The Exchanges, every show

Q Oh, I think that would do good ratings. Okay. Steven, you also talked a little bit about in, in a recent newsletter about how, uh, basically we have very limited regulation on these companies. Uh, and even then they might still not be following. So can you just expand upon that briefly?

A As of 2026, there is finally some amount of law in the United States about how companies are meant to do testing for the catastrophic risks we have talked about. Um, until this point, purely voluntary. This bill is called SB 53. It came into effect in January and it's very, very light touch. It basically says the most major of the AI companies, you need to publish how you are going to test for these risks. You need to do what you said you are going to do, and you can't be misleading about it, but there's no quality standard. You could basically say, we will test for the risks as we deem appropriate and nothing further, and that, that would be fine. But if you say you are going to do this testing, you need to, in fact, follow through on it. Um, and unfortunately, it seems like OpenAI's release of last week, GPT, 5.3 codex, one of the big breakthrough models we've been talking about. As I look over the evidence, It seems like open AI did not abide by the testing that they had committed to in various ways. And so, you know, ultimately this decision now is with the attorney general of California to investigate it, whether to enforce a fine, a pretty small fine, maybe like up to a million dollars compared to open AI, hundreds of billions of dollars in valuation. Um, it just really seems to me like if we care about these risks, letting companies self assess in this framework is reall…

AI assessment note: “This bill is called SB 53... It seems like open AI did not abide”

Q That's awesome. You, um, you had, um, a pretty bold, uh, thought last time that you were on. I think you said something, Laura, you, uh, you predicted that America's decade, the next decade for America is going to be flat in terms of economic growth, and, um, I think you also said for the, uh, index funds. Do you still believe that to be true?

A Yeah, I'm selling down my American stocks, mostly because I'm diversifying, because I don't want to lose. I've lost all, I've been rich three times, which means I've lost it twice. I can't go back. I'm not, you guys are young and have good hair. I'm neither, neither of those things. I can't make it back again. So I'm diversifying. And if you just look at the cycle of American markets or the global markets, typically the U.S. outperforms for eight years, then emerging markets outperform for eight years. It goes back and forth. We've been outperforming emerging markets for 17 years. I still believe the markets are cyclical. The Buffett index, stock market valuation versus GDP, he likes it at about 90%. It's at 210%. The S&P is trading at historic highs. 97% of the time, the S&P has traded at lower valuations relative to earnings. So, it's not, it's not a criticism of America. I just think America, America is an asset. The rest of the world is an asset. There's America as an asset, everything, every public company in America, every public company outside of America. They're equally priced right now. They're both, you can own every public company in America for a hundred bucks, or you can own every public company outside of America for a hundred bucks. What do you think is the better value right now?

AI assessment note: “Yeah, I'm selling down my American stocks, mostly because I'm diversifying”

Q What brought your interest in finance when you were in school?

A I wouldn't have heard of Goldman Sachs till I was 21, but Hunter High School had a program where you only had to take two classes as a senior. So I worked at a stock brokerage firm in 1987. I was there for the crash. I learned what money management was. Reading the tape, going through the quotrons, going through the annual reports. I wouldn't have said I was particularly interested in finance. I was a numbers guy growing up. I majored in political science in college, but when I got to be a senior, I joined the campus recruiting. Now people are like, hey, my dream is to be an investment banker, but that wasn't the world back then. What you saw was that the highest end kids were going into finance, and there was two choices. You could go down the banking route, or you can go down the trading route. I remember I went to a recruiting dinner at two-thirty in the morning. They went back to work, and I said, wow. Then the O'Connor guy showed up. O'Connor was one of the original trading shops The predecessors to the prop shops. Susquehanna and O'Connor were the two back then. The interview question was, what's 49 times 28? And I say 1372. They say, Mets play the Yankees in the World Series. What are the chances the Mets win in four? I say one out of 16, they say you're hired. So that's how I got into trading.

AI assessment note: “Hunter High School had a program... So I worked at a stock brokerage firm in 1987.”

Q Why don't you take me all the way back to your upbringing?

