission, which is we actually want to help our customers spend less money, not more. And we would get all these questions
Starting point is 00:26:35 of, you know, but don't you make money when businesses spend more? And we'd say, you know, Yes, that's true, but it turns out if businesses stick around for a while and spend less, maybe they'll spend less this year, but I think there's going to be a lot more. Their health span will increase. Maybe I'll make 5% less on the card spend, but you might expand into more of the business, and the business might become larger over time. And so, you know, in general, we're actually totally okay if our customers spend less on software in one given year.
Starting point is 00:27:06 We think kind of doing right by businesses, earn us more businesses for the long run. Eric, just to be clear here, you're talking about interchange revenues that you make when people use their ramp cards, and that drives a large chunk of your revenue. So you're happy if they spend a little bit less as long as they stay with you and grow with you. That's right. And I think the same is true. We do have a component where you can add on paid seat-based software. It is an extraordinarily fast-growing business line. You know, it's two years old and, you know, already the second largest component of what we do.
Starting point is 00:27:42 But what I would say is, you know, we're very happy, actually, if people are downgrading the number of seats at any particular point. The goal is, you know, we just want to be a partner that helps businesses be more profitable. I think that approach in aggregate may make, may make less than any individual customer has worked. Over the last year, you know, Jason, we passed over a billion a year in revenue. the business is just about doubling and, you know, we're doing it while generating cash, which is, you know. So are you profitable or are you not trying to be profitable now? We're generating free cash flow.
Starting point is 00:28:17 Wow. Congrats. What do your investors think about that? Like, I guess pre-IPO, that's a good thing because it sets you up. But aren't they also some board member saying, hey, listen, I got in the seed round. I got in the Series A. Why don't we acquire more customers here, Eric? Like, what are you doing with this free cash flow?
Starting point is 00:28:32 We don't need free cash flow. We're not here for a dividend. How do you manage that? It's very funny that you say that. When your product is selling money to companies, you sometimes want them to burn money and to go spend more. And so one, to your point, we definitely have investors and board members saying, you know, that's great, yourself sufficient, but maybe this is a bug, not a feature.
Starting point is 00:28:57 Can you go find more ways to spend more money and grow? And I think they have a point where, you know, something like 2% of all corporate and small business card spend in the US is, you know, is happening on ramp, but 98% is not. And so I think there is a good point of we want to find ways to efficiently deploy more capital to reach more businesses. Let me hit you with an idea. Let me hit you with a couple ideas because this is what, you know, seasoned board members like myself do. We send you on side quests just based on our own personal experience. That has nothing to do with reality. No, in some cases, it's based on some reality. But I assume that, you know,
Starting point is 00:29:31 many people, like our company, the executives have an American Express Platinum or Centurion. They got a United Business and then I got a ramp card. So when I am out and about in the world doing stuff, I'm like, my rank and file employees, go ahead and use the ramp because you're not spending a lot. But when we have big spending, I'm like, get me those United Points, get me my platinum, get me my Centurion Lounge, because we'll use those. So I guess first question, where do you stand in terms of like benefits and competing against the American, you know, wonderful, the platinum card is absurd. Not that I'm optimizing for these things,
Starting point is 00:30:06 but man, the United Flight Points is a really incredible program. So how do you think about Amex Point, this incredible United? And then we were doing Bonvoy for a while and getting, I mean, I didn't pay for a hotel for a couple of years there. So tell me how you think about your value prop versus theirs. Obviously, the world's greatest moderator and the world's greatest danger and investor needs the world's greatest solution for managing. as funds. So I want to tell you about PaperOS and why we use it here at our own companies launch and the syndicate. PaperOS has helped over 10,000 funds, founders and investors, including may automate their workflows. Their tools will help take you through every stage
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Starting point is 00:31:48 Yep. Great question. So I'll start up with like our general philosophy that I'll hit to the specific. So first, for most business owners, I think the average American business is a profit margin of 8%, I think roughly last year, which, you know, if you just think about the math of that, and if you're valued, most businesses in America are profitable and valued on a, you know, a multiple of profits. A dollar saved is not equivalent to a dollar earned. You know, a dollar cut of cost is mathematically equivalent to $12 earned if you were trying to get more profit dollars.
Starting point is 00:32:20 And so we think that actually reducing cost and helping people spend less, Ramp helps businesses spend more than 5% less every year, is just much more powerful than, you know, the points and rewards. And so we focused on how can we take what at launch when when Alex first covered us. We were, you know, help companies cut their expense by 2% per year. You know, now it's upwards of 5. And I think that's too low. I think it should be closer to 10. And so I think it's more leverage. And second, I actually would argue, I think that the luxury in today's world in 2025,
Starting point is 00:32:57 it's not access to a lounge or anything like that. If anything, when I go to JFK, you know, the lunch. lines for these lounges are too long. They have screwed them up. This has become a literal thing that they, the velvet ropes, they're not building enough velvet ropes behind the velvet ropes in my experience.
Starting point is 00:33:16 So that makes sense. I always felt Alex that like this was a bit of a grift because I remember when I had my last job working for somebody, which was Sony in 92, 93, everybody was trying to figure out not how to get the cheapest flight in hotel, but trying to figure out how to get the cheapest flight in hotel, but trying to figure out how to get
Starting point is 00:33:33 at the most points so they could take their summer vacation. The company just kind of turned a blind eye to it. It goes like, yeah, whatever, we're making billions of dollars. But I think that's probably correct. And then you have new entrants like Robin Hood. I have that, I was an early investor in Robin Hood. They sent me one of the first gold cards. And they pay you back money like 3%.
