SPEAKER_01: How did we end up in a world with $100 trillion in assets and a terrible fund management stack?

SPEAKER_00: It's human duct tape, legacy services businesses that are running the entire backbone of these 100 trillion of global assets. They're buying QuickBooks, they're

SPEAKER_04: buying bill.com, they're buying Excel. And so you end up in this like crazy situation where you're stuck with a bunch of human middlemen that they're holding your own data hostage. B2B SaaS was dead, but everyone's like, you're insane. You want to go build

SPEAKER_07: financial info for the most complex investment firms in the entire world.

SPEAKER_08: And you've never done this before. Hello, and welcome back to Twist. My name is Alex. Now, on a recent episode, one of our venture capital roundtables we do every Wednesday, Turner Novak of Banana Capital gushed over one of his port coasts. Now, that's not a very rare occurrence. VCs do love to come on the show and talk about their investments. But in this case, we actually looked into the company in question, got them on the phone to learn more. And it turns out it's a very interesting startup showing where AI meets traditional software and services. So to tell us about bringing AI to the world of fund ops, please join me in welcoming to the program, it's Chris Haloncic, the CEO and co-founder of Hanover Park. Chris, how you doing?

SPEAKER_10: Let's go. I'm pumped for this.

SPEAKER_08: I'm pumped for this too. Okay. So here's my thing. When I think about lots of money, which funds have, I think about the ability to pay for strong services and to really have a good operational backbone. But what you told me is that in the world of fund ops, the technology is outdated. There's too many people involved and you call it a kind of duct

SPEAKER_01: tape operation. So how did we end up in a world with a hundred trillion dollars in assets and a

SPEAKER_00: terrible fund management stack? Well, it's human duct tape where you basically think about like legacy services, businesses that are running the entire backbone of these hundred trillion of global assets are sitting there with a bunch of humans in Kentucky. They're buying QuickBooks,

SPEAKER_05: they're buying bill.com, they're buying Excel. And that CFO has to ask them, Hey, can you send me some data and get access to my own data? And they're literally like, that's insane in 2026. And so we looked at this and we're like massive untapped legacy services market with very low tech

SPEAKER_04: penetration and run by, you know, a bunch of fund accountants in a room that are delivering

SPEAKER_01: financial reporting every quarter. So tell me more about the data question, because one thing I've heard a lot about from companies in kind of the AI moment is people want to have access to their data. It's my data. At the same time, a lot of SAS companies want to hold on to that because it's

SPEAKER_15: kind of their secret sauce. But in this case, it sounds like funds often have their data stored in Kentucky, as you said, and don't have regular and easy access to it. That's the crazy part about

SPEAKER_00: this. So fund administration, traditionally you pay this fund admin, they have the service provider with a bunch of accountants that are doing your financial reporting. And they basically go and say,

SPEAKER_04: okay, we're going to buy access to QuickBooks and we're not going to give you access to it.

SPEAKER_05: Actually, you're not going to be able to have your own data. And so then you have to email them and say, hey guys, can I have my own data for this random report? I need to repul when I need to go fundraise

SPEAKER_04: for my new fund. And so you end up in this like crazy situation where you're stuck with a bunch of human middlemen that they're holding your own data hostage. And so, you know,

SPEAKER_08: why, like, why, why, why is that a service people would pay for it? To me, that sounds like giving someone money to slam the door in your face. So why, why wouldn't these funds, which have part of a lot of AUM just build their own internal stack? Why, why outsource it to someone who hates

SPEAKER_05: you, I guess. Traditionally, it's like, it doesn't even matter because all they're doing is delivers an output, which is that financial reporting that goes to your limited partners every quarter, your Harvard endowments, your Yale endowments. You know, I went to Yale, so I can say that. And so like, they're just delivering an outcome. And so in 10 years ago, CFS were like, I don't really care. They just do the work. It ends up being great and ends up being fine. And now we're in this moment where your data is a hundred times more valuable because this

SPEAKER_04: is like the backbone for every investing decision you've ever made. Right. And so that's now we're in

SPEAKER_22: this moment where everyone's like, I need my data back. All right. So tell me about the actual

SPEAKER_01: kind of our stack and what you're replacing from the various services that a fund buys, because I presume they buy a lot more stuff than just, you know, help with fund administration.

SPEAKER_04: When we started in 2024, we made this contrarian bet that I said the following, B2B SaaS was dead. We were going to go build this idea of an AI native services company in 2024, which was super contrarian, which is that we wanted to own the end to end outcome and not just build another tool that was going to get commoditized by Claude and ChatGPT. And so we started by saying,

SPEAKER_05: hey, we're going to go build an ERP for a fund. That in 2024, my investors started laughing at me, right? I won't say Turner was laughing at me. He probably would say, but everyone's like, you're insane. You want to go build financial info from the most complex investment firms in the entire world. And you've never done this before. And so we started by building the unsexy core system of record for the fund. On top of that, we said, okay, then there was a bunch of humans that were clicking buttons to actually do the accounting and financial reporting and capital calls and

SPEAKER_04: distribution who said, how can we build AI agents on top that learn from every single thing for a fund, right? So the key problem you're solving is like, say you have a person that's your accountant,

SPEAKER_05: they're doing your accounting, and then they leave in six months and say, hey, wait, all the things you taught them about your fund now go away. And so building agents with memory on top is actually the way you solve that problem. And then lastly, now we have all this data for your fund. What are the things we can do to weaponize it, right? And so now you have portfolio management and monitoring and

SPEAKER_13: LP port and there's like a stack that sits on top of the system of record for the fund is kind of

SPEAKER_08: how we think about it. Let's start with the ledger component of this because you said it's very complex and some investors were looking at you like you're crazy because why would you go out and tackle something that's that hard? To me, from where I said, it doesn't sound that complicated. Oh, of course. It's super easy, right? Well, no, no, no, no. Hear me out. I'm not trying to be coy or awry. I'm just going to say that like, you know, when I think about how we handle like high frequency trading, that seems like a much more difficult system to kind of keep track of what's going on

SPEAKER_22: than a fund that might make an X number of investments per quarter. So talk to me about the complexity of this and how long it took to build the ledger in question, because that sounds

SPEAKER_04: like the foundation for everything here. Totally. So think about Blackstone and think about like hundreds of billions of assets with tons of different, you know, entities that need to talk

SPEAKER_05: to each other. Think about QuickBooks. You have one entity, right? At one time, you know, with Blackstone, you might have hundreds of entities in a single fund and all of those entities have different ways you allocate profit and loss to all the different partners in these funds. And so when Harvard Endowment writes $100 million check into an entity, you have to allocate all the different costs and expenses and different funds. And everyone has different economic terms. And so think about the combination of tons of legal entities that need to talk to each other, tons of weird profit and loss allocations, and any weird stuff the lawyers want to dream up that they're

SPEAKER_04: going to toss into this thing called a limited partnership agreement to do that. And so herein lies the fund levels of complexity. And our job is to capture that somehow. So I'm thinking about a ton

SPEAKER_01: of contracts, like like an absolute mountain of PDFs and DocuSigns speaking loosely. How do you guys convert the written word here into the rules and kind of guidelines for the ledger system to understand?

SPEAKER_38: Is that done by humans, the translation process, or is that something that AI can now handle based on its ability to reason?