A I grew up in Queens. My parents were immigrants. My dad was an engineer and a builder. My mom was an accountant. Very excited to be in America. He was in the first wave of immigrants from Asia after the Six to Five Immigration Act. He gave us American names. He said, we're going to be completely integrated. I didn't meet another Indian family till I was 16. He said, in America, you have to learn golf, tennis, and skiing. In my neighborhood, I was the only kid that did that. Just me and my brother. I went to high school in Manhattan. I commuted an hour and 20 minutes each day from Queens. I went to Cornell. I majored in political science, government, and then I went on to Wall Street.

AI assessment note: “I grew up in Queens. My parents were immigrants.”

Q Where did you go when you left the trading floor?

A I ended up going to Credit Suisse Financial Products in 1996. That was the hot derivatives place at the time. For a derivatives trader, that was the ideal place to work. It was a joint venture, part of Credit Suisse versus Boston. I joined the index arbitrage desk. Now you'd call it the equity basis trade, maybe Delta One. Because most banks, the proprietary guy was the end of the desk of that relative group. We had one group with a special forces group, effectively, The job was to trade S&P futures versus the underlying 500 stocks. Credit Suisse Financial Products was a clever place. The guy before me made ten million dollars in P&L, making 40, 50 grand a day. My first year, we made fifty million dollars in P&L. We were treating every index R basket as an option. First, we were buying 500 stocks versus futures. Then I said, why don't we buy 50 stocks versus futures? Then instead of Stocks versus futures. Why not stocks versus stocks? Then if we're doing it in the US, why don't we do it in Europe and Asia? Within a short amount of time, it became a several hundred million dollar business. The first three arbitrages Were take technologists and pay them like traders, which people weren't doing then. So staffing yourself from the IT department and the quant research departments, not necessarily the MBA classes. The second was collecting and storing data and doing things with it an…

AI assessment note: “I ended up going to Credit Suisse Financial Products in 1996.”

Q Yeah. I'm like, have you used any other tools? Like why you, why suggest Google AI studio?

A I use AI, so AI studio is my favorite for like a one shot prototype. So if you just want to see something, you're not working in an existing code base, you're just like, what would this look like? Google AI studio is really good because it'll do it end to end. When I'm actually working day to day in an existing code base, um, like in my current startup, we typically focus on using cloud code just because it's really good at working within a code base. Um, and then sometimes if I do want the capabilities of Gemini, But I still want to work in, um, an existing code base. I'll use Gemini's model and cursor. And then I found that Gemini is really good at UI and shader work and like more complex animations.

AI assessment note: “AI studio is my favorite for like a one shot prototype.”

Q Six million homes. Really? And, okay, sorry, where are you selling into? Are you bottoms up selling to one homeowner, then you spread or you're top down selling to the logo?

A Yeah, absolutely top down. And, and we even started kind of far up market, large management companies, and we've gone kind of further and further kind of across that, that segment as we go. So our first customers had, you know, 50,000 plus doors or homes that they would manage at a time, but we sell to the community association management company. Those folks, we become the general ledger system of record for them and for all the communities that they manage, as well as the system of work for all the work that gets done within that community, coordinating with vendors, collecting dues, paying invoices, reporting, as well as the system of engagement for them to provide a technology kind of front door for all of the homeowners and residents in the communities that they manage.

AI assessment note: “Yeah, absolutely top down. And, and we even started kind of far up market”

Q in that order. So let's start in the mid-Atlantic. I want to get to this DOE emergency order and the, you know, concept of data centers bringing their own generation and all that, but I want to get there after we talk about what's happening in that market at the high level. So start me off with the 30,000 foot view. Like, what is the state of affairs in PJM?

