In short
Hanover Park’s AI-native fund operations platform replaces legacy fund administration “human duct tape” (QuickBooks/Bill.com/Excel run by accountants, often in Kentucky) that forces funds to request their own data for reporting.
Guest backgrounds
Chris Haloncic, CEO and co-founder of Hanover Park. He describes building an AI-native services company starting in 2024, with engineers working alongside fund accountants (no product managers/designers).
Key claims
Fund admins often buy software access but don’t provide easy data access, creating “data hostage” workflows. Hanover Park built an end-to-end system of record (ledger/ERP) plus AI agents with memory for accounting/reporting, capital calls, distributions, and later portfolio/LP monitoring. “One-click migration” of fund data is now feasible (released ~3 weeks ago; possible with Opus 4.6-era models).
Notable examples
Complexity like Blackstone-style multi-entity funds, profit/loss allocations, and mapping limited partnership agreement terms (PDF/Docusign) into ledger rules; example tracking “post-money in Uber’s latest round.” CPAs act as CFO advisors reviewing edge cases. Hanover Park charges BIPs off AUM and emphasizes data integrity and non-sharing.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Chapters
Tap a time to open that second in VOIntroduction to Fund Management Issues
0:00 to 0:30
Explore the challenges in fund management leading to inefficient operations.
“How did we end up in a world with$100 trillion in assets and a terrible fund management stack?”
The Duct Tape Problem in Fund Operations
1:45 to 3:40
Understanding how outdated technology hinders fund management efficiency.
“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.”
Hanover Park's Innovative Approach
3:40 to 5:42
Discover how Hanover Park aims to revolutionize fund management with AI.
“So why wouldn't these funds, which have quite a lot of AUM, just build their own internal stack?”
Complexities of Fund Data Management
5:42 to 7:21
Delve into the complexities of managing fund data and legal entities.
“Let's start with the ledger component of this, because you said it's very complex.”
One-Click Migration and AI Capabilities
7:21 to 11:34
Explore the advancements in AI that facilitate data migration for funds.
“We're only 20 billion of assets right now.”
Future Prospects for Hanover Park
11:42 to 14:00
Discussing the future of fund management as AI continues to evolve.
“We're not talking Blackstone size at this point.”
Exploring AI Fund Management Models
14:00 to 18:00
Learn about the implications of AI in fund management and the roles of CPAs.
“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 migrating a large fund, it's not going to take six days.”
Data Integrity and Customer Trust
18:00 to 21:56
Discover how Hanover Park ensures data integrity and customer trust in their services.
“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 to absolutely pay attention to.”
Business Model and Future Growth of Hanover Park
22:18 to 25:30
Understand the unique business model of Hanover Park and their growth strategy.
“And you were at$1 billion AUM 12 months before that.”
Future Directions and Hiring at Hanover Park
25:30 to 28:00
Explore Hanover Park's future directions and hiring needs amid growth.
“If you want to go parachute into special projects and figure some stuff out.”
Show all 28 chapters
Exploring Figma's AI Tools
28:00 to 28:41
Learn about Figma's AI agent aimed at enhancing design accessibility.
“Today, obviously, now it's had to be dressed up with all sorts of AI tools.”
Dylan on Figma's Go-to-Market Strategy
28:41 to 29:41
Dylan explains Figma's bottom-up approach for internal adoption.
“Jason has Dylan explaining the bottom-up go-to-market strategy that Figma was employing.”
Organic Growth and Team Adoption
30:19 to 31:16
Discussion on how Figma encourages organic growth within teams.
Security Concerns in the AI Era
31:16 to 32:15
Conversations about the importance of security in design tools.
“And we've got a great, amazing sales team that's able to partner with them on that.”
The Evolution of Bottom-Up Sales
32:15 to 33:41
Analyzing the historical context and current trends in bottom-up sales.
“A lot of interesting stuff going on there.”
User Adoption vs. Top-Down Mandates
33:41 to 34:26
Comparison of user-driven adoption versus imposed tool usage by executives.
