Podcasts about cagr

Ian Cassel, founder of MicroCapClub and author of Stock Picker, joins Matt Zeigler to break down the mindset, temperament and core skills required to outperform as an active stock picker. They discuss microcap investing, position sizing, active patience, valuation, management quality, portfolio survival, benchmarking against the S&P 500 and how great investors evolve their edge over decades.Stock Picker: How to Develop the Mindset, Temperament, and Strategy to Outperform Wall Streethttps://amzn.to/4hU28ImTopics coveredHow an investor's motivations change as ambition gives way to family, legacy and the scarcity of timeHow Ian turned $20,000 into $120,000, then watched it fall to $8,000, and why that early win permanently shaped his risk toleranceIan's four-part survival framework: recession-resistant growth, strong balance sheets, conservative valuation and signs of intelligent fanaticismWhy balance-sheet strength is not just defensive and can let great companies act aggressively when competitors are forced to retreatWhy Ian targets roughly a 25 percent CAGR without relying on multiple expansionThe Judas goat lesson, talking your book on social media and why investors still have to do their own workWhy comparing short-term returns can corrupt an investing process and why Ian measures himself against the S&P 500 over a 10-year horizonThe five core stock-picking skills: identifying, analyzing, buying, selling and holding, plus why selling matters especially in microcapsWhy position sizing should account for initial excitement, and why Ian now starts much smaller than he did earlier in his careerActive patience, expanding your circle of competence and the difference between good, great and GOAT stock pickersWhy temperament evolves with experience, why leverage can destroy otherwise good investing, and why the best investors keep sharpening their edgeWhy Ian is willing to back repeat-winner management teams before every piece of the business is fully in placeTimestamps00:00 Intro06:58 The $20,000 to $120,000 win and 90 percent loss11:02 Ian Cassel's four-part survival framework15:02 Why strong balance sheets create offensive optionality19:03 The Judas goat and social media stock promotion23:18 Why comparison is the enemy for stock pickers29:39 The five core stock-picking skills34:43 Active patience and knowing what you are looking for39:28 Good, great and GOAT stock pickers47:02 How investor temperament evolves over time52:03 Leverage, situational awareness and surviving to compound57:24 Betting on repeat-winner management before the numbers arriveLearn more about the Excess Returns podcast network:https://excessreturns.coNo information discussed in this podcast should be construed as investment advice. Securities discussed may be held by the hosts and guests, their firms or their clients.

DigitalOcean just raised its 2026 growth guidance to 30–31%, and the stock sold off anyway.In this episode we work through what DigitalOcean's (DOCN) Q2 update actually changed. Management lifted full-year 2026 revenue guidance from 25–27% to 30–31% and pointed to a possible 50%+ growth rate exiting fiscal 2027. The driver is a scaling cohort of large enterprise and developer customers landing in a supply-constrained compute market — the same capacity bottleneck hyperscalers like Microsoft have flagged around data center construction.We cover the shift from an SMB cloud provider toward a developer and enterprise-scaler platform, why the co-location approach gives it an edge over hyperscalers building from the ground up, and how management reworked the balance sheet by retiring convertible debt, raising cash, and continuing buybacks. We also run a DCF scenario assuming a 36% five-year per-share profit CAGR, and talk through why the move from small-cap to midcap matters for a fundamentals-first thesis.For the reasoning behind more names like this one, Semiconductor Insider covers the process in more depth. Get access to all our research, weekly live Q&A events, and a growing set of tools to build your process: https://www.chipstockinvestor.comAll our socials: https://linktr.ee/chipstockinvestorIf this was useful, follow the show so new episodes land in your feed.Disclaimer: Content is for general information or entertainment only and is not specific or individual investment advice. Forecasts and information presented may not develop as predicted, and there is no guarantee any strategies presented will be successful. All investing involves risk, and you could lose some or all of your principal. CSI owns shares of DigitalOcean.

Brian Szytel hosts Dividend Cafe on Tuesday, August 11, describing a quiet, rudderless market session ahead of tomorrow's CPI, with the Dow and S&P down about 0.3% and the Nasdaq down about 0.6%, the 10-year near 4.69%, and oil up about 1%. He notes better-than-expected NFIB small business optimism (99.8 vs. 97) and slightly stronger existing home sales (~4.1 million) though housing remains frozen by higher rates. Szytel then analyzes U.S. federal debt growth across eras since 2000, citing debt CAGR of 7.3% (2000–2008), 8.0% (2008–2017), 9.5% (2017–2022), and 6.6% (2022–now), arguing debt still grows faster than nominal GDP even in strong times. He also clarifies U.S. tax revenue is 17% of GDP federally but 27% including state and local when comparing to Europe's ~50%. 00:00 Market Snapshot 00:56 Economic Data Check 01:39 Debt Growth Explained 02:53 Debt Eras Breakdown 04:03 Why It Still Matters 05:43 Tax Revenue Clarification 06:47 Wrap Up Links mentioned in this episode: DividendCafe.com TheBahnsenGroup.com