A Yeah. Look, there's been a lot of change, and the change has been quite rapid. When we rewind back just a couple of years, we had capacity clears that were going off between 30 and 50 dollars per megawatt day, and that compares to a little bit over 300 dollars a megawatt day in the more recent clears, uh, and subject to the cap in the capacity auction mechanism. Those low clears were in many ways, I think, sending the signal that we had more than enough capacity to We had a period of time between, let's say, 2008, the great financial crisis, and, ah, really the last year or two where there was virtually no demand growth in the PJM market. And in the absence of that demand growth, the environment was really one where new assets were being added to the market to replace older assets, less efficient assets, higher fixed cost assets. Uh, along with the addition of renewable projects supported oftentimes by state-level mandates or corporate procurement. So in that environment, there wasn't a need, and there was certainly no price signal to go actively develop and build new generation outside of renewables. And that's the backdrop really Kind of shifted really quickly over the last couple of years as probably a combination of factors hit the market and has driven up demand growth from that very quiet, virtually no demand growth, almost a market stasis to the real need for new generat…

AI assessment note: “capacity clears that were going off between 30 and 50 dollars per megawatt day”

Q It seems like a lot of the focus, both from a policy perspective and also a market perspective, is on, let's build as much new gas generation as quickly as we can to meet the capacity need in BJM. And it sounds like you're saying, to some extent, yes, but that actually isn't necessarily the, the savior, especially in the near term. Is that right?

A Yeah. When I look at the resources that we have available, Large scale gas is a 20, 30 plus new resource. In the interim, there are other things that we can do. We can add demand response. We can add batteries. We can upgrade existing facilities. We're working on the conversion of some of our combustion turbines to combined cycle power plants that can be done more quickly than building something that's completely de novo. We have a project where we can swap out combustion turbine blades and get dramatically more capacity. So there are different things that we can do as a bridge to large scale, completely de novo, new generation. But if that's what we're hanging our hat on, we need to anticipate that that's an end of the decade plus project. Deliverable at large scale resource.

AI assessment note: “Large scale gas is a 20, 30 plus new resource. In the interim”

Q How can you model what that value looks like when you're talking about like construction, manufacturing, whatnot?

A Yeah. So there's usually a very good opportunity to help the company slash the customer understand your business case. I come from that world. I'm a non-technical founder, and when we work with our customer, we sit down with them. We look at all of their workflows, processes, and we do an AI potential analysis, which says, hey, if we do these five things, we can save you X amount of hours. You can reallocate your industrial engineers to actually meaningful work. We can reduce your failure rates. Humans make mistakes. AI can be better in certain things than humans. Not in everything, but in certain things. Um, and then the other thing is, can we generate more revenue because the AI takes action on certain things where humans are the limiting factor? So these three things usually drive a potential value of the system. And if we say, Hey, we think that value is a million a year. Our price tag is somewhere between 15 and 25% of that as an annual license. So 150 K to 250 K to generate a million in annual value.

AI assessment note: “we do an AI potential analysis, which says, hey, if we do these five things”

Q How does the UI paradigm change in the world of AI? Like, everyone's like, now we're just all going to be voice. Do you agree with like, it's all voice.

A I think, so voice is amazing for enterprise. I think that, uh, one dynamic UIs and two chat UIs are overstated in consumer. And the best thinker on this is actually Eugenia who founded Replica and now Wabi. She's, she's great on this. And what she would tell you if she was here is that, look, most people don't want to save time. They want to spend time. Okay. And the products are designed by the most high agency people in the world. Like Sam and Elon are the most high agency people in the world. For them, the optimal UI is a chat box where you say exactly what you want and like, voila, there it is. But for many people, they're again, looking to waste time, spend time. They want a browse based interface. They're not quite sure what they want. Can't always articulate it. So I think that in a world where we have intent-based and browse-based, browse-based largely stays the same. And perhaps the future of intent-based is chat. I'm still a little skeptical.

AI assessment note: “browse-based largely stays the same. And perhaps the future of intent-based is chat.”

Q How does the UI paradigm change in the world of AI? Like, everyone's like, now we're just all going to be voice. Do you agree with like, it's all voice.