“I mean, Granola, I feel like, is the most recent example.”
Accelerating Enterprise Buying Processes
34:26 to 35:36
Examining how AI impacts the speed of enterprise software purchasing.
“I'm reminded of the late, 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.”
Understanding SOC 2 Compliance
35:36 to 36:15
The importance of SOC 2 compliance in software security and trust.
“So what used to take months now takes weeks or days.”
Introduction to SaaS Burnout
36:15 to 36:31
Discussion on SaaS overload and its implications for businesses.
“You just find another provider and you work with the Vantas of the world to sort of take care of it.”
Reevaluating SaaS Pricing Models
36:31 to 42:01
An analysis of different pricing models and their impact on users.
“Here we hear a lot about SaaS overload and SaaS burnout.”
Token Maxing and Mahalo's Genesis
42:01 to 43:19
Explore the concept of token maxing and the origins of Mahalo.
“There was no Figma maxing back in the day.”
The Rise and Fall of Mahalo
43:20 to 46:18
Learn about Mahalo's journey from success to downfall at the hands of 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.”
Lessons from Mahalo's Experience
46:19 to 49:24
Discover the key lessons learned from Mahalo's business model and its challenges.
“how many people died of coronavirus, they put the number up top.”
Implications of Google's Dominance
49:25 to 51:26
Discuss the implications of Google's power in the search market and its evolution.
“I mean, and I think Jason listed us with a lot of like, you know, sort of lower quality, like eHow and HowStuffWorks, which are kind of content mills.”
Reflections on COVID and Work Culture
51:27 to 56:00
Reflect on how COVID changed work culture and the shift to remote work.
“I think the Panda update is what Google called it.”
The Impact of COVID on Remote Work
56:00 to 56:59
Explore how COVID accelerated the shift towards remote work and its implications.
“of pop culture memory that and COVID are inextricably tied.”
Personal Experiences with Remote Work
56:59 to 57:39
Reflect on personal experiences of working from home and the perception of work-life balance.
Closing Remarks and Guest Invitation
57:39 to 58:01
Wrap up the conversation and extend an invitation for a future guest appearance.
Transcript
Automatic transcript. May contain errors.0:00How did we end up in a world with$100 trillion in assets and a terrible fund management stack? 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 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 are holding your own data hostage. B2B SaaS was dead, 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.
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1:07Learn more at northwestregisteredagent.com slash twist. 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.
1:45Chris, how you doing? Let's go. I'm pumped for this. 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 a duct tape operation. So how did we end up in a world with a hundred trillion dollars in assets and a 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.
2:24They're buying QuickBooks, 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 penetration and run by a bunch of fund accountants in a room that are delivering 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.
2:54At the same time, a lot of SaaS companies want to hold on to that because it's 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 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, okay, we're going to buy access to QuickBooks, and we're not going to give you access to it, actually. You're not going to be able to have your own data.
3:19And so then you have to email them and say, hey, guys, can I have my own data for this random report I need to repull when I need to go fundraise 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 are holding your own data hostage. And so, you know. Why? Like, why is that a service people would pay for? To me, that sounds like giving someone money to slam the door in your face. So why wouldn't these funds, which have quite a lot of AUM, just build their own internal stack? Why outsource it to someone who hates you, I guess. Traditionally, it's like, it doesn't even matter because all they're doing is deliverance and output, which is that financial reporting that goes to your limited partners every quarter, your Harvard endowments, your Yale endowments.
3:56I went to Yale, so I can say that. And so they're just delivering an outcome. And so 10 years ago, CFOs 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 100 times more valuable because this is like the backbone for every investing decision you've ever made. And so now we're in this moment where everyone's like, I need my data back. All right. So tell me about the actual Hanover 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 help with fund administration.
4:27When 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 Chattapit. And so we started by saying, hey, we're going to go build an ERP for a fund. That in 2024, my investors started laughing at me. 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?
5:01And 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 distribution 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, 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.
