$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?

0:00

It's human duct tape legacy services businesses that are running the entire backbone of these hundred 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 from the most complex investment firms the entire world and you've never done this before.

0:05

This week in startups is brought to hi Sentry. Your team should be focused on shipping features, not chasing down bugs. New users can get $240 in free credits when they go to Sentry IO Twist and use the code TWIST. Vanta compliance and security shouldn't be a deal breaker for startups to win new business. Vanta makes it easy for companies to get a SOC 2 report fast. Get $1,000 off for a limited time at vanta.com twist and Northwest registered agent. Get more when you start your business With Northwest in 10 clicks in 10 minutes, you can form your company and walk away with a real business identity. Learn more@northwestregisteredagent.com 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 Holonczyk, the CEO and co founder of Hanover Park. Chris, how you doing?

0:30

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

1:46

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 But what you told me is that in the world of fund ops, the technology is outdated, there's too many people involved, and you call it a kind of a duct tape operation.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.

1:48

Well, it's human duct tape where you basically think about like legacy services. Businesses that are running the entire backbone of these hundred trillion of global assets are sitting there with a bunch of humans in Kentucky. They're buying QuickBooks, they're buying Bill.com, they're buying Excel. And that CFO is 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, you know, a bunch of fund accountants in a room that are delivering financial reporting every quarter.

2:13

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.

2:46

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.

3:05

And so you know, why, like 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 quite a lot of aum, just build their own internal stack? Why outsource it to someone who hates you?

3:32

I guess traditionally it's like it doesn't even matter because all they're doing is deliver some output, which is that financial reporting that goes to your limited partners every quarter, your Harvard endowments, your Yale endowments. You know, I went to Yale, so I can say that. And so like they're just delivering an outcome. And so in 10 years ago, 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 a hundred 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.

3:46

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.

4:16

When we started in 2024, we made this contrarian bet that I said the following B2B SaaS was dead. We were going to go build this idea of an AI native services company in 2024, which was super contrarian, which is that we wanted to own the end to end outcome and not just build another tool that was going to get commoditized by Claude and ChatGPT. And so we started by saying, 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's like, you're insane. You want to go build financial info from the most complex investment firms in the entire world, and you've never done this before. And so we started by building the unsexy, 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 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. And then they leave in six months and say, hey, wait, all the things you taught them about your fund, now go away. And so building agents with memory on top is actually the way you solve that problem. And then lastly, now we have all this data for your fund. What are the things we can do to weaponize it, right? And so now you have portfolio management and monitoring and 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.

4:27

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.

5:42

Of course, it's super easy. Right?

5:51

Well, no, no, no, no. Hear me, hear me out. I'm not trying to be coy or wry. I'm going to say that like, you know, when I think about how, how we handle, like, high frequency trading, that seems like a much more difficult system, 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.

5:53

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. Think about QuickBooks. You have one entity at one time. 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 rates $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. And so herein lies the, the fun levels of complexity, and our job is to capture that somehow.

6:12

So I'm thinking about a ton of contracts like, like an absolute mountain of PDFs and DocuSigns. Speaking loosely, how do you guys convert the written word here into the rules and kind of guidelines for the ledger system to understand? Is that done by humans, the translation process, or is that something that I can goal based on its ability to reason?

6:55

So if I take this in 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. 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 the whole time? And 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 a quote balance here.

7:16

Right?

7:44

Map that to a. Oh, yeah, 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.

7:44

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.

7:53

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 an earnings report. Ontology, maybe a working definition for how Hanover park thinks of it will be useful.

7:58

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.

8:09

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

8:28

Oh, boy. So, 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 jail, which is not only is Hanover park tracking cost and fair value and fund, simple 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.

8:30

Jason gives you five extra bonus points and a high. 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 six months? Because it does seem that we've seen a pretty rapid increase in agentic capabilities from what I can tell. So I'm Curious how that's kind of manifesting inside your operations.

9:03

For us, when we thought about what are the biggest problems with the company. 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's a lot of noise in there. So I think it's getting all of that data into Hanover park is 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. You know those I gotta pick.

9:35

Hanoverpark.com jobs, I presume.

10:02

Slash careers. Toss careers.