Starting point is 00:33:50 So I do think there's this trend towards that. I was going to tell you a ramp lounge that when you go to the ramp lounge, you you you buzz in with your ramp card and it's like um yeah here's a bottle of water get the fuck out it's like you're that's not why we're here we're not here to get two lawn chairs in a large open room totally there is something to be done here with the ramp card set it would be an anti-lounge i mean if ramp's all about saving you money here's where we're here's where we're cutting eric can we go back to the 2% and 5% thing though because i recall in when ramp was young you're helping people find double spend things they were paying for twice and excising that
Starting point is 00:34:29 How have you managed to do two and a half X the amount of money you save on average? Where is that coming from? Yeah. So a couple things. So first, we'll kind of build it from the basics to the really advanced stuff. You know, on your consumer card today, one of the most frustrating experiences people have is they sign up for a gym or a subscription to a service and they want to cancel it and you can't do it, you know, you call them, they won't pick up the phone, you wish you could go to the
Starting point is 00:34:55 card. You can't turn it off. with Ramp, we were the first in the world, and still one of the only companies on the planet where you can one click, whether it's on one merchant or 10,000, you know, merchants, 10,000 cards, you can say, I don't want to pay for this gym anymore. And every other merchant in the world can charge your card except for that one. That should exist on other cards, but somehow it doesn't. And, you know, when you're running a company, things like this happen all the time. You have engineers paying for software. You're trying things out.
Starting point is 00:35:27 and they just add up, and this gives you kind of a kill switch at the central level to kind of turn off spend. I love this. Yeah. So that's been... I had my own, I built, I've rolled my own ramp experience in this way when I would have a, I'd have like two cards created under my card, one for like media subscriptions, New York Times, whatever, and then one for SaaS subscriptions. And I would just say, cancel them.
Starting point is 00:35:51 I would literally cancel them in September because I know all these things are coming. And there's, trust me, if you're lost. on an island, like literally Wilson, what was the Tom Hanks movie? Castaway. Castaway with the handprint. You're like, Wilson, you're literally with that soccer ball and Salesforce and HubSpot, they'll come rescue you to get your payment for the next year. They will find you.
Starting point is 00:36:15 There's no way for them not to find you because they want that renewal so bad. And so I would just turn these cards off and everything would be ding, ding, ding, ding. We'd be phone calls. They call everybody. They get on LinkedIn. They would DM everybody, in-mail everybody to find out what's going on. How do we get this thing renewed? And man, that really works well.
Starting point is 00:36:34 That's my favorite use case for what you do, Eric, is to just ramp the cards down to one dollar a month and just watch people lose their mind because of these dark patterns. I wanted to share two things that I just think would be interesting for our discussion while we're here, you know, this crack team I have here doing live research to just go back to our discussion. Young male college grads are now jobless at the same rate. as non-grads. So just take a minute, Eric, to think about this.
Starting point is 00:37:01 If you look at the college grads on the left, the men there, seasonally adjusted, three-month-rolling average, 22-to-27-year-old by education type, non-college, which I'll call Generation Tool Belt. That's what we call it here on the program, versus college grads, in some cases getting, like, weird degrees.
Starting point is 00:37:19 The college grads spike up. Nobody needs them. Now, for women, the gap is not as, bad. I think there's more women in college, but for men, it does seem like maybe men are not as necessary in the business workforce with their college degrees, or maybe they get in the wrong ones. And here's from the Bureau of Labor Statistics. 2019, recent college graduates were at 3.25 second cell down in the second column. 2025 average, same time period, January to December. This is January to July versus January to December.
Starting point is 00:37:57 but 4.9%. It's up 1.34. But that's not, that's 1.34 is the point change, not the percentage change. That's like a 50% increase in unemployment versus those folks. There's something going on here, huh, Eric? Well, I have a lot of thoughts about this one. For me, so a couple things. Last week, OpenAI had their dev day and they highlighted it was only 30 companies ever that have consumed more than a trillion. tokens on their model and Ramp was one and so we're a very very heavy user of these models and one of the things that's very unusual about these large language models is you know i guarantee the you know all the latest models have read more about these specialized skills that one might learn in college uh than any person alive for it to be specific these models know more about accounting in aggregate than any account on oh this is such a great insight they know more about help, you know, diagnose.
Starting point is 00:38:56 Because that information is on the open web, because these are careers and people are searching out career information. So content producers, universities, they put all this stuff online. So therefore, the LLMs get, what a great insight. Wow. The thing that I think is going to be very strange for people to reconcile with is I believe over the last 100 years, the weight of wealth in the U.S. was specialization. you would go to university and you would pick up a craft.
Starting point is 00:39:27 Yep, yeah, that's, that's, uh, this is the, uh, if you're watching the audio version, I just pulled up. Before you go into this thing, what about the ramp? What are you using tokens for at ramp? Are you using it to identify, spend and categorize it? That is exactly it, you know, I think one of the very tedious areas of work for companies is, let's say you've, you've, you've booked that flight or hotel, you've, you know, paid for that SaaS subscription.