SPEAKER_00: So if I take this in different direction, imagine I go to Blackstone, they're not a customer,

SPEAKER_05: far from it, right? We're only 20 billion of assets right now. Say I go to the CFO of Blackstone and say, hey, here's all these magical things we can do for you. He's like, oh, my God, that sounds amazing. But isn't it going to take forever to get all my data into Hanover Park? Isn't that going to be the worst thing in the whole time? So we built these long horizon agents to do financial data cleaning at

SPEAKER_04: scale that capture all that ontology to quote Palantir, map that to a set of work. I got to quote Palantir, right? Map that to a set.

SPEAKER_42: Okay, fine. No, no, no. Now you're in trouble. Now I'm going to call you on this. All right, define ontology for me, something that Alex Karp has yet to do once.

SPEAKER_46: Well, wait, should I pull an Alex Karp and say, I'm not going to define ontology. We're

SPEAKER_22: going to have to like search this. You have to bounce in your chair while you do. No, I'm serious. Like for the people out there, for people for whom that is merely a buzzword, they've seen an earnings report. Ontology may be a working definition for how Hanover Park thinks

SPEAKER_04: of it will be useful. Totally. So it's like, you know, the way in which the fund does their work and how they capture the associated information tied to a legal document for given limited partner, portfolio company, et cetera. We take that information, we then translate that into a way in which our general ledger operates, right? So that's like the simplest definition and we can make it more

SPEAKER_52: complex. Oh, that's fun. Let's make it more complex.

SPEAKER_05: Oh boy. So beyond the simple stuff of like how the limited partner relationship is with a given

SPEAKER_04: fund, it's like, how is the relationship with the underlying portfolio companies? How is that portfolio company relationship from a given set of legal entities? Maybe you have tons of different funds that are investing in the same company. How do we want to capture that, analyze that? And then like that gets into the fund data that sits on top of like the core GL, which is not only is Hanover Park tracking cost and fair value and fun, simple stuff like that, but we're tracking like,

SPEAKER_05: what's the post money in Uber's latest round? I got to say Uber because I'm on this week in startups,

SPEAKER_01: right? Jason gives you five extra bonus points and a high five. Yeah. No. Okay. I appreciate that. Now you mentioned the long horizon agents. I think that was the quote. A lot of people are making noise about agents that are able to do tasks over a longer time period. I think METR does a lot of work on how long agents can work independently. Now in your case, why do they need to be so long horizon? And also how much have they improved in the last like maybe six months? Because it does seem that we've seen a pretty rapid increase in agenda capabilities from what I can tell. So I'm curious how that's kind of manifesting inside your operations. For us, when we thought about what are the biggest

SPEAKER_04: problems with the company, you know, step one is how do you get hundreds of thousands of documents for a given set of funds? If you have 20 billion of assets and you have 25 years of history, trust me, there's a lot there. There's a, there's a lot of noise in there. Right? So, so I think it's like getting all of that data into Hanover Park is like a massive set of technical challenges. And if you're an amazing engineer listening to this, these are types of fun things that we have. Right. And so it's like, you know, those, I got a handoverpark.com slash jobs,

SPEAKER_66: I presume slash careers. I'm sorry. Oh, come on. We're a little upscale from

SPEAKER_04: that. So, so, so look like, uh, you, we basically have to take all that data. You drop in 300,000 documents. You need to somehow map the ontology. I'm going to, I know you're going to make fun of this, take all that data, extract, analyze, you know, inception to date for the entire set of funds and all their vehicles and get that data into Hanover Park. So then we can do the next quarter of financial reporting or we can do the next capital call. So that's like, when we think

SPEAKER_05: about that process, traditionally, if you said Blackstone, Hey, do you want to migrate to Hanover Park? It'd be like, I'll see you in 24 months. I'll see you in two years. We say, I call it the

SPEAKER_73: one click migration future. How close are we to actually it being a one click migration future?

SPEAKER_75: Okay. So you have identified a real problem and you put together a solid solution and a business model that you believe in. So you're all set to launch your new company, right? Huh? Not so fast. If you want investors and potential customers to take your new business seriously, you need to consider forming a Delaware C Corp. And that's where Northwest registered agent comes in. They're going to give your new company a real identity. That means an address for your public filings, a domain, a custom website, a business email, and of course a phone number. And that's going to take just 10 minutes and 10 clicks. They don't charge hidden fees. Customer service is available around the clock. They're not overwhelming your inbox with spam and they make it easy to cancel at any time. So get all the advantages of a Delaware C Corp independent, regardless of where in the us you're operating from visit Northwest registered agent.com slash twist for more details. And the links are in the show notes.

SPEAKER_04: We got data of a venture capital fund, uh, from call it like 20 different entities. They got a handful of funds. We're not talking Blackstone size at this point, but some SPV is fun. Yeah, exactly. So it was, they had some stuff, right?

SPEAKER_05: We took that data. We got that data. We launched their limited partners six days later,

SPEAKER_22: six days later. And just to be a brat, uh, any mistakes, errors that had to go back and be corrected, or was that kind of a clean,

SPEAKER_01: clean sheet of paper once the migration was done?

SPEAKER_00: Of course, as with any workflow, where the importance of accuracy is everything,

SPEAKER_04: especially given the institutional LPs that are logging in Hanover Park, we of course have a team that's reviewing those outputs, right? But like it, if we're, if we're clicking a, uh, a button and it's taking 12 hours, we have, you know, all that time for them, the team to do the actual review.

SPEAKER_87: So it sounds then, and we'll get to the CPA point in a minute. It sounds then that the

SPEAKER_01: current world of AI models, AI agents and harnesses thereof are sufficiently intelligent to handle

SPEAKER_22: what Hanover Park needs today to ingest large amounts of data and to kind of define the ontology. Was that true a year ago or is that? Definitely not. This is all, oh my God. I literally was

SPEAKER_04: joking with my CTO. Cause I, so there's this internal joke at the company where I said,

SPEAKER_05: we're building a one click migration. I said this 12 months ago and I had engineers laughing at me.

David Friedberg: They literally were like, good joke, Chris, haha, funny, whatever. And I learned it yourself.

SPEAKER_05: Yeah, exactly. Exactly. They say they were laughing at me and I said one click migration, one click, and literally, and we released it three weeks ago. And that engineer, by the way, we love him, JT. He literally came to me and said, you were right. And so that was only, that was only possible probably three to six months ago with like Opus four, six.

SPEAKER_01: Opus four, six. Okay. So kind of in, okay. So right now we're at Opus four, eight, we're at, well, probably a little bit, it's uneven, but you don't need to have Fable five to make this work. Essentially. You can do this with Opus four, six technology. So you're not losing edge in the

SPEAKER_60: current market with the restrictions going on that we're seeing. Look, it was actually funny. So

SPEAKER_04: Fable five's out, you know, the team says, this is magical, et cetera. And literally then I have someone come to me when Fable five gets disbanded or stopped and they start crying to me. They're like, I literally, I love Fable five. What is this? What am I doing? You know, et cetera. So trust me,

SPEAKER_05: we like it. I think that the gap is, is less of a intelligence gap and more of a context gap is the way

SPEAKER_04: I think about like the context of the complexity of a given fund that we need to actually understand versus are the models good enough. However, when we think about reducing human, the loop and getting closer and closer to one click versus six days, versus look, if I'm a migrating large funds, not gonna take six days, maybe it's 30 days, right? Yeah. To get that closer to one click.