A I think, so voice is amazing for enterprise. I think that, uh, one dynamic UIs and two chat UIs are overstated in consumer. And the best thinker on this is actually Eugenia who founded Replica and now Wabi. She's, she's great on this. And what she would tell you if she was here is that, look, most people don't want to save time. They want to spend time. Okay. And the products are designed by the most high agency people in the world. Like Sam and Elon are the most high agency people in the world. For them, the optimal UI is a chat box where you say exactly what you want and like, voila, there it is. But for many people, they're again, looking to waste time, spend time. They want a browse based interface. They're not quite sure what they want. Can't always articulate it. So I think that in a world where we have intent-based and browse-based, browse-based largely stays the same. And perhaps the future of intent-based is chat. I'm still a little skeptical.

AI assessment note: “voice is amazing for enterprise. I think that... chat UIs are overstated in consumer”

Q terms of like having a command of technology, and you said earlier about the challenge of shipping products and getting from zero to one, showing that you've had a success building in the past is a great way to prove that you can do it moving forwards. Do you have an unreasonable or an unwavering leaning towards serial founders who've proven that they can do it because of their track?

A Yeah, I'll give you a nuance take on this. So I think that repeat founders working in their domain of expertise Are formidable. Like the Clutch guys sold a company to Carvana. Uh, you know, they weren't super happy with the way that the whole thing, you know, ended up in terms of their startup achieving their ambitions. They went and then started another company out of that also in the auto space called Clutch. It's going extraordinarily well. And they know, you know, they're taking all the shortcuts because they know the market. So I do think particularly in enterprise, um, working in the same domain and, you know, being a repeat entrepreneur is a huge, uh, source of alpha. I actually think conversely in consumer, having a beginner's mind and a high willingness to be embarrassed is a competitive advantage because so many consumer products feel embarrassing and, you know, they're immediately dismissed as embarrassing or impossible or a silly, non-serious thing to be working on. When you're 25 and like the stakes are low, you just want to make something happen in the world. That is a perfect setup. Once you've sold a company, all of a sudden it's like, your venture friends are like, what are you working on? You know, like your girlfriend or your boyfriend's like, what are you working on? You want to sound cool at dinner parties or at the bar, and that slight hesitation to be emb…

AI assessment note: “repeat founders working in their domain of expertise Are formidable”

Q So when you think about market composition for that market and the kind of developer tooling, Uh, space. Does that look more like cloud, or does that look more like Uber and Lyft?

A I don't think it looks like Uber and Lyft, right? I think Uber and Lyft are the, to my mind, the most extreme examples of pure substitutes, and a lot of the sort of price has been computed away. You look at cloud, you sort of have this oligopoly where they all actually have pretty reasonable margins, right? And, you know, you can squint and say, of course they have their specializations, but they're roughly substitutes, and yet they've all done well. I think the, uh, the foundation model companies look a little bit like that. And I think in the apps layer, you're just going to have people that want to Consume the code they generate through a rich IDE and those that want to be closer to the metal, and that's probably closer to AWS Google Cloud than it is Uber Lyft.

AI assessment note: “I don't think it looks like Uber and Lyft, right?”

Q You saw that both at Australia and then later back home, New Zealand super fund. What are some of the subtle differences in two different sovereign wealth funds applying the total portfolio approach?

A You've got to understand the objectives of each of the organizations. One thing that I spent quite a lot of time thinking about when I arrived at New Zealand Super was why Future Fund and New Zealand Super did things quite differently. Future Fund was set up in 2006, started operating in 2007, so it was later than New Zealand Super, which got going around 2003. They had a lot of similarities, sovereign wealth funds, both in Australasia. New Zealand Super had larger risk appetite than Future Fund. The reason being, it had a longer horizon. It was getting small contributions over a long period of time. The distributions from New Zealand super were going to be some way off in the distance. Future fund had a startup with a lot of money to begin with. Sixty billion Australian dollars. The last thing you want to do when you've got a big money to start off with is to lose a chunk of it. You're going to be conservative. They also started at a time when assets were cheap. They had a lot of liquidity and were able to benefit from those high prospective returns because of those cheap assets. That worked pretty well for a while. Future Fund was discretionary, active, a shorter horizon because the expectation was that they would have to make distributions to the budget come twenty-twenty. It turned out not to be the case, and those distributions have been put off further and further. The te…

AI assessment note: “New Zealand Super had larger risk appetite than Future Fund. The reason being, it had a longer horizon.”