Ryan Belanger — Founder & CEO, Claro Advisors Most firms are adding AI to existing workflows. Ryan Belanger chose a different path, acquiring a fintech company and rebuilding Claro Advisors around an AI-native platform. He explains why he believes the future belongs to firms that rethink how they operate, not just the tools they use. In Summary Most firms view AI as another technology investment. Ryan Belanger sees it as a business strategy. Louis sits down with the Founder & CEO of Claro Advisors to discuss why his $1.5 billion RIA acquired a fintech company, built an AI-native operating platform, and believes the firms that gain the biggest advantage won't simply adopt new technology—they'll rethink how their businesses are built. The conversation also explores the broader philosophy behind that decision. Ryan shares why he's consistently chosen unconventional paths—from recruiting younger advisors and embracing a partnership model built around ownership to investing in proprietary technology instead of relying on third-party solutions. For advisors, the bigger question isn't simply how AI will change their workflow. It's how it may change what it takes to build a durable, differentiated advisory firm. The Storyline Every generation of wealth management has been shaped by a different competitive advantage. For some, independence paved the way to build unique branding and a bespoke client experience. Inorganic growth and M&A gave many firms access to scale and growth. Today, many believe the next advantage will come from artificial intelligence. But simply adopting AI may not be enough. Ryan Belanger has spent his career challenging conventional thinking. He left Morgan Stanley in 2012, well before independence became mainstream. He built Claro Advisors by investing in younger advisors instead of competing for established producers. He embraced a partnership model centered on advisor ownership rather than restrictive employment structures. And when AI began reshaping the industry, he made another unconventional decision: instead of licensing another technology platform, Claro acquired a fintech company and built its own AI-native operating system. Louis explores the reasoning behind each decision and the philosophy that connects them. Ryan explains why he believes proprietary technology will become a defining competitive advantage, how Claro's AI platform, Claire, is changing advisor workflows, and why the biggest opportunity isn't replacing advisors; it's giving them more time to do the work clients value most. The conversation also tackles practical questions facing every advisory firm: how to integrate AI responsibly, where human judgment continues to matter most, and why the firms best positioned for the future may be the ones willing to redesign their businesses instead of simply adding another layer of technology. Topics Covered AI-native advisory firms Acquiring a fintech versus licensing technology Building proprietary advisor technology Advisor productivity and workflow automation Recruiting and developing younger advisors 1099 partnership model and advisor autonomy Enterprise building and long-term differentiation AI governance and advisor trust The future of wealth management technology > Download a transcript of this episode… Listen and Learn Highlights for Advisors Why did Ryan launch independently long before it became common? (7:30) Ryan explains why leaving Morgan Stanley in 2012 wasn't simply about independence—it was about creating a better business model while betting on himself. Why recruit emerging advisors instead of established producers? (15:00) Ryan shares why investing in younger advisors has become one of Claro's greatest competitive advantages and succession strategies. Why would an RIA buy a technology company? (23:45) Rather than licensing another platform, Ryan explains why Claro acquired NDVR to build proprietary technology that could fundamentally change advisor workflows. How does Claire actually help advisors day-to-day? (33:00) From meeting preparation and client follow-up to portfolio management and workflow automation, Ryan walks through how AI is saving advisors meaningful time. Will AI replace advisors—or make them better? (36:30) Ryan discusses where AI belongs, where human advice remains essential, and why he believes technology should enhance – not replace – the advisor relationship. What does the advisory firm of the future look like? (38:20) Ryan shares his long-term view of how AI, proprietary technology, and advisor expectations will reshape wealth management over the next decade. Key Takeaways Ryan believes firms that build AI into the foundation of their businesses will create greater long-term differentiation than those simply adding new software. Claro's acquisition of a fintech company reflects a strategy of owning core technology rather than relying exclusively on third-party vendors. AI is most valuable when it eliminates administrative work, allowing advisors to spend more time serving clients. Recruiting younger advisors and investing in long-term talent has become a defining part of Claro's growth strategy. Advisor autonomy, equity participation, and technology can create stronger retention than restrictive employment models. Human relationships remain central to wealth management, even as AI becomes increasingly capable. The firms that adapt fastest may be those willing to rethink their operating model—not just their technology stack. https://youtu.be/7XvSXi0PzXI Quotable Moments “I wanted to build something that was integrated instead of just layering another tool on top.” “We're trying to make really good advisors become super advisors.” “Clients still want advice from a person—but they're going to expect that person to know how to use AI.” “The firms that win won't necessarily be the ones using the most technology. They'll be the ones building differently.” FAQs Why did Claro Advisors acquire a fintech company? Ryan believed owning proprietary technology would create greater long-term differentiation than licensing another collection of third-party tools. What is Claire by Claro? Claire is Claro Advisors' AI-powered chief of staff, designed to automate advisor workflows, prepare meetings, organize client information, and streamline operational tasks. How is Claro using AI differently than many RIAs? Rather than layering AI onto multiple disconnected applications, Claro built an integrated operating platform where AI has access to the advisor's workflow, planning, portfolio, and client information. Will AI replace financial advisors? Ryan believes AI will automate much of the administrative work advisors perform today, but that clients—particularly those with more complex needs—will continue to value human advice and relationships. How does Claro recruit advisors? The firm emphasizes advisor ownership, partnership, equity participation, technology, and operational support instead of relying primarily on acquisition-based recruiting models. What does Ryan believe will differentiate advisory firms in the future? He believes proprietary technology, integrated AI, and the ability to improve advisor productivity will become increasingly important competitive advantages. Ryan believed owning proprietary technology would create greater long-term differentiation than licensing another collection of third-party tools. Claire is Claro Advisors' AI-powered chief of staff, designed to automate advisor workflows, prepare meetings, organize client information, and streamline operational tasks. Rather than layering AI onto multiple disconnected applications, Claro built an integrated operating platform where AI has access to the advisor's workflow, planning, portfolio, and client information. Ryan believes AI will automate much of the administrative work advisors perform today, but that clients—particularly those with more complex needs—will continue to value human advice and relationships. The firm emphasizes advisor ownership, partnership, equity participation, technology, and operational support instead of relying primarily on acquisition-based recruiting models. He believes proprietary technology, integrated AI, and the ability to improve advisor productivity will become increasingly important competitive advantages. Related Resources Why AI Matters Now: Filling the Estate Planning Gap with Wealth.com Emotional Intelligence: The “Untouchable” Differentiator in an AI World Diamond Consultants Annual Advisor Transition Report Ryan BelangerChief Executive Officer & Founder Ryan founded Claro Advisors in 2012 after seven years at Morgan Stanley. He named the company after a Latin phrase “to make clear in the mind.” All Claro advisors strive to give their clients clarity and transparency, core tenants of the firm. Claro is continuously recognized within industry for its growth and thought leadership. In 2004, Ryan received a BA in Economics from The College of the Holy Cross and in 2009, he earned the Certified Financial Planner™ distinction. He is most proud of his philanthropic activity. Along with his wife Rachel, they started a foundation that raises money for genetic research in the name of their late daughter, Bella. Their focus is on extreme rare disease. Ryan resides in Boston’s Back Bay with his wife Rachel and their three children. He enjoys exercising, golfing, reading and spending time with his family. He has been featured in numerous magazines and industry publications and is regularly on television sharing his market thoughts. NOTE: The views and opinions expressed by the guests on this podcast are their own and do not necessarily reflect the views and opinions of Diamond Consultants. Neither Diamond Consultants nor the guests on this podcast are compensated in any way for their participation. View the transcript of this episode… Why AI Matters Now: How a $1.5B RIA is Building the Firm of the Future A conversation with Louis Diamond and Ryan Belanger, Founder & CEO of Claro Advisors.      Louis Diamond: Welcome to the latest episode of our podcast series for financial advisors. Today’s episode is Why AI Matters Now: How a $1.5B RIA is Building the Firm of the Future. It’s a conversation with Ryan Belanger, the Founder and CEO of Claro Advisors. I’m Louis Diamond, and this is the Diamond Podcast for Financial Advisors. Mindy Diamond: At Diamond Consultants, we help elite advisors identify the right environment for their businesses to thrive, whether that’s at a wirehouse, boutique, or independent firm. With nearly three decades of experience, we’ve guided thousands of advisors and represented more than a quarter of a trillion dollars in assets transitioned. And each year, one in four advisors managing a billion dollars or more who change firms are our clients. Our process is education driven, and based on building relationships, starting as your strategic partner well before you’re even thinking of a move. To schedule a confidential conversation, call us at (908) 879-1002. Wondering why advisors change firms and where they’re headed? Are transition deals going up or down? Those very questions and more inspired us to create our annual Advisor Transition Report. It’s the award-winning data-driven resource designed for advisors that connects the dots between the motivations around movement and the firm’s appetite for top talent. Arm yourself with the knowledge you need to make smart decisions. Download your copy at diamond-consultants.com/transitionreport. Louis Diamond: Artificial intelligence has quickly become one of the biggest topics in wealth management in the world. Almost every firm is experimenting with new tools, looking for ways to automate tasks, improve efficiency, or help advisors serve clients more effectively. But what if AI isn’t just another technology to plug into your business? What if it becomes the foundation for how your business is built? That’s exactly why I wanted to have Ryan Belanger on the show. Ryan is the Founder and CEO of Claro Advisors, a billion and a half dollar RIA that’s taken a very different path than most firms in the industry. Rather than simply adding AI to an existing tech stack, Claro acquired a FinTech company and is building its own AI native operating system designed specifically for advisors. What’s interesting is that this isn’t really a conversation about software, it’s about strategy. Ryan has consistently gone against the grain from leaving Morgan Stanley to launch an independent firm in 2012 before it became commonplace, to recruiting younger advisors when others chased established producers, to betting that proprietary technology will become one of the biggest competitive advantages an advisory firm can have. If AI is going to reshape wealth management, and I think it will, the firms that benefit most may not be the ones using the most tools. They may be the ones rethinking how the entire business operates. Ryan shares what that looks like in practice, what he’s seeing from advisors today, and why he believes the next generation of advisory firms will look fundamentally different from the firms we’ve known over the last two decades. There’s a lot to cover, so let’s get to it. Ryan, thanks for joining us today. Ryan Belanger: Yeah, nice to see you. Louis Diamond: You too, good to see you again. For those who aren’t familiar with you and your firm Claro, why don’t you walk us through your background and how you found your way into the industry to set the table. Ryan Belanger: Yeah, sounds good. So background was after college, I got a job at Morgan Stanley. I’d done an internship while in college and that gentleman, Morgan Dewey, said you should look at the Morgan Stanley. So I applied, got a job immediately, and just a couple weeks after graduating, I began as a financial advisor in a training program at Morgan Stanley and spent a good amount of time there and was able to develop skills necessary that really I had all along just growing up, a lot of entrepreneurial spirit I think is important in this business, how to relate to people, some competitiveness. I just happened to luck out and get into a profession that rewarded some of those skill sets. Louis Diamond: I’d say it was the right choice for you. So I think you started at Morgan Stanley in 2004. You were 21, 22 years old, just cutting your teeth, but the financial crisis happens a handful of years later. So what was it like being a relative newbie and seeing client accounts falling, the world crumbling every day? What did living through that crash teach you that’s shaped how you’ve built your business or serve clients now? Ryan Belanger: I did learn a tremendous amount at Morgan Stanley and I do still tell people if they’re looking to start at a big shop with big training programs and resources and really try to figure out what you like and then you can go off and get more specialized. But I do feel like it was a great place to get trained. They would post how many cold calls we were making every day. So on the board every morning you’d walk in and say, “Okay, where did you fall?” And I’m a competitive person, and I just want to make sure I was first every single day. So it was those type of things that really propelled me to keep interested in this business but also see the benefits. It’s really hard to get clients and that’s what people underestimate the most is to build the level of trust with someone that they’ll allow you to manage their retirement nest egg is it takes time. And I was 22, I looked really young, I had no experience, but I was fortunate to have two great mentors at Morgan Stanley, a gentleman named Todd Wetzel. He was brilliant at developing relationships, really caring for people. And then the gentleman that I had done an internship with went to Morgan Stanley as well, and he allowed me to work on some small accounts and really cut my teeth with some customers. And I was very fortunate to have done that, but you’d asked about the crash, and I think what I learned from that when people were literally weeping when their account values were down by 50%, 60% was that money is really emotional, and you have to understand how much it means to people, it’s not just the number on your screen. So having some empathy towards someone who’s really in a period of distress is now a critical skill that those of us have been around for this long understand. And there’s a whole generation, Louis, of advisors that have never experienced a real bear market, and I do fear for them at some point because when you go through that, it really changes the perspective that you have. But for me, it happened, I was four or five years into the business at that point, so I’m thankful that it happened just for my own personal development and I’ll never forget it. Louis Diamond: Yeah. Things have a way of happening for a reason and then the best advisors, best humans, they learn from them, and they’re better off for it. You’re very much right. I like that perspective about how the empathy around the emotions of money was something that you still carry and wear as a badge of honor today. So you left Morgan Stanley in 2012. I think you were 30 years old I read. One, that’s very young to consider leaving a firm like that nonetheless to go independent when in 2012, it wasn’t like everyone was going independent. There weren’t as many infrastructure providers or tech vendors or as much capital available as there is today. It definitely wasn’t a path that was as well-worn as it was. So two-part question, what pushed you to leave the firm presumably without a huge book of business? And second part, how’d you think about risk and reward at that age? Ryan Belanger: Yeah, what drove me was ultimately I felt like I was not seeing the value from the firm I was at, Morgan Stanley at the time. They were just taking an exorbitant amount of the revenue I felt. And I would see product managers strolling through and going to steak dinners, and I’m thinking, geez, I’m here every night on weekends. I’m busting my butt, and I should be creating more value to myself. And so that was one kind of thing. And I think there was a right level of naivete just to think that I could pull this off. I did believe that I had a small number of clients. I was hopeful that they would come because I had to hit a minimum for the custodian platform to start the RIA, which I was able to do. But I felt that they would come with me and that I had developed enough trust with them that I could be their advisor for a long time. And so for me, it felt like the technology wasn’t great. I was just told the mother-in-law is an expression. She says to my kids sometimes, “You get what you get and you don’t get upset.” Have you heard that expression? Louis Diamond: I have. My daughter reads a book where that line is repeated frequently. Ryan Belanger: Yeah, okay. So that’s how I felt then. I was like, “This is what you have and deal with it.” And to me, it just felt like there had to be a better way, but I didn’t have any capital backing, so I bootstrapped it. I Craigslisted an office from an estate planning attorney. I cold called Fidelity at the time they were our only custodian. I called to get some compliance help and I just thought that there’d be other people that would want to join. I named the firm, it’s a Latin phrase, it’s Claro Advisors, and it means to make clear in the mind. And I felt like not only was I trying to do that for clients, but I was trying to push advisors to challenge the norms here. There are other solutions out there. So I purposefully did put my name on it, I knew that there’d be other people that might feel the same way. I’ve always been a team sport guy. I like being around other people and collaborating. And I did have a good friend and credit to him. He said, “If you put this together, I’ll come with you.” And so just a couple weeks after I did, we talked and I said, “It’s up and running.” He came and Dana was our first, he’s still with us. And then a couple of months later, another guy I used to work with called and said, “Hey, I’m at this bank, and it looks like what you’ve done is interesting.” And I said, “We like it if you’d like to give it a try.” And so he came, his name’s Mike. He’s still with us. And so teams started to get put together. But I met someone in 2014, so I was two years in at that point and I was doing legitimately everything, not only as an advisor, but just all the stuff that you have to do to run the business. And it was becoming too much, especially the compliance. And I think nowadays starting an RIA, the threshold is so much higher. That’s why you see better than anyone else. You just see a lot more tuck-ins. But Jen Street was someone that I met and she really allowed me to catapult the business and scale it, so she took over all the operations and compliance and that really freed me up to be an advisor. And I really was just an advisor moonlighting as someone running. I would recruit a little bit or just be introductions, very soft. All that has changed based on what we’ve done in the last couple of years. Louis Diamond: Amazing. So thinking about risk spectrum, obviously now if you look back and say, “Hey, I had 30 million or whatever it was, I didn’t have anything to lose.” Right? But when you’re in it and you had income, you had recurring revenue, you had a paycheck versus the dynamic of, “I’m going to incur a bunch of expenses. I’m not positive who’s going to come with me. I’m not going to have a paycheck for a period of time.” Did the fact that your business was relatively small and you were just getting up and running, do you think it made it easier for you to reconcile that risk, or in some ways it was harder because your dispersion, if someone didn’t come, was that much higher? Ryan Belanger: I think it was easier for me, I knew I could always go to another firm. They would take me and whatever clients I had. I did it at a time when I had little personal risk, no kids, no mortgage. I didn’t have a wife at that point. So for me, it felt like the right time to take a risk. And I had been entrepreneurial in my life. I mean, I had a business in high school and my parents and grandparents were entrepreneurial. So that was in me, even if I didn’t really recognize it, was that I was okay with a good level of risk. And I do say this now to anyone that I’m hoping to partner with is that if you want to bet on yourself, I’ll go all in on you too. But you’ve got to be able to take that jump. I won’t let you fail, but you’ve got to be the one. I think that inertia is what a lot of advisors are like, “Geez, I don’t know, I got to give something up.” And that’s why the data’s important and you have all the data. The clients overwhelmingly go with the advisor. These days it’s just much harder to try to establish a new relationship with a trusted advisor than it is to just DocuSign some forms and move your account somewhere. So to me, it’s just trying to support people, and really push them to the edge and say, “No, this is possible. You should definitely explore this.” And I get it’s totally different, and you might be at a different life stage, but you know the numbers. I mean, tens of thousands of advisors are moving every year and not all of them have a small book like I did when I did it. Louis Diamond: Right, exactly. On one hand, making this entrepreneurial move as early in your career as you did, it was a benefit, right? Because you didn’t have as much to lose, like you said, the stage of life you’re in allowed you to absorb more risk. On the other end of the spectrum, if someone who has a massive business with immense value, they’re well situated financially, maybe their kids are through college, et cetera. And then most people are somewhere in the middle. So it’s interesting hearing that dynamic in real time. Let’s talk about Claro today. So you launched the business, like you said, you had to work hard to meet a minimum custodial threshold. So started from a very small base in 2012, but where is it today as far as assets, team size? Just give us some stats or perspective on what you’ve built in the last decade and a half or so. Ryan Belanger: Yeah, sure. So we enjoyed a tremendous amount of organic growth, Louis. We are not capital-backed. We don’t buy books of businesses, so I would recruit or partner with advisors that were coming from all the various places that you could think of that were finding us to be a very friendly place to work where you had a high level of autonomy, freedom, control, just great economics. We stayed out of people’s ways. We were just good people trying to help other good people, and it was just that friendly environment that allowed us to grow. And of course, we can’t discount market. I think markets had a tremendous growth for everybody in the business. And so the business as it stands right now, we’re about 1.5 billion in assets, 15 to 20 advisors. We got a 40-person team based primarily at a Boston headquarter, but we have advisors all over. And I think as we’ll get to, we’ve just gone through a really exciting new chapter for us where the next 15 years are going to look a lot different than the previous 15 years. Louis Diamond: Very cool. That’s amazing, and I’m in the recruiting businesses and doing recruiting yourself, it’s not easy to tell your story, get in front of the right people, the right like-minded people too, who are willing to take the leap to you, especially if you don’t have the capital backing and you can’t pay big deals or write big checks like others could, so that’s a massive testament to you and your vision. I know the average age of an advisor at Claro is around 40, yet the average advisor in the industry is 59, 60, 61, depending upon what data source you look at. What do you think you figured out about attracting, training, and really cultivating younger advisors that the rest of the industry either gets wrong or ignores? What’s been your hack in that regard? Ryan Belanger: I’ll just take a chance on people that others might not. And typically what that really means is someone with nothing, I’ll make them a deal and I’ll say, “Look, I believe in you. I think you’d be a great advisor. Let’s work on an arrangement where you feel like you can do this and I’ll support you.” And so our specialty was growing advisors from 20 million or 30 million into hundreds of million of client assets. And some of it was just being willing to look where others wouldn’t possibly want to spend their time. But when I was 22, someone took a chance on me, and so I owe it to the next generation to do that as well because there’s some great talent out there that really just isn’t getting the attention they deserve because they don’t have big books of business yet. But one of my core values is long-term thinking, and so that’s the way I frame my decisions is it doesn’t have to be a win today, but it can be a championship tomorrow or down three or five years from now. And so that’s how I’ve positioned it. I think that’s why we tend to get younger advisors. And then what happens when you get a lot of younger advisors, you have some older advisors say, “Hey, look, that’s an attractive bench of talent. I needed a succession plan. You guys seem to have a bunch of guys and gals that know how to do really great work and serve clients.” But I think that’s probably one of the things that I just was willing to take some chances on people at an earlier stage. Louis Diamond: Yep. I love it. I mean, once again, you said in the beginning, you developed an empathy for the emotional side of money and what people were going through that you carry through to this day. So not losing touch with the fact that you started. I mean, everyone starts in this business at some time, but I feel like once you’re successful or you’re through the first few years, you forget what it was like to be a newbie. So keeping that perspective and appreciation for the mentors you had, et cetera, is great. And honestly, from a business building standpoint, to me in this environment, unless you take on private equity capital, or you have capital from a BD or from a wirehouse behind you for recruiting, it’s really hard to win advisors with large books of business. So going in the blue part of the ocean instead of the red ocean, if anyone’s read that book, is very smart, looking under rocks that others don’t or really buying into or leaning into folks that you see something in that you know you can cultivate is a brilliant way. And it’s honestly more scalable, cheaper, you build a better business as well doing it the way that you do, but still, it’s hard. And my guess is the ROI is shorter. I’m sure you’ve made some hires that don’t pan out. So you have to have the tolerance and the demeanor to really invest in people. So long-winded way to say I love what you’re doing. How much of your recruitment of advisors and the retention of that talent as they become successful would you tie to how you compensate them, or equity if that’s available versus the culture of the firm and the mentorship that you and your team provide? Ryan Belanger: Yeah, I mean I’ll speak to what we’re offering now just because that’s more relevant, and so we are positioning ourselves now as the best home for advisors in the country and we really believe that’s the case, but our problem is we’re just a secret. We’ve just come to the market after our deal and all the technology that I know we’ll talk about. So we’re now marketing this message to advisors that want to partner with us. Economics will help them grow. We have a really interesting growth program. We’ll give them equity and Claro. I firmly believe that we should tie each other, just get in the same boat, so to speak. So our success is their success, but allowing them to operate in a 1099 model, which I know is not a popular strategy. I know everyone wants to buy books and own the assets and own the clients, but I feel there’s a tremendous amount of advisors that do not that probably should not be monetizing their businesses so quickly. And so I’m trying to foster a home for those like-minded advisors that want the autonomy to own their clients, maybe even still have a brand, but partner with a firm that’s got really credible technology, just unbelievable back office support and a firm of the future so that they can grow at 10X to what they could have on their own and then they could monetize. That’s what we’ve tried to put together here with our partnership model. Louis Diamond: Love it. Yeah, I mean it is definitely going against the grain a little bit, leaning into growing a 1099 model versus more of an acquisition model where everyone coming over as W-2s. So do you think about those trade-offs when it comes time to raising capital down the line or if you want to sell the business or even just an advisor wants to leave, that would stink if that happened. How do you think about those trade-offs? The ability to let advisors keep control and ownership. And honestly, in my view, probably win many people that you wouldn’t otherwise versus the stickiness, and the enterprise building abilities of owning the books of business. Ryan Belanger: Yeah, it’s a paradox because I understand why you want to own the client, but that’s a different business model. And frankly, I think it attracts different type of people. I had to really look myself in the mirror a couple years ago. We had enjoyed a tremendous amount of success, high growth and all organic, growing at 30% more per year on a CAGR basis. Nothing could stop us. But what happened was when private equity entered the space, everyone wanted to buy Claro. And to me, it didn’t feel like I did a lot of due diligence. I talked to a lot of firms. I didn’t see any differentiation in the market, Louis. To me from a technology perspective, everyone was doing the same thing. They’re using six to 12 different tools. We all know who they are. And now there’s a bunch of AI tools they’re layering on. And to me, it just didn’t feel like that was going to be any… There was no differentiation in the market. But admittedly, I had a couple of friends who I’d brought in at very low levels of AUMB that wanted to leave. And they said, “Look, I want to go to a firm that has more resources.” And so I had to just make a business decision and say, “Where do I want to take this?” And so it was only after some real adversity because you get emotionally attached to these people that you’ve developed friendships with and they still are friends, no doubt, but they can leave and they’re not captive. So we have to plan for that at Claro now, and I think we’ve got two ways that we’ve done that where it really ties the advisors to us, but in a way where they want to be here because we have something that’s really different. Louis Diamond: I like it. I’m sure we’ll get into that. But before we do, we’ll get into what you’re doing on the technology side, which is very cool and unique. How do you balance being an advisor and being a CEO? And what percentage of your time is advisor versus CEO and has that fluctuated or changed over time? Ryan Belanger: Drastically changed in the last year, two years or so. So the first 10, 12 years, I was really an advisor first and foremost. That’s inverse at this point, I’m strictly running the business. I have a great team here that deals with our clients, and I’ll still attend the client meetings and such, but I’m really laser-focused on running the business, trying to develop new partnerships with advisors, running an engineering team, sales and marketing. So the change for me has definitely occurred, and I’ll miss not keeping up with planning as much. I’m a CFP, but I just recognized that for me, I had to make a clear change and commit all my time to running the business, and so that’s the decision that I’ve made. Louis Diamond: It is a hard balance. I mean, there’s some people that try to do both, run a business, be an advisor, be a rainmaker, and something breaks. You’re not able to give all yourself to one thing. Then there’s others that would much prefer to be an advisor over a business owner. Others who say, “I’m over being an advisor. I want to be a business owner.” So I think the cool thing about doing what you’ve done is you get to choose, right? Some of it might be circumstances, but you really got to decide which elements of the business you personally want to invest your time in. And you really push your chips in the middle of the table. So let’s get into what you did in November of 2025. I read that you acquired a tech company of all things called NDVR. I’ve done this podcast for a while, speak to a ton of people. I can’t really think of anyone, any advisor or RIA that’s actually bought a tech company. So what made you puck the trend, buy a tech company and not just license all the FinTech that’s available today? Ryan Belanger: Yeah, that was the decision I had to make was do I really want to be different, or do I want to just say that I’m different? And so I was fortunate enough to get introduced to a gentleman named Michael Simon about 18 months ago, two years ago. And him and I immediately could see that we were both trying to solve the same problem, and we had perfectly mirrored image skills of one another so I had this deep wealth experience and he had a deep tech experience. And sometimes it’s just about timing in life, about catching someone at the right time. And I think we each caught each other at a really good time where we could see that coming together, we could create something really magical. And this AI wave was cresting. And I could see when I was talking to all the national PE firms or RIA firms about what people wanted to do, no one had quite figured out how AI was going to come into the technology mix, and it appears as though it’s just going to be another add-on tool to everything else. And for me, I wanted to try to build something that was integrated an all- in-one platform for an advisor so they didn’t have to use a ton of different tools. And I thought if you could do that, couldn’t you have AI that’s really much more rich and purposeful to help the clients? And so I felt like here’s an opportunity to elevate financial advice throughout the country, really give the clients all the value. And so what we’ve built allows advisors who are really good advisors to become super advisors because they’ve got this technology cape that no one else has that is allowing them to save a bunch of time and do all these really cool things for their clients. But it just felt like right time, right place. I’d been through a little bit of adversity and I felt like taking another swing just like I did 15 years ago going for it. I’ve really never been averse to risk, and so this felt like it was too good to pass up and so we went for it. Louis Diamond: Interesting. So that makes sense on the build or acquire versus rent dynamic, wanting to own the IP that makes you actually different. What does NDVR actually do? Ryan Belanger: Yeah, so everything’s all integrated. So we’ve kept the Claro Advisors name. We feel like clients really want to know that they’re still getting a person to deliver the advice. And so having the advisor’s name in our brand is important, but we have a Claro Intelligent Hub, and that’s where it’s an AI native operating system for the advisors. They spend their entire day in there, Louis. So they’re not toggling between 10 different Chrome tasks to perform all their business. And so what that allows them to do is not only it’s CRM, calendar, contacts, emails, messages, but we also have all the portfolio information. So trading history and we can do tax loss harvesting and factor-based investing. So we’ve got institutional grade portfolio management, and that’s really what Endeavor had created through their R&D was the hyper-personalized portfolios where you have a customer’s financial plan directly tied to their account. So there’s never any de-linking between the two. It’s really sophisticated technology that we can provide to our clients. So that’s all integrated as well. And so we’ve since continued to build the build upon that layer of integrated proprietary technology. Louis Diamond: It’s very interesting. And we have to imagine part of you maybe now or in the future is, okay, we’ve built this amazing technology mousetrap for our advisors, but do we become a FinTech? Is there any thought of eventually licensing what Endeavor is doing for your business and your clients to other RIAs? How do you think about that dynamic of just building something unique and different for Claro that advisors can latch onto versus making what you and your partners have developed into something that someone else can take and license themselves? Ryan Belanger: Yeah, it’s a fair question. We get it a good amount. While there might be a possibility that we license this to some other businesses, our main goal right now is to keep it captive to RIAs that want to partner with Claro. And so we feel like this gives them a true level of differentiation in the market, and so that’s the approach that we’re taking right now. Being a FinTech company, there’s a lot of different skills. The setup and tear down of getting someone to use the platform and I think all that time and resources we want on sales and marketing to try to attract new advisors and continue to develop just jaw-dropping technology for the existing advisors. Louis Diamond: Very cool. Let’s talk a little bit about your partnership model. So it does sound unique in that you have people that are 1099, but you don’t usually also hear partner. So how does it work? Ryan Belanger: Yeah, so we’re offering advisors to come and use Claro as a back office so you can have your own brand if you want or you can just be a Claro advisor. We have both here and you’ll be a 1099 advisor so you’ll still own the business that you’ve owned. So if you were at a wirehouse or something, you would actually now be creating some enterprise value for yourself. But if you’re an existing REA, you’d be coming to us because you’re tired of doing tech vendor due diligence all the time or you’re tired of the compliance, the AI regulations. That’s just coming. So that’s going to be a huge challenge for REAs, so we’re seeing a lot of interest from REAs saying, “Look, you’re not asking me to give up really anything except the stuff that I hate to do anyway, so this sounds great.” So they partner with us. In return, they get all access to our technology And we’ll provide all the back office support, office space, dedicated resources, planning, everything you could want to have to operate a business. We do have a growth program that’s really interesting. And then we’ve got this equity in Claro. As you’re a partner with Claro, you should get equity so we give stock options to our advisors who are here and every year thereafter. And naturally, that’s a way to stay connected with the advisor. So hopefully they never want to leave, and I do believe that once you experience our technology, you never want to go back to trying to do it the way you were doing it before. Louis Diamond: It’s like instead of building the most enclosed box that you keep people in with sticks and with locks and keys like a lot of firms do, it’s we’re going to keep advisors here, but not by force, but because they have the stock options, because you’re delivering value, because they have this amazing technology. To me, that’s the dynamic that so many firms across the industry get wrong is that they try to keep advisors where they are by restrictive covenants and by fear, and by retribution rather than if we just do good work for people, we add value, we make ourselves indispensable to the advisor. To me, it creates a healthier dynamic. I think firms would actually retain more even if it’s a gentler approach. And I love what you’re doing there. I think it’s the exact right way to think about we have advisors that are 1099, so yeah, they could leave us, but we’re doing things that make it that they don’t want to leave us. And that’s your charge as the owner to create the infrastructure and the structure where people could go out on their own, but there isn’t an advantage to do so. Ryan Belanger: Yeah, I think the culture is a big thing for us. And if you have people here that don’t want to be here, that’s a problem. And I think that’s what you see in a lot of the wirehouses. Frankly, they scare people and they don’t. It’s like, oh my God, if I leave. And for us, it’s like personally, life is too short. I want to work with people that want to work with me. I’ve got other things going on in my life and these things are just work things. And so I want to enjoy being in the office every day with people that want to be here. And if you think you’ve found a different place, you should go explore that. It’s really a soft approach. I know it’s not the most popular approach, but that’s just the style that I have. Louis Diamond: Yeah. I mean, it sounds like the trend in your career and in launching Claro was we’re going to do things that aren’t popular, but that work for us, like hiring younger advisors that may not have a book or have a small book, buying a tech company instead of licensing it, being 1099 when you’re recruiting instead of owning books of business. There’s a series of decisions you’ve made as the business owner that they’ve worked out, they’ve paid off, but they’re definitely against the grain. And I very much respect that. Ryan Belanger: I really have never been afraid to be a little different, and so I think typically you find other people that might be interested, but it’s a big pool out there. There’s 300,000 advisors so there’s something for everyone, which is awesome. Louis Diamond: Totally agree. Let’s get back to the AI platform that you’ve built, or that you’re building. Maybe give a real tangible example. If I’m a Claro advisor, how has my life changed now that I’m using this platform versus before? So the old model was I log in, like you said, to 10 different Chrome tabs. I’m meeting with clients, doing planning, et cetera. What is the day in the life? How does it look different from what an advisor’s actually doing today versus before this platform was rolled out? Ryan Belanger: Yeah. All right. I’ll just give you a couple examples. So a client will send you a request and say, “Louis, I need $25,000.” And so a typical advisor would either write a note down, go drop it off at the CSA’s desk, or maybe forward that email to the CSA and then that person would have to input it into their CRM, and they go perform the task. And then the advisor would want to know where things are in that process so that there’s a lot of back and forth. With our system, Claire, our intelligent chief of staff, AI chief of staff, you just forward that task to tasks@claroadvisors.com. It recognizes the email address that the client is emailing from, it knows the account number. It talks to our portfolio engineer. It knows which account to raise the cash from because it knows the tax jurisdiction, and otherwise, and it performs the task. And the last push of a button is that CSA just moving money from the custodian. So all along the way, the advisor can check on the task and see where it is in the process. It’s beautifully integrated in the intelligent hub, but you could see how that would save a tremendous amount of time and it’s a better customer experience. The mistakes get limited. So it really allows the advisor to get things done at a much higher level. So we’re raising productivity quite a bit. First of all, she’ll establish your meetings, Claire will. So she’ll schedule them for you. She’ll prep them for you. So we have a button, say prep the meeting because we have all the notes, emails. If you’re texting portfolio data, because she has all that information in about 30 to 45 seconds, she’s going to present to the advisor a really nice meeting summary that, “Hey, here’s the things that we should talk about.” She’s going to surface things that the advisor’s forgotten about because she doesn’t forget things. And so she’s prepped the meeting for you, so you’ve saved a couple hours there. She joins the meeting, she takes all of your notes, stores them in the system. She’ll give you a follow-up email. She knows your writing style, so she’ll know that you like to call this client this, and you send these emails typically at this time. And so she’ll deliver a nice follow-up email instantly for the advisor. They click that button, that’s done. So there’s just a lot of things that where she’s efficiency-wise where on 20, 30 hours a week that we’re saving advisors just on the productivity tools alone, so that’s where we’re seeing advisors seeing a ton of value in this. Louis Diamond: It’s very cool. Ryan Belanger: And then there’s a whole portfolio management capabilities, sweeping idle cash and tax loss harvesting and rebalancing that gets done while advisors are having a cup of coffee. They don’t have to think about these things. It just gets done for them. Louis Diamond: It’s so cool because it’s like I think I can conceptualize or think of building in Claude any one of those functionalities for the most part, but the way that the flow of things works and the journey of it is unique. I think every advisor would be interested in that type of promise of saving that much time. So how do you think now in the future, how do you think about the human advisor interaction, and what the human and the advisor will do versus what can be offloaded to AI? Ryan Belanger: Yeah, certainly a lot of the non-client-facing activity can be unloaded and that’s where advisors spend, according to recent studies, almost 60% of their time non-client-facing. So we’re trying to take all that off of their plates for them. We strongly believe clients still want the message to come from a person that has a level of experience and understands them. But at the same point, I think there’s a growing curiosity about, geez, what could it do for me? And so shouldn’t my advisor know how to use it? And so I think you’re seeing a lot of advisors put their head in the sand and say, “I don’t know. I’m just going to hope people don’t really want to use this and adopt it.” They’re a little bit shortsighted there. Our bet is that clients are going to want an advisor that knows how to use tech, has really sophisticated tech, but it isn’t just another tool layered on top that now my data is in that tool. The reason our system is so beautiful and integrated is because it captures everything in a structured and secure way. So all of the compliance is in there. We whitewash all the PII that’s sensitive information, so we’re not layering another tool on, because it’s integrated, we have an AI governance committee that really takes it seriously. How are we using this information? And so we’ve got an approach and we’ve put guardrails around what it can do and what it can’t do. Might there be a generation, Louis, that wants an AI advisor? I don’t know, that could happen. A twin, a digital twin where you say, “Look, I want to talk to Louis.” It’s 10 o’clock at night. He might be in a different time zone than me. He’s got little kids, but I do have this question. And so we’re iterating ideas on how we can surface that for an advisor to be advisable 24/7 without actually having to be available 24/7. Louis Diamond: Seven. It’s amazing to think about. I mean, obviously you’re deeply in this. You have a front row seat into the power of AI, how it’s transforming your business, doing due diligence on acquiring this technology five years from now, 10 years from now, what does the industry look like as a result of AI? What’s your big bet? Ryan Belanger: A lot of the big firms are going to try to figure out how to layer in tech. It’s going to be very difficult to do that. It’s built on extremely old legacy technology. They’ll be slow. They’ll figure out how to do some things. What we’re already seeing from advisors is the wow factor. Wow, I didn’t know this was even possible, and so I think just given our size and where we are, we have an advantage that we can build things from the ground up very quickly. I mean, what used to take an engineer a couple of months or years can be done in a couple of days or weeks, so things have really sped up in terms of the development. It’s much easier to build it than buy it. And so I think you’ll see a lot of firms trying to do what we’ve done, really build proprietary technology. And I think there’ll be a few winners that are able to do that, but being tech forward and aligned with someone who’s thinking about it, I think is what a lot of advisors are going to want to be. That’s the type of firm people would want to partner with, I think. Louis Diamond: What about the dynamic of, like you said, the digital twin thing is equal parts cool as it is terrifying, how do you see, we’ll say the threat of AI impacting the profession of being a financial advisor? Do you look at it as the entire pie is going to grow because everyone’s more efficient? Or do you look at it as it’s going to take out a lot of the advisor capacity we have because it’s no longer necessary? Where do you fall on that spectrum? Ryan Belanger: So robo-advisors came and went, you remember those. I mean, not that they went, but they never took off the way that it was projected. They’re still great businesses, but the human advisor won that battle. Clients do want an advisor, particularly at the higher end, and so I think at the lower end of the market, you’re going to see some AI solutions where people are perfectly comfortable just talking to someone in AI, and they’ll figure out if there’s a hallucinization or not. But I think there’s definitely going to be a market for it, and so I think it just depends on where the clients are and what level of complexity they have. On the higher end, I do feel like the advisors will continue to have a huge advantage there. But we’re building tools to give optionality to advisors. There might be some advisors who say, “Look, I’ll charge half the fee that I used to charge so you can get my digital twin. And that’s a win-win situation for everybody.” Louis Diamond: Yep, that’s fair. So do you look at your competitive ecosystem now? Not for recruiting advisors, let’s say for winning clients. Do you look at Farther and Savvy and different AI or FinTechs as your competition or do you still look at it as the wirehouses and other traditional RIAs? Ryan Belanger: I mean, Farther and Savvy have done a great job of going after this market. I think we’re not as well known yet as they are. We’ve certainly built out what we think is tremendous technology second to none. There’s a huge market of the IBD space that is just these guys and gals are stuck on these old platforms and things are okay, but they’re not super compelled to switch until maybe they see something like this, and so we have a massive pipeline of advisors and I’ve been recruiting for a long time. I’ve never had a pipeline like this. So I know it feels different to me. People really are interested in this. It’s enough for them to want to see tech demos and come visit us and really understand, okay, this is a firm that is challenging what’s possible and that’s someone that maybe I want to be aligned with, and so I think that there’s a lot of places where we can get the talent. And so for us, it’s just trying to find the right people that we want to partner with for the long term. Louis Diamond: Very cool, I got two more questions for you. It’s pretty remarkable that to get from where you started to now, the recruiting you’ve done, buying a FinTech, integrating it, that you still don’t have private equity investor outside capital. So you think it’s on the roadmap, whether it’s a certain size or you’re looking for personal liquidity where the business will just need it because it’s expensive to operate a FinTech platform and to scale up and to keep growing the firm. Do you think there’s a world in which you take on external capital to fuel your growth? Ryan Belanger: Most certainly. I mean, things have developed for us very quickly here, and outside capital and venture particular is a space that we’re actively in discussions with firms that believe in our vision, understand the value that we can create, and there’s just no doubt that you have to have some wind at your back to get to the market, and so while we’re not a household name right now, I’m confident in two years we will be, and our plan is to grow to hundreds and thousands of advisors across the country. Louis Diamond: Wow, big vision, but I love it. Last question for you. If you were 30 years old again, which I think everyone would kill for that opportunity, leaving Morgan Stanley today instead of in 2012, what do you think you would do differently knowing what you know now? Ryan Belanger: At that point, interest rates were near zero, Louis. Valuations you remember were two to three times revenue. It felt expensive then. Obviously things have changed quite a bit. So I would’ve begged, borrowed, and stole all the money I could from friends and family and said, “I need to buy as many businesses as I could at two times, three times revenue and pay, I don’t know, 3% loan.” Just in hindsight, that’s what everyone should have done. That’s not the path that we chose, but I think there’s a huge opportunity in front of us to elevate financial advice across the country, make really good advisors even better by putting that super cape on them. And so we’re very excited about the future, what we’ve got in store, and what we’re going to deliver to the market. And it seems like just yesterday that I walked out of Morgan Stanley with very little assets and tried to start this RIA, but I’m very thankful for all the people that have been supporting me throughout this journey. Louis Diamond: Amazing. And that’s a great spot to end, but let me ask the inverse of that question. Let’s say you leave in 2026, so leave today, you’re 30 years old, but you have the benefit of hindsight. You know what you know now. What would you do differently around the transition or building the firm other than of course be amazing if you can buy businesses for a fraction of what they cost today? Ryan Belanger: I would want to make sure that I’ve got an integrated solution. I don’t want to be picking a bunch of different vendor tools. I know that’s going to become way too time-consuming for me. So I would really try to figure out how you can get something that’s integrated that can scale, but I wouldn’t change anything about the people. I think you got to be able to connect with people that are like-minded and you still take the risk. What I can’t believe, Louis, is that people that sit at the wirehouses take a home team discount and they’re so fearful of leaving Morgan Stanley or Merrill Lynch or UBS, but why are they taking that? The market says you should be paid double what you paid. And it’s not just like that’s 20, 30 years of data here that show that. And so I just would keep pushing people to bet on yourself. Your clients will come with you. Yes, that firm that you love will be the first ones to try to steal your clients. They’re going to call them, and that’s one way, loyalty. Another thing I don’t understand, but that’s the way the business is structured. I think there’s a huge opportunity to just educate advisors about what’s out there and I would take the risk. Louis Diamond: Love it. Ryan, this has been very fun. What you’ve accomplished, like I said earlier, gone against the grain at every turn. Leaving on the younger side without a huge business, buying and integrating a technology company, recruiting younger advisors without books of business. Every single thing you’ve done has been a different playbook. So I’m pumped to watch how we make Claro a household name and how this approach is going to pay off in spade. So I appreciate hearing this different perspective, and I know our listeners did as well, so much appreciated today. Ryan Belanger: Well, thanks for having me on. I know it’s a long time coming. Thanks for your patience. I wanted to make sure we had something really exciting to talk about when we finally did this, and hopefully I can come back in a couple years and catch up. And congratulations on everything you guys have built. You guys are just a premier name out there, and it’s been fun to watch your success as well. Louis Diamond: Thank you, Ryan, I appreciate it. Mindy Diamond: As a financial advisor, you hold yourself to the highest standards of integrity, honesty, and credibility. You are successful because you take your professional responsibilities seriously and are dedicated to your clients. But are you living your best business life? Are your goals aligned with your firms or could a better option exist? Should I Stay or Should I Go? is a book written with you in mind. It’s a self-guided journey that walks you through the key steps that we take with our advisor clients. This strategic thought process and roadmap to professional self-discovery is designed to help you ask the right questions and think critically and objectively whether you’re considering change or not. Learn how to get your copy at diamond-consultants.com/thebook. Why AI Matters Now: How a $1.5B RIA is Building the Firm of the Future A conversation with Louis Diamond and Ryan Belanger, Founder & CEO of Claro Advisors.      Louis Diamond: Welcome to the latest episode of our podcast series for financial advisors. Today’s episode is Why AI Matters Now: How a $1.5B RIA is Building the Firm of the Future. It’s a conversation with Ryan Belanger, the Founder and CEO of Claro Advisors. I’m Louis Diamond, and this is the Diamond Podcast for Financial Advisors. Mindy Diamond: At Diamond Consultants, we help elite advisors identify the right environment for their businesses to thrive, whether that’s at a wirehouse, boutique, or independent firm. With nearly three decades of experience, we’ve guided thousands of advisors and represented more than a quarter of a trillion dollars in assets transitioned. And each year, one in four advisors managing a billion dollars or more who change firms are our clients. Our process is education driven, and based on building relationships, starting as your strategic partner well before you’re even thinking of a move. To schedule a confidential conversation, call us at (908) 879-1002. Wondering why advisors change firms and where they’re headed? Are transition deals going up or down? Those very questions and more inspired us to create our annual Advisor Transition Report. It’s the award-winning data-driven resource designed for advisors that connects the dots between the motivations around movement and the firm’s appetite for top talent. Arm yourself with the knowledge you need to make smart decisions. Download your copy at diamond-consultants.com/transitionreport. Louis Diamond: Artificial intelligence has quickly become one of the biggest topics in wealth management in the world. Almost every firm is experimenting with new tools, looking for ways to automate tasks, improve efficiency, or help advisors serve clients more effectively. But what if AI isn’t just another technology to plug into your business? What if it becomes the foundation for how your business is built? That’s exactly why I wanted to have Ryan Belanger on the show. Ryan is the Founder and CEO of Claro Advisors, a billion and a half dollar RIA that’s taken a very different path than most firms in the industry. Rather than simply adding AI to an existing tech stack, Claro acquired a FinTech company and is building its own AI native operating system designed specifically for advisors. What’s interesting is that this isn’t really a conversation about software, it’s about strategy. Ryan has consistently gone against the grain from leaving Morgan Stanley to launch an independent firm in 2012 before it became commonplace, to recruiting younger advisors when others chased established producers, to betting that proprietary technology will b