10:05

I'm sorry, Come on.

10:07

We're a little upscale from that so forth.

10:08

So.

10:10

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 then we can do the next quarter of financial reporting or we can do the next capital call. So that's like when we think about that process, traditionally if you said Blackstone, hey, do you want to migrate to Hanover Park? It'd be like, I'll see in 24 months, I'll see you in two years. We say, I call it the one click migration future.

10:10

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

10:44

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10:48

We got data of a venture capital fund from. Call it like 20 different entities. They got a handful of funds. We're not talking Blackstone size at this

11:41

point, but some SPVs, fun ones.

11:49

They got some SVB. Yeah, exactly. So they had some stuff. Right. We took that data, we got that data. We launched their limited partners six days later.

11:51

Six 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?

11:59

Of course, as with any workflow where the importance of accuracy is everything, especially given the institutional LPs that are logging in, we of course have a team that's reviewing those outputs. Right? But like, if we're. If we're clicking a button and it's taking 12 hours, we have, you know, all that time for then the team to do the actual review.

12:08

So it sounds then. And we'll get to 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 Handover 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.

12:25

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. Ha ha, funny, whatever.

12:44

And I built it yourself.

12:58

Yeah, exactly, exactly. They say they were laughing at me and I literally said, one click migration, one click. And literally. And we released it three weeks ago. And that engineer, by the way, we love him, jt, he literally came to me and said, you were right. And so that was only. That was only possible probably three to six months ago with like, Opus 4.

12:59

6.

13:16

Opus 4. 6. Okay, so kind of in. Okay, so right now we're at Opus 4.8. We're at. Whoa. Model releases right now. 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 losing an edge in the current market with the restrictions going on that we're seeing.

13:16

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, etc. 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, like the context of the complexity of a given fund that we need to actually understand versus are the models good enough? However, when we think about reducing human the loop and getting closer and closer to one click versus six days, versus look, if I'm migrating a large fund, it's not going to take six days. Maybe it's 30 days. Right? Yeah. To get that closer to one click, of course I want better models.

13:36

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?

14:18

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?

14:42

Right.

14:52

Corporate expense charge card company. Oh, I remember.

14:53

They're. Yeah. Remember they're in AI. They're now an AI finance lab.

14:55

Right.

14:58

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.

14:59

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 give 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.

15:18

Look, I think it's incredibly important when you think about 10,000 institutional LPs in the platform including large institutional asset managers. Everyone knows we need to have incredible CPAs that are crushing it, that are tier one, reviewing associated outputs and handling edge cases. Right. Maybe AI hasn't seen something before and we want to make sure that the Blackstone fund accountant can come in there and be like, hey, this is a more complex thing that we need to think about from a product perspective. 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. So part of your job is obviously the fund services component, but part is actually the product piece.

15:46

You put the accountants next to the engineers.

16:32

Yes.

16:35

That's gotta be a very interesting room to work in.

16:36

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.

16:38

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

16:47

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

17:11

that suddenly mafia references. Let's go to Sicily. Okay, keep going.

17:18

So consiglier 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.

17:23

Yeah.

17:43

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.

17:44

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 a first fund operations. So once you have all these, these front 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 as a data product? Because to me, Carta'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.

17:57

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

18:30

their data siloed even in an aggregated, you know, de anonymized, blah, blah, blah, blah, blah, all that.

18:58

That's not, not something we're focused on right now.

19:03

Well, that's disappointing for me as a

19:06

journalist, but yes, that's okay though.

19:07

That's good.

19:10

You know, I got to know who's my boss at the end of the day. The cfo.

19:10

Yeah, well, I mean that's, that's true of every company though.

19:13

CFO of an investment firm.

19:18

All right, okay, so business model time. Now I know you guys charge. I think it's bips off of a whim versus SaaS. Why is that the right approach for Hanover park compared to more of a traditional SaaS approach? I know you said, you know, B2B SaaS is dead, but why in this case?

19:20

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 fundament, 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, right?

19:36

That's like the old plans on or even more.

20:01

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.

20:04

Right.

20:09

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.

20:09

So have you guys talked at all publicly about how many bips you charge off of aum or should I just do a kind of a guess?