5:31And 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 LP port. And there's like a stack that sits on top of the system of record for the fund is kind of 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?
5:53Well, 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 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 like the foundation for everything here. Totally. So think about Blackstone and think about like hundreds of billions of assets with tons of different entities that need to talk to each other.
6:19Think 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 going to toss into this thing called a limited partnership agreement to do that.
6:50And so herein lies the fund levels of complexity, and our job is to capture that somehow. So I'm thinking about a ton of contracts, 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? Is that done by humans, the translation process? Or is that something that AI can now handle based on its ability to reason? So if I take this in a different direction, imagine I go to Blackstone. They're not a customer, far from it. 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.
7:26He'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 of the whole time? So we built these long horizon agents to do financial data cleaning at 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. Okay, fine. No, no, no. Now you're in trouble. Now I'm going to call you on this. Define ontology for me. something that Alex Karp has yet to do once. Wait, should I pull an Alex Karp and say, I'm not going to define ontology.
7:57We're 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, it may be a working definition for how Hanover Park thinks 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 a given limited partner, portfolio company, et cetera. We take that information. We then translate that into a way in which our general ledger operates.
8:23Right. So that's like the simplest definition and we can make it we can make it more complex. Oh, that's fun. Let's make it more complex. Oh, boy. So beyond the simple stuff of like the how the limited partner relationship is with a given 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 fun 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, what's the post money in Uber's latest round?
9:00I got to say Uber because I'm on this week in startups, right? Jason gives you five extra bonus points and a high five. 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 maybe six months? Because it does seem that we've seen a pretty rapid increase in agenda capabilities, from what I can tell.
9:32So I'm curious how that's kind of manifesting inside your operations. For us, when we thought about what are the biggest 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 lot of noise in there. Right. 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 the types of fun things that we have. Right.
10:00And so it's like, you know, those I got a handoverpark.com slash jobs, I presume. Slash careers. Toss that in there. I'm sorry. Come on. We're a little upscale from that. Hey, go for it. So look, we basically have to take all that data. You drop in 300 ,000 documents. You need to somehow map the ontology. I know you're going to make fun of this. Take all that data, extract, analyze, 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 do the next capital call. So that's like when we think about that process, traditionally, if you said Blackstone, hey, do you want to migrate to Hanover Park?
10:38I'd be like, I'll see you in 24 months. I'll see you in two years. We say, I call it the one-click migration future. How close are we to actually it being a one-click migration future? Okay, so you've 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? 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.
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11:47They got a handful of funds. We're not talking Blackstone size at this point. But some SPVs, fund one, two, three, four. Yeah, exactly. So they had some stuff, right? We took that data. We got that data. We launched their limited partner six days later. Six days later. And just to be a brat, any mistakes, errors that had to go back and be correct? or was that kind of a clean sheet of paper once the migration was done? Of course, as with any workflow where the importance of accuracy is everything, especially given the institutional LPs that are logging in Hanover Park, we of course have a team that's reviewing those outputs, right?
12:18But like if we're clicking a button and it's taking 12 hours, we have all that time for then the team to do the actual review. So it sounds then, and we'll get to the CPA point in a minute, it sounds then that the current world of AI models, AI agents and harnesses thereof are sufficiently intelligent to handle what hand-off-off-market 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 joking with my CTO because I, so there's this internal joke at the company where I said, we're building a one-click migration.
12:50I said this 12 months ago and I had engineers laughing at me. They literally were like, good joke, Chris, ha-ha, funny, whatever. Don't build it yourself. Yeah, 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 possible probably three to six months ago with like Opus 4.6. Opus 4.6. Okay. So kind of in, okay. So right now we're at Opus 4.8. We're at, well, a little bit uneven, but you don't need to have Fable 5 to make this work.