Het is één van de interessantste sectoren die er is: de advertentiemarkt. En met een CAGR van meer dan 41% sinds de beursgang is Applovin een van de snelst groeiende ad-techbedrijven van deze tijd. Het verdient geld met mobiele advertenties, door de perfecte match te maken tussen adverteerders en appmakers – sneller en preciezer dan de concurrentie. Wat ze verkopen? Winstgevende omzet! Remon Kalloe schuift aan en geeft een voorzet voor een fundamentele analyse van dit interessante bedrijf, waar de oprichter Adam Foroughi (bijzonder type!) nog altijd aan het roer staat. ► Uitgebreide show notes en achtergrondinformatie: https://jongbeleggendepodcast.nl/224-deep-dive-applovin-app ► Word Vriend: https://portfoliodividendtracker.com ► Updates via Instagram: https://www.instagram.com/jongbeleggen ► Mijn volledige portfolio: https://app.portfoliodividendtracker.com/p/jongbeleggen 1) We maken gebruik van programmatic advertising, wat inhoudt dat we geen invloed hebben op de spots die in de podcast worden afgespeeld. Dit is vergelijkbaar met tv, YouTube, radio en de krant, uiteraard met uitzondering van de advertenties die we zelf hebben ingesproken. 2) Deze podcast is 100% expertise-vrij en alleen geschikt voor amusementsdoeleinden. De inhoud mag niet worden beschouwd als financieel advies.See omnystudio.com/listener for privacy information.

Freight audit is one of supply chain's most stubborn cost centers, and the traditional model of catching errors months after the fact is no longer good enough. In this episode of Supply Chain Now, Scott W. Luton and Marty Parker are joined by Jason Murray, CEO at Shipium, and Tim Meester, Vice President, Network Performance & Intelligence at Shipium, to discuss the shift from reactive freight audit to always-on, AI-native monitoring. The panel explores why the freight audit industry keeps growing at a 14.2% CAGR even as billing errors persist at 2 to 6% of all parcel invoices, and why every dollar lost to those errors can take 19 to 20 new revenue dollars to recover. They address how delayed, after-the-fact reconciliation lets small pricing mistakes snowball into major margin loss, outlining a vision for continuous, agentic auditing that catches issues before invoices even arrive. By leveraging live data, simulation, and autonomous AI agents, shippers can detect root causes in real time and act on them immediately rather than weeks later. Jason Murray concludes by challenging operators to start building a data-first culture now, before the competitive gap becomes impossible to close.   Jump into the conversation: (00:00) Intro  (02:40) Meet Jason Murray and Tim Meester of Shipium (08:36) Jason's journey from Amazon to founding Shipium (12:30) Why freight audit keeps growing yet errors persist (12:47) Auditing as reconciliation hell and the GLP-1 analogy (17:55) Always On Audit reframes reconciliation as monitoring (22:08) Reframing leakage and loss spend as a margin tax (26:47) Where the money actually leaks in parcel billing (33:16) Always on audit versus traditional after the fact review (46:18) Why the data layer has to come first for AI (50:37) Real world use cases where AI catches hidden savings (56:21) Holistic differentiation and the next 24 months for audit Additional Links & Resources: Connect with Jason Murray: https://www.linkedin.com/in/jason-shipium/ Connect with Tim Meester: https://www.linkedin.com/in/meester/ Connect with Marty Parker: https://www.linkedin.com/in/martyparker/ Learn more about Shipium: https://www.shipium.com/ Learn more about Adæpt Advising: https://www.adaeptadvising.com/ Learn more about our hosts: https://supplychainnow.com/about Learn more about Supply Chain Now: https://supplychainnow.com Watch and listen to more Supply Chain Now episodes here: https://supplychainnow.com/program/supply-chain-now Subscribe to Supply Chain Now on your favorite platform: https://supplychainnow.com/join Work with us! Download Supply Chain Now's NEW Media Kit: https://supplychainnow.com/media-kit/ WEBINAR- The Future of Supply Chains: Where Talent Meets Technology: https://bit.ly/4uUuxkc WEBINAR- Peak Reality Check: What Shippers, Analysts, and AI Models Are Predicting for 2026: https://bit.ly/4aTlsRv WEBINAR- From Volume to Resilience: How Automotive Supply Chains Are Adapting to a New Market Reality: https://bit.ly/4f6SUGA WEBINAR- The Automotive Industry's Next Digital Breakthrough: https://bit.ly/4vhUwT4 WEBINAR- From Disruption to Stability: Building Resilient Logistics Solutions in a Rapidly Changing Global Market: https://bit.ly/3TguZMt This episode was hosted by Scott Luton and Marty Parker, and produced by Trisha Cordes, Joshua Miranda, and Amanda Luton. For additional information, please visit our dedicated show page at: https://supplychainnow.com/inside-shipium-plan-turn-freight-audit-into-real-time-monitoring-1611 The content in this episode, including all audio, videos, visuals, and graphics, is the property of Supply Chain Now and is protected by copyright law. Unauthorized use, reproduction, distribution, modification, or re-uploading of this content in any form is strictly prohibited without explicit written permission from Supply Chain Now.For licensing inquiries or permissions, please contact us at production@supplychainnow.com© 2026 Supply Chain Now. All rights reserved. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Qualcomm just held its 2026 Investor Day, and the headline number is a new $15 billion AI data center revenue target for 2029 — up from essentially zero two years ago. We break down whether this fabless smartphone-royalty giant can actually pull off a pivot into AI data centers.We cover the AlphaWave Semiconductor acquisition and why Arm-based data center networking IP matters to hyperscaler customers, Qualcomm's 3D-stacked silicon packaging approach designed to work around the high bandwidth memory bottleneck amid the 2026 memory shortage, and the Modular acquisition — an AI-native software platform positioned as a potential CUDA alternative. On fundamentals, we walk through the revenue mix as smartphone growth slows to a 5% CAGR following the Apple wind-down, and why automotive and IoT are beating original targets. We close with a reverse DCF on the ~$190 stock price to see how much growth is already priced in, and why QCOM still holds a place in our portfolio as a diversified, value-oriented semiconductor stock.Content is for general information and entertainment only, not individual investment advice. All investing involves risk, including loss of principal. CSI owns shares of Qualcomm.Semi Insider members get full access to our research platform and tools. Join at chipstockinvestor.com.

India's private credit market is moving from IBC-era rescue finance to a broader asset class. Performing credit is hot, but complexity-driven capital remains scarce and potentially higher alpha.InCred Alternatives' Ankur Jain, who is a managing director for private credit strategies, tells 9fin APAC reporter Rajhkumar Shaaw about a market that is still only about $25bn-$30bn in AUM, or 0.6% of GDP, but growing at roughly 25% CAGR.Jain also unpacks India's private credit boom, why global macro has had limited impact on India-focused borrowers, and how domestic funds and wealth-market co-investments are increasingly challenging foreign investors.Have any feedback for us? Send us a note at podcast@9fin.com. Thanks for listening!

Today’s headline news for Canadian IT solution providers: HPE Discover 2026 wraps up in Las Vegas today, and if you’ve been following our coverage, you know we’ve had plenty to unpack this week. For the Friday edition of The Buzz, we doing something slightly different – a reporter’s notebook on what HPE’s channel leadership said when they were off the keynote stage. The quote validity extension was the headline that drew the most relief, but the backstory is more interesting than the policy change itself. HPE extended standard quotes from 14 days to 30 days for compute, storage, and GreenLake, effective Monday. Simon Ewington, who leads HPE’s worldwide partner organisation, told press and partners Wednesday that the change was ‘pretty well kept secret’ – his own staff didn’t know about it either. The commodity volatility that had forced the two-week window had moderated enough that HPE could stand behind a 30-day price with confidence. Behind the ‘Power of One’ marketing, there are mechanical changes that determine whether partners can actually make money. Juniper’s Elite Plus, Elite, and Select tiers will map to HPE Platinum, Gold, and Silver starting November 1. HPE introduced a 3x multiplier on software sales for Zerto, Morpheus, and OpsRamp, plus a 1.5x GreenLake multiplier, to help partners climb tiers faster. Smart Choice SKUs – pre-configured servers missing only drives – are a speed play for distributors. The competitive storage take-out targets 14,000 customers under the VH Rail framing, with Alletra MP already outpacing market growth by 2x and 0% financing for three years. Then there was candour. Ewington noted HPE is the vendor who ‘typically moves first… and then others polish.’ The distributor overlap between HPE and Juniper is only about 10%, so they’re ‘refining the landscape’ rather than forcing universal carry. Service provider growth is running 23% to 30% CAGR. And HPE’s sustainability insight dashboard gives partners a concrete tool to analyse customer environments and open carbon footprint conversations. You can find every episode of The Buzz and In The Channel from HPE Discover on our HPE Discover news hub. Read Full Transcript This epsisode of The Buzz is brought to you by HPE Discover 2026. Check out our full coverage of the event on ChannelBuzz.ca — you’ll find out HPE Discover 2026 News Hub in the menu bar at the top of the page. Welcome to The Buzz from ChannelBuzz.ca, I’m Robert Dutt, today is Friday, June 19th, and here’s what’s happening in the channel today. I’m recording this a bit earl in Las Vegas, because I’m on a plane all day heading home from Discover.  If you’ve been following our coverage this week, you know we’ve had a lot to unpack – the Partner Growth Summit on Monday, the networking and AI infrastructure keynote on Tuesday, and a steady drumbeat of announcements through Wednesday. For this episode, I want to do something slightly different. Think of it as a reporter’s notebook – the details, the mechanics, and the candour that came out when HPE’s channel leadership sat down with press and partners on Wednesday morning, off the keynote stage. Let’s start with the quote validity extension, because the backstory here is as interesting than the policy change itself. HPE extended standard quote validity from 14 days to 30 days for compute, storage, and GreenLake, effective Monday. You’ve heard that already. What you probably haven’t heard is how closely they guarded it. Simon Ewington, who runs HPE’s worldwide partner organisation, told us Wednesday that the change was a ‘pretty well kept secret.’  His own staff didn’t know about it either. They wanted zero leaks because the commodity and supply chain volatility that had forced the two-week window in the first place had finally moderated enough that HPE could stand behind a 30-day price with confidence. Keeping it quiet meant announcing it without hedging. For partners who’ve been managing customer decision cycles that simply don’t fit a 14-day window, the relief was audible. The Partner Growth Summit was dense enough that Ewington admitted partners told him it was ‘almost too much’ and they ‘needed an AI summary to recap everything.’ So let me pull out the operational details that actually affect how you navigate the program. First, Juniper integration. We now have firm tier mapping: Juniper Elite Plus goes to HPE Platinum, Elite to Gold, Select to Silver, effective November 1. HPE is also launching a Routing competency – number 15 in the framework – to support that transition. Second, multipliers. HPE introduced a 3x multiplier on software sales for Zerto, Morpheus, and OpsRamp, plus a 1.5x multiplier for GreenLake, to help partners hit higher membership tiers faster by weighting software more heavily than hardware. Third, Smart Choice SKUs – pre-configured servers that ship missing only hard drives. It’s a speed and velocity play for distributors. Fourth, the competitive storage take-out. HPE has identified 14,000 target customers for what they’re calling the VH Rail opportunity. Alletra MP is outpacing market growth by 2x, and they’re backing the migration with 0% financing for three years. These aren’t marketing headlines. These are the details that determine whether you can actually make money on the portfolio. Then there were the moments of genuine candour. Ewington’s line that HPE is the vendor who ‘typically moves first… and then others polish’ is either confidence or arrogance depending on your perspective, but it’s not ambiguous. You may have seen recently that HP formally announced its two main global distributors as Ingram Micro and TD SYNNEX. The distributor overlap reality is worth noting: only about 10% overlap between HPE and Juniper distributors. HPE is actively ‘refining the landscape’ rather than forcing every distributor to carry everything. That’s a concession that operational integration takes time and care. On services, HPE is expanding partner-branded services so partners own the Level 1 and 2 support relationship while HPE stays in the background for Level 3 and 4. Ewington said this largely came about because there have been some large partners who have declined to get closer to HPE because of the company’s previous retisense to allow partners to lead on services around its gear.  For service providers specifically, leadership cited 23% to 30% CAGR growth rates, and they’re opening CloudOps software to CSPs to build new services around. And on sustainability, which came up in the context of AI’s energy demands, HPE has built an insight dashboard that lets partners analyse customer environments and open conversations about carbon footprint and efficiency. It’s a practical tool rather than a vague pledge. If there’s a through-line to the week, it’s that HPE is trying to make ‘Power of One’ mean something operationally, not just rhetorically. The quote validity change was a trust repair. The multiplier and tier mapping are structural incentives. The distributor and services refinements are admissions that integration is hard and takes time. Whether it all lands as promised is what we’ll be watching through the second half of this year. That’s it for this edition of The Buzz. You can find our full HPE Discover 2026 coverage on ChannelBuzz.ca – there’s a news hub in the menu bar at the top of the page. And we’ll also have more epsidoes of In The Channel from Discover next week here on the site, including more HPE executives, and more reactions from Canadian HPE partners. That’s how we’re seeing the headlines from HPE Discover. I’m Robert Dutt for ChannelBuzz.ca, thanks for listening. Have a great day.

Welcome Tarek Moursi, the founder of Better Sundays - the hard kombucha brand proving that you don't have to choose between a good time and a good gut. We've spent the last decade watching the 'low and no' category take off, and while it's great for a Tuesday night, sometimes you still want a drink - you just don't want the beer bloat or the sugar-laden cider crash. Enter the 'healthy hedonist'. Reflecting the cultural shift that's happening where drinkers are moving away from the 'all or nothing' mentality and looking for what Tarek calls 'sessionable' alternatives that fit a more modern lifestyle.    This is a category on fire. While the general UK kombucha market is growing at a healthy clip, the hard kombucha segment is projected to rocket at a staggering CAGR of 18.7% through to 2033. People are waking up to the fact that you can have your live cultures and your 3% ABV too.   Tarek didn't come from a drinks background. He spent his 20s in the high-pressure worlds of fintech and asset management, making 200 calls a day and leaving jobs just before he was asked to go. Better Sundays was born out of a personal need - traditional booze was making him feel gross, and the alternatives weren't hitting the mark. From brewing in his kitchen to a 50-store Waitrose launch this November, Tarek has built Better Sundays with a 'brutal speed' that most founders only dream of. In this episode, we delve into the 'bloody awful' reality of bootstrapping, why being an industry outsider is actually a superpower, and the 3 a.m. cash-flow worries that come with an opportunity that's outstripping your balance sheet. Pop a can, enjoy the cultures, and enjoy.