Starting point is 00:39:50 Uh, there's a lot of work that goes in to go and get that receipt. go, you know, put it into clean readable form, and then put it into your accounting software. You usually have controllers, finance, folks, accountants kind of tagging these. It's very tedious and monotonous. And are, you know, today ramp is not only faster, but more accurate, you know, really than almost all accountants, you know, using the platform. And so just as you can kind of auto-complete your sentence for, you know, things you're writing, you can have like a faster form, rough draft essay. You can have your books virtually almost done before you even open them to go review them. And so we use a lot on accounting automation, bill payment automation,
Starting point is 00:40:30 procurement automation. So we use a lot of this. But I think, and we can go a lot deeper, but to the macro point, you know, I think that in a world where you can, through a query or an API call, call on this knowledge base of, you don't need to be an accountant, but you know how to interface with a digital accountant. You don't need to be a you know, a lawyer but can interface with a model that knows more about law and how it relates. I actually think there might be a good reason why non-college graduates are doing just as well as college graduates, which is if you know how to use these tools, you may not need to have the specialized knowledge.
Starting point is 00:41:11 Levels the playing field. Exactly. What you learned in college is so superficial and light compared to the depth of AI. if you just spent one year using AI tools exclusively, you would be so much further ahead than trying to remember that top 10% of the knowledge. Interestingly, to spend a, if you've spent over a trillion, I'm just looking at Claude AI explaining to me what that costs.
Starting point is 00:41:37 Looks like you're spending tens of millions of dollars on AI spend to do this. Ballpark correct with Open AI? It is, I think that estimate is a bit high. There's a lot more efficient ways. There's calls, and then there's also what's the amount of data you send through for the query, which lowers the cost quite a bit. So if not tens of millions, you're certainly spending millions on AI with Open AI. Just as a founder, Open AI came out first, but are you looking at the other models and low balancing beside them and actually thinking, like people did in year five, six, and seven of,
Starting point is 00:42:15 you know, their cloud spent years one through five, you're like, this is amazing. I don't have to stand up my servers. Then you get to year six or seven, you're like, wait a second. I wonder if, you know, Google Cloud is going to beat Azure, if Azure is going to be at MDS or Oracle's Cloud. I feel like we're now in that moment where people are going to start price comparison. And then there's always deep seek open source. And there's another open source competitor in America now that's doing pretty well.
Starting point is 00:42:39 So how much do you spend your, which one was it? Together AI, I believe. Together AI, yeah. So take me through how you think about load balancing and or comparison shopping and negotiating for tokens versus I'm going to just stand up one of these open source models. Have you tried standing up an open source model and just saying I'll just do it myself? Yes. The short, like to be direct and quick, the answer is you have to do this. You're a great guest, Eric, because when I answer your question, you actually listen to it.
Starting point is 00:43:09 They're like, yes, no, it's a really good question. And I think like one of the lenses to sort of understand. this is you know whenever um so i remember when there was this release where um open i went from chat like gpt 4 to gpt4 mini um or the 4 o model and people you know investors saw wait a minute this this this this task is to call the mini model it costs only 10 per call of what it would take you to call the main model and they said it was 90 percent accurate um and people said what does this mean are you using this or your your cost going way down. How do you deal with the inaccuracy? And it's like, no, no, no. What you do is you send, you invest a lot in benchmarking and different tools to kind of go and
Starting point is 00:43:52 see what's the accuracy of the models for certain tasks. And it turned out that for 90% of tasks, roughly, it is 100% accurate. And for 10% of tasks, it is completely inaccurate. And so you learn, once the models are good at, what you do is you take this 90% of traffic that works really well and you send it to the low cost model here. And this last 10% of traffic, you send it to the expensive model. And models are kind of like that. What's strange about these new models as they jump out is things that suddenly didn't work, do work, things that worked before you might be able to find a much more efficient model architecture is able to take them mind. So you've got to be on top of this. Your tech team's got to be on top of this because it's a major
Starting point is 00:44:32 expense and it's a major opportunity. After Open AI, which obviously you had a major partnership with, who's most impressive to your tech team? It depends a lot on the fun. It depends a lot on the fun. I mean, I think that, you know, for example. Well, who do they keep bringing up? Like, who do they keep saying? This is impressive. Which one? Anthropic in particular for coding and engineering.
Starting point is 00:44:52 There's just something in the model, I think, in the way that's developed, which lends itself to be, I think, extremely compelling, consistently for software engineering in particular. I think it's really good. I think that the latest Gemini model has also, because of the much longer context window for very complex tasks. Heavy research, I think, has been extraordinary. And even GROC as well, I think for physics and math related. Yeah, they're doing great on math. I was, for sure. I was at the XIA office and I was meeting with the math team specifically. And they had, yeah, you know that, Elon invited me there on a Saturday, parking lot full, ordered in stakes,
Starting point is 00:45:38 hung out with the top people. It was very impressive to see their commitment. And they were working on that humanity's last test, is that what it's called, Humanity's Last Test? Yep. And they were like walking me through the problems that are like the hardest things in the world to solve. And they didn't want it to like have known the answer just from like, you know, I got, I stole the teacher's
Starting point is 00:45:57 quiz book and I got the answers. They wanted to know how to actually do it. So they introduced a demonic AI agent into the group of agents solving the problem. And they said the goal of this demon is to try to give the wrong answer and then these five agents have to explain to it why it's wrong.