13:28Essentially. You can do this with Opus 4.6 technology. So you're not losing an edge in the current market with the restrictions going on that we're seeing. Look, it was actually funny. So Fable 5's out. You know, the team says this is magical, et cetera. And literally then I have someone come to me when Fable 5 gets disbanded or stopped and they start crying to me. They're like, I literally I love Fable 5. What is this? What am I doing? You know, et cetera. So trust me, we like it. I think that the gap is less of a intelligence gap and more of a context gap is the way I think about it. Like the context of the complexity of a given fund that we need to actually understand versus are the models good enough?
14:04However, when we think about reducing human the loop and getting closer and closer to one click versus six days versus look, if I'm migrating a large fund, it's not going to take six days. Maybe it's 30 days, right? To get that closer to one click, 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 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 improved model intelligence, what does the incremental, what does that gain you?
14:37I suppose. And what does it unlock? Because I get that better models is better, but how? So, I mean, there's a, there's a lot around, like, we're not just doing fund ad. 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 expense charge card company. Oh, I remember. Yeah. Yeah. Remember they're now an AI finance lab, right? If I think about financial infrastructure for the investment firm, AI fund admin is obviously a massively important piece. We understand the importance of what we're doing on there, but the ability to layer these things on top and build this intelligence layer to help CFOs make better decisions, there's obviously a bigger prize here.
15:18Well, we're kind of getting towards where I wanted to go in a minute, but I want to loop back to the CPA point because some people listening to this are going to say, whoa, I'm not ready to get 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 important when you think about 10 ,000 institutional LPs and platform, including large institutional asset managers that 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?
16:03Maybe 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. 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. And so that's kind of how we think about it. So part of your job is obviously the fund services component, but part is actually the product piece.
16:32You put the accountants next to the engineers? Yes. That's got to be a very interesting room to work in. Oh, it is fun. I'm looking. There's a few of them. There's a Muhammad Ali picture in the background. We got 50 people here in New York City and we're having fun. 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.
17:06And is it more of like a makes the humans feel better thing or if it's a requirement to make the product work thing? I think it's a consigliere to the CFO. I said that consigliere to the CFO is like, there is, you can quote that. Suddenly mafia references. Let's go to Sicily. Okay, keep going. So consigliere to the CFO, it's like, there is complex advisory that the CFO values of like, hey, 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?
17:43Right. 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, 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?
18:21Because to me, Carto's data blog has done a fantastic job taking a relatively staid business and turning it into something that I have to absolutely pay attention to. We're 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 ask 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.
18:53And so I might be I might be bucking the trend here, but I'd rather than be like, you know, keep their data siloed. Even in an aggregated, you know, de-anonymized, 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. That's okay, though. That's good. You know, I got to, you know, who's my boss at the end of the day? The CFO. Yeah, well, I mean, that's true. That's true of every company, though. CFO of an investment firm. Yeah, there you go. All right. Okay, so business bottle time.
19:24Now, I know you guys charge, I think it's BIPs off of AUM versus SaaS. Why is that the right approach for Hanover Park compared to more of a traditional SaaS approach? I know you said B2B SaaS is dead, but why in this case? We've kind of taken the business 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 a legacy fund, if we zoom all the way out, you might want to do a capital call. You 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.
20:01Right. 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, 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 to be thoughtful of as well and 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?
20:33Yeah, we don't. I'm not sharing that information either. I love this. Alex, like in the pre-call, Alex was like, hey, like, you know, what's your revenue? I'm like, come on. I asked it way more slyly than that, but I have one 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.
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21:50So get started today at vanta.com slash twist. That's V-A-N-T-A dot com slash twist. 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.
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22:22And 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 growth of the company look like? How many people are on your list to bring on to Hanover Park in the future? 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 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.
22:56If we build a product and service where they are a raving fan of Hanover Park, nothing else matters. Right. And so that's the focus. Yeah. So, I mean, in terms of growth, does this company grow, say, 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. There's a lot of opportunity to launch new products and services, new asset classes, new geographies. There's a lot going on there, but I'm not going to give you a growth target. What does the applicability of the model you've built now or the product you've built now translate to, let's say, commodities if you're moving elsewhere in the world of finance?