Morgan Stanley analysts Ravi Shanker and Jeff Adelson take a look at what the fight for affluent, loyal travelers could mean for banks and airlines. Read more insights from Morgan Stanley.----- Transcript -----Ravi Shanker: Welcome to Thoughts on the Market. I'm Ravi Shanker, Morgan Stanley's North American Airlines analyst. Jeff Adelson: And I'm Jeff Adelson, Morgan Stanley's U.S. Consumer Finance analyst. Ravi Shanker: Today, who really owns your travel loyalty? The airline, the bank, the rewards platform, or you? It's Wednesday, June 10th at 7am in New York. Jeff Adelson: So, Ravi, you just came from your annual travel conference, and I'm about to head into the second day of Morgan Stanley's 17th Annual Financials Conference here in New York, where we're hosting roughly 135 corporates.A lot of themes are coming up there: retail engagement, product innovation, regulatory change, AI digital assets, capital markets recovery, and so on. All of these connect back to a bigger question. Who owns the customer relationship? Ravi Shanker: And that's exactly where travel co-branded cards come in. They sit at the crossroads of premium consumer spending, loyalty, and the competition for wallet share. They've become a more important revenue stream across travel, banking, and hospitality.But it's not as simple as more travel means more co-brand growth. Most customers still want flexibility, cashback, and low fees. Premium travelers and loyal airline customers behave differently. Let's start with the cardholder. Most consumers have a credit card, but travel co-branded cards are still a much smaller piece of the overall wallet. So, how big is the opportunity here, and how hard is it to get consumers to switch? Jeff Adelson: So, what's actually interesting, Ravi, is that travel co-branded cards are still relatively under-penetrated. In our survey, about 90 percent of cardholders have a general purpose card, while only about 22 percent have an airline card, and 12 percent have an hotel co-brand card. So, on the surface, the runway for growth does look significant. The upshot is also that once you get these consumers in the door, they are much higher spending and drive a ton of volume and incremental card economics for both the banks and their co-brand travel partners. The challenge is that consumers are pretty loyal to their cards or airlines that they already use, so most people aren't actively looking to switch. They tend to add a new card only when the value proposition is compelling enough. And sometimes given these one-time nature of the signup bonuses, it results in some churning without keeping the customer for the long term. So ultimately, what this all means is issuers and travel brands aren't just competing with each other, they're competing against habit. So, to win, they need to offer something that's meaningfully better than what's already in the consumer's wallet. Ravi Shanker: Got it. So, consumers seem to care most about value, fees, rates, and reward. Cashback still leads by a wide margin. So where do travel-specific rewards fit in? Jeff Adelson: The nuance here matters. Travel rewards don't need to win with everybody to be valuable. What makes them so powerful is they resonate with a specific group of customers, specifically the ones who are traveling – the frequent travelers, the ones who spend more, and those who engage more deeply with loyalty airline programs, for instance. For those consumers, lounge access, status benefits, upgrades, and airline or hotel points can create a level of engagement that's difficult for just a basic cashback card to replicate. The nuance here matters. Travel rewards don't need to win with everybody to be valuable. What makes them so powerful is they resonate with a specific group of customers, specifically the ones who are traveling – the frequent travelers, the ones who spend more, and those who engage more deeply with loyalty airline programs, for instance. For those consumers, lounge access, status benefits, upgrades, and airline or hotel points can create a level of engagement that's difficult for just a basic cashback card to replicate. Ravi Shanker: So, the premium consumer looks different. Why is that customer so important to card issuers? Jeff Adelson: So, higher income consumers frankly just spend a lot more. They're more loyal, they carry more cards, and they're more willing to pay a higher annual fee if they feel like they're getting the value from the card back after they pay that fee. In our survey, consumers earning over [$]150,000 per year of income spent roughly twice the amount on their primary card, and they were willing to pay almost twice the annual fee as other income cohorts. They're also attractive from a credit standpoint, from a, you know, delinquency perspective. These customers are more likely to pay their balances in full each month, and as a result, have lower credit risk. And often they keep long-standing relationships with their banks or their airline partner. That's why premium card and travel partnerships remain such an important customer acquisition tool for a bank. It has a really long lifetime value. The battle isn't really for the average card holder; it's for the affluent consumer who's driving a disproportionate share of spend in the U.S. economy.Ravi Shanker: Got it. So, the banks and travel brands are partners today. But they're also starting to potentially compete more directly for the same customer. What should investors watch to see whether this stays a partnership or becomes more of a tug-of-war? Jeff Adelson: So historically, this has been a successful partnership, especially in recent years as high-income consumer spending pie has grown in the U.S. How this works is airlines provide loyalty and travel experiences. Banks provide the card issuance, distribution scale, and share back those card economics to the airlines. Everybody wins when the travel spend grows. But we're starting to see some things overlap. Banks are building their own premium travel ecosystems. That includes things like flexible rewards points with the ability to transfer to any airline you want, proprietary lounges away from the airlines, and travel benefits that increasingly compete with airline loyalty programs. So, what investors should watch from here, in our view, are two things. Number one, is the high-income consumer and the travel pie continuing to grow? That's really what's held everything up and frankly, driven the airlines that you cover to realize that they hold this golden ticket. They hold the access to that consumer, so they've begun negotiating for more of the economics away from the card issuers. The second thing we think that you need to watch out for is whether consumers really continue to value these airline-specific rewards enough to justify the existing partnership model. Our survey indicated that most consumers still prefer flexible rewards over points tied to a single airline. But among frequent travelers and airline loyalists, the airline ecosystem does remain powerful. So, the future does seem to depend in part on whether these travel brands can continue to deliver on experiences that the consumers really can't get elsewhere. So, Ravi, maybe switching to you. For the airlines, the question I have for you is a little different. How do you turn loyalty into a durable, profitable revenue stream without losing sight of the core travel product? Ravi Shanker: That's exactly it. Kind of you referenced the strength of the travel ecosystem in your previous response, and I think that's exactly what the airlines need to focus on. I think the takeaways for the airlines from the survey is very clear. You cannot have a co-brand revenue opportunity in isolation. It is just a layer on top of your core revenues. You cannot build an incredible loyalty or co-brand franchise without having a very strong core airline product. The analogy we use in our report is that it's sort of like the restaurant business.Most restaurants usually make the bulk of their profitability off of the wine menu or the liquor menu, even though you're going there primarily for the food and the ambiance and the service. If you don't have really good food and ambiance and service, you can't make money off of the wine menu. Similarly, we think the airlines need to continue to focus on their core product, whether it's their network or their reliability, their safety, where they fly, the quality of the product in the sky, the lounges, as you mentioned. And once you get all of that in order, then you can tap into the co-brand revenue opportunity over time. Jeff Adelson: So maybe just running with that analogy on, you know, co-branded revenues becoming a more meaningful part of the airline business. Why are they so strategically important in your view? Why should the consumer pay for that bottle of wine that they can get? Ravi Shanker: Look, we, we don't have a full disclosure from the airlines just yet, but we have some nuggets that tell you that this is a very attractive revenue opportunity, right? So, look at some of the numbers we do have. We think that this business has been growing at a low double-digit CAGR for the industry, which is much faster than core revenue growth. We think it has already grown to be about low double-digit percentage of overall revenues. And from the little info we have, we can surmise that this is a very, very profitable business. Something in the order of 35-50 percent operating margins, if not much higher than that in an industry that is overall working really hard to get to double-digit margins on a core basis. So, this business can be about half of overall mid-cycle profitability, maybe even higher for some of the airlines, even though, it is considered to be an ancillary revenue stream. This is also a very, very stable business that doesn't exhibit the kind of cyclicality or volatility as the core passenger airline business. And so, we think the airlines will be looking to grow this for the margins, for the stability, and for the, honestly, growth opportunity over time. Jeff Adelson: And if we think about that opportunity growing over time, if consumers really do care more about tangible benefits than brand prestige, as I think our survey indicated, what does that mean for the airlines trying to build that loyalty through these card partnerships?Ravi Shanker: It's exactly as you mentioned, kind of, earlier – that we think both the banks and the airlines need to keep investing in the product. They need to keep giving the consumers enough rewards that make it seem worth the fees and worth the while to subscribe to a travel co-brand card – versus going with a more generic card that gives you just plain cash back. And I think, again, it comes down to whether the core airline product is strong enough for the consumer to warrant going down the path of building loyalty with the airline franchise. And if the consumer is committed to travel, as a share of the consumer's wallet significantly enough to commit to travel cards' benefits over generic benefits. We have a lot of confidence in the latter. In that all of our data, all of our surveys since the pandemic have shown that travel is now almost a consumer staple spending item rather than being a consumer discretionary spending item that it was before. And travel is now a significant spending priority – after only groceries and household staples for the average consumer. For the high-end consumer, it is the number one spending intent category. So, we know that travel is very important. Whether the airline is worth, kind of, committing to or not is very airline specific in our view.Jeff Adelson: So, if we put this all together and, you know, you think about your forecast for the industry and, you know, our joint forecast for the co-branded card revenues… Ravi Shanker: Mm-hmm. Jeff Adelson: Maybe just talk a little bit about how you think those revenues keep growing so strongly, or whether they continue to grow strongly. Or is there a risk that this all plateaus at some point in the near future? Ravi Shanker: Look, that's a great question, and that's why we highlight three possible scenarios in the report. In our base case, we have the industry growing at roughly the same double-digit CAGR that it has been for the last few years. That sees the market go from about $25 billion today to about [$]60 billion in the next 10 years. In our bull case, we have travel as a share of overall spending, and travel cards as a percentage of overall credit card issuance, which you highlighted earlier was a pretty low number, actually expand to something more reasonable. And that's where we see the potential for the market almost quadrupling from $25 billion today to [$]100 billion in the next 10 years. And our bear case, kind of that's when you talk about a macro risk. Second, maybe some kind of slowing down in travel as a spending priority, which we actually don't think happens. But what's more likely is the point you referenced earlier, in response to my question about the relationship between the airlines and the hotel companies versus the credit card issuers may be changing a little bit. And this becoming a little more of a free-for-all in the industry and a little more competitive. That could potentially, kind of, hurt the economics for the overall industry, even though the size of the pie will continue to grow. So that brings us back to the consumer's wallet. So, every time I'm on a trip, I have several options – maybe a cashback card, maybe a premium travel card, maybe an airliner hotel co-brand card. So, which one am I reaching for every time I look to swipe? Jeff Adelson: Well, I mean, I think at its core, it really depends. It's a battle at the end of the day for the loyalty of a high quality, sticky and heavy spending consumer. And consumers are largely rational, right? So, they're going to go with a card where they think they get the best value. And if that's their airline card where they think they can accrue the best loyalty status and maybe get their first class upgrade every now and then and get unlimited access to the lounges, maybe they'll choose that. But really in a survey what we learned was most consumers tell us they care about value, flexibility and rewards. So, the highest value consumers I just mentioned are also looking for experiences, convenience and status. So that's why the banks, airlines and hotels are all investing so aggressively in these premium ecosystems to try to lock them in and keep them loyal. Every swipe is really a vote for which ecosystem delivers the most value if you think about it, right? The winner isn't necessarily the company with the best card too. It's the company that creates so much of the strongest overall relationship with the consumer. And that's why this competition matters so much across banking, travel and hospitality. So, we are watching this competition. So far, it's working. It's a rising tide that's lifting all boats. But as I mentioned before, it really will only continue to work if our forecasts are right and the high-income consumer views this as less of a discretionary spend item and more of a stable spend item. And, if that pie, and the high-income consumer, continues to grow in the U.S., then this relationship can continue to work for the foreseeable future, we think. Ravi Shanker: That makes a ton of sense. Jeff, thanks so much for joining me on the show today. Jeff Adelson: Thanks, Ravi. It was my pleasure. Ravi Shanker: And to our listeners, thanks for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you get your podcasts and share with a friend or colleague today.

Vamshi Ambati has spent more than two decades in AI, through the symbolic era, statistical era, and the neural wave we're experiencing today. A CMU PhD, founder of LatentStructure and Predera (which was acquired), now an investor at Virama Ventures, he's one of the sharper voices on what's actually happening under the hood of the AI boom.We discuss a simple question: Who wins when models become cheaper and more abundant? And try to answer this by looking at how inference spend v/s compute spend is shifting, and why inference may become the biggest infrastructure opportunity of the next decade.Vamshi explains what actually goes into the cost of a token, why AI is simultaneously getting cheaper and more expensive, and why the inference market alone could reach $1.3 trillion by 2030. If you're building in AI or someone who wants a clear mental model of where this industry is headed, this conversation is for you. 00:00 - Trailer0:45 - How an AI researcher thinks after 20 years05:53 - Where enterprise AI adoption is headed08:35 - Drawing parallels between cloud and AI11:20 - If building is cheap, what's valuable?13:37 - Can computing get cheaper?16:41 - What is inference, really?22:22 - Why coding and customer support got eaten first?26:48 - Which technologies are overvalued and undervalued?29:56 - An accidental entrepreneur's journey33:15 - Why is healthcare slow to adopt technology?38:59 - Landing Walmart as a customer42:36 - Should founders build in services if product isn't visible?43:47 - Is Palantir a product company or a services company?44:15 - How to win as a forward-deployed company46:23 - What it takes to land large enterprise customers49:20 - Building sales muscles as a technical founder-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

The Last Trade: Chris Kuiper, VP of Research at Fidelity Digital Assets, returns to make the case that this is the worst sentiment he has seen in his decade-plus following Bitcoin even though nothing fundamental has actually broken, why Bitcoin is finally decoupling from the AI-led "everything-but-Bitcoin" rally, how Fidelity's updated "Getting Off Zero" report uses mean variance optimization to show a 90/0/10 stocks-bonds-Bitcoin allocation maximizing the Sharpe ratio at a conservative 25% Bitcoin CAGR assumption, why bondholders have spent decades underwater on a real-return basis, and why the Czech National Bank's small but symbolic Bitcoin position may be the start of central bank adoption gradually then suddenly.---

In this episode, we explore the latest Dell'Oro Group Broadband Access and Home Networking forecast and what it signals for cable, fiber, and fixed wireless providers worldwide. After three consecutive years of revenue declines, the market is projected to grow at just a 0.3% CAGR through 2030, with another dip expected in 2025 before a potential rebound in 2026 driven by DOCSIS 4.0 and XGS-PON rollouts. Jeff Heynen, Vice President of Broadband Access and Home Networking Research at Dell'Oro Group, joins Gary Bolton, President & CEO of the Fiber Broadband Association, to break down what this means for network operators — from timing infrastructure investments and managing capital amid macro uncertainty to balancing fiber expansion with cable upgrades and planning for moderating bandwidth growth. The message is clear: disciplined deployment decisions over the next three years will shape long-term competitiveness and ROI. With Special Guest: Jeff Heynen, VP of Broadband Access and Home Networking Research, Dell'Oro Group

Chinese consumer brands are rapidly expanding across Southeast Asia, moving beyond electronics and electric vehicles into sectors such as beauty, food service and home appliances, according to a report by Euromonitor International.市场研究机构欧睿国际的一份报告显示，中国消费品牌正在东南亚迅速扩张，其业务已从电子产品和电动汽车拓展至美妆、餐饮和家用电器等领域。Its “Rise of Chinese Brands in Southeast Asia” report found that the ASEAN economies of Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam account for 95 percent of the region‘s $4 trillion GDP. The region has become the largest and fastest-growing export destination for Chinese goods.该机构发布的《中国品牌在东南亚的崛起》报告指出，在东南亚地区4万亿美元的经济总量中，印度尼西亚、马来西亚、菲律宾、新加坡、泰国和越南这六个东盟经济体合计占95%。该地区已成为中国商品最大且增长最快的出口目的地。In 2024, China's exports to Southeast Asia reached $587 billion, up 12 percent year-on-year. More than 70 percent of Chinese companies operating in ASEAN plan further expansion, citing strong performance and untapped consumer demand, said the China Council for the Promotion of International Trade.据中国国际贸易促进委员会数据，2024年中国对东南亚出口额达到5870亿美元，同比增长12%。超过70%在东盟经营的中国企业表示将进一步扩大业务，这得益于其强劲的业绩表现以及尚未充分开发的消费市场。With a population exceeding 650 million, 63 percent under 40 and a median age of 31, Southeast Asia‘s consumer market is thriving. This demographic fuels demand for e-commerce, livestreaming shopping, fintech solutions and affordable premium products.东南亚人口超过6.5亿，其中63%在40岁以下，中位年龄为31岁，消费市场充满活力。这一人口结构推动了对电子商务、直播购物、金融科技解决方案以及高性价比优质产品的充分需求。Countries like Vietnam and Indonesia are outpacing China in GDP growth, offering Chinese brands a rapidly expanding consumer base with rising disposable incomes and accelerating urbanization, said the report.报告称，越南、印度尼西亚等国的经济增速已领先中国，这为中国品牌提供了一个蓬勃发展的消费市场——那里的居民收入不断增长，城市化步伐也在加快。Chinese companies have long dominated sectors such as EVs, consumer electronics and home appliances. In EVs, BYD is now the top brand in most Southeast Asian markets and the number-one car brand in Singapore, surpassing Toyota. In home appliances, Chinese brands‘ share of the air conditioner market rose from 9 percent in 2015 to 25 percent in 2024. Haier, Midea and Gree have become household names. In smartphones, Chinese brands' market share has increased from 21 percent in 2014 to over 60 percent today.长期以来，中国企业在电动汽车、消费电子产品和家用电器等领域占据主导地位。在电动汽车领域，比亚迪现已成为大多数东南亚市场的头号品牌，并在新加坡超越丰田成为第一大汽车品牌。在家电领域，中国品牌在空调市场的份额从2015年的9%上升至2024年的25%。海尔、美的和格力已成为家喻户晓的名字。在智能手机领域，中国品牌的市场份额已从2014年的21%提升至如今的60%以上。Now, Chinese companies are breaking into sectors once considered difficult for foreign entrants. In beauty and personal care, mass-market skincare brands achieved a 115 percent compound annual growth rate (CAGR) from 2019 to 2024. In the consumer food and beverage sector, chains such as Mixue, Luckin Coffee and Chagee are expanding aggressively. Mixue outlets grew 80 percent between 2019 and 2024, and by April 2026, Mixue had 4,153 overseas stores, while Chagee reached 262, said the China Chain Store and Franchise Association.如今，中国企业正挺进昔日外资难以进入的领域。美妆个护方面，大众护肤品品牌2019—2024年复合年增长率高达115%。餐饮消费方面，蜜雪冰城、瑞幸咖啡、霸王茶姬等品牌正加速扩张。中国连锁经营协会数据显示，2019至2024年，蜜雪冰城门店增长80%，截至2026年4月，其海外门店达4153家，霸王茶姬海外门店达262家。Nathanael Lim, APAC insight manager for beverages at Euromonitor International, said: “Chinese coffee and tea chains maintain consumer interest through relentless product innovation, often unveiling new menu items monthly. Significant investment in research and development and direct ingredient sourcing allows them to craft unique flavors that resonate with local palates.”欧睿国际亚太地区饮料行业洞察经理纳撒尼尔·林（音译）表示：“中国咖啡和茶饮连锁品牌通过不断的产品创新来维持消费者的兴趣，每月都会推出新品菜单。对研发和原材料直接采购的大量投入，使他们能够打造出与当地口味产生共鸣的独特风味。”Partnerships with local players are also central to expansion. In January, Eastroc Beverage signed a cooperation agreement with Indonesia‘s Salim Group to establish a joint venture, with investments of up to $200 million. Since 2021, Eastroc has exported products to 30 countries and regions.与当地企业建立合作伙伴关系对扩张同样至关重要。今年1月，东鹏饮料与印尼三林集团签署合作协议，共同成立合资公司，投资额高达2亿美元。自2021年以来，东鹏饮料已向30个国家和地区出口产品。Euromonitor said deep localization is key to Chinese brands' success, surpassing mere price competition. Many beauty and F&B companies register as local entities, adapt products for tropical climates and employ local teams for livestreaming and marketing activities.欧睿国际表示，深度本土化是中国品牌取得成功的关键，其重要性超越了单纯的价格竞争。许多美妆和餐饮企业在当地注册为本土实体，针对热带气候调整产品，并聘请本地团队从事直播带货和营销活动。“To move beyond transactional entry points, Chinese companies must transition from exporters to long-term ecosystem participants. Embedding within local value chains, adapting to cultural and economic contexts, and cultivating trust — through local manufacturing, customer service and community engagement — will be essential to sustaining growth,” the report said.报告指出：“为了超越交易性进入方式，中国企业必须从出口商转型为长期的生态系统参与者。通过本地制造、客户服务和社区参与等方式，融入当地价值链、适应文化与经济环境并建立信任，对于实现持续增长至关重要。”Euromonitor International /ˌjʊərəʊˈmɒnɪtər ˌɪntəˈnæʃənəl/欧睿国际untapped /ʌnˈtæpt/未开发的，未利用的fintech /ˈfɪntek/金融科技affordable premium products /əˈfɔːdəbəl ˈpriːmiəm ˈprɒdʌkts/高性价比优质产品disposable income /dɪˈspəʊzəbəl ˈɪnkʌm/可支配收入unveil /ʌnˈveɪl/推出，公布partnership /ˈpɑːtnəʃɪp/合作伙伴关系

