$100T is managed by “human duct tape” | E2308

How 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, 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 for the most complex investment firms in the entire world and you've never done this before?

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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 But what you told me is that in the world of fund ops, The technology is outdated.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 $100 trillion 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 $100 trillion of global assets are sitting there with a bunch of humans in Kentucky. They'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, um, and run by, you know, 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. At 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. 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 pull 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, that are holding your own data hostage. And so, so, you know, why?

Like, why, why, 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, why wouldn't these funds, which have 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 delivering 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 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. Right? And so that's— 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, you know, help with fund administration.

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 cloud and ChatGPT. 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, right? I won't say Turner was laughing at me. You know, he probably would say, But everyone was like, you're insane. You want to go build financial info for the most complex investment firms in the entire world and you've never done this before? And so we started by building the unsexy, like, core, like, 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 distributions. 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 6 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 LP portal, 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 sit, it doesn't sound that complicated.

Oh, of course, it's super easy, right?

Well, no, no, no, no, no. Hear me out. I'm not trying to be coy or wry. 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, you know, entities that need to talk 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 a $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 gonna toss into this thing called a limited partnership agreement to do that. And so herein lies the, the fun levels of complexity, and our job is to capture that somehow.

So I'm thinking about a ton of contracts, like, like an absolute mountain of PDFs and DocuSigns, speaking loosely.

Yeah.

How do you guys convert the written word here into the rules and, um, kind of guidelines for the, 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, 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 my— 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 scale that capture all that ontology, to quote Palantir, map that to a set of words. 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.

Well, wait, should I, should I pull an Alex Karp and say I'm not going to define ontology? We're going to have to, like, search this.

You have to bounce in your chair while you do it. No, I'm serious. Like, for the people out there, for, for, for people for whom that is merely a buzzword they've seen in an earnings report, ontology, maybe a working definition for how Hannover Fonds 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, etc. 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, 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, you know, 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 deal, which is not only is Hanover Park tracking cost and fair value and fund symbol stuff like that, but we're tracking like what's the post-money in Uber's latest round? I got to say Uber because I'm on This Week in Startups, right?

Jason gives you 5 extra bonus points on a high five for Uber. No.

Okay.

I appreciate that. Now, you mentioned 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 6 months? Because it does seem that we've seen a pretty rapid increase in agent capabilities, from what I can tell. So I'm curious how that's kind of manifesting inside your operation.

For us, when we thought about what are the biggest problems of 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 the types of fun things that we have, right? So it's like You know, those— I got to pick HanoverPark.com/jobs, I presume, slash careers. I'm sorry, we're a little off scale from that. So, so, so look, like, 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 that we can do the next quarter of financial reporting or we can 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? It'd be like, I'll see you in 24 months. I'll see you in 2 years. We say— I call it the one-click migration future.

How close are we to actually it being a one-click migration future?

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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 SPVs, fund one, they got some sports.

Yeah, exactly. So it was— they had some stuff, right? We took that data, we got that data, we launched their limited partners 6 days later.

6 days later. And just to be a brat, any mistakes, errors that had to go back and be corrected, or was that kind of a clean, 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 and out, we of course have a team that's reviewing those outputs, right? But like, if we're, if we're clicking a button, it's taking 12 hours. We have, you know, 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 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 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. I said this 12 months ago, and I had engineers laughing at me. They literally were like, good joke, Chris. Haha, funny, whatever.

And I literally—

Yeah, exactly.

Exactly.

They said they were laughing at me. And I literally said, one-click migration, one-click. And literally, and we released it 3 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 3 to 6 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, whoa. A little bit. It's uneven, but you don't need to have Fable 5 to make this work. Essentially, you can do this with Opus 4/6 technology, so you're not, uh, losing an edge in the current market with the restrictions going on that we're seeing.

Uh, look, it was actually funny. So Fable 5's out, you know, the team says this is magical, etc., 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, etc. So trust me, we like it. I think the gap is, is less of an intelligence gap and more of a context gap is the way 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 in the loop and getting closer and closer to one click versus 6 days versus look, if I'm migrating large funds, not going to take 6 days, maybe it's 30 days, right? Yeah. 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, I suppose? What does it unlock? Because I get that better models is better, but how?

So I mean, there's a lot around like we're not just doing fund 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?

Right.

Corporate expense charge card company.

Oh, I remember.

Remember they're in—

yeah, remember they're in AI. They're now on AI Finance Lab, right? Like, if I think about, like, you know, if I think about, look, like, financial infrastructure for the investment firm, we're— AI Fund Admin is obviously a massively important piece. Like, we understand the importance of what we're doing on there, but like the ability to layer these things on top and build this intelligence layer to help CFOs make better decisions, like there's obviously a bigger prize here.

Well, 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 have 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, etc.?

Look, like, I think it's incredibly important when you think about 10,000 institutional LPs in platform, including large institutional asset managers that everyone knows, like, we need to have incredible CPAs that are crushing it, that are tier 1 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 compliant 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 code, 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.