23:35Because I presume those are quite different than firms that are doing venture capital investments. So is there a lot of work you'll have to do to tune Hanover Park to fit other asset classes? Me and my co-founder CTO talk about this almost daily. It says, how do we build an ERP 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, and we think about extensibility.
24:08I'll be curious to see what the Hanover Park for the oil market looks like. You know, that would be very interesting. HP Oil. Okay. Rockefeller. No, why not? I mean, well, it worked out pretty well for them, I heard. One last question for me then. So let's say you kind of solve 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. 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 operations?
24:45Or do you plan on staying pretty much entirely focused on just the asset manager side of the equation? We're focused on asset managers. There's a hundred trillion out there. As you've said a few times, there's a lot of room to run and we're focused on the asset manager for now. All right. Well, in six months when that's no longer the case, come back on, tell me about it. And we'll be keeping a tab on your AUM number. And one day I will squeeze the BIPs number out of you. But Chris, thank you so much. What's the website? And is there a role you're looking to hire for? I see you have a tweet looking for a chief of staff.
25:15Hanoverpark.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 going to put my email in this, but Chris at Hanoverpark.com. Just did it anyway. You can ping me. 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. 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.
25:43Of 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, Alex. I feel like everybody remembers where they were when this episode came out. March 27th, 2020. Yep. Yeah. What was going on around then? What was the news item? And I can't recall exactly. A week which will live in infamy. There was people were getting sick, that hospitals were getting overloaded in New York. There was this coronavirus, this novel coronavirus out there. I don't know if you remember it. A little disease we call COVID. And it was it was brand new.
26:22And we will take a look at one point during this segment of some fascinating, very wrong 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, which I realize is they're all global. 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. So fascinating to look at a clip from, you know, the the peak SaaS era when, you know, that that was what all of the huge tech companies were doing.
27:06They were all selling the software. That was the hot venture category of the time. And to look at it now from the sort of SaaSpocalypse perspective when AI is kind of filling all these roles. And yet Figma, you know, still very much a player in this world. Absolutely. I mean, they went public recently. 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 mark instead of an exclamation point.
27:39Figma, for those of you who don't know, they're a SaaS company providing a collaborative platform for UI and UX design and product development. So basically, 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 web page 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 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 aren't even creatives, so that the whole company can kind of participate together in the process of putting these products and designs together.
28:29Because there's nothing a designer wants more than more cooks in their kitchen. Yeah, 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 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.
29:07And that's how they grow. So let's take a look, starting at 21 minutes in, at Dylan discussing how they go to market. 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.
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30:19your 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 on a court 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 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 yeah so you know people are hopping 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 rigorous process especially at larger corporations.
31:19And we've got a great, amazing sales team that's able to partner with them on that. Got it. What is their main concern? Like what are they trying to accomplish with all that friction? Something like security is a big one. So I wanna make sure that if you are a cloud provider that you're gonna 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 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. So you have all of my designs. I'm, I don't know, Nike or something, and I'm building a bunch of apps.
31:50It's a lot of trust. I have to trust that your people are not looking at my designs, 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. Did you hear that story? No, I did. Crazy. Yeah. And so there's SOC 2, I was simplifying before, it encompasses a wide variety of It controls everything from like hiring, offer approvals, all the way to like how are your servers run and what are your runbooks for those. Oh, really? 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.
32:28This 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 products. You know, it was a different time, and yet it was so much of a similar concern. 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.
33:01So 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, Lon, the whole concept of bottom-up sales was kind of a Dropbox invention, if you go back in startup history. The idea that people would just buy something, 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. It provided a lot of strong net dollar retention.
33:30All those acronyms, CAC, NDR, that investors used to love. But today, fast forward six years, and we're still talking about people bringing AI tools into their company, driving usage, wanting to run enterprise control. I mean, Granola, I feel like, is the most recent example. I think we had a VC on the show talking about it where it's like they decided to invest in Granola because so many people around the office were already just using it without being asked or told. It's just these things sort of catch on their own. 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.