In this episode of the Founder's Sandbox, Brenda McCabe sits down with growth advisor and author Vanessa Golsby to explore what it really takes to scale private equity-backed SaaS companies. Vanessa shares the story behind her new book, The $100M Push: The Four Decisions PE-Backed SaaS CEOs Make to Deliver Growth in 100 Days, and reveals the four critical decisions CEOs must lead to build scalable, resilient growth: defining the ideal customer profile, aligning go-to-market execution, making strategic investment decisions, and creating long-term operational accountability. Drawing from her experience advising more than 100 middle-market software companies and serving as an operating partner in private equity, Vanessa offers an inside look at how investors think, why commercial alignment matters, and how CEOs can create predictable growth through disciplined execution. The conversation also explores the role of generative AI in modern go-to-market strategy, the importance of reputation and purpose-driven leadership, and the entrepreneurial leap Vanessa took to launch her own advisory firm. This episode is packed with practical insights for founders, SaaS executives, and growth leaders looking to scale with clarity, confidence, and purpose. You can find out more about Vanessa at: https://www.linkedin.com/in/vanessa-goolsby/ https://www.linkedin.com/in/vanessa-goolsby https://vanessagoolsby.com/ Or order her book at: https://www.amazon.com/100M-Push-Decisions-PE-Backed-Deliver/dp/1963549309 Transcript: 00:04 Welcome back to the Founder's Sandbox. I am Brenda McCabe, your host. Now in the fourth season, the Founder's Sandbox is a podcast that gathers business owners, founders, professional service providers. 00:31 and corporate directors. And we all are working towards the same mission, which is building scalable, resilient, purpose-driven companies to build a better world. We do this with underpinning, with great corporate governance, and really working with the founders to build that resilience and scalability. My guest, um join me here in what I like to consider a fun sandbox. 00:55 And this month, my guest, I'm actually delighted to invite Vanessa Golsby. Vanessa's joining me from, is it Dallas? Dallas, that's right. Dallas, Texas. So um more here, but thank you Vanessa for joining me on the Founder's Sandbox. And I wanna give a brief introduction to why Vanessa's here today. There's multiple um boxes that she checks, largely Vanessa. 01:22 has her own firm. She is a growth advisor who specializes in scaling private equity back middle market software companies. And it's an interesting time and that space that I'm certain we're going to get to a question here in a minute about the impact of generative AI and all those models out there and the effect on software businesses. You're a seven-year veteran as an operating partner. 01:48 in two private equity firms and portfolio SaaS CEOs. She has helped more than 100 middle market software companies drive growth, execute go-to-market companies, go-to-market, pardon me, turnarounds, and deliver investor returns through sharper commercial execution. That's all in the commercial execution, isn't it, Vanessa? That's right. Yeah. And prior to advising, she was a former operator leading product and commercial. 02:16 teams for 18 years at brands like Travelocity and Financial Times, which I didn't know that when we first were talking. I hadn't realized when we had our first conversations of your corporate experience with Travelocity and Financial Times. So you brought a lot of that corporate kind of know-how into the private equity world and you actually started your own firm. it four months back? 02:44 October, October of 2025. My goodness. So you're not even into your first year. I know. So, and, and, uh, you are an author. So your book, um, so I don't know when you found the time, Vanessa, but your book, the 100 million push the four decisions PE backed as SAS CEOs make to deliver growth. And a hundred days is out. 03:13 Matter of fact, this last week and we're in the third week of April, it uh hit bestseller, right? That's right. Amazon. Yeah. And in that book, we'll get into it. You distill the framework that you've developed. I don't know when, while setting up your own firm, but you developed over decades in the trenches, codifying the sequence behind the big four decisions. 03:40 that enable CEOs to scale with speed, clarity, and confidence. So welcome to the Founder Sandbox. Great. Thanks for having me. Happy to be here. Well, I always like to start with uh my guests to really talk about your origin story. And I think what's very appropriate for today's uh episode is what drove you to actually write a book, right? 04:09 because it distills both your professional as well as um this new tool that you got out there in the market. Yeah, you know, I never thought I would set out to write a book, if I'm being honest. I had, I'd spent, at this point, I'd spent probably about five years as an operating partner, so as a growth advisor for PE firms. And so in that role, I had been 04:38 pretty well practiced at writing best practices. So I understood how to codify a framework and explain it, you know, in long form, basically. But I never had dreams of being like a full author, like writing a book is totally different than writing a best practice. uh But a really strange thing happened about five years into my career as an operating partner. So I'd had about 18 years, as you mentioned, like in the trenches, like a tactical, and then about five years as an advisor. 05:06 And um over the course of those five years, I had developed for myself this framework because when I moved to the firm that I was at at that point, I was having to work on about 10 software companies at a time. And it's really difficult to show results uh efficiently when you're having to focus on so many different companies who have different industries and different sizes and different needs. And so I created this framework just so I could work at scale. 05:35 And uh I had been running it probably about three years at this point when I needed to go back and take a look at some of my case studies. So I wanted to collect case studies. And luckily, because I was still at the firm, I was able to get access to actual data from these companies that had been running the framework. And oftentimes what happens, because I focus on middle market software, there's a sales cycle. So oftentimes what happens 06:04 is we'll run through this framework and we'll see immediate results by way of pipeline and maybe bookings depending on the sales cycle time. But oftentimes we don't see the actual bookings and revenue results until a quarter or two after, depending on what it is that we're selling. So this was really the first time that I had really paused and like done, if anybody here has had to do a case study or fact finding exercise for a PE firm, know like what a... 06:32 slog it is to have to like go look through all this data. I like found the time, I prioritized it. And what I found was, I mean, there was no surprises in terms of like when we wrapped up our, usually my engagements, I try not to be there longer than 90 days. So it's either a 30 day, 60 day or 90 day plan that we run through. It's pretty tight ah in terms of how we manage through it. So by the end of our... 06:57 I have a sense of some results, like whether it's pipeline or early bookings. have some walking away knowing that we've seen some lift, but this was the first time I'd been able to go back like a couple of years to see like, what about those first companies that ran through it? And I'll tell you, Brenda, I fell out of my chair. I was like, I cannot believe the consistency. You can see in the data, like the trajectory, the upward trajectory from when we started working on the framework and then where they were today. And 07:27 At that, that was like the first seed. Like that was like a Thursday. And I was like, I don't know what to do with this information, but I have this information. Oh my gosh, this works. can't believe it. Right. And I really had to sit with that. And over the course of like two or three weeks, a few other things kind of happened that led me to the path of writing a book. Um, and one of those is I was listening to a podcast. I'm an avid podcast listener. 07:54 And I was catching up on April Dunford. She wrote a book on positioning. Obviously awesome. It's a great book for positioning. And I was going to have to run a positioning workshop. And so I was like, oh, let me like get into my head back into the game on messaging. So I just like queued up like the latest podcast I could find from her and then went on a run. And then I was like a captive audience. I went on this run. It turns out the podcast I had queued up was not about positioning. It was about her journey as an author and writing her book. 08:23 So I spent an hour listening and getting really inspired. And when I came back from that run, I thought, you know what? I have to tell the people, there is a way to consistently build and scale companies when they're going from, my framework is very from 10 to that first 100 million. And so that was really the inspiration for me. then it's just been a journey from there. 08:52 We'll get to it, but you uh codified um when you had those aha moments, right? You went back and looked at the cohorts of the companies that you had been working with, right? 30, 60, 90 day framework, for lack of another word. Can you share what are those four things that enterprise SaaS CEOs do? 09:18 Sure, so my framework is an order of operations. So everything that happens at the beginning has like downstream implications on the other activities. And originally when I created this order of operations, I hadn't high leveled it in terms of four decisions. I did that for the book because I wanted to write the book for CEOs. CEOs are such a, especially going to the first hundred million. CEOs. 09:45 have to have their hand on the strategic wheel of commercial growth. not yet mature, they haven't yet matured out of that. There is a place over a hundred where you can start to delegate more of the idea of commercial strategy to like a, you know, top tier executive CRO, for example. But when you're working on the path, especially if you're PE-backed to a hundred, you really need to stay involved. And that had, I had noticed that that core ingredient oftentimes was 10:15 one of the gaps I was inadvertently closing when I was working with these companies. And so because of that, I wrote the book for CEOs. And since I was writing it for CEOs, I was like, oh, I need to go one level higher than my traditional order of operations, which is very like activity sequenced and like talk about more of like, what is like, what is strategy? Strategy is making a decision and committing to it. So what are the four decisions that a CEO needs to direct and commit to have their team commit to in order to see this growth? 10:44 And those four decisions kind of tell the story of growth from up to the first hundred million. Frankly, it's kind of the same above a hundred, except the last decision actually becomes the first decision over a hundred. But anyway, that's right. So four decisions that CEOs that you were saying that are 10 and get to and to get in order to get to a hundred million, they have to be really continuously involved. 11:13 in the growth of the company. They cannot delegate until they reach that um upper level. They don't necessarily need to direct or be boots on the ground in these areas. But when they make these decisions and they guide their teams and champion these decisions, what happens as a byproduct of this is they inadvertently align their business in a way that is 11:43 successful for commercial strategy. So for example, I'll just walk through the decisions quickly to give you an example of how this works. um So the first decision, I high level it as the ideal customer profile or the ICP, which is just another way of saying who are we going to target? And my bit, my specialization is being PE backed. So part of what CEOs and companies hire me for is certainly the pattern recognition of working on over a hundred software engagements. 12:13 but also that sort of behind the scenes view of what the investor is expecting. you know, bringing that idea. When your PE backed, once that investment round closes, are inadvertent, not inadvertently, you are inherently um signing up to expand and grow either within your market, into an adjacent market, or in some other capacity. And just by that definition, you need to, 12:41 understand who your target is going to be, who your best buyer is going to look like for this next round of growth. So it's generally, this is such a major trigger event, this idea of becoming um PE backed, that it's generally a signal for CEOs to say, okay, now let's take a look and see if our existing customer today is going to get us to where we need to be in five years. Because that's five year journey is what you've signed up to take on essentially. So the first 13:10 The first decision is that ICP decision. Once we have an understanding of who we're going to target, then we focus, especially with the commercial side, we focus on how are we going to turn those targets into opportunities, right? So in software, it very much goes from like lead to opportunity to closed one deal, right? So that's what I mean when I say opportunities and or pipeline opening. And this idea of how do we turn targets into opportunities? I high level this decision as the SLA. 13:40 which is a pretty common service level agreement. in this framework, it covers about five or six very specific decisions that your sales, marketing, channel partner and CS teams need to align around to ensure that the build of their lead management system and how they're qualifying those leads to become opportunities is sufficient enough to have some predictability. like you have some confidence that when you put a dollar out, 14:10 into a marketing campaign, it's going to convert into pipeline, really, right? And then ideally into bookings from there. And so that's the second decision. the first one, who do we target? ICP decision. The second, how do we turn those targets into opportunities? The SLA decision. Once you reach... 14:29 Once you have the confidence and some predictability flowing through, now you're ready to make a more strategic decision. And these last two decisions are really where the CEO not just champions, but takes an active role in the decision making. The next one is the contribution decision. So this is now that we know who we're going to target and we understand and have confidence that when we target those buyers, they are going to turn into customers. The next question is where do we invest? 14:57 to go get more of those targets. So who's going to contribute to our revenue number? How much are we going to put into channel partners? How much are we going to invest into marketing? How much are we investing into outbound? How much are we investing into PLG or a self-serve motion, right? How much is new? How much is expansion? And in this decision, we start to bring the CFO in to take more of a governance posture around commercial. So we give the CEO more context around 15:26 Some of the horse trading that typically happens in a silo between the teams. We now have those kinds of conversations around investment decisions and headcount and budgets all together in a room. I run this like a workshop, but all together in a room. And the book teaches the CFO and the CEO how to run this on their own. Excellent. for kind of the terminology that I would use and correct me if I'm wrong, it's kind of capital allocation. So a bit more rigor. 15:56 is brought in with this discipline of budgeting, right? You're talking about contribution decisions, So it's budgeting, capital allocation, and um bringing another uh kind of the controller of the purse strings, the CFO. That's right. Right? And jointly with the CEO are posturing and actually sprinkling it down to their direct reports, I suspect. 16:25 Right. Well, we so the way that I teach contribution modeling is everyone needs to be in the room. No one function, not the CFO, not the CEO, not the CRO can make these decisions for the entire commercial team who is actually going to need to. Yes, it is a budget allocation exercise, but actually that's the second step. The first step, it's a goal setting exercise. oh We break down. 16:53 Each of those pipeline sources has different stages, which we just got very deep on in our SLA decision. So we understand what those stages are called. We understand how long we expect somebody to stick in those stages. We understand what those conversion rates are through those stages. And now that we have some sense of those inputs, we basically enabled ourselves to sign up for a number. So now we can look at marketing and we can say, oh 17:22 If you're gonna sign up for a million dollars in pipeline this year, that means at this selling price, you're gonna drive this many deals, right? At this conversion rate, at this close rate, this means you need to have this many opportunities and that this conversion rate from lead to opportunity, you need to drive this many leads. Can you drive this many leads? And the marketing person's like, that's a lot of leads. I don't know if I can drive that many leads, right? 17:48 And if they hesitate and they say like, can't realistically get that many, we look around the room and we say, okay, who else can drive more leads? Let's look at channel partners. Now we do the same thing from referral to meetings booked to, know, et cetera, et cetera down the So it's very like, it's very precise in terms of setting goals at the funnel stages, but not to become that, like we're not expecting frankly, to get a bullseye out of this workshop. What we're doing is we're kind of snapping the chalk line to say, 18:17 Okay, this is what we think we can go do. And now we're gonna meet with the CFO leading, we're gonna meet every two weeks or every month, and we're gonna see how we're doing. Are we driving this many leads for marketing? Are we getting this many referrals from channel partners? Are we booking this many meetings through the BDRs? And if the answer is no, then we look around the room. Where else can we do it this month? So we have something we can react to in real time, and rather than showing up to the board meeting and saying like, yeah, it was kind of a miss, but I think we have some ideas for next quarter. 18:46 Like this puts everyone in a position now to become far more reactive to what's happening in real time uh as a group, as like a singular one team. And what about the fourth? Yeah, so the fourth decision. And again, this decision is fourth when you're going to 100 million. But if you were above 200 million or as you like progress to like four up to a billion, this actually can become sometimes the first decision. 19:14 when you kind of need to work your way to this point um for when you're going to 100 million, especially after the contribution decision, that contribution. Yeah. Cause that's going to surface a lot of ahas for teams. Like oftentimes you're like, Oh, actually we need to break into a new market. We're saturated or, my gosh, you know, like we need a, you know, too many, we need a ton more reps or actually we don't need more new sale reps. What we need is expansion reps and really need more there. So 19:43 Like in that contribution conversation, you really surface so many of your growth levers that you're prepared for the fourth decision. So the fourth decision is now that we know who we're going to target and we know with confidence how we're going to turn those targets into opportunities. And we understand where we're going to investigate more of those targets. Now we talk about how are we going to do this over the long term? So how are we going to do this not just this year, but for the hold period? So for five years. 20:10 And so this decision I high level as the OKRs, which is an industry term. I didn't come up with that, but it stands for objectives and key results. And it's essentially gives the CEO like almost like a project management framework for long-term planning. um And you really can't necessarily jump to number four if you're going up to that hundred day plan without having these first three decisions at least somewhat cemented or somewhat committed to. 20:39 um Otherwise, what ends up happening is your OKRs are, you know, have like 25 things you're going to try and go tackle. So you kind of like, kind of, you know, by just by um the effort of making these first three decisions, you've already like started to prioritize for your team where the important levers are that you're going to focus on. 21:01 Thank you. I wanted to ask you by publishing this book, are you putting yourself out of business? That's a good question. A grow-to-market advisor, The enterprise SaaS sector that's under a lot of pressure right now with the dinner to bay eye. So let's take the two questions. Let's take them apart. And I'm being a bit. It's a great question. I asked myself that question. Yeah. 21:29 Yeah, my publisher asked this too. Why put it out there? You're putting yourself out of business or no? Yeah. Well, you know, the way I, there's a couple of answers to this, a couple of dimensions to this. The first is, you know, a lot of the motivation to write this book was to get the word out. Like when I saw the consistency and how well the results sustain when companies run through this framework, I was like, Oh my. 21:56 Why aren't we telling all of the CEOs that there's a way to go do this? Like we know these activities, it's things like territory planning and quota setting and SLAs. like, know, people know that activities that need to happen, but the unlock here is the sequence, like it's important to do them in order and that they're done altogether, which is the role of the CEO, right? Is to ensure that the right people are in the room when you're making these decisions and everything's like. 22:24 That's the those are the connectors right is are the those are the interlocks are the decisions the activations happen You know within the function so I? Was passionate like we talk about purpose the reason I was excited to be on this podcast is because this is very purposeful for me It felt like holy cow Look what I discovered under the pyramid I got to tell the people like there's an easier way to do this We don't have to bang our head against the wall to try and figure this out the hard way so 22:53 In that way, it didn't really feel like an option to necessarily hide it. ah And then the other side of me thought about it in terms of like changing the oil in my car. Like, I know that I can change the oil in my car. It's not a difficult, complex process. Like, it's very straightforward. But do I want to do, do I want to like get in coveralls and crawl underneath my car, like find the little lackey thing? No, I don't want to do any of that. I would far rather just bring someone in. 23:22 take the guesswork out, have it done, have it done correctly the first time, and leverage someone else's expertise in case they find something that I wasn't expecting. ah So I feel like I'm still bring, like when people leverage me to run through this, I'm still bringing a lot of value that you're not gonna necessarily get out of the book. mean, people, CEOs and firms hire me because of the pattern recognition and because I've seen these things play out enough times across different industries. 23:51 uh But I don't want to be a holdup. Like, please, if you are able to do it, then I welcome, I encourage you please to go run these plays yourself. And I try to give a lot of, it's very structured. This book is, the structure of this book was really difficult to come up with. It probably took me the longest amount of time, honestly. But I wrote it in a way that a CEO could read it quickly, because I know they don't want to read too many things. They are very busy. um 24:18 And so like they could digest it quickly and they could hand it off because that's kind of their role is to say like, I'm going to now equip my leaders to go do this and do it successfully. And they still have a role to play. But again, they don't have to be like in the trenches. Right. And without um seeing the book right now, I sound and Kendall on audibles or Kendall, um are there like exercises? Are there, is it like a handbook or is it um I'm a CEO? I 24:48 read your book um and I want to contact you. Do I to come in and maybe do some seminars? How does that work? Because this is a marketing tool as well. Yeah, yes. mean, of course I this book can be just a step by step guide for CEOs and their teams if they want to take it that way. So I tried to write it dimensionally. So the first dimension is 25:13 It equips the CEOs to understand, like the first two chapters are really around what is the investor expecting of you? Basically it's like, here's a little bit of the behind the scenes. Yeah, that was intriguing for me when we first spoke of it. Yeah, you've been in that room. Yeah, like I've been in it. Yeah, exactly. like, you know, one of the things that, again, like a lot of things happened in this like two or three week time period when I was kind of coming to the conclusion that I was going to write this book. And one of them was I was in a board. 25:44 meeting and there was a CEO advisor also in this board meeting and I could see the CEO advisor was um giving great advice based on their singular experience but the truth is is their experience was so unique to them that it would be really difficult it'd be like saying like 26:07 Yeah, just, once you press post, it's gonna go viral. It's like, let's not over promise here, you know, what's realistic. And that really hit me to say like, oh, this is a unique perspective. Like I'm not necessarily an investor and I'm not a CEO. it's been years since I've like managed a commercial team or been a GM, but I have... 26:34 I've flown all of those altitudes and I've been an observer in all of those rooms so many times that like the patterns, you just can't deny the patterns. um So yeah, I'll stop there. I'll pause there. So you do the reveal, right? So for any CEOs of enterprise, um SAS companies, this is a must read, right? Because you're doing the real deal. What is actually happening in the boardrooms of those private equity? uh 27:05 partners right that are yes looking at their portfolio companies yes yes thank you yes so i start with like you need to equip yourself with understanding what is expected of you when you took this investment which isn't frankly always talked about like it's not always revealed to the CEO ah so that's the first step and then it is a step-by-step guide so like there are the four decisions and then within each decision 27:33 I show them the book is structured to show them, tell them what the decision is, give them some case studies of other companies who have solved it, give them some red flags that say like, look, this is a really helpful book if you just closed your investment and you need to run like a, they call it a hundred day plan of like, you're going to deploy a lot of that, those investment dollars very quickly in order to like try to get traction on growth. So this is, I wrote it in that framework just because it is naturally 28:00 predisposed to running in like a 90 day plan framework anyway. um But it's also one that oftentimes in a hold period, you're going to hit some kind of plateau, right? It's very rare to like knock a home run out of the park right out of the gate. And so I also, so like in that, in that first part, so like each part, each decision has a part. So there's like a part for, there's like a four chapters on ICP, four chapters on SLA, four chapters on contribution. 28:26 The first chapter tells you, like gives you the red flags to look for if this is an issue, tells you what the investor is expecting, tells you your role and how you can direct the team, tells you when you need to maybe outsource, like what's the things you should absolutely do and the things that are kind of like nice to haves. Then the next chapter goes into how do you make this decision? And each of these decisions, the way that my approach is, 28:53 Um, is I like to do like 50 % gut and like 50 % data. So I always start my engagements with like surfacing from your internal experts already. Like a lot of times your C-suite lieutenants. Yeah. They like, I get called in for audits. Like that's like oftentimes I'm brought in initially for an audit of some kind. And in that audit, it's like a 360 commercial audit. And in that audit, I have like a week that I just cap off and I talk to anyone that you'll let me talk to. 29:23 And they're telling me the problems. like, this is really like, we've known this is very rare for people to like, I have no idea. They know what they did to get here. And so we start with the gut. And so in this framework for the book, the gut is surfaced through workshops. I'm a huge advocate of workshops. think, you know, honestly, my time with Vista really beat this into me, like the importance and the value of workshops, because not only is it a great place to surface everyone altogether, but it's 29:52 early adoption. Like when your voice is heard and you could challenge something in the room, when the decision is being made, you're far more likely to adopt it when we get to the final output. So I'm a huge fan of workshops. So each of these has a workshop. And this is a lot by and large when I'm training, when I'm teaching the CEOs, it's like, this is what you need to get out of the workshop. This is agendas. You can, have all of my agendas are up for download. Like you can download the agenda. You can run through it yourself. And this is who needs to be. 30:21 Yeah, like I want this to be helpful. That's the whole point is like it's supposed to be taking the guesswork out for the CEOs. uh And then you need to there's a data validation. Like, yeah, everyone's got gut. But then we do need like we are going to make some commitments here. So exactly. Yeah. So we need to like in each of these have different places that you go and source that data to validate. uh 30:43 So that's how we make the decision. Then I go through how you execute the decision. And for CEOs, this is almost like the TLDR. It's like, give you like, look, these are the steps that they're go through. Then in each of these chapters, I go far more into detail. This is what you're gonna go tell, like this is what your management team is gonna go do. And this is what good is gonna look like. So you're not done with this step until you've seen these five things come out of this exercise, essentially. 31:07 And then finally, each of these parts, so we've got like, what is the decision? How do we execute the decision? I'm sorry, how do we make the decision? How do we execute the decision? And then how do we measure the decision? And this goes back to how your growth story. So a CEO's role is not just to understand, right, our long-term objectives that may be surfaced in our investment thesis, right? Those are the first two chapters. It's not just coordinating the execution and setting the priorities and resourcing your team, right? Those are the four decisions. 31:37 But you also need to tell that story and you need to tell it in a way that makes you show well, that makes your company show well, and that makes you more attractive, frankly, at your next round of investment. so, yeah, externally telling exactly. So as well as internally. that's right. So that was really long winded, but that's basically the structure. It goes pretty far into detail, but I do. 32:02 high level for CEOs, like you can skip this part, just give it to your zero. So, so the book is out and um you started as you went rogue yourself and said, I'm working for myself and yeah, that's right. And um what happened is you've got some of your clients that had seen your, your work in prior years and, have taken you on as their advisor. 32:31 Why are they taking you on? it around your, are you scalable or your purpose? I mean, you're wanting to give back. So yeah, tell me. And you shared a little bit when we were talking before the podcast about you got a call from a client that you had from many, many years ago. Yeah. Yeah. I, you know, when I was deciding to go out on my own, it was really scary, right? Because I had, I never really even, I, I had been motivated to write the book. 33:00 And that was almost as far as my thinking had gone. And then at that point, the book was supposed to come out. Originally, the book was supposed to come out in January and we could have a whole other podcast about writing a book. so originally it was kind of, I knew like internally, I was like, gosh, by October, I was like, I need to make a decision. Like, what am I going to do? Am I staying? Am I going? Am I doing something else? And so I reached out to every person that, that I, you know, had some sort of like respected conversation, like a respected relationship with. 33:29 over the course of my career. And I basically asked him like, what do I do? What would you do? And I'm really lucky because at this point, I had been an advisor for about seven years, you know, with really established firms and the folks that I had worked with, that knew me, knew what I could do, had since gone on to a million other firms. So like my network on the firm side was pretty large. 33:59 And in those conversations, there was just inevitably a conversation that ended with like, look, if you go, I'll give you your first client right now. And so I was like, well, there you go. Close the door, a window, let's go. That was how it went. Yeah, so you reached out to your network, which is super powerful. Yeah, it really was. And it was honestly, I had surfaced my network throughout kind of writing the book because 34:27 You know, one of the things I think that is unique about my situation versus some of the other authors who have written fantastic, and I'm an avid business book reader, Fantastic Frameworks, is that my perspective is from the operating partner's point of view. And I am, yeah, it's very like, and so I'm really lucky because I, as I mentioned, like a lot of the folks that I have worked with over the years are now at so many different firms. 34:57 And so as I was writing this book, I would send out surveys to people and just say, Hey, just like gut check, do you see this too? Are you seeing this? Like when I wrote a whole chapter on like the value creation plan and you know, the value creation plan is one of those things that people talk about. Like it's this like standardized formal process, but it's wildly different, like firm to firm, like it's so totally different. And I just wanted to uh get a better sense of how these different firms of these different sizes were actually running their value creation plans. 35:26 And that's just impossible for me to do by myself. Like I need my network for that. So this whole process has been really great. And just like also bringing together some of my work friends that I hadn't been able to really, or I hadn't like, you know, kept up with as well as I should have. And so now I feel like my network is just like really thriving and humming. And I feel so much closer to like these people now than I have in a long time. So it's been really beautiful in that way. 35:54 Thanks for sharing. know, I want to ask you how has, well, your frameworks be at all affected in your opinion by the generative AI and how it's taken quite a bit of value out of the stock market. So now it's back up, right? So let's, so was, are you isolated from that effect? Your, your, your, your, just your, your frameworks. 36:22 Yeah, you know it's funny I wrote this book so I've done a lot around writing best practices for AI for go-to-market teams so I was pretty what by the time I wrote this book I had a lot of already like pretty packed research and thinking around AI and what it could do and what it couldn't do. I of course how could I you know I wrote this book almost two years ago now like 36:46 has really changed the game and just some of the new models that have come out. We knew that they were gonna be pretty revolutionary, but it was hard to be very specific. But I did, in the book, I have a very specific point of view on how AI can ah make what you do more effective, more scalable, where can use what you are bringing to the table and... uh 37:12 The word is escaping me, which is ironic scale, basically what you could do. And so that's my approach to AI and it's still my approach to AI. So I don't see AI as a competitor. I see it as an accelerator, really. And so I'll take account scoring as a great example. So in this idea of 37:38 these four decisions, one of the activities that you inevitably will need to do, it's under the ICP decision. So once you have an understanding of who you're going to target, you want to then score the accounts that are in your database to say like, is this a tier one, is this a tier two, is this a tier three, is this a tier four, and we're not gonna like, they're actually gonna churn too fast for them to even be worth that selling to. And so you're building out this account scoring model. Now, there are platforms that can just do this for you. 38:06 and they're just like, look at your data and they're like, great, we're gonna do this for you. But those platforms don't know your growth plan. They don't understand like what your investment thesis is. They don't understand that you have a very concentrated point in time where you're going to make, you know, a 30 % CAGR, you know, you've got like big, big goals. You're not just trying to do status quo every year. And so it's in that same kind of vein, like the human still needs to drive and be the director of... 38:33 where the AI is going to execute. um But AI is a fantastic accelerator. I'm excited. I love partnering with AI. It's not perfect. I think of it as almost like an MBA intern, like whip smart, smarter than I will ever be. But you can't totally take your hands off the wheel. You're like, there's context. That's great analogy. Oh my goodness, that's hilarious. It is true. um 39:03 AI. particularly like the perplexity model because it's on top of all of them for uh writing and preparing some of the work I do with my clients. So it becomes my companion is what I call it. Right? Yeah. Oh yeah. Definitely. Excellent. Well, I'd like to give you an opportunity to share how my listeners can reach out to you. Oh, sure. They'll be in your notes. Vanessa. Carry on. Okay. Great. 39:32 So I have a website Vanessa ghouls be calm I'm also on LinkedIn both ways You know are pretty easy ways to just you can look at my calendar and schedule time if you're interested Often time like my most most of the ways that I get brought into engagements is There is some kind of trigger event where the CEO or the PE firm Says like we need we need some 39:59 things, some kind of audit, some kind of assessment, some kind of strategy, some kind of like, what are our growth levers, right, to get us to whatever the next thing is. It's generally a two to four week audit. em And as I mentioned earlier, it combines interviews with your team with I have like a list of artifacts that we start off with. It's, I don't want to say it's like diligence, because it's not like diligence. But it is a pretty thorough 40:25 uh So you get sales, marketing, customer success, channel partners, digital, all of that. uh And oftentimes CEOs will have like a specific need on top of that. you know, I've got one where I just did one where it was like, we want to see, you know, we know we just got our investment came through and we kind of need to set our hundred day plan. So where should we go? You know, what are the foundations we need to build and fortify for this next round? uh We have one. 40:53 One other trigger that's pretty common is on the back of maybe M &A, where you have like two go-to-market teams that need to integrate together. Yeah, they like will bring me into sales. How are we gonna do that? Yeah. Or they have done that and maybe they're still not quite hitting that like expansion number that was originally conceptualized. um And then, yeah. And then the third, which is, I mean, it's like the... 41:21 the least positive, but honestly, the most exciting for me is, you you're like an a mid hold plateau. You're like, gosh, you know, I had one just last month where it was like, they hit this $30 million ceiling and they for like three years have thrown every spaghetti they could at the wall and just could not get past this ceiling. And, um, and so like the audit can, it's very focused and like trying to get to whatever the objective is, but it's, it's holistic because my whole, my whole shtick, right. Is that like, 41:51 It's no one team. It's like all of the teams kind of have to interlock in a line together. Yeah. Yeah. Quite revealing. Excellent. Those are excellent use cases. Um, and we'll put this in the show notes as well as your website and Vanessa. Um, let's come back to the sandbox. I do like to do a round of just questions about three words and what is the meaning for you. Um, and each of my guests comes up with their own um interpretation, their own meaning. it's 42:19 So what does resilience mean to you, Vanessa? Yeah, think resilience means being internally motivated. There's a drive that is not necessarily anchored or reactive to anything that's happening externally. uh For some reason, you just can't let it go. 42:47 How about scalable? What's scalable? Oh, wow. I mean, spent so many years uh writing about being scalable. Yeah, you know, it's funny when I think about being scalable, you know, it actually initially comes to mind as like growing pains, like this idea of growing pains. uh And I'm just now kicking myself for not reading the prep questions closer. We're going to rip a little bit, but. 43:15 But yes, being scalable is having that resilience through the growing pains, knowing, right, having like some kind of faith that at the end it's gonna be bigger, better, probably bigger than you even really could even have imagined or maybe even in a direction that might not have been initially planned. Excellent, excellent. Yes, and I also wanna just, I think. 43:43 you know, we're back to the title of the episode, is, um, and which is building purpose, building reputation with purpose. And you were adamant about that. So what does purpose mean? And maybe you'll bring into, know, what, what is building reputation with purpose for you? know, I, um, 44:11 It's funny, I feel like it really goes back to this resilience question, but it's so much of it just comes down to acting with kind of like, like I work with companies that have like cultural values, right? And they're like, oh, or Patrick Lindsay only has a great one, like the heat, likes to say, you know, hire people that are hungry, humble and smart, right? So like, you have your like keywords, your brand words, your value words. And I think for me, 44:40 um over the years, my purpose has been to act with integrity and grace and curiosity. And, um and that's something that I don't think about logically, right in life. But I try to bring that kind of inspiration to the teams that I'm working with. And it's a lot of the reason why I wrote the book was to say like, 45:10 Look, there is a way. You don't have to follow every single thing that's in this book. But if you get stuck, isn't it helpful to have a guide, like a troubleshooting guide to say like, oh, let me just go to the index here. I'm a little stuck on territories. I'm going to get over it. And that's the spirit that I try to bring to everything that I do, which is, yeah, we can solve any problem. Like any problem is solvable. And guess what? Execution problems are the easiest thing to solve. So like, 45:40 Let's have some fun and we can, we can, there's a way to do it basically. Right. Excellent. Thank you. And last question, did you have fun in the sandbox today? I had so much fun. This was great. You know, honestly, I didn't really know how this, like I do enough of these podcasts now and it's so usually anchored on the framework and like, you know, the execution and like, you know, very tactical. 46:07 And so this was just a really, this was like a breath of fresh air because we got to talk a little bit about the human side of it, which I find really motivating. It is. And I do recall you were really set on building you and you it's your reputation. Do you have Vanessa Goldsby that has gotten to you, gotten you where you are today and by giving back and providing that, you know, writing that book and then, you know, serendipity, you decide, Oh my gosh, I'm going to go out on my own. So it's, your reputation. 46:35 that has been built with purpose. I want to thank you for joining me here in the Founders Sandbox. To my listeners, if you like this episode with Vanessa Goldsby, sign up for the month release of the Founders Sandbox where I have guests that are Founders, business owners, service providers like Vanessa, um and board directors who build with strong governance, resilient, scalable, and purpose-driven companies. 47:03 So signing off for this month. Thank you very much. Thank you, Brenda.