SPEAKER_22: Of course I want better models. Does that impact your economics at all though? Because look, one thing that you and I talked about during our, our first chat was just how big the world of funds is. I was asking about Tam and you're like, Alex, don't be silly. It's enormous. Now, when we think about the, the improved model intelligence, what does the incremental, what does that gain you? I suppose. And what does it unlock? Because I get that better models

SPEAKER_05: is better, but how? So, I mean, there's, there's a lot around like, we're not just doing fund

SPEAKER_04: admin. I think like I joke, I said, Stripe for payments, ramp for expenses, Hanover Park for investments. Ramp was a credit card company at one point. Remember that? It was a corporate

SPEAKER_05: expense charge card company. Yeah. Remember they're in AI, they're now an AI finance lab, right? Like if I think about like, if I think about, look, like financial infrastructure for the investment firm, AI fund admin is obviously a massively important piece. Like we understand

SPEAKER_04: the importance of what we're doing on there, but like the ability to layer these things on top and

David Friedberg: build this intelligence layer to help CFOs make better decisions. Like there's obviously a bigger

SPEAKER_106: prize here. Well, we're kind of getting towards where I wanted to go in a minute, but I want to loop back to

SPEAKER_22: the CPA point because some people listening to this are going to say, whoa, I'm not ready to get

SPEAKER_01: agents run all of this for me. And you guys are aware of that. And you have some CPAs in the loop to review outputs from the AI systems. What I'm curious about is what the kind of like number of CPAs you need per billion dollars of AUM looks like today and how that ratio changes as the company scales, gets more data, improves its own internal models, et cetera. Look, like I think it's incredibly

SPEAKER_00: important when you think about 10,000 institutional LPs and platform, including large institutional

SPEAKER_04: asset managers, everyone knows like we need to have incredible CPAs that are crushing it, that are tier one, reviewing associated outputs and handling edge cases, right? Maybe AI hasn't seen something before and we want to make sure that the Blackstone fund accountant can come in there and be like, hey, this is a more complex thing that we need to think about from a product perspective.

SPEAKER_05: I would say more uniquely too, we have a very unique AI org design, I call it, which is we have no product managers. We have no designers. We just have engineers shipping codes sitting alongside fund accountants. And so part of the fund accounting job here is to actually help us inform the product.

SPEAKER_13: And so that's kind of how we think about it. So part of your job is obviously the fund services

SPEAKER_87: component, but part is actually the product piece. You put the accountants next to the engineers? Yes. That's got to be a very interesting room to work in.

SPEAKER_46: Oh, it is fun. I'm looking, there's a few of them. There's a Muhammad Ali picture in the background.

SPEAKER_110: We got, you know, 50 people here in New York City and we're having fun.

SPEAKER_01: But as you guys do continue to build a product, learn more, figure out edge cases, you know, improve. Does the number of CPAs you need to kind of like service the marginal billion dollars in AUM you bring in go down? Or does that say relatively static because people want to have that? I'm trying to figure out what's the role here of the CPA long-term and is it more of like a makes the humans feel better thing? Or if it's a requirement to make the product work thing?

SPEAKER_46: I think it's a consigliere to the CFO. I said that consigliere to the CFO is like, there is, you can quote that.

SPEAKER_115: Suddenly mafia references. Let's go to Sicily. Okay. Keep going.

David Friedberg: So consigliere to the CFO. It's like, there is complex advisory that the CFO values of like,

SPEAKER_04: hey, you know, we're doing this weird cashless offset thing that we haven't seen before. What do your other clients do? How do you think about this? What is the approach you've seen from experience? And like that is high value advisory work, not did you book this journal entry correctly?

SPEAKER_05: Right? By the way, 95% of fund admins, did you book this journal entry correctly, by the way? And so if we're doing, if we're automating those lower value tasks and we're delivering real-time data versus delayed quarters and quarters, because that's when humans are doing it, then we can be the consigliere. Tell me more about real-time data,

SPEAKER_01: because earlier on you discussed how, you know, you're building a system that has applicability, I think, kind of broader spaces than just doing kind of like AI first fund operations. So once you have all these firms and funds onboarded and you have this flow of data about kind of the state of global investment, what can you do in a product sense, both for existing customers and also maybe breaking that out as a data product? Because to me, Carto's data blog has done a fantastic job taking a relatively staid business and turning it into something that I have

SPEAKER_04: to absolutely pay attention to. So I'll make the commitment to customers on this call. Like, we are laser focused on data integrity, not sharing your data with others, being incredibly focused on that and ensuring that your data is segregated and your data is, you know, is not shared broadly. And like, this is actually a commitment that customers asked me. They're like, hey, like, look, I want to make sure my data, all the alpha that they have from their own fund level data, like we are not sharing that. And so, um, I might be, I might be bucking the trend here, but I'd rather them be like, you know, keep their data siloed. Even in an aggregated, you know, de-anonymized,

SPEAKER_22: blah, blah, blah, blah, blah, blah, all that. That's not, not something we're focused on right now. Well, that's disappointing for me as a journalist, but that makes sense for me as a customer.

SPEAKER_110: That's okay though. That's good. You know, I got to, you know, who's my boss at the end of the day,

SPEAKER_55: the CFO. Yeah. Well, I mean, that's true. That's true of every company though.

SPEAKER_53: Yeah. CFO of an investment firm. Yeah. There you go. All right. Um, okay. So business model time.

SPEAKER_22: Now I know you guys charge, I think it's a BIPs off of AUM versus SaaS. Why is that the right

SPEAKER_01: approach for Hanover Park compared to more of a traditional SaaS approach? I know you've said, you know, B2B SaaS is dead, but why in this case? Yeah, we've, we've kind of taken the business

SPEAKER_04: model of the existing industry. And our vision for this is how do we deliver a premium product and service with an all-in-one bundle that is incredibly transparent from a pricing perspective. If you think about the legacy fund, if we zoom all the way out, you might want to do a capital call. You

SPEAKER_05: might want to do a distribution. They're going to say, actually, if you do four capital calls, not three capital calls, we're going to charge you per capital call. Right. That's like the old SMS plans on. Even more. Oh, if you do things that are outside our quote unquote scope of services, we're going to charge you some sort of extra hourly rate. Right. And so there is a lot of random hidden opaque fees that live in the market today that we've completely said,

SPEAKER_04: actually, here's the all-in-one bundle that we're laser focused on, right? That you can have that is obviously competitive. And we can talk about that as well, um, to be thoughtful of as well and

SPEAKER_01: bundle everything else in. So have you guys talked at all publicly about how many bips you charge off of AOM or should I just do a kind of a guess? Yeah, we, we don't, I'm not sharing that information

SPEAKER_05: either. I love, I love this Alec, like in the pre-call Alex was like, Hey, like, you know,

SPEAKER_140: what's your revenue? I'm like, come on. I asked it way more slyly than that, but I have, I have one

SPEAKER_75: more for you. The AI revolution isn't just creating new tools and new products. It's reinvented the entire landscape when it comes to compliance. Startups face an intricate patchwork of overlapping rules and regs from the EU, the United States, federal agencies, everywhere. It's coming at us from all angles. And if it sounds like a lot for you to track while you're also trying to build your business, well, you're right. And that's why you need a reliable trusted partner like Vanta, V-A-N-T-A. Vanta's AI powered platform automates your entire compliance process. Whether you're preparing for a SOC 2, running an enterprise GRC program, or doing an audit, Vanta is going to worry about the security. So your team can focus on building great products. That's why some of our favorite companies like Ramp and Writer, and they're both doing great, are spending 82% less time on their audits by working with Vanta. Whether you're a fast growing startup or a global enterprise, Vanta is here to help you automate your security and compliance and earn and prove trust. So get started today at Vanta.com slash twist. That's V-A-N-T-A dot com slash twist.