34:09Like that always feels like a chore. No, it's the other way around. Whenever a CEO tells me to use a tool, I just presume it's dumb. Like I'm just like, oh, it came from above. Oh, God, someone bought this. And now it's been rolled out to me nine months later with half 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 on. Exactly. I'm reminded of the late, 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.
34:40It 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. We have a lot of internal tools we've passed around behind the scenes to make twist happen. One more note for me on this. He was talking about how at the time, you still had to go in the enterprise sales process, go to a company, and it could take months to get purchasing orders and 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 is every company today is sprinting, trying to figure out what's next, what to reinvent, what to cut, what to invest in.
35:15And so I wonder if you've seen kind of the enterprise buying process for AI today versus SaaS then become compressed. I wonder if it's a faster cadence process today. Yeah, I mean, I feel like it's one of those situations where it's like SaaS 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 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 sort of, they figured it out and now it just got like massively compressed.
35:50And speaking about things that got massively compressed, don't forget there was a company called Delve. I think its reputation was compacted after its 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 through, 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, do not change. And that is you will have to get the SOC 2 report. Yeah, and it's never a thing that companies are excited about doing or looking forward to.
36:17You just find another provider and you work with the Vantas of the world to sort of take care of it. I was about to say, I'm going to throw a bone to our sales team. This is not in the script, but Vanta.com slash twist if you want to save$1 ,000 off your SOC tube report. All right, next clip. Here we hear a lot about SaaS overload and SaaS burnout. Really key concept at the time as tools proliferated. Let's see what the two had to say at the time. Burnout. I, during this COVID crisis, said, that's it. Give me a list of every single SaaS product. Yep. Then I said, there's a website called privacy.com and another one where you can set.
36:55Because I just saw a SaaS 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 gnarly thing where they charge you for accounts but not usage yep dirty and that really upsets me because i like slacks model where they're just like this is how many people you use so i never know it's very divisive because some people like slice model and some people don't i like sex model too we're not doing it for figma because we've actually heard people and that's that they don't like it got it because it's variable cost explain explain the the issue to somebody who doesn't understand what we're talking about right yeah so the slacks model is that you've got active user pricing now the question is like okay is there enough trust to know that there's an active user we've definitely looked at the model for Figma and it's mean that I think could be really interesting to me it incentivize the right behaviors like if you get to the point where anyone could become an active user and then 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 so in slacks 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.
38:07I wonder if there's a minimum threshold. There probably is. I don't know what it is. I think the flip side of it for us, at least, is in Figma, if you tried to rip Slack out, you'd have people protest. Of course. I just can't not even continue. So here, but they don't turn your account off. 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 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 cheat our system 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 if we if we thought it was like really uh clear that it was wrong but um but also you know if it's like depends on the case by case basis too this is what you got to do is you got to build the sas industry now has to build trust and when they 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 yeah so i love that about slacks the trust part.
39:20So Lon, I love so much of that clip. But first of all, it really strikes me how thoughtful Dylan is about pricing, 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. Yeah. I mean, we talk a lot, I think about whether the incentives for a company and its users are like aligned, like a lot, a lot of businesses are, you know, like ramp.
39:57That'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?
40:35And obviously, again, a huge conversation that people are having right now only about tokens and compute and AI. Like everything in this clip comes back to like the SaaS industry and the AI industry are really it's not so much AI SaaSpocalypse destroying this old industry so much as it is just kind of like disrupting it with some new kinds of tools. I think also the progression in how startups charge for things really did ding the SaaS model. Because in the old days, 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, we added all these features and it costs twice as much.
41:12Good luck ripping it out of your life. And you're just stuck eating the price. Yes. 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 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.
41:42What 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 were talking about it at the time because I can't recall the last time someone said, we have to cut our SaaS spend. That doesn't come up. Instead, it's exactly what you said. It's, dear God, did you see our clogged bill? We're broke. Yeah, that's right. It's token maxing. There was no Figma maxing back in the day. It's token maxing. No, I mean, what is that? 13 extra seats that you pay for? Okay, email the CEO, get a credit, whatever.