Starting point is 00:46:19 And it was really, really interesting. What are you showing here, Alex? This is the humanity's last exam, the test we're talking about, and this is the leaderboard of current winners and Grockford, GPT5, and Gemini 2.5 Pro, the models that Eric just mentioned
Starting point is 00:46:32 are at the top of it. Eric, can we talk about agents, though, for a little bit? Because you guys rolled out agents for controllers in Q3, and you rolled out agents for accounts payable in Q3, Q4. How strong are these tools and how are they different from, I think you rolled out ramp
Starting point is 00:46:46 intelligence back in like 2003. So to me it feels like a reprise, but I presume they're doing something different this time. The big, I would say when you think about 2023 with intelligence, large language models could go. And I think that the dominant design then was this idea of a co-pilot. You could feed a questions and it would suggest kind of the outcome. What's unique about agents is I just I think there's a lot of jargon around this as I think of them as models plus tools you know they're not just the model response but you give them permission to go do something on your behalf whereas intelligence might have said I suggest you categorize it in this way I think this might be fraud an agent will go and can automatically approve that report for you can go
Starting point is 00:47:34 actually initiate the buying purchase so from an advisor to an assistant to send Instead of telling you what you might do, it just does it for you. That's right, is I think one of the big things. And some of that has to do with just the sheer level of improvement in accuracy and predictability, coupled with the ability to handle more generalized tasks going on a web page, completing some outcome. And maybe to explain what's so useful about the policy agent, ever since, you know, Enron happened, and that failure blew up, there was this act called Sir Baines-Oxley, which says that for any transaction, you can't buy the thing and review the transaction yourself, someone else needs to do it. Makes sense. Good idea
Starting point is 00:48:15 for people keeping books, but what it's resulted in is for anyone who's worked at a large company, you know, decades of, you know, part of my language, but just like corporate bullshit where like, you know, if you buy like a $5 coffee, your boss needs to sign off, was it appropriate for you to buy like a coffee or a hotel or something like that? And it's just this cottage industry of an unbelievable amount of work where, you know, today most people, they get an expense for their report and they don't review it because it's a waste of their time, or they do and it's, you know, do you really want the boss reviewing? Is it deep human intelligence to go and do this? Functionally, what we built in the policy agent was, you know, we built an AI that knows your
Starting point is 00:48:55 expense policy in detail, can see all the context around the transaction and with 99% plus accuracy is able to approve flag or deny transactions on the manager's behalf. We've seen leaders, you know, like a Notion or a Cora or, you know, today, you know, thousands and thousands of other companies adopt this. And they're able to automatically approve 90% of transactions that are in policy. You can show you all the reasoning for why that is. Flagged the last 10% and you catch like 15 times more out of policy spend and you save a whole lot of time that just would have been, you know, people doing low value task. And so it's a bit of an example of it's not really in anyone's job description to do this stuff today.
Starting point is 00:49:38 but it's a perfect use case for an agent to go and does make work feel a lot less clodgy. Yeah. And so, yeah. I'm curious about adoption of agents inside of the ramp customer base because you mentioned earlier that your customers are now much more
Starting point is 00:49:51 than tech startups. So when you look outside of the realm of tech, do you see a similar adoption curve for agents amongst your more mainstream customers? I do. And in some sense, it's actually been, you know, almost faster. I think one of the lenses to think about is like there's this revolution happening in the world of AI.
Starting point is 00:50:13 And people know that this technology is out there. But most businesses don't have, you know, a single software engineer working at their company, let alone, you know, an engineer working just for their finance team. And so if our customers are not saying like, hey, I'm coming to you for, you know, go sell me the AI product. They're just saying, I want to close my books faster. I want, you know, convenience to get, you know, the expenses in quicker. And so if it's easier and it's quicker, intuitive, and it's embedded, they'll just turn it on. And so...
Starting point is 00:50:41 So there's no concern from them about hallucinations or mistakes. Because if you go back a year ago to AI, people were talking about the flaws more than the productivity. It sounds like in this case, because you package it up in a way that's like, save time, people are just willing to go with it. That's right. And what's so interesting about, in our model, there are hundreds of millions of transactions that occur every year on RAM. And it goes at the end of the month to a controller who... who, you know, they are quite literally hired by companies to review and ensure the expenses are accurate. And so rather than before, you know, they're tagging every transaction by hand, you know, and then reviewing it and then pushing it over, the transactions are all categorized.
Starting point is 00:51:22 They review it and based on their, what they approve or deny, it's functionally a large-scale context engine to learn not just how companies keep their books, but how you specific. specifically do this. And so with every progressive run, less and less needs to be reviewed. You gain trust. Then you see these companies move from heavy review to, you know, I trust the model to go take this through on this 90%. And so that training step has been helpful. How long does that take for them to go from, we'll try this out to, we're confident that this is taking care of 90% of the work for us? Because that seems like a pretty important time spend to understand AI agentic adoption. Yeah, not that long. I mean, I think, even for the first month that people go and take, you know, do transactions. I think we,
Starting point is 00:52:11 you know, one shot see, you know, it's 90% plus accuracy on our recommendations are ultimately accepted. And every progressive month that goes and teeter up to the 95, 99, and goes from there in. So, yeah. All right, everybody. Eric, you are an amazing guest. You got to come back soon. I would just like to have you on and talk about like the news with you. Great guest. You know, I have a four quadrant guests, like expertise and candidness, and you're like in my top right quadrant. You got great expertise and you're candid. That's how I cast Freedberg, Sachs, Gersner, Gurley, all these great people I cast into shows previously is, are they candid? And are they really competent?
Starting point is 00:52:53 You're in the candid competent quadrant. Great job. Eric. Everybody go try RAM. It's awesome. I use it. Yeah. Not an advertisement.