SPEAKER_01: If Hanover Park took, for example, 25 bips off their AUM and they have 20 billion in AUM today, that's about $50 million a year in run rate, just to kind of put a marker on it. The number might be 50, it might be 15 bips, we don't know, Chris can't tell us. But that's just a data point for folks, because the 20 billion AUM number I think is a little bit in the clouds for folks. But when you kind of think about it in revenue terms, it's quite a lot of money. Now, you were at $15 billion in AUM in March when you raised your last round, 27 million, and you were at 1 billion AUM 12 months before that. So you've gone from 1 to 20 in essentially 15 months. What does the future of growth of the company look like? How many people are on your list to bring on to Hanover Park in the future?

SPEAKER_04: Look, I think we're, so today the team's 50 people. We've been scaling the team exponentially. We doubled the team in the past quarter as we think about scaling and being ready for the future. You know, all we care, I told the team the other day, I said, there's only one thing that matters

SPEAKER_05: at the end of the day. In an industry where people generally, you ask a CFO what they think about their fund admin and they start cursing at you because they're upset. If we build a product and service where they are a raving fan of Hanover Park, nothing else matters. Right. And

SPEAKER_22: so that's the focus. Yeah. So, I mean, in terms of growth, does this company grow its AUM like 2X a year or is it more like 20? Because I know there's $100 trillion in assets out there. You guys only have 20 billion of them, which to me implies you have years of hyper growth ahead of you.

SPEAKER_00: There's a lot of opportunity to launch new products and services, new asset classes,

SPEAKER_05: new geographies. There's, there's a lot going on there, but I'm not going to give you a growth

SPEAKER_150: target. What does the applicability of the model you built now or the product you built now translate

SPEAKER_01: to let's say commodities. If you're moving, you know, elsewhere in the world of finance, because I presume those are quite different than, you know, firms that are doing venture capital

SPEAKER_22: investments. So is there a lot of work you'll have to do to, uh, tune Hanover Park to fit other asset

SPEAKER_00: classes? Me and my co-founder CTO talk about this on this daily. It says, how do we build an ERP

SPEAKER_04: that's extensible and modular to every asset class in the world? Today, we're focused purely on closed end funds. Think venture capital, private equity, and private credit. There is a massive market there. We're really excited about that. We're obsessively focused on delivering for those customers, but we think about the future of what does Hanover Park look like in five years, 10 years, 20 years,

SPEAKER_106: and we think about extensibility. I'll be curious to see what the Hanover Park for the oil market looks like, you know, that would be, that would be very interesting.

SPEAKER_22: HP, HP oil. Okay. Rockefeller. No, why not? I mean, well, it worked out pretty well for them,

SPEAKER_01: I heard. Um, one last question for me then. So let's say you kind of solve the, the asset management game and you have built this kind of financial operating system for how a business kind of deals with money in and out and so forth. To me, that feels pretty generalizable. Um, do you guys ever think you'll end up kind of like butting up against companies like ramp and taking on more of the customer of the fund, like the startups themselves, any of their business

SPEAKER_22: operations, or do you plan on staying pretty much entirely focused on just the asset manager side of

SPEAKER_00: the equation? We're focused on asset managers. There's a hundred trillion out there as, as you, as you've said a few times, there's a, there's a lot of room to run. Um, and we're focused on the asset

SPEAKER_22: manager for now. All right. Well, in six months when that's no longer the case, come back on,

SPEAKER_08: tell me about it. And, uh, we'll be keeping a tab on your AUM number. And one day I will squeeze the bips number out of you. Uh, but Chris, thank you so much. Well, what's the website and, um, is there a role you're looking to hire for? I see you have a tweet looking for a chief of staff.

SPEAKER_05: Hanoverpark.com. Very simple, straightforward. You can go to our careers page. You can ping me on Twitter at Chris Hillad. If you're interested, email me, I'm not gonna put my email in this, but Chris at Hanoverpark.com just did it anyway. Uh, you can ping me. Um, yeah, we're hiring a chief of staff. We're in hyper growth. If you want to go parachute into special projects and figure some stuff out,

SPEAKER_157: join us. All right. Thank you, Chris. We'll talk to you in six months. Talk soon. All right. Welcome back to twist. We're here. I'm joined by Alex Wilhelm. Alex, how you doing? Oh, fantastic. As always. I am Lon Harris. Of course, Jason, not here, but he's in this classic twist clip that we're about to take a look at right now. This comes from the memorable date,

SPEAKER_159: Alex. I feel like everybody remembers where they were when this episode came out March 27th, 2020.

SPEAKER_156: Yep. Yeah. What was going on around then? What, what, what was the news item? And I can't recall

SPEAKER_157: exactly a week, which will live in infamy. There was the people were getting sick. That hospitals

SPEAKER_159: were getting overloaded in New York. There was this Corona virus, this novel Corona virus out there. I don't know if you remember it, uh, a little disease. We call COVID. Uh, and it was, it was brand

SPEAKER_157: new and we will take a look at one point during this segment of some fascinating, very wrong

SPEAKER_159: predictions for March, 2020 about where that was all going and what was going on there. But I don't, we're not trying to bring you down. We're not trying to depress. No, this is a fascinating interview. Barely touches on global pandemics, uh, which I realize is they're all global. Um,

SPEAKER_157: Dylan field, the co-founder and CEO of figma is Jason's guest on this March, 2020 clip. And what's so fascinating and a theme I think Alex will come back to a few times while we're going back and reviewing highlights from this. Uh, so fascinating to look at a clip from, you know, the, the peak SAS era when, you know, that, that was what all of the huge tech companies were doing. They were all selling the software. That was the, the hot venture category of the time. And to look at it now from the sort of SAS apocalypse perspective, when AI is kind of filling all of these roles and yet figma, you know, still very much a player in this world. Absolutely. I mean, they went public recently.

SPEAKER_08: They're worth, I think $13 billion today, but this clip comes two years before Adobe offered $20 billion to buy the company. So we are going very far back in time. This is before figma became the Goliath that is today before it became the market crusher back when it was more of a question

SPEAKER_157: mark instead of the exclamation point figma. For those of you who don't know, they're a SAS company providing a collaborative platform for UI and UX design and product development. So basically

SPEAKER_159: in the pre AI era, this was a place where designers could go and sort of lay out what they wanted to do with a new feature or a new webpage or a new product and sort of get it all together in terms of the architecture and the design and make everything look nice in a collaborative workspace. Today, obviously now it's had to be dressed up with all sorts of AI tools. They recently launched

SPEAKER_157: an AI agent that allows you to build with it sort of vibe code, your designs, which is they're hoping going to open up the design process to people who aren't naturally designers, maybe people who

SPEAKER_159: aren't even creatives so that the whole company can kind of participate together in the process of

SPEAKER_167: putting these products and designs together. Because there's nothing a designer wants more

SPEAKER_157: than more cooks in their kitchen. Yeah, they were, they were still sort of a scrappy startup in this era. And I think that's what's so interesting to sort of look back. So we're going to jump to about 20 minutes into the interview. Jason has Dylan explaining the bottom up go to market strategy that Figma was employing, basically allowing people to start using the product within companies. You don't have to sign up your entire organization right off the bat. It's not a thing everybody needs

SPEAKER_159: to use. You can allow it to sort of gather some organic heat within enterprises, and then team members can share it and evangelize with other team members. And that's how they grow. So let's take a look, starting at 21 minutes in at Dylan discussing how they go to market for Figma.