42:12But you can't email Dario and say, Dario, can I take back that$10 million in tokens? I didn't mean to. It was a big accident. No, that can be burned. We didn't end up shipping any of those products. They just look nice. 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. 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?
42:41I 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 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 and now of Stillcore Capital. He was the sort of the editorial director, the chief technical officer of Mahalo, I guess you could say. And so, yeah, the idea was Mahalo was this alternate to Google.
43:24Because 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.
44:00Ten 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. OK. 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 L.A. 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.
44:37The first page I ever made for 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 Stone. And here's another recent piece about whatever. And, you know, we'd sculpt those. Yeah. Yeah. Yeah. So, Lon, let's see the story about how Jason Calacanis' idea for luxury communism for partially employed Hollywood screenwriters worked out. Well, I do think there's one more vital piece of context for this clip. I didn't mean to get into a whole story time. The vital piece of context here is that for a while, Mahalo actually worked because we started ranking well in Google for these pages.
45:17We 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 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, I have a Mahalo mug. Or rather, my mother has Mahalo mug. That is hilarious. Thank you for my PTSD. 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.
45:58Yeah, it 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. 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.
46:46Like people are coming to landing pages that aren't filled out, like a short Wikipedia page. So we're like, fine. I told Matt, well, just no index, anything under 400 words everything above 400 words then we'll index it we'll just write 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.
47:20And 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?
47:51And they're like, yeah, we don't know who's in charge. 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 in the last six years. I mean, what was it like knowing what I know now when Jason hired me to do 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.
48:26These 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 most of the big search terms at any given day are not actually things like Paris hotels or Bob Dylan. And 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 Super Bowl Day, they're looking up the big Super Bowl commercials that are just on TV. So we were constantly racing against the clock to make pages in time to catch the tail of, you know, Google trends and rank highly for them.
49:08And 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 from those pages to make it profitable as just kind of like a destination site on the Internet to look things up. So Mahalo walked so Grokipedia could run. Right. I mean, and I think Jason listed us with 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.
49:45So 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 we were we were really trying to make better quality content than that. The whole idea was to make better pages than Google. Like that was the concept. Well, I don't think that was a very high bar to cross, but what Google has done is consistently optimize for monetization. Right. User experience be damned. And I think we've all kind of seen the results of that, which is today Google has essentially thrown in the towel and gone, what if it's all just AI?
50:18Right. And that's exactly what 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 you didn't have to leave Google and you didn't have to click away. And now they're just, 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 need to link you to anything. Frankly, I think the most important company in the world is whichever company beats Google at AI.
50:50Because 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. This is sort of a bit much for a single company. This was honestly Sam and Elon's like open AI original spark of an idea. Like they were, they were like, Google can't control this. We need to 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 dropped the don't be evil slogan may be up to some shenanigans. It is. I think we all can concede that it is possible.
51:24And 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 so much power collected in just the hands of a few people. It is kind of scary. Thinking about things that scare us, Lon, why don't we rewind the clock to everyone's favorite public nightmare, the COVID crisis. Now at the time of this clip, we knew a lot less. So we're not here to just Just poke fun.
51:56Oh, I am here. I am here mostly to poke fun. Lon is here mostly to poke fun. I am here to provide... That's my job. I thought I was the funny one. Anyways, here's a clip of Dylan and Jason talking about COVID before we knew much in the early days of lockdowns. Now that you're a work-from-home company, and you obviously did not... You were not all in for work-from-home. You believe in people being in the office and collaborating. I think it's great for people to be in physical spaces together. Yeah, so you were not bought into this like other people are. Do you think - Let me define that more. So I think bought into the possibility of it, but still think there's great benefits to being in an office.