Saylor just broke Strategy's "NEVER SELL" Bitcoin rule. The $1.5B dividend math, the 11.5% yield, the Q1 -$12.5B net loss, and what it means for Canadian MSTR holders — explained.Michael Saylor told investors on Strategy's Q1 2026 earnings call that he will "probably sell some Bitcoin to pay a dividend, just to inoculate the market and send the message that we did it." Three days later he walked it back, saying the remark wasintended to "jam short-sellers and 'haters.'" Strategy holds 818,334 BTC at an average cost basis of $75,537. The annualized preferred dividend obligation is roughly $1.5 billion. Q1 net loss was $12.54 billion. Bitcoin briefly traded below $81,000 after the call.In this episode of the Canadian Bitcoiners Podcast:- The actual mechanism: buy with credit, let it appreciate, sell to fund preferreds- Why this isn't an MSTR "Ponzi" reveal — and why it kind of is- Sequans' 1,025 BTC sale, the $35.9M convertible-note pressure, and what "treasury reckoning" looks like in practice- Canada's first regulated CAD stablecoin: Tetra's CADD with Shopify and National Bank backing- Coinbase cuts 14% of staff for "AI-native pods" while the exchange goes down for an AWS chiller failure- Germany ends its 12-month Bitcoin tax exemption — €2B revenue target by 2027- The Netherlands prepares 36% tax on UNREALIZED Bitcoin gains by 2028- Bitcoin Core's first-ever memory-safety bug, CVE-2024-52911, quietly patched a year before public disclosure- Notable North: Alberta separation petition crosses 300k signatures, Honda walks from a $15B Ontario EV plant, Doug Ford sacks the Conestoga College board, Ottawa finally starts tracking which temporary residents have actually leftThe orange-pill takeaway: every "treasury company" model — Strategy, Sequans, the next wave — gets stress-tested when the dividends and debts come due in fiat. The companies that buy and never sell are betting that their cost of capital stayslower than Bitcoin's CAGR forever. Saylor just admitted that the bet has a release valve. Canadian retail and Canadian pensions are sitting on MSTR exposure; the next 12 months are the test of whether the model is genius or a glorified levered Bitcoin ETF..Canadian Bitcoiners Podcast- Website: https://canadianbitcoiners.com- X: @CanadianBTCPod- Subscribe & turn on notifications for the weekly orange-pill drop.————————————————————————————————SPONSORS■ easyDNS — Canadian-owned, ICANN-accredited registrar that has accepted Bitcoin since 2013. Domains, DNS, email,hosting, all without selling you out. Use promo code CBP Media for 50% off your first purchase, no limits.→ https://easydns.com■ Bull Bitcoin — Canada's non-custodial, Bitcoin-only exchange. Founded 2013 in Montreal. They never hold your keys;you self-custody from day one. CBP listeners get 25% off fees for life.→ https://app.bullbitcoin.com/registration/cbp■ 256 Heat — Hashrate heaters: Bitcoin miners purpose-built to heat a space. Every watt of electricity becomes heat AND hashrate, so you're warming your space and stacking sats at the same time. Custom solutions available. Tell them CBPsent you for a discount.→ https://256heat.com■ Bitcoin Mentor — One-on-one coaching to take you from "I bought some Bitcoin" to true self-sovereign ownership. Wallets, keys, collaborative custody, inheritance planning, node setup, the whole stack. 30-day money-back guarantee on every package.→ https://btcmentor.io/aff/joey————————————————————————————————FOLLOW THE SHOW■■ CBP — https://x.com/CanadianBTCPod■ Joey — https://x.com/joeytweeets■ Len — https://x.com/thebtcpricebot————————————————————————————————#Bitcoin #Saylor #Strategy #MSTR #Canadian

Saylor just broke Strategy's "NEVER SELL" Bitcoin rule. The $1.5B dividend math, the 11.5% yield, the Q1 -$12.5B net loss, and what it means for Canadian MSTR holders — explained.Michael Saylor told investors on Strategy's Q1 2026 earnings call that he will "probably sell some Bitcoin to pay a dividend, just to inoculate the market and send the message that we did it." Three days later he walked it back, saying the remark wasintended to "jam short-sellers and 'haters.'" Strategy holds 818,334 BTC at an average cost basis of $75,537. The annualized preferred dividend obligation is roughly $1.5 billion. Q1 net loss was $12.54 billion. Bitcoin briefly traded below $81,000 after the call.In this episode of the Canadian Bitcoiners Podcast:- The actual mechanism: buy with credit, let it appreciate, sell to fund preferreds- Why this isn't an MSTR "Ponzi" reveal — and why it kind of is- Sequans' 1,025 BTC sale, the $35.9M convertible-note pressure, and what "treasury reckoning" looks like in practice- Canada's first regulated CAD stablecoin: Tetra's CADD with Shopify and National Bank backing- Coinbase cuts 14% of staff for "AI-native pods" while the exchange goes down for an AWS chiller failure- Germany ends its 12-month Bitcoin tax exemption — €2B revenue target by 2027- The Netherlands prepares 36% tax on UNREALIZED Bitcoin gains by 2028- Bitcoin Core's first-ever memory-safety bug, CVE-2024-52911, quietly patched a year before public disclosure- Notable North: Alberta separation petition crosses 300k signatures, Honda walks from a $15B Ontario EV plant, Doug Ford sacks the Conestoga College board, Ottawa finally starts tracking which temporary residents have actually leftThe orange-pill takeaway: every "treasury company" model — Strategy, Sequans, the next wave — gets stress-tested when the dividends and debts come due in fiat. The companies that buy and never sell are betting that their cost of capital stayslower than Bitcoin's CAGR forever. Saylor just admitted that the bet has a release valve. Canadian retail and Canadian pensions are sitting on MSTR exposure; the next 12 months are the test of whether the model is genius or a glorified levered Bitcoin ETF..Canadian Bitcoiners Podcast- Website: https://canadianbitcoiners.com- X: @CanadianBTCPod- Subscribe & turn on notifications for the weekly orange-pill drop.————————————————————————————————SPONSORS■ easyDNS — Canadian-owned, ICANN-accredited registrar that has accepted Bitcoin since 2013. Domains, DNS, email,hosting, all without selling you out. Use promo code CBP Media for 50% off your first purchase, no limits.→ https://easydns.com■ Bull Bitcoin — Canada's non-custodial, Bitcoin-only exchange. Founded 2013 in Montreal. They never hold your keys;you self-custody from day one. CBP listeners get 25% off fees for life.→ https://app.bullbitcoin.com/registration/cbp■ 256 Heat — Hashrate heaters: Bitcoin miners purpose-built to heat a space. Every watt of electricity becomes heat AND hashrate, so you're warming your space and stacking sats at the same time. Custom solutions available. Tell them CBPsent you for a discount.→ https://256heat.com■ Bitcoin Mentor — One-on-one coaching to take you from "I bought some Bitcoin" to true self-sovereign ownership. Wallets, keys, collaborative custody, inheritance planning, node setup, the whole stack. 30-day money-back guarantee on every package.→ https://btcmentor.io/aff/joey————————————————————————————————FOLLOW THE SHOW■■ CBP — https://x.com/CanadianBTCPod■ Joey — https://x.com/joeytweeets■ Len — https://x.com/thebtcpricebot————————————————————————————————#Bitcoin #Saylor #Strategy #MSTR #Canadian

A transformation and growth leader at heart, Paul Idziak is a CEO who thrives in complexity and turns bold vision into disciplined execution and scalable results. Like a catalyst for momentum, he does not just grow businesses; he engineers ecosystems where people, process, and performance move in sync. He leads from the front, combining grit with clarity to transform underperforming operations into high-impact, multi-location enterprises. What he brings to the table is a rare blend of private equity acumen, operational rigor, and commercial instinct. He builds strong leadership teams, installs KPI-driven cultures, and creates structures that scale with precision. From due diligence to exit readiness, he aligns strategy with execution, driving profitability, expanding markets, and reducing risk. He operates with urgency, accountability, and a relentless focus on value creation. Over the years, Paul has scaled businesses from the ground up, launching new divisions, expanding across the U.S., Canada, and international markets, and building distributed workforces of 300+ technicians. He has driven 35% revenue CAGR and 110% EBITDA growth, transforming operational performance and positioning companies for successful exits. He has secured tier-1 OEM partnerships, negotiated MSAs, and led high-value projects exceeding $20M while building diversified, resilient customer portfolios. From sourcing more than 100 acquisition targets and supporting approximately $3B in transaction value to executing value creation plans targeting 4X returns, his experience spans the full investment lifecycle. He has improved margins, reduced the cost of poor quality, implemented Lean 6S practices, and built safety cultures, achieving 0 recordables, consistently delivering measurable, repeatable results. His previous experience across Johnson Controls, Siemens, and AWC has further sharpened his leadership approach, strengthening his ability to scale operations, build high-performing teams, and drive consistent enterprise-level impact. What matters most to Paul is building businesses that endure and teams that win long after the strategy is set. He measures success not just by growth, but by the legacy of performance, discipline, and leadership he leaves behind.