20:26

Yeah, we don't. I'm not sharing that information either. I love, I love this Alec. In the pre call Alex was like hey, like you know, what's your revenue? I'm like, come on.

20:33

I asked it way more slightly than that, but I have one more for you.

20:42

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20:46

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

21:55

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.

22:35

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

23:03

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.

23:18

What does the applicability of the model you built now or the product you built 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?

23:27

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 is Hanover park look like in 5 years, 10 years, 20 years, and we think about extensibility.

23:44

I'll be curious to see what the Hanover park for the oil market looks like. You know, that would be.

24:08

That would be very hp. HP Oil. Okay, Rockefeller?

24:12

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, 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?

24:16

We're focused on asset managers. There's 100 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.

24:49

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.

24:57

Hanoverpark.com, very simple, straightforward. You can go to our careers page. You can ping me on Twitter, Hrisalad. If you're 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.

25:14

All right, thank you, Chris. We'll talk to you in six months.

25:34

Talk soon.

25:35

All right. Welcome back to Twist. We're here. I'm joined by Alex Wilhelm. Alex, how you doing?

25:36

Oh, fantastic as always.

25:41

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 27, 2020.

25:42

Yep.

25:59

Yeah.

25:59

What was going on around then? What was the news item? And I can't recall exactly a week

26:00

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 vaguely 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 from 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. 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 SAS era when you know that that was what all of the huge tech companies were doing. They were all selling the software that was the hot venture category of the time. And to look at it now from the sort of SaaS apocalypse perspective when AI is kind of filling all of these roles. And yet Figma, you know, still very much a player in this world.

26:05

Absolutely. I mean, they were in 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.

27:20

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, 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.

27:39

Because there's nothing a designer wants more than more cooks in their kitchen.

28:29

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 and 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 starting at 21 minutes in at Dylan discussing how they go to market from Figma.

28:34

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29:15

Jcal sent you, 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 being paying for it and they're like, this is actually really good. Like, let's go bring this into the organization. Let's have this entire team on this. And for what it's worth, we also see a lot of people spread figma when they change jobs. They'll bring it with them. Yeah, of course, people are hopping between jobs every few years and they're bringing the tools they like. But anyway, so to go back to the question about bottom up and legal and sort of what the buy decision looks like, we're seeing a range of behaviors right now. There's definitely a ton of companies that need to spend multiple months or whatever evaluating software. Go through a rigorous process, especially at larger corporations. And we've got a great, amazing sales team that's like able to partner with them on that.

30:17

Got it.

31:22

We also.

31:22

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

31:23

Something like security is a big one. So I want to make sure that if you are a cloud provider that you're going to be as secure as possible. And so that's something that like, for example, we've gone through like the SoC2 process now, which is, it's basically just a process to make sure that you're able to be as secure as possible even though you're hosted in the cloud.

31:27

So you have all of my designs. I am, I don't know, Nike or something. And I'm building a bunch of trust. I have to trust that your people are not looking at my designs, speaking 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?

31:45

No, I did.

32:03

Crazy.

32:04

Yeah. And so there's SOC 2. 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?

32:05

Oh, really?

32:17

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 air. 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 was a, it was a different time. And yet it was so much of a similar concern.

32:17

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 line, 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, all those acronyms, cac, ndr, that investors used to love. But today, fast forward, you know, six years and we're still talking about people bringing AI tools into their company, driving usage, wanting to run, you know, enterprise control.

32:46

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's 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.

33:43

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. Ongoing.

34:10

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 on on exactly the five posts that you wanted. It was revolutionary and I never would have tried except a different person who worked on a podcast was like, hey, if you're not using Gummy Search, it's the best way to find Reddit posts.

34:27

Like, 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 know, he 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. 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.

34:47

Yeah, I mean, I feel like it's one of those situations where it's like SAS led the way. Like, these guys figured out how to sort of worm into enterprises and get people excited about what you were doing. And now AI is like taking that model and 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.

35:25

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 going to go back over it, but I just love that Dylan's walking Jason there. And Jason already knew. But walking the audience through, what is SOC 2, why does it matter? Some things, no matter if it's the SAS era or the AI era, do not change. And that is, you will have to get sock to report.