SPEAKER_169: It's the worst nightmare of every founder, you've built a product, everything's working great, then real users start flooding in and suddenly it all breaks. What a disaster. You need to get it back up and running. And you got to do that fast. You're looking like an amateur. That's why you need a partner like Sentry. Applications can break in many different ways, but Sentry sees everything. You'll get all the relevant details like stack traces, commits, releases, and even the developers who push that problem code in the first place. With Sentry, you're not going to be jumping around between different tools, trying to figure out what happened. And Sear, Sentry's AI debugging agent, uses all this data and context to identify the root cause of the problem and suggest a fix. It can even take a look at your code before it ships and warn you if any problems are likely. Try Sear and Sentry for free. If you're a This Week in Startups listener at Sentry.io slash twist, use the code twist for $240 in Sentry credits. Make sure you use that code, make sure you use that URL, Sentry.io slash twist, so they know your uncle J Cal sent you.

SPEAKER_174: Your organization are able to adopt it and they're able to spread it without having to be to like necessarily get a lot of buy-in from others around them. And you know, if you're able to do that

SPEAKER_176: on a credit card and people are able to be empowered to actually get their own tools, hopefully they're able to first trial Figma, for example, for free, and they can go like have a purchasing conversation with somebody if they need to. That's like our ideal scenario is they're not even being paying for it. And they're like, this is actually really good. Like, let's go bring this into the organization. Let's have this entire team on this. And for what it's worth, we also see a lot of people spread Figma when they change jobs. They'll bring it with them. So, you know, people are popping between jobs every few years and they're, they're bringing the tools they like. But anyway, so to go back to the question about bottom up and legal and sort of what the buy decision looks like, we're seeing a range of behaviors right now. There's definitely a ton of companies that need to spend multiple months or whatever, evaluating software, go through a rigorous process, especially at larger corporations. And we've got a great, amazing sales team that's like able to partner with them on that.

SPEAKER_180: Got it. What is their main concern? Like what are they trying to accomplish with all that friction?

SPEAKER_176: Something like security is a big one. So I want to make sure that if you are a cloud provider, that you're going to be as secure as possible. And so that's something that like, for example, we've gone through like the SOC 2 process now, which is, it's basically just a process to make sure that you're able to be as secure as possible, even though you're hosted in the cloud.

SPEAKER_184: So you have all of my designs, I'm, I don't know, Nike or something, and I'm building a bunch of stuff.

SPEAKER_185: I have to trust that. I have to trust that your people are not looking at my designs,

SPEAKER_187: leaking it or selling it, or the Chinese government or the Saudi government hasn't put a plant into Figma like they did at Twitter. The Saudis actually did this. You hear that story?

SPEAKER_176: No, I did. Crazy. Yeah. And so there's SOC 2, and I was simplifying before it encompasses a wide variety of controls,

SPEAKER_191: everything from like hiring offer approvals, all the way to like, how are your servers run and what are your run books for those? Oh, really?

SPEAKER_157: Yeah. A lot of interesting stuff going on there. I mean, the thing that jumps out to me, Alex, so much about this is we're still having these same kinds of discussions in the AI. This

SPEAKER_159: was obviously the pre AI era. People were not worried about Figma training models based on their data. They were just worried about Figma looking at their data, getting inspired, building competing

SPEAKER_157: products, you know, like it was a, it was a different time and yet it was so much of a similar concern.

SPEAKER_47: Well, also it's interesting because at the time, if you're concerned about say Nike stealing your designs, you're thinking about kind of a one-off, like you're stealing that set of designs in the AI era. If you steal everyone's information, you can create a model that can replicate them at scale with frequency. So it's actually, I think a higher risk now, but it's interesting that it was still so important at the time. But going back to the top of that clip line, the whole concept of bottom up sales was kind of a Dropbox invention. If you go back and start up history, the idea that people would just buy something and start using it, then their company would say, oh my gosh, we have 28 users of Dropbox. We need to manage this, sign up for an enterprise contract, revenue flows, everyone's happy. And that was an engine that powered SaaS for a long time. It lowered customer acquisition costs, provided a lot of strong net dollar retention, all those acronyms, CAC, NDR, that investors used to love. But today, fast forward, you know, six years,

SPEAKER_120: and we're still talking about people bringing AI tools into their company, driving usage,

SPEAKER_157: wanting to run, you know, enterprise control. I mean, the granola, I feel like is the most recent example where even, I think we had a VC on the show talking about it, where it's like,

SPEAKER_159: they decided to invest in granola because so many people around the office were already just using it without being asked or told. It just, these things sort of catch on, on their own. And that, and that's always, I mean, that kind of word of mouth viral spread is always going to be more powerful than your boss emailing you like, Hey, install this tool and start using it. Like that always feels like a chore. No, it's the other way around. Whenever

SPEAKER_120: a CEO tells me to use a tool, I just presume it's dumb. Like I'm just like, Oh, it came, it came from above. Oh God, someone bought this. And now it's been rolled out to me nine months later with half

SPEAKER_35: the implementation that it needed, you know? But if a friend goes, Hey dude, are you in a hurry? Use this. It'll save you seven steps instantly. Exactly. I'm reminded, I'm reminded of the late,

SPEAKER_159: great gummy search. One of my favorite AI tools that no longer exists where it was a way of just like cruising through Reddit and like zeroing in on exactly the five posts that you wanted. It was revolutionary. And I never would have tried it except a different person who worked on a podcast was like, Hey, if you're using gummy search, it's the best way to find Reddit posts.

SPEAKER_120: Like we have a lot of internal tools we've passed around behind the scenes to make twist happen.

SPEAKER_47: Uh, one more note for me on this. Sure. He was talking about how at the time, you know, you still had to go in the enterprise sales process, go to a company and it could take months to get

SPEAKER_22: purchasing orders and you know, all that stuff, which is still true to a degree, but the vibe that I got from him was companies not in a hurry. And I think a difference between that era and today

SPEAKER_47: is every company today is sprinting, trying to figure out what's next, what to reinvent, what to cut, what to invest in. Uh, and so I, I wonder if he's seen kind of the enterprise

SPEAKER_35: buying process for AI today versus SAS, then become compressed. I wonder if it's a, a faster

SPEAKER_157: cadence process today. Yeah. I mean, I feel like it's one of those situations where it's like

SPEAKER_159: SAS led the way, like these guys figured out how to sort of worm into enterprises and get people excited about what you were doing. And now AI is like taking that model and, and replicating it and making it faster and tighter and more efficient. So what used to take months now takes weeks or days. I think that's what we've seen is everything's sort of, they figured it out and now it just got

SPEAKER_206: like massively compressed. Uh, and speaking about things that got massively compressed, don't forget there was a company called delve. I think its reputation was compacted after it's,

SPEAKER_22: um, alleged scandal. Let's say we covered it on the show a lot. I'm not going to go back over it, but I just love that Dylan's walking Jason there and Jason already knew, but walking the audience through what is SOC 2? Why does it matter? Some things, no matter if it's the SAS era or the AI era,

SPEAKER_208: do not change. And that is, you will have to get the SOC 2 report.