You 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, you know, 50 people here in New York City and we're having fun.

But as you guys do continue to build the 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 stay 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?

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, 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, right?

Yeah.

By the way, 95% of fund admin is 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, 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, 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, Carta's data blog has done a fantastic job taking a relatively staid business and turn 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. And so 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, 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 yes, I think 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.

And CFO of an investment firm.

Yeah, there you go.

All right.

Um, okay, so business model time. Now I know you guys charge, I think it's, uh, 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've said, you know, B2B SaaS is dead, but why in this case?

Yeah, we've, 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 4 capital calls, not 3 capital calls, we're going to charge you per capital call. Oh, right.

That's like the old SMS plans.

Or 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 BPS you charge off of AOM, or should I just do a kind of a guess?

Yeah, 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 slightly than that, but I have, I have one more for you.

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If Hanover Park took, for example, 25 bps 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, put a marker on it. The number might be 50, might be 15 bps. 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 growth of the company look like? How many people are on your, your list to bring on to Hanover Park in the future?

Look, I think, 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. If 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 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 hypergrowth ahead of you.

There's a lot of opportunity to launch new products and services, new asset classes, new geographies. There's, there's a lot going on there. But I'm not going to give you a growth target.

What is the applicability of the model you built now or the product you build now translate 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 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 5 years, 10 years, 20 years? 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.

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, 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, than any of their business operations? Or 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 $100 trillion out there, 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 manager for now.

All right. Well, in 6 months when that's no longer the case, come back on, 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. Uh, 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.

hannoverpark.com. Very simple, straightforward. You can go to our careers page. You can ping me on Twitter @ChrisAllad if interested, email me. I'm not going to put my email in this, but chris@hanoverpark.com. Just did it anyway. You can ping me. Yeah, we're hiring a chief of staff. We're in hypergrowth. 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 6 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, 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. And 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 you. No, this is a fascinating interview that 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. They were all selling the software. That was the hot venture category of the time. And to look at it now from the sort of SaaS-pocalypse 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 2 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.

Figma, 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.

Together.

Because there's nothing a designer wants more 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 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, uh, starting at 21 minutes in, uh, at Dylan discussing how they go to market from Figma.

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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 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 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. Um, huh. They'll bring it with them. Yeah, of course. 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. Mm-hmm. Um, 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. Got it. We also see customers—

What is their main concern? Like what are they trying to accomplish with all that friction?

Something like, uh, security is a big one. Ah. So, uh, 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, um, which is—

Explain what that is. Yeah.

It's basically just a process to make sure that you're able to be as secure as possible.

Mm-hmm.

Even though you're hosted in the cloud.

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

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.

You hear that story? I did.

Crazy.

Yeah. And so there's SOC 2, and I was simplifying before.

Yeah.

Encompasses a wide variety of 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, 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 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, like it, it was a, it was a different time and yet it, 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, right? 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, 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, provided a lot of strong net dollar retention, right? All those acronyms, CAC, NDR, that investors used to love. But today, fast forward, you know, 6 years and we're still talking about people bringing AI tools into their company, driving usage, wanting to run, you know, enterprise control.

I mean, 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 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'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 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 9 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 7 steps," instantly on board.

Exactly. I'm reminded of the late, great Gummisearch, 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 5 posts that you wanted. It was revolutionary and I never would've tried it except a different person who worked on a podcast was like, "Hey, if you're not using Gummisearch, 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.

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 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 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 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.

And 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 gonna 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 SaaS era or the AI era, do not change. And that is you will have to get SOC 2 report.

Yeah, and 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 world to sort of take care of it.

I was about to say, I'm gonna, I'm gonna throw a bone to our sales team. This is not in the script, but, uh, vanta.com/twist if you want to save $1,000 off your StockTubeReport. 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— because 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 upset me because I like Slack's model where they're just like, this is how many people you use. So I never—

Yeah, 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 that said they don't like it. Got it. Because it's variable cost.

Explain the—

you don't know what's going to come.

Explain the issue to somebody who doesn't understand what we're talking about right 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 looked at the model for Figma. Um, and it's something that I think could be really interesting. Uh, to me it incentivizes the right behaviors. Like if you get to the point where anyone can 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, 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.

That's right.

Even if it's for 30 seconds.

Yep. I wonder if there's a, like a minimum threshold, like The problem is I, I don't know what it is cuz I've always, I think like the, the sort of flip side of it for us at least is in Figma, like if you tried to rip Slack out, like you'd have like people would protest, you know?

Of course.

Uh, it just can't not even—

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. Mm-hmm. And I opened figma.com and I looked at something on Figma, I'm okay.

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 pay 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.

But if somebody came to you and was like, hey, you have, you billed us for 3 editors for the last 6 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.

Yeah.

But, um, but also, you know, if it's like, depends on the case, but case basis too.

This is what you gotta do is that you gotta build, the SaaS industry now has to build trust.

Yeah. 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 gold standard. They send you your monthly utilization every month.