Q There's a lot of steps there. In your time at Wall Street, what were some of the different roles that led you to understand how you thought about markets?

A It's an interesting question because you learn something in each role. When I was at Chase before the merger with JP Morgan, I got to, to sit in the dealing room and to combine different products. I got to sit with the swaps traders, the floating, floating traders, the option traders, and I would structure transactions. Seeing things from different perspectives was very helpful. I still think about going through the pricing on a floating, floating swap. That was insightful. Then moving to the FX options desk, it was quite a revelation because when you come from an academic background, you think it's all about the formula. And you don't really understand how people derive or how they trade implied vol. That was another lesson. There are lots of incidents like that. Those are two early ones that stand out.

AI assessment note: “When I was at Chase before the merger with JP Morgan, I got to”

Q So geographically, it fit. How did you end up professionally deciding to make this move?

A I've been at New Zealand Super for five years. It's a great place, and it's nice being home. I got a call from a recruiter. They mentioned the co-oper's role. Frankly, I wasn't that interested. It's a tough gig. But the call prompted me to think about it some more, to do some due diligence. I thought, there's so much potential there. When the recruiter called back, I was more open, and the recruiter immediately got Marcy on the phone. She's very persuasive and very engaging. Not long after that call, at the same day, the recruiter called me and said, we want you to interview with the board subcommittee. Shortly thereafter, I interviewed with the board subcommittee, and great questions, and I really enjoyed the interaction. That's what I wanted to roll.

AI assessment note: “I interviewed with the board subcommittee, and great questions, and I really enjoyed the interaction.”

Q How do you think about how to measure appropriate diversification in a TPA approach?

A Scenario analysis is important. Let's take a simple example. Equities and bonds. Do they diversify? Is a bond exposure going to diversify an equity exposure? Well, it may. It depends on what's happening. Take the example of an inflation shock. If inflation goes up, nominal bonds are going to be hit. Equities are probably going to be hit as well. If you have a growth shock, it's going to be the opposite. Equity is going to benefit. Bonds are probably going to be hit, so bonds are diversifying there. You need to look at what's driving the event. Rather than simply looking at historical correlations, one needs to be thinking about multi-dimensional scenarios and to think about how the portfolio behaves given those scenarios.

AI assessment note: “one needs to be thinking about multi-dimensional scenarios”

Q you, because you were a young guy, when you started this, you were like 31, 32. How did you start to manage that side of the business? Because you were making this thing and writing a paper, explaining it, thinking deeply about it, but there's another whole other side to it, which is a business, which is the people that you bring in and then that you have to manage.

A Yeah, um, that was my MBA is essentially was pure software. Uh, and luckily the products were amazing because my management was not. I only really had one gear, which was work hard, and so whenever things got harder, you know, difficult or challenging, I would just work more, so I would, you know, be coding at night, um, and then, you know, trying to be CEO in the day, but I looked haggard, you know, I smelled, I hadn't showered, uh, you know, it was sort of not a very inspiring look. Typically, you know, your Salesforce and that kind of business is very important. Um, and unfortunately I had little grasp of who's the right type of person to run the Salesforce. And so I kept hiring the wrong people and then taking a year to figure that out. And so we had a new head of sales every year, five years in a row, which is chaos in enterprise software. And yet, despite that, um, we doubled sales every year in that time. So again, that was the strength of the products. Um, but to say it was unevenly managed would be generous.

AI assessment note: “I only really had one gear, which was work hard”

Q because, you know, I asked you earlier about your previous companies. You said sometimes, you know, when you're chopping wood, you can't sharpen the axe. In this case, clearly you took the time to sharpen the axe. So how did this, uh, sort of approach to building culture and building, uh, An environment, uh, around excellence, some people would say, um, mercenary culture. How, how, how did you develop that?