Veeva Systems has been hammered by the AI-driven software selloff — but when you look past the stock chart, the fundamentals tell a completely different story. Zero debt, over $6 billion in cash, $1.4 billion in free cash flow, and a reverse DCF suggesting the market is pricing in only 5% growth. That seems like a very easy hurdle for Veeva to clear.In this episode, Kasey breaks down why Veeva is far more than a boring CRM company. Built specifically for the biopharma and life sciences industry, Veeva has embedded itself into every stage of the drug development process — from R&D and clinical trials through manufacturing compliance and global regulatory filings.We cover:- What Veeva actually does — the four-segment cloud stack explained- FY2026 results: $3.2B revenue, 16% year-over-year growth- The balance sheet: $6B+ cash, zero debt- Free cash flow growing at a 16% CAGR on a per-share basis- Is AI a genuine threat to Veeva — or a tailwind?- CEO Peter Gassner's case for AI as symbiotic, not disruptive- The real bottleneck in getting drugs to patients — and where Veeva fits- A reverse DCF valuation walkthrough: what growth rate is actually priced in?We lay out the full case and leave the conclusion where it belongs — with you.Want deeper research and live discussion? Join our Semi Insider community at chipstockinvestor.com. New members can access the Discord server until April 15th.Disclaimer: Content is for general information and educational purposes only and does not constitute specific investment advice. All investing involves risk. Nick and Kasey hold a position in Veeva Systems.

The song should be in your trading journal. Congrats to those that took trades that I suggested over the past few weeks and I hope your portfolios are doing as well as mine. Many folks have already made back the yearly subscription prices just today alone or at least over the last few weeks. Stick around to the end for the latest trade idea I have and put a taco emoji as a comment if you agree with it.