Starting point is 00:53:00 Just authentically, I use it and love it. All right, Eric. We'll see you, see you, man. Thanks for time. Thank you guys. I'll upload that audio file. Yeah. Thanks, pal. What a great guest, huh, Alex? I just, I love a guest who just was like, yes, I'll answer that question. Not the question my PR department asked me to filibuster in and shoehorn into the discussion. Eric has been like that since the very earliest days that I knew him. Because I covered Grant back when it was raising its early rounds. Not trying to brag. Just I have no, no, no. I mean, part of the reason you're here is that you have such great industry knowledge having been at TechCrunch as a high school. smaller. Yeah, basically. But he was always that candid. I mean, even back in the day, he's managed to maintain it, too, which is even rare, I think, amongst founders who get to the deck of corn
Starting point is 00:53:41 stage, they tend to get a little more closed off. Not so. All right. Here we are. We're in, we're in our docket. If you want to follow the docket, you can watch us build the docket starting the night before this week in startups.com slash docket. And then as we're doing the show, you can see me in real time looking at the docket. And I do strike through when we've covered something. And I really want to cover this story about the broken handshake deal with YC and God, it seems like every day is another YC drama. Let's go to the drama. Tell me about the drama this week in YC drama.
Starting point is 00:54:10 Yeah, well, you know, YC is very large. It's very well known. It's well capitalized. Has a lot of founders. You put all that together, Jason, you're going to get some drama. Now, here's what's going on this time. There's a founder by the name of Daniel Jung. He is in charge of a company called Omen,
Starting point is 00:54:26 which calls itself the first agentic investing platform tagline, trade anything. Pretty standard. not go through YC. This company applied late, got into YC, used that in premature, that label, that YC credibility to go out and hire people. And then backed away, turned down the traditional $500,000 YC safe investment and essentially just left the program after taking their whipped cream off the top. This led to a lot of folks being a little bit concerned because handshake agreements are pretty important in early stage investing, and especially in Accelerator's like YC, and so the founder was heavily criticized. His point is, well, hey, you guys say drop out of college, why can't I drop out of YC? And folks are pretty mad. So I want to start, Jason,
Starting point is 00:55:12 by asking you explain the importance of handshake agreements in early stage investing. And then I want you to give this guy a grade from he's being the good kind of trouble to he just torch his entire reputation in Silicon Valley. This kid's a genius. Totally genius. If you want to do something punk rock, that's what... Pause. You stop screen sharing. I'm going to pull us up.
Starting point is 00:55:38 I have a better version of it. Okay, great. Yeah, yeah. I was just showing people the docket, by the way. If you're looking at the YouTube video, you can see our docket here. That's why I encourage everybody to go to the docket. This week in startups.com slash docket.
Starting point is 00:55:49 You see the notes that we're actually reading from and our research team did and producer Claude did. But yes, you share and I'll talk. So here's what I want to say. Boohoo, why combinator complaint? about this and using the YC brand to say it's a YC dropout. Harvard doesn't complain when Zuckerberg does it. And in fact, Y Combinator is known for asking that question.
Starting point is 00:56:11 Tell us when you broke some rules. I don't have the exact question, but they ask people and they sort for people like Sam Altman, who are rule breakers who do, you know, crazy things. Like take a nonprofit for open source, you know, LLMs and make it a for-profit. Yeah. Yeah, you know, like, that's what they're optimizing for it.
Starting point is 00:56:32 They're optimizing for punk rock. And then they want Daniel, the Daniel Young on Twitter, they want him to be well-behaved and stay in his lane. I mean, F off. This kid's punk rock. He can say, hey, you know, I did the handshake, but I didn't sign the safe. I'm out. In fact, he can sign the safe and say, you know what, I don't like this.
Starting point is 00:56:53 I want you to let me out of the safe. Now, they don't have to let him out of the safe, but he can be punk rock. That's like the whole reason, you know, founders win is because they're willing to be a little punk rock. And if I'm YC, the proper response from the YC people, you know, with this, I see Pete Cooman, who I guess it looks like from his Y Combinator logo,
Starting point is 00:57:19 actually this triggered them. Wow. Oh, yeah. So you have multiple Y Combinator people responding to him? Yes. And they were very, very, very unhappy. And Daniel later on said to Mr. Pete Cooman, Pete respectfully, blah, blah, blah, you let us into YC. We're grateful that you were willing to bet on us. We think you were right to do so.
Starting point is 00:57:38 And we want the rest of the world to know why, even if our stent at YC were shorter than initially anticipated. But YC seems really, really mad about this. And that's why I was curious about the handshake element, because I didn't realize that's so much. Until it's signed, it's a handshake. That's why they call it a handshake. You know, is it? Um, rude? Is it unethical, immoral? All right, whatever. Yes. Yes and no. But the deal's not signed. Until the deal is signed, you have the right to back out of it. You know, you can say like,
Starting point is 00:58:10 okay, I want to do that. But if like on the way to your car, somebody's like, I'll just put a million dollars into your company directly at a $10 million valuation, you don't have to give 10% to YC for, you know, 200K. Well, okay, YC should be happy for them. The reason why C is, is overreacting here is, well, one, they're super dramatic. Everything they do has to have this drama. But this is anti-founder, you know, and they're, like, really concerned that this is going to become a trend. I think they've been very threatened by some of the new speed run from A16Z.
Starting point is 00:58:45 ARC by Sequoia. Pear has their summer program. We have Launch Accelerator and Founding University for a long time. We're not a new entrant. Techstar is just coming back. Antler. all of these programs are better for founders, in my mind, than going to YC. Not that YC is bad.