A Um, the core of it was if you had incredibly talented people, you didn't need a lot of process and rules. Netflix was anti-process and rules and pro-talent density. And then to get talent density, we modeled it on a championship sports team and they had to swap out players. And that was a normal part, uh, of the ethos. And so that contrasted with the notion of company as family, you know, you're all like my family, that kind of CEO talk. But then you go and lay someone off, which, you know, if you were on hard times, you wouldn't say, we're gonna lay off your sons, you know, your daughters get to eat, and you know, um, you know, our, our ethos in family is around undying loyalty. That's what we admire. And so I realized, oh, it's really that we want to organize as a professional sports team and not a family. And lots of people were operating their Silicon Valley business that way, but none of them admitted it or not many. And so the shock was this, the sort of resonated because it was the truth of the, what we aspired in much of the competitive ecosystem of team, not family, but no one had said it so directly.

AI assessment note: “we modeled it on a championship sports team and they had to swap out players”

Q So, how did the idea to make original content come about? Was that in response to where you saw the The, this sort of whole industry headed that if you didn't do that, you would just, and you were just a rental streaming rental service, then your business wouldn't survive.

A Well, every cable network, which is a subscription business, had started on other people's content, build some audience, and then start to add their own content. HBO was built on other people's content, and then got good at original programming. So Again, it was a very well-trod path. And when Ted Sarandos came in, which he joined us in 2000, um, he was the one who sort of articulated, you know, eventually we're going to want to do original content. And then we actually started in 2005 doing original content on DVD. And we didn't have a big enough subscriber base. And so after two years, we closed that down. That was red envelope entertainment. We closed that down in 2007, and then we reopened it essentially with House of Cards. Uh, I believe we commissioned that Ted did in 2010, um, and then it came out in 2013.

AI assessment note: “Again, it was a very well-trod path. And when Ted Sarandos came in”

Q own company. You called it Pure Software. And, and I'm wondering, I mean, did you feel ready to, to do that at that point? I mean, I mean, clearly you'd made connections at, at, you know, previous startups and, and maybe, you know, in your previous job and, and at Stanford. Um, but like, how did you start to build a team and, and to start to build a company?

A I was underprepared, um, for sure. But I would say one of the things about being around Stanford is, Is all these pretty normal people create companies and you meet them. And so it doesn't seem so impossible at all. Um, but I didn't know specifically how to do it. I didn't understand what incorporation was or how to get a lease or anything. The first year was trying to do a proof of concept. So I spent a year in a cold cabin in the Santa Cruz mountains in La Honda, uh, where we just had a wood fireplace. Um, and And had bought a Sun Microsystems computer, uh, and at the time that was like as expensive as a car.

AI assessment note: “I was underprepared, um, for sure.”

Q video rentals was, uh, was like a, a blue ocean? I mean, yeah, and Blockbuster, you know, I, I remember going to Blockbuster sucked. You know, you go to Blockbuster and there'd be like, you know, a hundred cassette, you know, a hundred, uh, boxes for a movie you don't want to see. And the movie you want to see, you couldn't get. And then you'd pay late fees, right?

A They had out of stock and various problems. One advantage is that relative to Amazon, the nice thing about rental is because you got to return the good. It's a very different logistic path than selling things. So then it makes less sense for Amazon to invest in because it's only one category that does this. You know, you don't rent computers or bicycles or other things where they get shipped and shipped back. And it was a large enough business to be interesting. Blockbuster was about five billion in revenue, but not so large as to attract Amazon, uh, you know, and others into it. So, you know, it was, uh, that, that, that crosshairs made it potentially interesting from an e-commerce standpoint.

AI assessment note: “that crosshairs made it potentially interesting from an e-commerce standpoint.”

Q the headache, check out Delve at the link in the description or go to delve.co slash starter story. Thank you to Delve for sponsoring today's video. Let's get back to the story. Okay, cool. So number one source of traffic. That's cool. You do run 20 different products though. I'm curious if there's any strategy there in terms of having all these different products. How does this help you grow?