SPEAKER_159: Yeah. And, and it, and no, it's never a thing that companies are excited about doing or looking forward to. You just find another provider and you sort of, you work with the, the vantas of the

SPEAKER_211: world to sort of take care of it.

SPEAKER_205: I was about to say, I'm going to, I'm going to throw a bone to our sales team. This is not in the script, but, uh, vantage.com slash twist. If you want to save a thousand dollars off your

SPEAKER_47: SOC 2 report. All right. Next clip here, we hear a lot about SAS overload and SAS burnout, really key concepts at the time as tools proliferated. Let's see what the two had to

SPEAKER_185: say at the time. Burnout. I, during this COVID crisis said, that's it. Give me a list of every

SPEAKER_215: single SAS product. Yep. Then I said, there's a website, uh, called privacy.com and another one

SPEAKER_185: where you can set. Cause I just saw a SAS provider just whacked us for $1,200. And I guess they had increased their price and they assumed we had all these accounts. They were doing kind of the, the gnarly thing where they charge you for accounts, but not usage. Yep. Dirty.

SPEAKER_187: And that really upsets me. Cause I like Slack's model where they're just like, this is how many

SPEAKER_174: people you use. So I never, it's very divisive because some people like Slack's model and some people don't. I like Slack's model too. We're not doing it for Figma because we've actually heard people in vets that they don't like it. Got it. Cause it's, it's variable cost. You don't know it's

Chamath Palihapitiya: going to come. Explain the, the issue to somebody who doesn't understand what we're talking about right

SPEAKER_174: now. Yeah. So Slack's model is that you've got active user pricing. Um, now the question is like, okay, is there enough trust to know that there's an active user? Um, we've definitely

SPEAKER_176: looked at the model for Figma. Um, and it's something that I think could be really interesting. Uh, to me, it incentivized the right behaviors. Like if you get to the point where anyone could

SPEAKER_174: become an active user and then, uh, you only charge the people that are using the service actively, that seems like a good thing. It seems very easy to talk about. Right. Uh,

SPEAKER_185: so in Slack's model, if you are in a Slack room and you open Slack and the green light goes on, you get charged that month, even if it's for 30 seconds. Yep. I wonder if there's a, like a minimum threshold, like, yeah.

SPEAKER_174: Probably is. I don't know what it is. Cause I've always, I think like the,

SPEAKER_176: the sort of flip side of it for us at least is Figma. Like if you tried to rip Slack out, like you'd have like people protest, you know, of course, I just can't not even. So here, but they don't turn your account off.

SPEAKER_185: It's only if you use it. So for Figma, the equivalent would be if I clicked on a link and I opened Figma.com and I looked at something on Figma,

SPEAKER_176: right now. So viewers are free in Figma. Okay. Uh, so editors are the only ones we charge for. Great. So if you edit something, but we're not doing that yet right now, it's like, right now it's like, okay, if you're an editor, uh, you know, you can kind of restrict it before your next period. And if you restrict it, we kind of, we just assume that you're in good intention and not trying to like cheat our system.

SPEAKER_187: But if somebody came to you and was like, Hey, you have, you build this for three editors for the last six months, you would give them a credit, right? Uh, yeah.

SPEAKER_174: Yeah. If we, if we thought it was like really, uh, clear that it was wrong,

SPEAKER_228: but, um, but also, you know, if it's like, depends on the case by case basis too,

SPEAKER_185: this is what you gotta do is you gotta build the SaaS industry now has to build trust. I completely agree with that. They don't send a monthly notice of your bill by email. They should do that. They don't send the monthly recap of who used the product and Slack is the goal center. They send you your monthly utilization every month.

SPEAKER_229: Yeah. So I love that about Slack's the trust part.

SPEAKER_22: So Lon, I love so much of that clip, but first of all, it really strikes me how thoughtful Dylan is about pricing,

SPEAKER_47: trying to understand what his customers want. He's even applying a pricing model to his company that he doesn't really favor, but he's listening to his customers and saying, okay, this is what they want. I absolutely love this clip. I think it just shows the difference between a leader who does only what they want or a leader who does what they think is best, but also has at least one ear to the customer.

SPEAKER_157: Yeah. I mean, we talk a lot, I think about whether the incentives for a company

SPEAKER_159: and its users are like aligned, like a lot, a lot of businesses are, you know, like ramp. That's like their whole thing is like, we, you want to spend less money. We also want you to spend less money, unlike a credit card, like our interests are aligned. And I think that's, that's what's sort of interesting about this is you would normally think of these kinds of SaaS companies as well, they're it's adversarial. They want you to have more team members using more of their product for more time so that you're spending that much more on the product every month. And you can't extract your business sort of out of it. But I think, yeah, this is sort of like, well, what if we sort of played on a more of an even playing ground so that everybody felt good about how much they were spending in their Figma budget. And obviously again, a huge conversation that people are having right now, only about tokens

SPEAKER_157: and compute and AI, like everything in this clip comes back to like the SaaS industry and the AI industry are really, it's, it's not so much AI SaaS-pocalypse destroying this old industry so much as it is just kind of like disrupting it with some new kinds of tools.

SPEAKER_22: I think also the progression and how startups charge for things really did ding the SaaS model. Because in the old days, you know, as Jason said in that clip, you get a new contract, say every year or every three years, depending on how long you sign up for. And they go, good news,

SPEAKER_47: we added all these features and it costs twice as much. Good luck ripping it out of your life. And you're just stuck eating the price. Now for startups, that was net dollar retention. It was companies spending more over time, that magical SaaS revenue growth that everyone just loved. And then things began to change. So I think the, the, the movement from selling software in a box to selling hosted software on a per seat basis, then to active user pricing, which is what they're discussing in this clip. Right. And then from there, we've gone today to usage based pricing tokens, as you said, and people are now saying the next progression is going to be outcome based pricing. What did you do for me with all that code with all that tokens? Right. And then charge me for that. So I think this is one step along a larger journey that we've been seeing, but I just love to see how we're talking about it at the time, because I can't recall the last time someone said, we have to cut our SaaS spent. That doesn't come up. Right. Instead, it's exactly what you said. It's dear God, did you see our clog bill?

SPEAKER_156: Yeah, that's right. It's token maxing. There was no Figma maxing back in the day.

SPEAKER_47: No, I mean, what is that? 13 extra seats that you paid for? Okay. Email the CEO, get a credit, whatever. But you can't email Dario and say, Dario, can I take back that 10 million dollars in tokens, man? I didn't mean to. It was a big accident.

SPEAKER_234: Yeah. We didn't end up shipping any of those products. They were just, they just look nice.

SPEAKER_35: As a very inefficient AI user, I'm sympathetic to people who are complaining about it, but also like, you got to pay for the servers one way or the other. Exactly.

SPEAKER_47: Now we're going to get back to this interview and we're going to go back in time to one of the first things that I knew Jason for, which was, and I think it's fair to say his ill-fated search engine, Mahalo. Now, Lon, weren't you part of that product to some degree?