Starting point is 00:59:02 YC is, you know, as good, but I think these other programs are better because they give better terms. Okay. And you're not one of 500 founders or 250 founders. They're more bespoke. So if you go to Speed Run, if you go to Sequoia Arc, if you go to Pair, if you come to our program, and I'm talking my own book here, obviously, it's less of a factory like Y Combinator, and it's, you're not going to get lost and give a one minute
Starting point is 00:59:25 presentation on demo day, right? Other programs like ours, two or three minutes, you know, you get a little more time. In ours, you're one of 12 companies, not one of 200 or in ARC. I think they take a dozen. So they're more bespoke. If you can get into one of the bespoke programs,
Starting point is 00:59:40 I think you'll have a better experience. And I think that's what Y Combinator's feeling is like they have competition now. So, and also there seems to be something with young founders. I don't know why this is, but there seems to be some pent up, and maybe it's just a nature of being number one in the space and having such a great reputation.
Starting point is 00:59:56 So it's actually in some ways a compliment that dropping out of YC is the equivalent of dropping at Harvard. If I was Tyler who says, imagine breaking a handjake agreement and bragging about on social media for likes, that's a terrible tweet. What they should have said was, we appreciate the founder,
Starting point is 01:00:14 we think they're amazing, we wish them great luck, we wish they would have come to Y Combinator. We hope that when they raised their next round, maybe we could participate. We wish them all the best. If the program's not for them, we want them to do what's best for them. That's the right response.
Starting point is 01:00:30 Tyler's response, not correct. Peters was, for everyone wondering, dropped out of YC, is just an edgy way of saying, broke a commitment and contract. They're attacking a new founder. You should have some grace for the new founders. They're going to do things that are spicy on the margins, Alex. They're going to do things that could annoy you as a more senior executive or somebody who's been in business for 30 years.
Starting point is 01:00:49 Sometimes founders do things. I've had founders do like multiple times. This has happened with like 10 founders. I've had 10 founders do a round of funding and not tell me. When we have rights in that round, when we have information rights.
Starting point is 01:01:03 Oh, so you didn't get your pro rata. Oh, my. Well, no. You could then have to go back and reverse it or they sign a deal without telling us or, you know, and then we're like, well, no, but did you talk to your lawyer first? Or like, no, no, I got this great deal. I signed it.
Starting point is 01:01:15 And you're like, oh, okay, just you're supposed to do that. So I always tell founders now, like, before you do any deal, or you give somebody three board seats like a founder did recently. I give him two or three board seats. I'm like, please call me first. Because I've already made my money. I'm already microfamous as everybody knows. And I'm slim now. Like everything I want in life, I've got a great family. I'm Schfeldt again. I made my money and a microcelebrity. And a microcelebrity, let me tell you, it's a pretty fantastic place to be. I got a lot of great invites. I can go to F1. I can go to all
Starting point is 01:01:45 this stuff and hang out in the pits. I don't have to buy a ticket. It's fantastic. If I tell you anything, it's in your best interest. I'm only doing it to help you and be a good participant in the ecosystem. Like literally, there's 100% of my motivation. So please don't give two seats to somebody. Please don't give two different investors or three different investors, three different terms and side deals and, you know, like just keep it standard. And if you're going to sell the company, let's have a process.
Starting point is 01:02:13 Don't just sell it to your friend and then, you know, not do the process. Don't give yourself shares without telling the board members you want to give yourself a new equity grant. Like, there's a process here. And let's not get you in trouble or, you know, cause reputation damage. But here, I think Daniel Young is punk rock, and I'd like to have them on the show on Wednesday. Okay. Well, we'll reach out to him and see. And I believe the YC question you mentioned is, what social hack did you do something along those lines?
Starting point is 01:02:39 Asking founders, how they managed to circumvent and kind of short-circuit the attention economy. I think the founder of Cluley, we had on the show back in the day, is a good example of the current young founder archetype, Jason, willing to kick sand in people's faces to make a lot of noise. And here we are. One more time. So there also was another comment.
Starting point is 01:02:58 There's this account called Speck, SPEC, that is obsessed with Gary Tan. I love Gary Tan. I've known Gary Tan. I think he's a great human being, and I think he's a great founder and great investor. I know he had a bad breakup
Starting point is 01:03:11 with Alexis O'Hannian, who I also have a lot of respect for us. I don't know. Sometimes founders can break up. But I think Gary's, great. But this account spec, which is open CV with underscores on either side on Twitter, keeps c-seeing me in this because I guess they want me in it on the trauma. Or they, they see-see a lot of people. Yes. But they had an interesting tweet.
Starting point is 01:03:33 Yeah, so the tweet reads, so you can't neg YC, but YC can neg you, if you're not familiar with the phrase, neg. It means to just dis somebody essentially, Jason. And so in this case, there was a girl who, quote, lost her full-right scholarship because she dropped out to to do YC. And then it shows an email and the email reads. I'll just read it out for folks. And by the way, nag means negative in this sort of space. So if you neg a girl in these like, you know those crazy pickup artist. Pickup artist. Yeah, yeah. That's what I couldn't find. The nag is like, oh, wow, you know, one of your earlobes, Alex is longer than the other. That's kind of weird. And Alex was like, will you date me? I'm already dating you're the co-host.
Starting point is 01:04:12 Okay, let's read this. I'm so conscious about my ears. All right, the email reads. And this is to a founder who is NYC. Perfect earlobes. Thank you, Jason. Also, I, there's one person in the world who's allowed to break my phone silence. It's my wife. Sorry about that. All right.