35:50

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 vantage of the world to sort of take care of it.

36:12

I was about to say, I'm going to. I'm going to throw a bone to our sales team. This is not in the script, but vantage.com twist if you want to save a thousand dollars off your sock tuber board. 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.

36:23

Burnout I, during this Covid crisis, said, that's it. Give me a list of every single SaaS product.

36:38

Yep.

36:47

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 $1200 and I guess I had increased their price and they assumed we had all these accountancies. They were doing kind of the, the gnarly thing where they charge you for accounts but not usage.

36:48

Yep, Dirty.

37:09

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.

37:10

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 say they don't like it.

37:15

Got it.

37:22

Because it's variable cost, you don't know what's going to come.

37:23

Explain the issue to somebody who doesn't understand what we're talking about right now.

37:25

Yeah. So Slack's 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 something that I think could be really interesting to me. It incentivizes the right behaviors. Like if you get to the point where anyone can 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.

37:30

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

37:58

I don't know what it is because 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 protest, you know, of course, I just can't. Not even hear.

38:11

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.

38:23

So viewers are free in figma.

38:32

Okay.

38:34

So editors are the only ones we charge for great.

38:34

So if you edit something.

38:36

But we're not doing that yet. Right now it's like, right now it's like, okay, if you're an editor, 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 cheat our system.

38:38

But if somebody came to you and it's like, hey, you have you built this for three editors for the last six months? You would give them a credit, right?

38:49

Yeah, if we thought it was like really clear that it was wrong. But also, you know, if it's like, depends on the case by case basis too.

38:54

This is what you got to do. You got to build. The SaaS industry now has to build trust. And when they.

39:02

I completely agree with that.

39:06

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 setter. They send you your monthly utilization every month.

39:08

Yeah, so I love that about Slack. It's the trust part.

39:18

So. 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.

39:20

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

39:47

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 three years, depending on how long you sign up for. And they go, good news, we added all these features and it cost 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 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, 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 and then charge me for that? So I think this is one step along a larger journey that we've been seeing. But I just love to see how we're talking about it at the time because I can't recall the last time someone said we have to cut our SaaS spent. That doesn't come up right. Instead it's exactly what you said. It's dear God, did you see our clog bill?

40:57

We're both right. It's token maxing. There was no figma maxing back in the day.

42:00

No, I mean, what is that, 13 extra seats that you pay 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.

42:05

Yeah, no, didn't end up any of those products. They were just, they just look nice.

42:17

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.

42:22

Exactly.

42:28

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, Lime, weren't you part of that product?

42:28

To some degree I was employee number 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 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. Because to take you back in time, folks, in 2007, this was around the time people first started to notice, you know, Google results, they're kind of not as reliable as they once were. Originally, when Google first launched, it was like a magic trick. It finds exactly what you want. But over the years, there would be a lot of ads at the top. They were pushing a lot of the best results down, or there were a lot of these like content farm, SEO pages that were crowding out the best stuff. So Jason's classic example back in the day was what if you search Paris hotels? The old Google would give you, your top page would be here, 10 great Paris hotels that are good options or maybe Yelp or TripAdvisor or something. But now you would get all these like travel blogs and like, you know, random ads. Whoever paid to be on the first page of Google. So that was Jason's observation. And the idea was we were going to have all of these. I'm sorry, I'm calling something. 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 Bahala 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.

42:40

So Lon, let's see the story about how Jason Calacanis idea for luxury communism for partially employed Hollywood screenwriters worked out well.

44:55

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.

45:04

We're like a high school kid.

45:38

Yeah. I have a Mahalo mug. Or rather my mother has Mahalo mug.

45:39

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.

45:43

Wow.

45:51

In run rate before Google just said Mahalo. Ehow how stuff works.

45:52

Yeah. It was a big change.

45:58

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 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.

46:00

Yep.

46:23

That was literally the idea for Mahalo.

46:23

I'm sorry to trigger this.

46:25

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 no index anything under 400 words. Everything above 400 words. Then we'll index it. We'll just break the software to do that.

46:27

Yep.