Yeah. So I love that about Slack, the trust part.

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

Yeah.

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, 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 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, you know, as Jason said in that clip, you get a new contract, say every year or every 3 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. Good 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, 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 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, right? Instead, it's exactly what you said. It's, dear God, did you see our cloud bill?

We're broke, right? It's token maxing. There was no Figma maxing back in the day.

It's—

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 in token spend? I didn't mean to. It was a big accident. Yeah.

No, you didn't end up shipping any of those products. They were just, they just looked nice.

As a very inefficient AI user, I'm sympathetic to people who are complaining about it, but also like you gotta pay for the servers one way or the other. Exactly. Now we're gonna get back to this interview and we're gonna 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, Lime, weren't you part of that product to some degree?

I was employee number 3.

At Mahalo. Funny enough that you should say this was the first, uh, job that I ever got. I was working at a video store, uh, in, uh, Rancho Park, California, a, a small community in Los Angeles. Uh, and I saw a Craigslist ad. They were looking for writers/researchers for this new website. So I went to what I later found out was Jason's Pool House in Brentwood. Uh, and I interviewed with Mark Jeffrey, still a frequent friend of the pod, now of Steelcore Capital. Uh, 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, the, the idea was Mahalo was this alternate to Google. Cause 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, a 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 caught up.

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 Bahá'u'lláh 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, you—

we'd scope those. Yeah, yeah, yeah.

So, Lon, 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 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. 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 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.

Sorry.

Mahalo was like my failed startup 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, it was a big change.

Answers.com, you all are too 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 5 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, they— 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, 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 noindex 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, uh, 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. Yeah. 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, you know, 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 know Larry, I knew Marissa, I knew everybody at the company and I called them all and I was like, I have to lay off 100 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'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 6 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. 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 most of the big search terms in any given day are not actually things like Paris hotels 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 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. And so it was— I don't think ultimately it was like very sustainable, but But for a short time, it really was working and we got enough SEO lift 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 Grok-o-pedia could run.

Right. I mean, I, and I think Jason listed us with a lot of like, you know, sort of lower quality like eHow and How Stuff Works, which are kind of content mills. Like there were a lot of competitors like that that were just churning out. 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, we were, we were really trying to make better quality content than that. The, 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 result of that, which is today Google has essentially thrown in the towel and gone, what if it's all just AI?

Right? What if we— and so, 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, 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 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. This is sort of a bit much for a single company.

This was honestly Sam and Elon's, like, OpenAI 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 drops the "Don't be evil" slogan, may 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 PageRank 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.

Oh, I am here mostly to poke fun.

Lon is here mostly to poke fun. I'm here to provide. That's my job. I thought I was the funny one. Anyway, 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. Yeah, I think bought into the possibility of it, but still think there's great benefits to being in an office.

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 Apple's opening their stores in the first 2 weeks of the rumor, and I don't know if it's been confirmed yet, but I heard some inside information they're gonna open Apple stores in the first 2 weeks.

Yep.

I think restaurants are gonna 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 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.

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

Yeah, do it. Nobody, I think Dylan, nobody knows. I mean, that's one thing you've learned here.

I think that we're going to see, I hope that for California and for other places that have put more restrictive measures in place earlier, that we'll see um, you know, sort of like the stabilization, uh, 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, uh, because I think we'll see a second wave effect, right, where there still is the virus out there, and we'll start to see it spread again, um, and then hospitals will be overloaded then. So I think the, um, uh, so what do you think?

You think San Francisco is a chance? San Francisco Bay Area, San Mateo County, etc., says 2 more weeks of this, 4 more weeks of this?

I, 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 it's, um, 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, that's something that's like, I think people aren't even thinking about right now.

Yeah, but it's, uh, that would be civil unrest on a level that would be disturbing.

I don't know what it depends on, sort of like how people think about the situation. But in any case, going back to— yeah, sorry, Mark.

So, Lon, this reminds me, just, I had this conversation with my mother-in-law. We were at my, my in-law's house, it was March around this time, probably plus or minus 2 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. Like, if you saw someone wearing a mask, you thought they were robbing a bank. Like, it was that, that rare. So we were getting used to wearing a mask here and there, trying to figure out like, are cloth masks good? Remember those days? You know, buying them on Etsy. And so 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 that was crazy. 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, 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 include myself. Like, nobody thought it was going to last beyond May or June. It was un— 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. I mean, amazing. Almost prescient when 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, of real change. And a lot of people didn't take the lessons that I took from it.

It is—

it is also interesting to go at the very beginning of the clip where the people want to work remotely revolution— in our minds, in 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? So like, But 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 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 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'd had some office jobs, I'd 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 work and there's just not someone sitting next to you. But it became this enormous touchstone of people doing the day in the life videos on TikTok back in the day. Yeah, yeah, yeah. Oh man, people really blew up some comfy jobs, didn't they?

For sure. The last—

never tell people when your job is easy. They'll give you more work or fire you.

Yeah, it's— no one needed to know how much time you're 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 2 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.