52:31And so - So how does that change when this crisis ends in, I think, April 15th? Oh, man. I think that'd be awesome if it's true. I think - That'd be awesome. 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. Yep. I think restaurants are going to start opening again April 15th or so in that time frame. 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're sitting here on the 24th.
53:01I 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. I don't want to be a downer here. Okay, go ahead. But should I be? Yeah, do it. Nobody, Dylan, nobody knows. I mean, that's one thing we've learned here is nobody knows. I think that we're going to see, I hope that for California and for other places that have but more restrictive measures in place earlier. Yeah. That we'll see, you know, 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 overloaded then.
53:43So I think the... 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? 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 it right now. Yeah. But I wouldn't be surprised. It would be civil unrest on a level that would be disturbing.
54:10I don't know. It depends on sort of like how people think about the situation. But in any case, going back to sort of arc. So Lon, this reminds me, I had this conversation with my mother-in-law. We were at my in-law's house. It was March around this time, probably plus or minus two days. And we were all sitting 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. If you'd also been wearing a mask, you thought they were robbing a bank. Like it was that rare. So we were getting used to wearing a mask here and there, trying to figure out like, are cloth masks good?
54:38Remember those days, you know, buying them on Etsy? And we're sitting around talking about this. And I'm like, you know, maybe a couple of months. People 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 24 months. No, yeah. I mean, Jason says, I think what, like, it sounds crazy to hear now in retrospect. But in March, we all thought June was like outside. Maybe. Maybe. Unbelievably far out. Maybe 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.
55:19Like, 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 it could get that bad. Yeah. I'm glad that Dylan was a little bit more bearish. A little bit. 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. 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 a real change. And a lot of people didn't take the lessons that I took from it.
55:54It is also interesting to go at the very beginning of the clip where the people want to work remotely revolution 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. 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 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?
56:31So like it does kind of go back and clarify, like these were actually like COVID accelerated a trend that was 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. yeah i find it really funny because i had already been working you know from home for a half decade at that point in time here and there i 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 as 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 tiktok back here yeah oh man people really blew up some comfy jobs didn't they yeah for sure the last never tell people when your job is easy they'll give you more work yeah or fire yeah no one needed to know how much time you were spending every day refilling your Stanley mug I don't 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 Lon an 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.
57:58There you go. Thanks everybody for joining us. We'll see you next time.
From the publisher
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Today’s show:
*There are $100 trillion in global assets sitting on top of what Hanover Park co-founder/CEO Chris Hladczuk calls “human duct tape”: armies of accountants in offices patching together work from various legacy tools (QuickBooks, Excel) that are holding funds’ own data hostage. Can all of this be replaced with AI? Find out how their startup went from overseeing $1B to $20B in assets in just 15 months.
PLUS, we flash back to March 2020, when Jason and Figma co-founder/CEO Dylan Field broke down the design tool’s initial go-to-market strategy, made some WILDLY inaccurate COVID predictions, and considered anxiety about “SaaS burnout” years before the category went full apocalyptic.
Guests:
Chris Hladczuk on X: https://x.com/chrishlad
Hanover Park: https://www.hanoverpark.com/
Dylan Field: https://x.com/zoink
Figma: https://www.figma.com/
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Turner Novak on X: https://x.com/TurnerNovak
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TechCrunch Mahalo coverage: https://techcrunch.com/2014/01/27/inside-mobile-news-launch/
Timestamps:
0:00 Hanover Park & the fund admin problem
3:32 Why funds outsource instead of building
5:44 Why fund accounting is so complex
10:38 The "one-click migration" goal
10:48 Northwest Registered Agent - Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at https://northwestregisteredagent.com/twist
13:51 Context vs. intelligence gaps
16:11 No PMs, No Designers
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23:18 This is a $100T opportunity
25:36 Flashback w/ Dylan Field of Figma
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31:22 Pre-AI enterprise security worries
36:30 SaaS overload and SaaS burnout
37:30 The evolution of Figma pricing
42:38 The rise and fall of Mahalo dot com
51:38 The work-from-home revolution begins
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