Starting point is 01:04:27 The email reads, I wish I was emailing under better circumstances. It's become clear that you three cannot operate as a functional team. We funded your company under the assumption that you could. And as a result, company name can no longer participate in YC. You have three options. Shut down. Give us the money back. Keep the company alive and give us the money back.
Starting point is 01:04:44 Or keep the company alive and keep the money. at which case we'll give you back your shares and cancel are safe and no longer be an investor. I strongly recommend you pick option one or two. So this is them essentially saying to a company, you aren't putting that. Is that confirmed? No, this is from someone with the initials MS.
Starting point is 01:05:01 I know one person. I wasn't going to say it out loud. I also know Michael. It could be Michael Cbole. Michael's fantastic. Gary's fantastic. But the point here is that YC will often, well, not often, but sometimes play a bit rough.
Starting point is 01:05:13 And so if they're allowed to play a bit rough, then why can't founders do the same, Jason? Okay. All right, listen, it's business. Things can get a little chippy sometimes. It can be very annoying if a founding group like this, you fund them, and then they start creating chaos.
Starting point is 01:05:28 Because what you don't want to do is have a distraction in the incubator for the other companies. That's not fair to the other companies. So, just like if you got accepted to Columbia or NYU and, you know, you start causing drama everywhere, and we've got you on a scholarship.
Starting point is 01:05:44 And you're going to be on the basketball team, or the hockey team, and you're just running amok. And it's like, well, maybe this isn't the right opportunity for you. We can take our scholarship back. In this case, it's $125K. In this case, if I was YC with billions of dollars under management and dozens of unicorns, including their most successful ever, I think, is Airbnb,
Starting point is 01:06:07 which is worth, I don't know, close to $100 billion. My two unicorns are worth more than that, but I know it's not... $74 billion. Airbnb is an incredible company. I think it's the largest one to ever go through there. Robin Hood's worth $125 billion, and Uber is worth $197 billion.
Starting point is 01:06:26 There you go, Jayes. So my two are bigger than their biggest, but it's not a competition. Oh, it's not. I see. It's not. There's not a scoreboard here. Oh, okay.
Starting point is 01:06:35 Everybody just tries to help the ecosystem. I'm kind of making a joke here because people do get competitive. And I can understand if it's Michael Seabold or if it's Mary Susan, whoever, you want to have a clean separation if there's going to be driving up. I don't think that email's too aggressive, except for maybe the last line, like pick one or two.
Starting point is 01:06:56 But sometimes you've got to be firm with a group of people who are causing chaos and be like, listen, one, two, three. And I have had similar situations happen where something comes out during due diligence. We haven't signed the deal yet, but maybe we're between handshake and due diligence. you can say a thousand times to a founder pending due diligence, and they will not hear that. That is like a frequency that, like, they're not capable of hearing. But if you do due diligence, and it turns out like your customers don't match or whatever, or, you know, it doesn't feel like particularly defensible technology, you have the right
Starting point is 01:07:33 to back out here. I think, I don't know, I might be on Michael's side here that he gave them some great options. He said they could keep the money and they would get off the cap table. I mean, that's the opposite of a lawsuit. I think I'm going to give Michael the win here that I think actually he gave them a firm, crisp set of decisions. You might say, like, pick one or two is my best suggestion. Might be a little agro, but I don't think it's overly agro at all.
Starting point is 01:08:03 I think he's giving them good founder advice, which is, hey, listen, if you guys want to have chaos, that's fine. That's not what WIC is about. We need harmony because we've, got two, like I mentioned earlier, like there's 200 other, there's 199 or 299 other people in your cohort. Like, please. But stay in your lane and just be productive for 12 weeks. The end. So anyway, long story short, YC's amazing. Gary's great. Michael's great. And this kid's great who's being a little punk rock. You can't optimize for punk rock and then be upset if somebody's
Starting point is 01:08:38 punk rock with you. The end, full stop, everybody. And for the YC's people, did they delete their tweets when they were dunking on the kid? I saw there's a bunch of deleted tweets in that thread. I don't know whose tweets got deleted or if we know. I took those screenshots of the Pete and Tyler tweets myself and then I grabbed that thread Jason just to highlight how many things have been taken down because Daniel had removed some of his initial tweets that kicked off the controversy. So we had to find them via. So Daniel did deleted his tweets. Anyway, I'd like to have Daniel on. Maybe there's a good investment for me. And if you get rejected from Y Combinator, don't wait six months, email your boy, J-Cow. Okay? That's very simple.
Starting point is 01:09:21 Jason at calicanus.com for life, or you can email me if you love the All-In program, Jason at all-in.com, or if you want to get a meeting with the 11 people on our investment team, forward your YC application that got rejected to YC at launch.co. YC at launch.com, and you will get a meeting with my team within 24 or 48 hours, including a little bit of weekend time because my team works a couple hours on the weekend to meet with founders. We will meet with you quickly. We'll do a 20-minute first call with you. You pitch us your product or service 10, 15 minutes. We ask you one or two questions. You ask us one or two questions. Then at the end of 20 minutes, you know, we end the call and then we will talk to you and have a follow-up and see
Starting point is 01:10:03 if it makes sense for us to go to a second call. We do this because it's founder-friendly. Like, it's good to, you know, save you time. And if you don't get into YC, I don't think you should just apply to YC. I think you should apply to our program, founding university if you're pre-revenue, you know, like year zero, or apply to the launch accelerator. We have a common app,
Starting point is 01:10:22 launch.com slash apply. I also think you should apply to Andresen Horowitz's speed run, Antler, Pear, does a pair VC, Marr does a great program over there with Pejman. These are great investors,
Starting point is 01:10:37 great founder-friendly folks. Rule off in the team, Stephanie and everybody, they do the ARC program. And we'll put those links in these show notes today. I am not a zero-sum person. You should, I think the Y Combinator folks
Starting point is 01:10:51 have a little bit of like circle the wagons. They're not, I think they're just a little too cutthroat, I'll be honest, it's a bad look, because they don't need to be. When you're winning, you should be magnanimous. I've had to learn this in my life. All of us have to learn this. Chalmots talked about learning this.