A It's really helpful having so many products, especially ones that are very closely related, because it means that we can cross promote them and get multiple sales from the same customer. And there are many ways that I would recommend doing that. We've got one plugin, And two plugin bundles. And this is a key part of how we benefit from having so many products. For each of our products, we have selected a closely related plugin that we try to upsell with it. We then do additional tasks such as after three days following the purchase, we send an email offering them 50% off their next plugin. On Black Friday, we have separate email campaigns for potential customers and existing customers. And for the existing customers, we will use language like discount off your next plugin. And I think the trick there is to target the customers and segment your list so that you are recommending very closely related products to the one that they're already using. And that maximizes the likelihood that they're going to buy. And then you can keep sending the message home, things like banners on your settings pages and constantly reminding them you have these complimentary products We should directly relevant to the one you're already using.

AI assessment note: “it means that we can cross promote them and get multiple sales from the same customer”

Q All right. Well, 20 apps, you run 20 different apps. That's crazy. Can you explain how this Even works. How do you run 20 apps? What kind of apps are these? And if you could pull up some of your revenue dashboards and show us would be awesome.

A Uh, 19 of our products are WordPress plugins. And the final one is our new Shopify app. Our plugins are fairly simple, which is how we can have so many. We've got one called Document Library Pro, um, which lets you add any kind of document library. And we've got lots for WooCommerce. They let you add product tables, product options. Protect areas of your store. They're typically, I would say, small to medium apps that let you add specific functionality to your WordPress website or WooCommerce store. So we have a choice of plans. We've got one site, five sites, or 20, where you either have an annual subscription or lifetime. This is our 20 25 revenue. You can see it's just over 1.7 million dollars. I know I said 1.8 million earlier. That's Because we have other revenue streams such as affiliate income, and we offer some development services. In terms of stats, our average monthly revenue is about a 150,000 dollars across all of our plugins. It's higher than that in busy months like November and lower in quiet months like December. Over the entire lifetime of the business, we've sold 9.8 million dollars worth of WordPress Plugins. Overall, we think that our plugins are used on over 90,000 sites. That's the premium plugins. And also we have free versions of some of our plugins. So that is the total number for paying customers. We have 17,000 on an active subscription. We do have m…

AI assessment note: “19 of our products are WordPress plugins... This is our 20 25 revenue.”

Q I think there's a lot of actual concern about, like, is the vision we had for the company in terms of its durability or its value, uh, still as valuable as we thought five years ago? And for Roblox, perhaps because you were You know, pointing at something so far away to begin with, it's like pretty clear, you know, I think we have crisped that up over the years.

A I would say two years ago, we were a little less crisp. We would say we're going for a billion DAUs. That's a good spec with this spec I just mentioned. It's a little harder to operationalize around product management teams and that. So we, we took a step, a stepping stone and said, we want to get to 10% of global gaming content. Um, on the way to that. It's actually a remarkably good step. It's about three hundred million DAUs. It's about twenty billion. It's about three X where we are. It can be forensically torn apart. We can see what part is the USA market. We actually have a higher target for us than 10%. Um, and so that has been very clarifying. I think for a software CEO, Always knowing both three X and 10 X is very helpful, because if you don't know 10 X, then it's hard to sleep at night. If you don't know three X, it's hard to plan forensically how we're going to operationalize that, how quickly we're going to get there.

AI assessment note: “I would say two years ago, we were a little less crisp.”

Q our company. And that is, you know, Indicative of progress. But, but I have no idea whether that's indicative of progress, right? Like, does that happen every single time? Is it always positive? Do people get rejected somewhere in this process? Like, what is it like in that murky, that murky early ground where there's all this iteration and, and work being done before you submit your formal construction permit?