SPEAKER_157: I was employee number three at Mahalo. Funny enough that you should say, this was the first job that I ever got. I was working at a video store in Rancho Park, California, a small community in Los Angeles. And I saw a Craigslist ad. They were looking for writers

SPEAKER_159: slash researchers for this new website. So I went to what I later found out was Jason's pool house in Brentwood. And I interviewed with Mark Jeffrey, still a frequent friend of the pod,

SPEAKER_157: now of still core capital. He was the sort of the, the editorial director, the chief technical officer of Mahalo, I guess you could say. Uh, and so, uh, yeah, that the, the idea was Mahalo was this alternate to Google because to take you back in time, folks in 2007, this was around the time people first started to notice, you know, Google results, they're kind of not as reliable as they once were originally when Google first launched, it was like a magic trick. It finds exactly what you want. But over the years, there would be a lot of ads at the top. They were pushing a lot of the best results down, or there were a lot of these like content farm SEO pages that were crowding out the best stuff. So Jason's classic example back in the day was what if you search Paris hotels, the old Google would give you your top page would be here, 10 great Paris hotels that are good options, or maybe Yelp or TripAdvisor or something. But now you would get all these like travel blogs and like, you know, random ads, whoever paid to be on the first page of Google. So that was Jason's observation. And the idea was we were going to have all of these, I'm sorry, I'm sorry. Okay. The idea was we were going to have all these like random writer researchers, guys like me who were screenwriters or creative writers or people in LA who needed writing jobs. And they were going to do the research and make the perfect search results page by hand for things like Paris hotels. The first page I ever made for

SPEAKER_159: Mahalo was for Bob Dylan. You know, so you put a little bio at the top and here are the 10 best YouTube videos. And here's a little history. And here's a great interview you did with Rolling

SPEAKER_157: Stone. And here's another recent piece about whatever. And you know, you we'd scope those.

SPEAKER_47: Yeah. Yeah. So let's see the story about how Jason Calacanis's idea for luxury communism for partially employed Hollywood screenwriters worked out. Well, I do think there's one more vital

SPEAKER_156: piece of context for this clip. I didn't mean to get into a whole story time. The vital piece of

SPEAKER_157: context here is that for a while Mahalo actually worked because we started ranking well in Google

SPEAKER_159: for these pages. We were doing SEO correctly. We were writing about popular topics like musicians and destinations or whatever. So for a while it was a sustainable business. Thanks to Google, the the plate thing we were trying to replace ultimately. And then now, Jason, you can hear describe what happened, the downfall, the reason it stopped working. We're like a high school kid. Yeah,

SPEAKER_176: I have a Mahalo mug. Or rather, my mother has Mahalo mug. That is hilarious. Thank you for my PTSD.

SPEAKER_185: Sorry. Mahalo was like my failed stardom. That got to 10, we were at $10 million a year. Wow. In run rate, before Google just said, Mahalo, eHow, how stuff works. Yeah, that was a big change. Answers.com. You all are ranking too high and off. And they took 80, 90% of our traffic overnight. Then they took the answers from our websites and put them in the one box five years later. And now when you go to Google and you type in how many people died of coronavirus, they put the number up top. Yep. That was literally the idea for Mahalo. I'm sorry to trigger this. And I look back on it and I just think, wow, what a sinister group of people. Matt Cutts and these guys lied and said, we were web spam. When we did everything according to the books, we would index pages only when they hit 400 words or more because they were like, oh, there's too many stubs in there. Like people are coming to landing pages that aren't filled out like a short Wikipedia page. So we're like, fine. I told Matt, we'll just no index anything under 400 words, everything above 400 words, then we'll index it. We'll just break the software to do that. Yep. And he lied to my face. And they literally, if there's somebody who wants to do an antitrust, just go back in time to them pushing Yelp down, putting eHow, Mahalo, everybody else out of business or moving them down the page and ankling them and then replacing them with the one box. And the sinister thing is they use their technology to find the answer on your page and then put an abstract on the top. And if you opted out of that, they wouldn't index you. So they gave you no choice. It was like one of the most sinister moves in the history of, it taught me a lot about business, which is when you're up against one of these big companies, they will lie to your face. And it doesn't matter who you knew. I knew Sergey, I knew Larry, I knew Marissa, I knew everybody at the company. And I called them all. And I was like, I have to lay off a hundred writers who are working from home for $15 an hour because you just took 80% of our revenue away. And we've been partners for years. What are you guys doing? And they were like, yeah, we don't know who's in charge.

SPEAKER_47: I'm like, so Lon, it seems like there was a good idea. It didn't end up working out and Google somehow had the ability to pull the strings and platforms had a lot of power. Things have changed so much

SPEAKER_156: in the last six years. I mean, what was it like knowing what I know now when Jason hired me to do

SPEAKER_159: Mahalo, I knew very little about how the internet works or like I had never heard the term SEO. Like I used the internet, but I was not, I was a movie guy. I was not a tech guy. So it sounded like a really good idea to me when I first heard it, I was like, oh yeah, Google does kind of suck a lot of the time. These pages are a lot better. But what I didn't realize, like the big lesson we learned at Mahalo that I think is interesting. And then I will stop distracting everybody was that

SPEAKER_157: most of the big search terms at any given day are not actually things like Paris hotels or, or Bob Dylan. They're things that are trending right now. Like that's what everybody was going to Google and searching for whatever the scandal of the moment was, whatever the hottest pop song was, or on Superbowl day, they're looking up the big Superbowl commercials that are just on TV. So we were race constantly racing against the clock to make pages in time to catch the tail of, you know, Google trends and rank highly for them. And so it was, I don't think ultimately it was like very sustainable, but for a short time, it really was working. And we got enough SEO live

SPEAKER_159: from those pages to make it profitable as just kind of like a destination site on the internet to look

SPEAKER_156: things up. So Mahalo walked so Grokopedia could run. Right. I mean, and I think Jason listed us with

SPEAKER_157: a lot of like, you know, sort of lower quality, like eHow and HowStuffWorks, which are kind of content mills. Like there were a lot of competitors like that that were just churning out. We had like freelance writers getting paid pretty handsomely by the hour to really write good quality pages. So I don't think we were, we weren't trying to do like, you know, like, like we got swept up in that like low quality garbage spam site sort of call. And I think that's what Jason's objecting to is like, aren't we were, we were really trying to make better quality content than that. The whole idea was to

SPEAKER_170: make better pages than Google. Like that was the concept. Well, I don't think that was a very high bar

SPEAKER_22: to cross, but what Google has done is consistently optimized for monetization. Right. User experience be damned. And I think we've all kind of seen the results of that, which is today, Google essentially thrown in the towel and gone, what if it's all just AI? Right. What did we say? And that's exactly what

SPEAKER_157: Jason is already complaining about in this clip. Like Google was basically scraping and looking at everybody's website, taking the information, putting it at the top of the page in their own results. So

SPEAKER_159: you didn't have to leave Google and you didn't have to click away. And now they're just, we, you know, Gemini is just the most sophisticated version of doing that ever, where now it literally can just explain everything to you having been trained on the entire corpus of the internet. And it doesn't

SPEAKER_120: need to link you to anything. Frankly, I think the most important company in the world is whichever company beats Google at AI, because if Google ends up owning the AI market, as well as the historical search market, then I think they become essentially the arbiter, not only of truth, but of speech.