Starting point is 01:11:10 When you win, especially in, you know, when you get to the top of the, you know, the top rungs of the ladder, where I've been lucky enough after a 30-year, brutally hard career, fought my way in here. I get it. I had to go punk rock. I launched a zine. It's as punk rock as it fucking gets.
Starting point is 01:11:29 Like, I couldn't get published, so I started my own magazine and photocopied it. You know, people didn't respect me. I started my own tech conference because I couldn't get into other ones. Period, full stop, right? I started my own podcast. It's okay to be punk rock, but then when you do win, you got to flip Alex. And this takes personal development work. And it starts from the top and the leadership.
Starting point is 01:11:52 The leadership has to say, hey, we've won. We're going to be relentlessly magnanimous. If I could put a post-it, you know, here on my teleprompter, it would be a mensch. Like my guy, Dave Goldberg, rest in peace. He was the menchiest guy ever. I model my career after Dave Goldberg, Goldie, rest in peace. He ran SurveyMonkey. He ran Launch.com in a way.
Starting point is 01:12:15 I did Launch.com as a tribute to him because I always loved the brand launch.com, which was his music startup. He gave me time when I was coming up in my career that he didn't need to give me. And if you ask anybody who met Goldie, he gave everybody an hour or two. He didn't need to.
Starting point is 01:12:32 He was rich already. He was living the life. He could get any meeting. You could hang out with any powerful person he wanted. Died too young. But when he was alive, what did you do?
Starting point is 01:12:40 He was, he was, if you met 10 menches and there was a mensch lunch, they'd say, where's Goldie? Because we want to have a mensch at this lunch. Literally, he's a munch's mench. That's what I aspire to be in my life. I aspire to be Goldie and be a mench. Another amazing episode of this week in startups. I'm going to get emotional, so I'm going to leave it there. All right.
Starting point is 01:13:01 Unless you have anything else we need to add or any housekeeping we need to do here. No. Other than saying that we're going to have a really fun AI Tam sheet all ready for you. well on Wednesday. It's going to be great. I notice you're taking those notes in the docket. Well done. If you want to tune in live, go to this week in startups.com slash YouTube and it will automatically send you to YouTube and subscribe you to the show. All you have to do after you subscribe is it gives you a little pop-up on YouTube. Hey, would you confirm you like to subscribe? You confirm you want to subscribe, but you hit the alert and the bell there. And then if you could,
Starting point is 01:13:32 do J-Cow and Alex a favor, write us a review on iTunes. I hate to beg for reviews on Apple Podcast, but it is a big part of the show getting surfaced to new people. If you write a great review, we're going to shout you at the end of the show, which we're about to do at the end of the show here. We'll read one of the great reviews. And if you email me your review at jason at allin.com or Jason at calicanus.com, all goes to the same place. I'll write you back and say thank you.
Starting point is 01:13:57 And you get to say hi to me because I'm a real person. It's true. Trying to be a mensch every day I'm my life. I'm a real human on planet Earth. And if you get to a position of power, which Y Combinator is the height of power, and you have this impact on people, best advice. Do what I did.
Starting point is 01:14:13 Do a little personal self-discovery, you know, whatever it takes. Just reflect. You can never go wrong by being helpful and being a match. And you can go wrong by being critical of people, especially publicly like this, especially for a nascent founder because some people will frame it as bullying. I'm not framing as bullying, but obviously that that's the reaction online here. So this is the thing about the power imbalance that YC, maybe. needs to, and this is something Gary has inherently in his DNA, I believe. He's a very competitive
Starting point is 01:14:45 person. He's a full contact person, as you can see with his, you know, opinions on KP, math, and San Francisco, all good character creates. But he should probably build into the YC culture being magnanimous. Be a little magnanimous when you're at the top, right? Because you sometimes forget how much power you have. I don't. anymore. I know that if I mentioned somebody on the podcast, it's going to carry a little bit of weight. I'm not over-indexing on it, but it could negatively impact them. So I've been more thoughtful in how I'll say things. I used to be a little more Howard Stern, a little more shoot from the hip. It's true. But we all learn as we age and we all become a little bit more patient, a little bit kinder,
Starting point is 01:15:29 and that's when you can give back. But more on Wednesday. We'll talk AI Tam. We'll have more guests. Actually, we have a very fun guest on Wednesday, Jason. So everyone stay tuned. Oh, tease it. Tease it. Even if they're not. It might be the first initial S, second initial J, perhaps. Oh, Stevie's coming? He might be. My Stevie? So Wednesday.
Starting point is 01:15:50 I love Steve Jervison. That's my guy. What an investor, board member, a Tesla, SpaceX investor. I mean, you want to talk about a mensch and a visionary investor? Steve Jervison, the J and DFJ. And now he's got his own venture firm. We'll see you on Wednesday, everybody. Bye.
Starting point is 01:16:05 Bye.

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