46:55

And he lied to my face. And they literally, if there's somebody who wants to do an antitrust, just go back in time to them pushing Yelp down, putting ehow, Mahalo, everybody else out of business or moving them down the page and ankling them and then replacing them with the one box. And the sinister thing is they use their technology to find the answer on your page and then put an abstract on the top. And if you opted out of that, they wouldn't index you. So they Gave you no choice. It was like one of the most sinister moves in the history of. It taught me a lot about business, which is, 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 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 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.

46:56

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.

47:53

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 race constantly racing against the clock to make pages in time to catch the tail of, you know, Google trends and rank highly for them. And so it was, I don't think ultimately it was, like, very sustainable, but for a short time, it really was working. And we got enough SEO lift from those pages to make it profitable as just kind of like a destination site on the Internet to look things up.

48:03

So Mahalo walked so Grokopedia could run, right?

49:21

I mean, 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. We had like freelance writers getting paid pretty handsomely by the hour to really write good quality pages. So I don't think we were, we weren't trying to do like, you know, like, like we got swept up in that like low quality garbage spam site sort of call. And I think that's what Jason's objecting to is like 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.

49:25

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?

50:05

What have we?

50:18

And so, yeah, and that's exactly what

50:18

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.

50:19

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 bit much for a single company.

50:45

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.

51:00

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.

51:12

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

51:21

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. Lon is here mostly to poke fun. I'm 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.

51:43

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.

52:11

I think it's great for people to be in physical spaces together.

52:19

Yeah. So you were not bought into this like other people are, do you think?

52:21

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.

52:25

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

52:31

Oh, man. I think that'd be awesome. If it's true, I think.

52:37

Well, 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 gonna open Apple stores in the first two weeks. I think restaurants are gonna start opening again April 15th or so in that time frame.

52:40

Sadly, no.

52:53

I think Trump said something like, they'll be back for Easter. So I think people are going to get the test results back. We're sitting here on the 24th. I think people last week was peak fear in my mind. It could be this week for people, but I was experiencing peak fear last week.

52:53

Bummer.

53:08

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

53:09

Yeah, do it, Dylan. Nobody knows. I mean, that's one thing we guarantee. Nobody knows.

53:12

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, 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. So I think the.

53:17

So what do you think? You think San Francisco is a chance? San Francisco Bay Area, San Mateo county, et cetera, says two more weeks of this, four more weeks of this.

53:46

I, I think it could be a lot longer potentially. And I think there could be all

53:53

the way to May or June.

53:55

I don't know, I'm not sure. But it's, I think that there's also potential for. If we start to see people disregarding the orders, I wouldn't be surprised if we see enforcement. Yeah, I think people aren't even thinking about right now. Yeah, but it's.

53:56

That would be civil unrest on a level that would be disturbing.

54:08

I don't know. But it depends on sort of like how people think about the situation. But any case going back to sort of arc.

54:10

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 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 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 they're trying to figure it out. Like our cloth masks.

54:16

Good.

54:37

Remember 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 that was crazy. It was 24 months.

54:38

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 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, like you're hysterical, you're paranoid, you're a hypochondriac. Like no. And I clue myself like nobody thought it was going to last beyond May or June. It was on. It was unthinkable to us that, that it could get that bad.

54:54

Yeah. I'm glad that Dylan was a little bit more bearish, a little bit amazing, almost prescient. But he said, you know, if we go back out, there'll be A second wave. I mean, there was more than two, but he was looking ahead there. Yeah, yeah. It's interesting how the COVID moment changed so many people's thinking patterns.

55:27

Yes.

55:46

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 is.

55:47

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

55:55

work from home revolution?

56:30

So like, like it does kind of go back and clarify. Like these were actually like covet 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.

56:31

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 touchstone of people doing the day in the life videos on TikTok back in the day.

56:59

Yeah.

57:21

Yeah.

57:22

Oh, man, people really blew up some comfy jobs, didn't they?

57:22

Yeah, for sure.

57:25

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

57:27

Yeah, it's. No one needed to know how much time you're spending every day refilling your Stanley mug. I don't think.

57:32

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 Lawn a excellent trip down memory lane. We're going to keep pulling out these epic moments when we can we do them here and there, but lan 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.

57:38

There you go. Thanks, everybody, for joining us. We'll see you next time.

57:58