SPEAKER_157: This is sort of a bit much for a single company. This was honestly, Sam and Elon's like open AI

SPEAKER_159: original spark of an idea. Like they were, they were like, Google can't control this. We need to

SPEAKER_167: come up with a better system. Well, I mean, Google doesn't come off looking great in Jason's story. So maybe they were right to think that Google, the company that drops the don't be evil slogan may

SPEAKER_159: be up to some shenanigans. It is. I think we all can concede that it is possible. And I mean, we were not the only company that got wiped out in that. I think the Panda update is what Google called it. Like thousands of businesses were just like decimated overnight because Google decided to like change the algorithm, change how page rank worked and flip a switch. So it really was like

SPEAKER_267: so much power collected in just the hands of a few people. It is kind of scary. Thinking about things

SPEAKER_206: that scare us, Lon, why don't we rewind the clock to everyone's favorite public nightmare, the COVID

SPEAKER_47: crisis. Now at the time of this clip, we knew a lot less. So we're not here to just, just poke fun. Lon is here mostly to poke fun. I'm here to provide. That's my job. I thought

SPEAKER_200: I was the funny one. Anyways, here's a clip of Dylan and Jason talking about COVID before we knew much

SPEAKER_271: in the early days of lockdowns. Now that you're a work from home company,

SPEAKER_185: and you obviously did not, you were not all in for work from home. You believe in people being in the

SPEAKER_228: office and collaborating. I think it's great for people to be in physical spaces together.

SPEAKER_215: Yeah. So you were not bought into this like other people are. Let me define that more. So I think

SPEAKER_176: bought into the possibility of it, but still think there's great benefits to being in an office.

SPEAKER_274: So how does that change when this crisis ends in, I think, April 15th?

SPEAKER_275: Oh, man. I think that'd be awesome if it's true.

SPEAKER_187: I think Apple's opening their stores in the first two weeks of the rumor. And I don't know if it's been confirmed yet, but I heard some inside information. They're going to open Apple stores in the first two weeks. I think restaurants are going to start opening again, April 15th or so in that time. Sadly, no. I think Trump said something like we'll be back for Easter. So I think people are going to get the test results back. We were sitting here on the 24th. I think people, last week was peak fear. Oh, man. In my mind. It could be this week for people, but I was experiencing peak fear last week. Bummer.

SPEAKER_278: I don't want to be a downer here, but should I be?

SPEAKER_279: Yeah, do it. Nobody knows. I mean, that's one thing we've learned here is nobody knows.

SPEAKER_176: I think that we're going to see, I hope that for California and for other places that have put more restricted measures in place earlier, that we'll see sort of like the stabilization, the fact that you're talking about and hospitals won't be overloaded. I don't think that means that we can all just go back to work and go back to the way we were living before because I think we'll see a second wave effect where there still is the virus out there and we'll start to see it spread again. And then hospitals will be over later then. So I think the-

Chamath Palihapitiya: So what do you think? You think San Francisco, there's a chance San Francisco Bay Area, San Mateo County, et cetera, says two more weeks of this, four more weeks of this?

SPEAKER_176: I think it could be a lot longer potentially. And I think there could be- All the way to May or June? I don't know. I'm not sure. But I think that there's also potential for if we start to see people disregarding the orders, I wouldn't be surprised if we see enforcement. Yeah. I think people aren't even thinking about right now. Yeah. But it's- I wouldn't be surprised.

SPEAKER_285: It would be civil unrest on a level that would be disturbing.

SPEAKER_176: I don't know. It depends on how people think about the situation. But in any case,

SPEAKER_174: going back to our sort of arc.

SPEAKER_120: So Lon, this reminds me, I had this conversation with my mother-in-law. We were at my in-law's

SPEAKER_22: house. It was March around this time, probably plus or minus two days. And we were all sitting

SPEAKER_47: around trying to figure out what was going on, what was going to change. And at this time, no one in the States wore a mask, ever. He's also wearing a mask. He thought they were robbing a bank. It was that rare. So we were getting used to wearing a mask here and there, trying to figure out, are cloth masks good? Remember those days, buying them on Etsy? And we're sitting around talking about this. And I'm like, you know, maybe a couple of months. People

SPEAKER_08: say maybe a couple of weeks. My mother-in-law goes, 18 months. And we all looked at her like she had just fallen off the planet. Like we just didn't believe it. And then it was crazy. It was 24 months.

SPEAKER_157: No, yeah. I mean, Jason says, I think what, like, it sounds crazy to hear now in retrospect,

SPEAKER_159: but in March, we all thought June was like outside. Maybe, maybe. Maybe. Unbelievably far out. Maybe we're still, we're still doing some of this stuff in June, but that would be like anything longer than that was considered. Like you're hysterical, you're paranoid, you're a hypochondriac. Like no. And I clued myself, like nobody thought it was going to last beyond May or June. It was, it was unthinkable to us that, that it could get that bad.

SPEAKER_47: Yeah. I'm glad that Dylan was a little bit more bearish, a little bit. Amazing. Almost prescient. But he said, you know, if we go back out, there'll be a second wave. I mean, there was more than two, but he was looking ahead there. Yeah. Yeah. I, it's interesting how the COVID moment changed so many people's thinking patterns. Yes. It really, you know, it does seem to have been a moment of, uh, of real change. And a lot of people didn't take the lessons that I took from it.

SPEAKER_156: It is also interesting to go at the very beginning of the clip where the people want to work remotely

SPEAKER_157: revolution, it, it, in, in our minds and sort of pop culture memory that and COVID are inextricably tied. Like that was what everybody started working from home because of COVID.

SPEAKER_159: And then it just kind of never all fully went back to normal and people got used to it or whatever. But at the very beginning, you could see way before anybody would be thinking about like COVID is going

SPEAKER_157: to permanently change the nature of work in America. They were already having that discussion of like, what do you think about this work from home revolution? So like, it does kind of go back and clarify, like these were actually like COVID accelerated a trend that was

SPEAKER_159: already happening, which was telecommuting and like zoom and apps like Skype at that time or whatever were allowing more people to work remotely. And it was already a conversation that was going on. Do you think your team could do as good a job from home as they can in an office? And then COVID just massively like lit a rocket under that revolution. And now everybody works from home.

SPEAKER_303: Yeah. I find it really funny because I had already been working, you know, from home for a half

SPEAKER_22: decade at that point in time here and there, I'd had some office jobs. I had some non-office jobs. So I lived both sides of that coin and people were talking about working from home is this revolutionary idea. And I was like, well, no, it's just, it just work. And there's just not someone sitting next to you. But it became this enormous touchdown of people doing the day in the life videos on Tik Tok back in the day. Yeah. Oh man, people really blew up some comfy jobs. Didn't they?

SPEAKER_47: Yeah, for sure. Never tell people when your job is easy. They'll give you more work or fire. Yeah.

SPEAKER_170: No one needed to know how much time you're spending every day refilling your Stanley mug. I don't

SPEAKER_22: think. Yeah. No, we don't need that. Also, Dylan, when you see this, we'd love to have you back on. Come on the show soon. We'd love to talk about where things are now and your AI agent. But

SPEAKER_47: Lon, a excellent trip down memory lane. We're going to keep pulling out these epic moments when we can. We do them here and there when Lon and I have the time, but I love that you found this one. I love Dylan. I love Figma and I hope that they just crush it because they've had two good quarters in a row and I'm watching those earnings. There you go. Thanks everybody for joining us. We'll see you next time.