A Yeah, absolutely. Um, I would say that while it is an indicator that things are happening in the company and an indicator that the NRC is not in the dark about what's happening in that company, at no point, sort of, in that process is NRC really issuing official decisions of any kind. In the pre-application activities, you do have to submit kind of a letter of intent. You have to submit, you know, billing information so that the NRC can start billing you for their time. Uh, and you, You do things like a regulatory engagement plan gets put together, and you tell the regulator how you want to, like, go about the process of engaging with them, and then there's usually public kickoff meetings and readiness assessments as a part of that, including public outreach meetings, and all of that is before you submit your application. Once you submit your application, NRC then decides whether or not to accept That application and start actually doing the review. People do get rejected at the acceptance of application stage, for example, if it just doesn't reflect the level of technical depth that NRC is going to need to do the review. That is certainly a thing that happens, and sometimes it's, you know, years after you've started your pre-application activities.

AI assessment note: “People do get rejected at the acceptance of application stage, for example”

Q Where did that take you in terms of the roles that you played as you got interested in what was happening in the banking system?

A I became increasingly curious about them, and I applied for a job at Westpac, one of the big four banks, Australia's oldest bank. The role I went into was called group controller. It had the potential to be quite a dry roll because its title ultimately meant that you were head of accounting policy, but it gave me great insights to the operations of one of Australia's largest companies. It had Over a 150 years of history at that stage, and there had been some great leaders. The leader of Westpac at the time was a guy called David Morgan. They had survived that banking crisis in the early 19 nineties when there were hedge funds on the register came through, and it was growing extremely well. I took that as a great learning experience. In a five year period We sold a very profitable but low growth finance business called AGC to GE Capital. That was an interesting experience negotiating with a bunch of Americans because that was the peak of their power. We bought one of the asset managers off Bankers Trust. The old Bankers Trust investment bank had a large funds management business in Australia. And I finished my time there on the executive committee of the financial markets team of Westpac in The world awash with liquidity. I clearly had no idea as to what was about to happen, and credit spreads at all-time lows. I was thinking that these asset managers I was curious about, and I …

AI assessment note: “I applied for a job at Westpac... The role I went into was called group controller”

Q That's when we all first started getting online, right? I think I got AOL in 1993. This is the very beginning.

A Wait, what was that called? AOL, yeah. Hey, growing up in the, you know, the DC area, we know a lot about AOL. But, uh, I, I lived with the whole thing. You know, the first couple of intrusions happened in 88 with the Hanover hackers and Cliff Stoll and those sort of things. You have the Morris worm. Actually, I think Cliff Stoll was 84. Morris worm was 88. Guy at Cornell, you know, right in a worm that, uh, had a finger demon buffer overflow and kind of spread them across Unix machines. By 93, I'm sitting at the Pentagon looking at log files, TS log file, secret log files, figuring out who's doing what. And by 1995, I'm responding to my first ever computer intrusions as an Air Force Uh, special agent in the Air Force Office of Special Investigations.

AI assessment note: “By 93, I'm sitting at the Pentagon looking at log files”

Q And then did you intentionally or make a point of getting, getting everyone together throughout the year?

A We did. We had, uh, we, we, we joked, we had onsites instead of offsites. We'd have onsites. Uh, we would fly. So I had people in India, um, uh, Europe, California, Atlanta, South Carolina. I'm here in New York, someone in Denver, someone in Chicago. I'm sure there's a couple of other spots. Uh, I picked Atlanta actually as my, as our, as our hub. Because it's everyone, there's always a direct flight to Atlanta and it doesn't have the same overhead as New York does. So what we did about once a quarter is we, we find a large Airbnb, like a 10 bedroom house or whatever. And, uh, we'd hole up there for four or five days. We would do some productivity sessions, some culture building sessions, some volunteering. I always would have a volunteering session in the midst of what we do. Uh, we would cook all our meals. I mean, we'd go out once or twice, but we would do a thing about cooking together as a team. And we'd always do a sort of a variation on a hackathon. I would call it, I always called it a scrimmage with the subtle difference between the hackathon where the goal is just to sort of prototype. The goal was to actually ship. So we would pick some very small thing. It could have been just a feature with an Augie, but a couple of times it was standalone products. Uh, and, and build and ship them inside of 48 hours.

AI assessment note: “We did. We had, uh, we, we, we joked, we had onsites”