We've been on a bit of a mini World Models series over the last quarter: from introducing the topic with Yi Tay, to exploring Marble with World Labs' Fei-Fei Li and Justin Johnson, to previewing World Models learned from massive gaming datasets with General Intuition's Pim de Witte (who has now written down their approach to World Models with Not Boring), to discussing the Cosmos World Model with with Andrew White of Edison Scientific on our new Science pod, to writing up our own theses on Adversarial World Models. Meanwhile Nvidia, Waymo and Tesla have published their own approaches, Google has released Genie 3, and Yann LeCun has raised $1B for AMI and published LeWorldModel.Today's guests have a radically different approach to World Modeling to every player we just mentioned — while Genie 3 is impressive, its many flaws demonstrate the issues with their approach - terrain clipping, noninteractivity (single player, no physics/no objects other than the player move), and maximum of 60 second immersion. Moonlake AI (inspired by the Dreamworks logo) is the diametric opposite - immediately multiplayer, incredibly interactive, indefinite lifetime, capable of MANY different kinds of world models by simulating environments, predicting outcomes, and planning over long horizons. This is enabled by bootstrapping from game engines and training custom agents: In Towards Efficient World Models, Chris Manning and Ian Goodfellow join Fan-Yun in explaining why their approach to efficiency with structure and casuality instead of just blind scaling is sorely needed:SOTA models still show physical or spatial understanding glitches, such as solid objects floating in mid-air or moving “inside” other solid objects.If the goal is to plan for the next action, how often is a high-resolution pixel view necessary for modeling the world? Our bet is that there is a disproportionately large share of economically valuable tasks where such detail is not required. After all, humans with a wide variety of sensory limitations have little difficulty doing almost everything in the world. Furthermore, for a large number of purposes, describing a scene or a situation in a few words of language (“the car's tires squealed as it cornered sharply”) is sufficient for understanding and planning.Experiments also show that humans only partially process visual input in a top-down, task-directed way, often making use of abstracted object-level modeling. In almost all cases, partial representations combined with semantic understanding are sufficient.…If the goal is to facilitate the understanding of causality in multimodal environments, then the world model—whether it is used in the virtual world or the physical world—must prioritize properties such as spatial and physical state consistency maintained over long time periods, and an ability to evolve the world that accurately reflects the consequences of actions. That's what Moonlake is building.Game engines are the right starting point abstraction to efficiently extract causal relationships, and building the interfaces and community (including their new $30,000 Creator Cup) to kickstart the flywheel of actions-to-observations.We were fortunate enough to attend their sessions at GDC 2026 (the Mecca of Game Devs), and were impressed by the huge variety and flexibility of the worlds people were building with Moonlake's tools already! Live videos on the pod.Full Video Pod on YouTube!Timestamps00:00 Benchmarking Gets Hard00:47 Meet Moonlake Founders01:26 Why Build World Models03:12 Structure Not Just Scale05:37 Defining Action Conditioned Worlds07:32 Abstraction Versus Bitter Lesson14:39 Language Versus JEPA Debate20:27 Reasoning Traces And Rendering Layer37:00 Gameplay Over Graphics38:02 Fiction Rules And World Tweaks39:15 Code Engines Beat Learned Priors41:10 Diffusion Scaling Limits43:23 Symbolic Versus Diffusion Boundary46:14 Platform Vision Beyond Games50:24 Spatial Audio And Multimodal Latents54:23 NLP Roots Hiring And Moon Lake NameTranscript[00:00:00] Cold Open[00:00:00] Chris Manning: Think this whole space is extremely difficult as things are emerging now. And I mean, it's not only for world models, I think it's for everything including text-based models, right? ‘cause in the early days it seemed very easy to have good benchmarks ‘cause we could do things like question answering benchmarks.[00:00:20] But these days so much of what people are wanting to do is nothing like that, right? You're wanting to get some recommendations about which backpack would be best for you for your trip in Europe next month. It's not so easy to come up with a benchmark, and it's the same problem with these world models.[00:00:41] Meet the Founders[00:00:41] swyx: Okay. We're back in the studio with Moon Lake's, two leads. I, I guess there's other founders as well, but, sun and Chris Manning. Welcome to the studio.[00:00:54] Fan-yun Sun: Thanks. Thanks, Chris. Thanks for having us.[00:00:56] swyx: You've got, you guys have, come burst onto the scene with a really refreshing [00:01:00] new take of mold models.[00:01:01] I would just want to, I guess ask how you, the two of you came together. Chris, you're a legend in NLP and just AI in, in, in general. You're, you're his grad student, I guess[00:01:10] Fan-yun Sun: Actually my co-founder.[00:01:11] swyx: Oh, yeah.[00:01:12] Fan-yun Sun: I should give a lot of credit to my co-founder, Sharon. Yeah. She was, she was actually working with Professor Fe Androgyn and then she ended up working with, Ron and Chris Manning here.[00:01:22] And then, so I got connected through to Chris initially, actually through my co-founder,[00:01:26] What is Moon Lake?[00:01:26] swyx: what is Moon Lake? What, what is, actually, I'm also very curious about the name, but like why going into world models?[00:01:33] Fan-yun Sun: So I was working a lot. With actually Nvidia research during my PhD years on essentially generating interactive worlds to train reinforcement learning agents or embody EA agents.[00:01:44] And then there's two observations. One in academia and one in industry. An industry like folks at Nvidia are actually paying a lot of dollars to purchase these types of interactive worlds, whether it's for the sake of evaluation or training the robots, or policies or models. And [00:02:00] then, in academia, same thing is happening.[00:02:02] And more specifically, when I was actually working with Nvidia on the synthetic data foundation model training project, we were actually generating a lot of these synthetic data and showing that, hey, you can actually, these synthetic data are actually as useful as real world data when it comes to multimodal pre-training.[00:02:16] But then, like I said, there's a lot of dollars being paid out to like external vendors or, or like. Other folks to manually curate these types of data. It was very clear to us that, okay, on our way to, let's call it embody general intelligence models need to learn the consequences behind their actions, which means that they need interactive data and the demand for those types of data are growing exponentially.[00:02:38] But everybody's sort of thinking about it from a pure, say, video generation perspective or something else. But we feel like the true actually opportunity is actually building reasoning models that can do these things, like how humans do these things today. So that's a little bit on the genesis of Moon Lake, and I think the reason I got into world models was partly.[00:02:59] A philosophical [00:03:00] take of the on the world where I like, believe the simulation theory and stuff like that. But on the other, on the other hand, it's really just like, oh, like there's an opportunity there that I feel like nobody's doing it the way I think should be done.[00:03:10] Structure, Not Scale: The Vision[00:03:10] Chris Manning: I can say a little bit about that.[00:03:12] Yeah. So of the overall goal is the pursuit of artificial intelligence and most of my career has been doing that in the language space and that's been just extremely productive. As we all know, the story of the last few years, I don't have to tell about how much we've achieved with large language models, but, uh.[00:03:31] Although they have been extremely effective for ramping language and general intelligence, it's clearly not the whole world. There's this multimodal world of vision, sound, taste that you'd like to be dealing with more than just, language. And then the question is how to do it. And despite, a huge investment in the computer vision space, right, as the research field computer [00:04:00] vision has been for decades, far, far larger than the language space, actually.[00:04:05] I think it's fair. Say that, vision, understanding sort of stalled out, right? You got to object recognition and then progress just wasn't being made right? If you look at any of these, vision language models, it's the language that's doing 90% of the work and the vision barely works. And so there's really an interesting research question as to why that is and at heart, the ideas behind Moon Lake are an attempt to answer that, believing that there can be a really rich connection between a more symbolic layer of abstracted understanding of visual domains, which aren't in the mainstream vision models, which are still trying to operate on the surface level of pixels.[00:04:50] swyx: I think one of your blog posts, you put it as structure, not scale. Is that, a general thesis?[00:04:57] Chris Manning: Yeah. Well, scale is good too.[00:04:58] swyx: Yeah. Scale is good. Too[00:04:59] lot,[00:04:59] Chris Manning: [00:05:00] lots of data is good as well and scale, but nevertheless, you want the structure Yeah. To be able to much more efficiently learn.[00:05:07] swyx: Yeah. The other thing I really liked also is you put out an example of what your kind of reasoning traces look like.[00:05:12] Right. Which you would distill is the word that comes to mind. I don't even think that's a good, good description, but it would involve, for example, geometry, physics, affordances, symbolic logic, perceptual mappings, and what, what have you. But like that, that is the kind of example that involves, let's call it spatial reasoning, role model reasoning as as compared to normal LM reasoning.[00:05:35] Yeah.[00:05:36] Defining World Models vs Video Generation[00:05:36] Vibhu: But also like taking it a step back. So how do you guys define world models? A lot of people see okay, you can do diffusion, you can do video generation. But, you guys put out quite a few blog posts. You put out a essay recently, we can even pull it up about efficient world models. You have a pretty like structural definition here, but for the general audience that don't super follow the space, right.[00:05:55] What's, what's the difference in what we see from like a video generation model to [00:06:00] a world gen A simulator? How do you kind of paint that last[00:06:02] Chris Manning: year? Yeah, so I think this is actually a little bit subtle because, people look at these amazing generative AI video models, SAWA VO three, one of these things, and they think Genie, they think, oh, this is amazing.[00:06:17] This is we've solved understanding the world because you can produce these generative AI videos, but. The reality is that although the visuals do look fantastic, those visuals actually are accompanied by an understanding of the 3D world, understanding how objects can move, what the consequences of different actions are, and that's what's really needed for spatial intelligence.[00:06:49] So I mean, a term we sometimes use is that you need action condition, world models. That you only actually have a world model if you can predict, [00:07:00] given some action is taken, what is going to change in the world because of it. And in particular, that becomes hard over longer time scales. So if you're simply, trying to.[00:07:12] Predict the next video frame. That's not so difficult. But what you actually want to do is understand the consequences, likely consequences of actions minutes into the future. And to do that, you actually much more of an abstracted semantic model of the world.[00:07:32] The Bitter Lesson & Data Abstraction[00:07:32] swyx: Yeah, the question comes where you want to have more structure than is available in just predicting the next token.[00:07:41] And typically, well, let's, let's call it the experience of the last five years has been that is just washed away by scale, right? So what is the right middle ground here that, you don't ignore the bitter lesson, but also you. Can be more efficient than what we're doing today.[00:07:57] Chris Manning: One possibility [00:08:00] is, look, if we just collect masses and masses and masses and masses of video data, this problem will be solved.[00:08:11] Under certain assumptions that could be true, but there are sort of multiple avenues in which it could not be true. The first is what's really essential is understanding the, the consequences of actions producing an action conditioned world model. And if you are simply, collecting observational video data, which is the easy stuff to collect, when you're sort of mining online videos, you don't actually.[00:08:41] Know the actions that are being taken to see how the video is changing. And so if you are never collecting directly actions and you are having to try and infer them from what happened in the observed video, that's not impossible. But it's very [00:09:00] hard and it's not really established that you can get that to work at any scale yet.[00:09:05] And so there's a lot of premium on collecting action condition video data, which is part of why there's been a lot of interest in using simulation so that you can be collecting data where you do know the actions, which isn't quite limited supply, but there's also in the limit of as much data as you could possibly have.[00:09:28] Maybe the problem is eventually solvable, but. Even though we collect huge amounts of text data is always at a great level of abstraction, right? Language is a human designed, abstracted representation where there's meaning in each token and it's representing and abstraction of the world, right?[00:09:51] As soon as you are describing someone as a professor, and as soon as you are saying that they're condescending, right? These are very [00:10:00] abstracted descriptions of the world. It's not at what you're observing as pixel level, and to get to that kind of degree of abstraction, starting from pixels is orders and magnitude of extra data and processing.[00:10:14] And so, although, we absolutely want to exploit, get as much data as possible, use the bitter lesson. Nevertheless, if there are ways in which you can work with five orders of magnitude less data than people working purely from pixels, you're gonna be able to make a lot more progress, a lot more quickly.[00:10:34] And that's the bet here. And so you could just say that's only wanting to be able to, do it more efficiently, do it more quickly, do it more cheaply. But I think it's actually more than that, I think. One should be making the analogy to how human beings work at one level. You know? Yes, we have these high [00:11:00] resolution eyes and we can look and see a scene like a video, but all of the evidence from neuroscience and psychology is that most of what comes into people's eyes is never processed.[00:11:13] Right. That you are doing fairly fine ated processing of exactly what you're focusing on. But as soon as it's away from that of yeah, there's another guy over there that you've sort of only processing top down this very abstracted semantic description of the world around you. And so, that's what human beings are doing.[00:11:33] They're working with semantic abstractions and so. I think it is just the right representation. ‘cause we also have other goals we want to be able to do, real time worlds. So that means there's a limit to how much processing you can do and we want to do long-term planning and consistency. And again, that favors abstraction.[00:11:55] I mean, I guess there was actually a recent. Blog posts that [00:12:00] came out from our Friends of physical intelligence and, they were sort of heading in the same direction they were saying Oh, to the pay[00:12:06] swyx: pay model.[00:12:07] Chris Manning: Yeah. Yeah. To maintain a long term memory of what's happening in the world. So we can, do longer term we actually storing text of what is, been happening in the world.[00:12:19] Right. It is not such a successful strategy of trying to keep it all at a pixel level.[00:12:24] Vibhu: And yeah, I mean, you can see it in video models like that Temporal consistency. We're at a scale of train on, all the video data we have. We have it for maybe 30 seconds, a few minutes. That's not the same as a game state played for half an hour.[00:12:37] Right. I thought you guys break it down pretty well. You have a, you have a blog post about. Building multimodal worlds with an agent. I dunno if you guys wanna talk about this. This is one of the things I read, I[00:12:48] swyx: thought, yeah, it's the thing I talked about with the reasoning chain. Yeah.[00:12:51] Vibhu: So there's like different phases to this.[00:12:53] It seems like it's more of an agent, a scaffold, very different approach than just, type in a prompt and you, you don't have the same consistency. [00:13:00] It also, like, for people that are listening, I, I would highly recommend reading it. It breaks down the problem in a different light, right?[00:13:06] So like, what do you need to consider when you're talking about video, like world game models, right? How would, what do you need to consider? What are the factors? What are the elements? What's the state? So I don't know if you guys have stuff to talk about for this one.[00:13:19] Fan-yun Sun: Yeah. Actually, I wanted to add on a little bit Yeah.[00:13:22] On our previous point, which is just like, change topics so quickly. I, I do feel like sometimes people confuse like, oh, like we're taking an an, an method with abstraction. That means they don't believe in bitter lesson. Like that's just false, right? Like we are believed is a bitter lesson. But then I feel like the question that we always discuss is like, what is the right abstraction level today?[00:13:42] The analogy I like to make is like, let's just say we can encode and decode. Represent all of images, videos, audio and bytes. Then the most bitter lesson approached is to train a next byte prediction model as opposed to the next token prediction model where it's just like, okay, it's natively multimodal, can just, but it's like, yeah, like [00:14:00] to, to Chris's point, it's like the scale and computing you need to achieve that.[00:14:03] So that's why we always come back to like, okay, what is the most efficient way to do it? And reasoning models to the point of this blog post is a showcase of like, Hey, we're actually just like reasoning about the world and reasoning about. The aspects of the world that CAGR that matter for me to learn what I want to learn from this role model.[00:14:21] swyx: Yeah, it's like you're improving the en encoder of whatever you're, trying to model. And like a better representation would just represent the important things in less space. Yeah. Which would just be more efficient.[00:14:33] Fan-yun Sun: Yeah.[00:14:34] swyx: So yeah, I, I, I fully agree that it is not, antagonistic to, bitter lesson.[00:14:38] I do wanna wanna mention one more thing. Is there any philosophical differences with the JPA stuff that, Yun is working on? I gotta go there. You, you, you, you're, you're imagining like some latent abstraction. I'm like, okay, fine. Let's, let's talk about it, right? Like it's an elephant in the room.[00:14:52] Chris Manning: Yeah.[00:14:53] JEPA & Philosophical Differences with LeCun[00:14:53] Chris Manning: There are philosophical differences. Jan Lacoon is a dear friend of mine, but. [00:15:00] He has never appreciated the power of language in particular, or symbolic representations in general. Yarn is a very visual thinker. He always wants to claim that he thinks visually and there are no words, symbols, or math in his head.[00:15:21] Maybe that's true of yarn. It's certainly not the way I think. Um. But at any rate, the world according to yarn is the basic stuff of the, the world and of intelligence is visual and language is just. This low bit rate communication mechanism between humans and it doesn't have much other utility and it's far inferior to the high bit rate video, that comes into your eyes.[00:15:53] And I think he's fundamentally missing a number of important things [00:16:00] there. Think of this evolutionary argument looking at animals, right? That the closest analogies, the things with chimps, right? So chimpanzees, have fairly similar brains to human beings. They have great vision systems, they have great memory systems.[00:16:18] They've got, better memory than we do of short term memories. They can plan, they can build primitive tools that, humans. Massively ahead in what we understand about the world, what we can plan, what we can build. And essentially what took off for us was that humans managed to develop language and that gave a symbolic knowledge, representation, and reasoning level, which just, okay if this sort of vaulting of what could be done with the intelligence in brains.[00:16:59] So the [00:17:00] philosopher Dan de refers to language as a cognitive tool and argues that, humans unique among the creatures in the world have managed to build their own cognitive tools and language is the famous first example. But other things like, mathematics and programming languages are also cognitive tools.[00:17:21] They give you an ability to. Think in abstractions, in extended causal reasoning chains. And that allows you to do much more. And we use that for spatial representation and intelligence and planning and gameplay as well. So we believe, and this is, underlying the specific technologies that Moon Lake is making, that symbolic representations are powerful.[00:17:50] And you want to use that in your understanding of the visual world when you want a causal understanding, when you want to maintain long-term [00:18:00] consistency and prediction. And as I understand it, that's just not in ya Koon's worldview. So I think that's the fundamental philosophical difference. Then there's the specific model.[00:18:11] He's been advancing jpa, that's a reasonable. Research bed is a direction as to, to head for building out a model of the visual world. To my mind, it's sort of one reasonable research bed. It's not really established. It's the best one that everyone should be following,[00:18:32] swyx: at least developed at scale, at Meta.[00:18:34] But it's not just vision, right? Like, I mean, JPA is a, just joint admitting prediction can be applied to anything really. And people have done it. The argument is that there is a latent representation or that is probably more. Suited to the task, then why not let machines do it for us instead of predefining it at all?[00:18:50] And isn't something like a JPA shaped thing the right answer? And if not, why not?[00:18:55] Chris Manning: So I think there's a part of jpa that's right, which is [00:19:00] you do want to have a joint. Embedding that gives you a consistent model of the world. And Jan's argument is you can never get that from auto aggressive language models ‘cause they're sort of left to right churning out one token at a time.[00:19:22] I guess this is where we're the research arguments of the field, I'm not actually convinced that's right. ‘cause although the token production is this auto aggressive, process that's heading, left to right, I guess don't have to be left to right. But anyway, in sequence of tokens we could have right to left Arabic.[00:19:40] But although that's true, all of the weights of the model that are internal to the transformer, they are a joint model of the model's understanding of the world. And so I think you can think of the weights of the model as a form of. Joint representation, [00:20:00] and therefore it is plausible to think that could be the basis of a world model, which avoids, ya's objections.[00:20:10] swyx: I think I follow, and obviously that would touch on what Moon Lake eventually ends up doing as well. Right. Like, which it's hard to tell because you put out the end results, but we don't know the inputs that go into it. So it's, it's, that's something that we have to figure out over time.[00:20:25] Vibhu: Yeah. I mean, I guess this kind of breaks down some of the outputs. Do you wanna walk us through it?[00:20:31] Reasoning Traces & Interactive Worlds[00:20:31] Fan-yun Sun: Yeah. So this, this really just walks us through the reasoning traces of like, okay. So that just say, if we wanna build a world in this context, it's really just a game demo that, that shows the, the variety of interactions that this world model can build.[00:20:45] And yeah, it's really just a reasoning traces of like, okay it prompted to create a bowling game. Like how did it achieve what you saw? That level of causality, interaction and consistency, right? So yeah, this is almost just like a, an example of [00:21:00] like a reasoning traces. Very[00:21:01] swyx: detailed.[00:21:01] Fan-yun Sun: Yeah.[00:21:01] Vibhu: Very, very detailed.[00:21:02] You gotta you don't even realize it, right? Like when a video is generated, what happens when a ball strikes a pin, right? So first, like you, there's audio in that, like audio triggers happens, score increments, the world changes. Like pins have to start dropping. There's a timer that goes on. It's just like very similar to how now we're used to reasoning for language models.[00:21:20] There's a whole state of what happens. So geometry, physics, all this stuff. And then yeah, there's kind of that single prompt. So asset, ation all this stuff. It's like a, it's a nice view to see what's going on.[00:21:32] swyx: I think Sun is also too polite to point out that, both like Google's genie, demos as well as world Labs is marble, do not have interactive worlds.[00:21:41] Fan-yun Sun: That's the benefit of having a reasoning model, right? Like, because you can, you can say, oh, like maybe in this particular context, I want to learn how to bowl. And then you can say, okay, then what is it important when it comes to learning how to bowl? Okay, maybe it's like I need to understand the, the basic of like, physics and I want to throw it over [00:22:00] them.[00:22:00] I wanna know that when I, when it resets it's a new game. So I know that yeah, basically, you know to pick up the ball, you know that ball's gonna cause the pins to fall down. You know that what's important to this particular bowling game is to score and you know that the score corresponds to the number of pins that fell down.[00:22:19] So it's just like, if it's a model that sort of knows what it. Looks like, knows what a bowling game looks like, but doesn't actually allows you to practice over and over again and to understand that, oh, like what it takes to actually get a high score. Then it sort of doesn't actually allow you to learn what you set out to learn within the world model.[00:22:38] And I think this is really just one example of showing like the advantages of the approach that we're taking over most the, let's call it the zeitgeist, is today, when people talk about clinical role models,[00:22:51] Chris Manning: right? So it sort of seems like the question to ask when there's a world model is.[00:22:58] Can I not [00:23:00] only just wander around the world and look at the beautiful graphics, can I interact with the objects in the world and see the right consequences of actions?[00:23:11] Vibhu: And you also understand what the consequences would be if you do something right. So it's not just like, okay, there's one thing if I pick it up, something will happen.[00:23:19] But, there's 50 options and I know I can expect, I can infer what would happen if I do any of them. Right. So very different when you can actually see it play around with it.[00:23:28] swyx: There,[00:23:28] Beyond Unity: Cognitive Tools for World Building[00:23:31] swyx: there's two cheeky elements of that. I mean, the, the, the I guess, less ambitious one is, let's really establish for listeners, why is this fundamentally different than writing Unity code, right?[00:23:40] Like just creating a model to translate a prompt into Unity code[00:23:44] Fan-yun Sun: so there is an underlying physics engine. Yeah. In that sense, there's some overlapping things to Unity, but the way we think about it is like physics engine. Tools or code are cognitive tools like borrowing Chris's term, right? Like tools [00:24:00] that the model can employ as means to an end.[00:24:04] So today maybe you say, okay, in this particular context we care about physics, we care about the long-term causality consequences. Then yes, we deploy it, employ physics engine, and then maybe tomorrow we say, okay, we're we're training that. Just say drones where we only care about really fluid dynamics and the visual aspect of the world.[00:24:25] Then, then yeah, maybe we don't actually, the model actually doesn't have to use a physics engine. Or maybe it employs other types of representation or physics engine to achieve the task. So yes, writing code for Unity is sort of similar to a tool that our A model can employ, but our goal is for a model to take a representation conditioned reasoning.[00:24:46] Approach or process.[00:24:47] swyx: Yeah,[00:24:47] Fan-yun Sun: internally.[00:24:48] swyx: Yeah. Using these things as just like general two calls. Right. Which I think is very interesting. The other more ambitious one is, some kind of recursive element where it becomes multiplayer, right? Like here, there's a single player element, you're not [00:25:00] modeling any other people involved.[00:25:01] And that is a whole other thing.[00:25:04] Fan-yun Sun: But in fact, we can really do multiplayers. Oh yeah, okay. I haven't seen any double situations. So just actually just like prompt our, our model to say, Hey, like configure to multiplayer. Then it'll do like this. You'll be able to configure multiplayer[00:25:16] swyx: great[00:25:17] Fan-yun Sun: persistency database for you.[00:25:18] Easy. Yeah.[00:25:19] Vibhu: So what, what are like some of the current limitations in where we're at? So there's one approach of like, okay, scale up video predictors. Obviously there's data issues. With approaches like this, is it data constraints? What are like the next steps? Is it real time? Like, so there's one side of, write an agent to write Unity code, but okay, I want to be streaming a game real time.[00:25:38] I want to have characters being also like agent, but where, where do we kinda see this scaling up? Right?[00:25:44] Fan-yun Sun: Yeah, there's definitely a data constraint. Like the more data, the, the better. This reasoning model can almost basically act as humans to like operate a variety of tools and softwares to build whatever's necessary.[00:25:57] And then there's a sort [00:26:00] of fidelity constraint, which we're actually solving with another model, which we can talk about later. But it's like, it's not as easy to get to photorealism with the approach that we're taking. But we think there are better solutions to that, which is we can dive into later.[00:26:14] Later.[00:26:15] Vibhu: The one one thing you note here is it's a diffusion model, right? So there's, there's a few approaches, diffusion caution, splatting, yeah, so Ry diffusion model, you guys wanna[00:26:25] Fan-yun Sun: Yeah.[00:26:25] Vibhu: Introduce,[00:26:26] Fan-yun Sun: yeah, totally.[00:26:26] Rie: Neural Rendering & Skins for Worlds[00:26:26] Fan-yun Sun: So within our world modeling framework, we think there are two models that we train, right?[00:26:31] Like, there's the multimodal reasoning model that we just talked about that essentially handles. Mainly the, the causality, the persistency and logic determinism of the world. And then RY is our bet on saying, okay, like while all those model, can take care of all these things that we just talked about, it's limitations compared to existing, say, video models, is that it doesn't have as high of a pixel [00:27:00] ality right off the gate, right?[00:27:02] And EE is to say, Hey, we can actually take whatever persistent representation that we generate with our multimodal reasoning model and learn to restyle it into photo photorealistic styles or arbitrary styles you want. So this model is almost to say, Hey, I'm going to respect the persistency and interactivity of the world that you created, but my only job is to make sure that its pixel distribution is close to what we want.[00:27:29] Vibhu: Yeah.[00:27:30] swyx: Great example right there. You kept the KL divergence.[00:27:33] Fan-yun Sun: Oh. Where,[00:27:34] swyx: no, no. I mean this, this is a, a classic like, how you don't stray too far from the source material as you, you kept the kl, which is Oh yeah. Kind of cool. Yeah.[00:27:43] Fan-yun Sun: Yeah.[00:27:44] swyx: I mean, and the[00:27:44] Chris Manning: difference is, and I mean sun was pointing at this, where sort of saying it's in one way a more difficult path, but a better path that, typically the diffusion models are producing the whole scene and it looks lovely, [00:28:00] but there isn't spatial understanding behind it, which is allowing for the real time graphics gameplay, the spatial intelligence, understanding the consequences of worlds where this is, taking a path where it is assuming an abstracted semantic model of the world's state.[00:28:20] And then the diffusion model is then being used on top of that to produce the high quality graphics.[00:28:27] swyx: Is there an intended practical, or business use for this, or is it like a, like a demonstration of capabilities?[00:28:34] Fan-yun Sun: We actually believe that this is gonna be the next paradigm of rendering. So it's gonna replace how ra raizer, it's gonna replace DLSS today because it not only has these pixel prior that's learned from the world such that you can literally play any game in photo realistic styles, which is a lot of people's desire when they do GTA, right?[00:28:51] Like,[00:28:51] Vibhu: all the mods, all the people adding perfect lighting and all this.[00:28:54] swyx: So[00:28:54] Fan-yun Sun: skins[00:28:55] swyx: for worlds, let's call it[00:28:56] Fan-yun Sun: skins, let's call it skin for worlds. I,[00:28:58] Vibhu: it's also like, you can call it skin, you can call it [00:29:00] customization. You can play it how you want, right?[00:29:01] Fan-yun Sun: Yeah, exactly. And I think another thing that we really pointed out specific specifically in this blog is the programmability of it, right?[00:29:09] So what this means is that this render historically render is always a derivative of the game state, right? You're saying, oh, here's the game state, I'm rendering out a frame. But here I'm saying actually this render can be part of the gameplay loop. I can say something along the lines of, if upon getting 10.[00:29:26] Apples, I'm gonna, my weapon of choice, my bullet's gonna turn into apples. And that's, that's possible because we can say, we can basically dynamically have certain game state trigger the, the preconditions to the render such that the rendering is now part of the game loop too. One thing is to just say, okay, it's, it's, it's the appearance.[00:29:47] But the second thing is also to say there's these novel interactions that are possible because this render now has actually priors of the world.[00:29:57] swyx: It is up to the artist to figure out what to do with it.[00:29:59] Fan-yun Sun: It [00:30:00] is up to the creators. Yes.[00:30:01] swyx: Yeah.[00:30:01] Fan-yun Sun: And I also think that's actually another big argument that we're making and the reason that we're picking, taking the bet we're baking is that a lot of the times, whether it's for embody AI gaming, like you want a layer where human can inject their intentions.[00:30:15] So, for example, let's just say in the context of gaming, it's obviously like my creative intent, but maybe in the context of embodied ai, it's like, oh, like I take this foundational policy and I want to actually fine tune it to deploy in my house. So you want to almost say, inject, have a layer where human can say, oh, here's the distribution of things I want to create to achieve my goal.[00:30:35] And I think 3D graphics as it as it is today, is basic, the layer for people to say, Hey, what do I care about in this world? And it allows, basically human intent to be expressed in these worlds much more explicitly and distributionally as opposed to just saying, Hey, I'm gonna generate like, arbitrary.[00:30:54] And it's like just prompts,[00:30:55] swyx: it's one of those things where like, I think you, you're going to build up a series of models, right? [00:31:00] This is just one of, this is probably like the highest utility or heaviest, frequency one, I don't dunno what to call this. Where like you Yeah. You can immediately drop this in on any game and you don't need anything else that.[00:31:10] That you guys do. But, I, I could see, I could see that I think the, the human intent is something that people are not even used to because we're so used to static worlds or, worlds that just don't react, or, I don't know. It's, it, you're kind of blowing my mind right now with like, I'm, I wonder if you've talked to people at GDC Hmm.[00:31:27] And what are they gonna do with it?[00:31:30] Fan-yun Sun: Yeah. Now the stance that we take on this front is like, we're not gonna be more creative than our users to ship[00:31:35] swyx: it out.[00:31:35] Fan-yun Sun: Yeah. But we wanna make sure that we're building things in a way that really allows them to express their intent.[00:31:41] swyx: The thing that you said about, here's the distribution that I want.[00:31:45] I think text may be too low of a bandwidth to. To really demonstrate, because I, I, there, I'm, I'm probably just gonna want to drop in a bunch of, reference assets and then you can figure it out from[00:31:58] Vibhu: there. But you probably wanna do a, a mixture of [00:32:00] both, right? Like you throw in a few images. I wanted this style.[00:32:02] Yeah. I want it to look like this. So it, it's, it's a mixture, right?[00:32:05] Chris Manning: I, I think it's a mixture. I mean, yeah, I mean there's clearly a visual component of this, and it's not that, everything can be text. ‘cause of course you want to give a visual look, but there's also a massive amount of giving the overall picture of the look of the world and the behavior of things that you can express in a few words of text.[00:32:32] And it be very time consuming and difficult to do via visual means. So I think, yeah, you want a combination of both.[00:32:40] Evaluating World Models[00:32:40] Vibhu: So one question I kind of have is, how do we go about evaluating world models? So like, there's many axes, right? One is like, okay. I have preferences. How well do we adhere to prompts? One is the simulation.[00:32:50] One is like do things, is there core logic that's broken? So coming from we know how to evaluate diffusion, there's fidelity, there's [00:33:00] stuff like that. But what are some of the challenges that most people probably aren't thinking about?[00:33:04] Fan-yun Sun: Yeah, I think this is like a great question and probably one of the hardest questions in role models because like, I think it always comes back to what are you building this role model for?[00:33:13] And depending on your end goal and purpose, the evaluation should defer. So in the context of games, then the most direct way of measuring is how much behind are people actually spending in this world that you create? And if your goal is to say, for example, in the context that we just talked about, like, hey, deploying, deploying action in body, a agent, then your, your end.[00:33:33] Metric is then, okay, after training in these worlds that you generate how robust it is to when you actually deploy to the target environment. But then, it's, it's hard to measure these end metrics. So today people have like these proxy metrics that I call that basically try to measure what we really care about, which is the end metrics, but then frankly it's different for every use case.[00:33:57] Yeah,[00:33:57] Vibhu: which seems like quite a challenge, right? Like in [00:34:00] in language models or video models. Image models, your benchmarks are proxies, right? People aren't actually asking instruction, following tool use questions. They're proxies of how well it will do downstream. But for this, so like, should teams, should companies have their own individual benchmarks outside of games?[00:34:16] If you think of stuff like, okay, video production, movies, stuff like that, that also want to use world models. Should, should they sort of internalize like. Their own proxy. Is this something you guys do? Where, where does that connect[00:34:28] Chris Manning: go? Yeah, I think this whole space is extremely difficult as things are emerging now.[00:34:35] And I mean, it's not only for world models, I think it's for everything including text-based models, right? ‘cause in the early days it seemed very easy to have good benchmarks ‘cause we could do things like question answering benchmarks and could you answer the question based on these documents and the various other kinds of, do pieces of logical reasoning or math.[00:34:58] But again, these are sort of. [00:35:00] And there were sort of visual equivalents of things like object recognition, right? For these small component tasks. These days so much of what people are wanting to do also with language models is nothing like that, right? You're wanting to, have an interaction with the language model and get some recommendations about which backpack would be best for you for your trip in Europe next month.[00:35:25] And it's not the same kind of thing, right? And it's not so easy to come up with a benchmark as to does this large language model give you an effective interaction for guiding you in a good way for shopping, right? So, and it's the same problem with these world models. So if we take the game design case, well success is that a game designer can.[00:35:57] Produce what they are [00:36:00] imagining in a reasonable amount of time. And that's really the kind of macro task. That's a very hard thing to turn into a benchmark and I think a lot of this is actually going to turn into people walking, walking with their feet. Right? I mean, I guess that's what's happening, at the large language model level, right?[00:36:23] When people are choosing to use, GPT five or Gemini or clawed, individuals are trying out these different models and deciding, oh, I like the kind of answers that GT five gives me, or no, I feel like I get more accurate detail from Claude, right?[00:36:43] Vibhu: It's a lot of[00:36:43] Chris Manning: vitech, a lot of people just using it.[00:36:45] It's vibe checking. I realize that, but it's actually whether. People feel it's giving them utility in what they want. Right.[00:36:52] Vibhu: And the the interesting thing there is like a lot of people prefer the visual, right? This looks pretty, which is not the objective of what this is [00:37:00] for, right? It's if a, if a game designer is working on something, they care about the game engine, right?[00:37:04] The state, it's, it can look whatever. You can fix that up later. Or you can have a really good game state and you can quickly edit it to 20. 20 different versions, like Keep State,[00:37:14] Chris Manning: right?[00:37:14] Vibhu: So[00:37:14] Chris Manning: that's a really important distinction, for and for speaking to Moon Lake strength, right? So, yeah, great visuals are lovely to look at for a few seconds, but gains are really all about the concept, the game play.[00:37:33] And a lot of the time that doesn't actually even require great visuals. I mean, there are just lots of very successful games which have relatively primitive visuals, and there are other games where people have spent millions producing photo realistic, visuals, and the game sucks, right? So, keeping those two axes apart is really important in thinking about what's important in a [00:38:00] world model for different uses.[00:38:02] swyx: This conversation is reminding me of some game review and fiction discussions I've, had in my sort of non-AI related life. Some, for some people might know Brandon Sanderson, who's a very famous, fiction author, had, is is a big game reviewer. And he, he's a big fan of video games where you change one thing about a normal what you might assume about, about the world.[00:38:22] For example, Baba is you, I don't know if you might have come across that, where like the rules change as you play the game. And also like where, you can do things like reverse time selectively or like change gravity selectively. And I think this is also reminds, reminds me of other kinds of world models that are created by authors.[00:38:38] Where Ted Chang is, is my typical example where he'll take the world that, you know today, but change one thing about it and, but then create a consistent world based on that. Which is long-winded answer of me to, of. For me to say is it's it easy to create alternative roles that don't exist, but you change one thing and then let's, let's run a whole bunch of people through it to see if it works.[00:38:58] Chris Manning: My first dance will [00:39:00] be, that seems a lot easier and more conceivable to do using Techn technology like Moon Lakes than with some of the other world models out there, where the sun can actually make it happen. I'll let him give a second answer.[00:39:15] swyx: If I guess for you, you're constrained by the game engine tool, right?[00:39:18] Like at the end of the day, that's the, that's the thought, partner that you have. If I ask for something where like, if it never is allowed to reverse time or if gravity only ever works one way, then well that's it. But sometimes gravity might change,[00:39:33] Fan-yun Sun: but it's a lot easier to change with code as opposed to a model that is learned primarily on data of.[00:39:42] Real world and virtual worlds that are, I guess, like for example, junior, like there's actually trained on a lot of real world data and a lot of virtual gaming data, and it's hard to say maybe it's easier to say, okay, I wanna change the visuals in like the time period of, of the world. Like, you can't change gravity, for [00:40:00] example.[00:40:00] Vibhu: I feel like you can to light bounds, right? Everything comes down to like, code is a better way to execute it, but the models aren't that diverse and creative, right? You can say, okay, make gravity slower. It can do that, but it's limited to your representation of how you text it out, right? Like they're, they're only gonna do a few iterations, whereas programmatically, if there's a game engine under the hood, you can kind of go wild, right?[00:40:22] So one of the, I dunno, one of the limitations of most models is that they're very overtrained to one style. Right. And extracting diversity is pretty difficult. At least that's something we've seen.[00:40:35] Fan-yun Sun: I mean, are there examples you have in mind where you Existing models? Yeah. Like it would be easier to do that's not using code.[00:40:43] Certain types of creative intent or like transition state transitions,[00:40:47] swyx: Clipping, other models, other wo models are very good at clipping through things. Clipping my, my, my legs clipping through a rock because it's, it's just, it's just bad. [00:41:00] Like, you would have to struggle very hard with your stuff to actually make that happen.[00:41:04] Which I think is maybe a topic that you actually prepared on, Gian Splatting versus, the other stuff.[00:41:09] Vibhu: Yeah. Yeah. It's just for those not super familiar, right? There's a, there's gian splatting, there is diffusion. Like what works, what scales up. I feel like in February when Soro one came out the blog post was literally titled like,[00:41:21] swyx: you bring it up.[00:41:22] You never know.[00:41:23] Vibhu: World, world, video generation models are world simulators. It's super bitter lesson pilled. Yeah, emer, a lot of it is emergence, right? So, not to go through their blog post, basically their whole thing was as you scale up all this consistency, all this stuff just kind of solves, it's a very simple premise, right?[00:41:41] They just scaled up, diffusion, and from there, this is, this is Feb 2024, how much can we, it's already been two years, which is basically five years. How much more in AI time do we need to just scale up or, or do we hit a data cap? But I think we already talked about this a lot, right? Like this is back to the beginning discussion of what's [00:42:00] appropriate for the time.[00:42:01] And that seems like your approach, right?[00:42:03] Fan-yun Sun: Yeah. The point I'm trying to make is that they're very many, many different types of world simulators and like having a world simulator that can produce pixel coherency is very, very useful for games and, marketing and all these things, but it's not as useful as people think when it comes to causal reasoning.[00:42:25] When it comes to embodied ai. Yeah, like it this title is true. We're not saying that it's, it's like, not a great world simulator, but actually in the blog that we, we, we, we wrote, the bet is more so that there are gonna be disproportionately large share of value of real world tasks or, and virtual tasks where high resolution pixel fidelity is not needed.[00:42:47] Yes. Video models have their values.[00:42:50] swyx: Yeah. This is at the absolute limit of my physics understanding, but one example that comes to mind is basically having to solve like ba the equivalent of a three [00:43:00] body problem in a deterministic Well, where the video models, which is approximated good enough. Yeah.[00:43:08] Right. Like there's, there's some point at which your approach kind of runs into like the you now have to simulate the world. Please, thank you very much. And like you're trying to do that, but only to the extent that the game engine lets you and like game engines cannot do some things.[00:43:23] Fan-yun Sun: Yeah, no, I mean, I think the interesting or more technical question here actually is where do you draw the boundary between.[00:43:32] What's handled with, let's say, diffusion prior and what, when? What's handled with symbolic priors?[00:43:38] swyx: Yes.[00:43:38] Fan-yun Sun: Okay.[00:43:38] swyx: Okay.[00:43:39] Fan-yun Sun: Right. Let's go there. Because this, this boundary can actually be fluid. Like I think like maybe what you're trying to get at is like, okay, people are saying pixel prior, everything. But what we're saying is, okay, there's a boundary that we draw where this is where we think provides the most economical value for the domains and things that we care about today.[00:43:59] [00:44:00] And I actually do think, and it's something that we do internally all the time, which is like, okay, given new equations that we learn or new elements of the world and that we, we learn, or maybe some other knowledge that we acquire in the process of developing the models. Should we still be maintaining this line exactly as it is today?[00:44:22] Or should we move it a little bit left or a little bit right? Right. Like sometimes that we realize that, oh, like maybe customers or, or folks like want certain things that are better handled with preop pryor as opposed to, symbolic prior than,[00:44:34] swyx: yeah. Your, your skin thing is a, is a example moving it, right.[00:44:37] Yeah.[00:44:37] Or left. Yeah,[00:44:37] Fan-yun Sun: exactly.[00:44:38] swyx: I dunno what the, the left right is.[00:44:39] Fan-yun Sun: Yeah, yeah, yeah. No the, the model.[00:44:42] swyx: Yes.[00:44:42] Fan-yun Sun: Actually we have a few iterations of them. They're actually at slightly different[00:44:45] swyx: I know boundaries. You should, you should do that. That's a cool dimension to show.[00:44:49] Fan-yun Sun: Yeah.[00:44:50] swyx: Is quantum mechanics the diffusion prior of our world?[00:44:55] Right. It's like that's the boundary of classical mechanics versus quantum. Right? Like, that's it. At one [00:45:00] point God plays dice and the other point doesn't.[00:45:02] Fan-yun Sun: I dunno if Chris, you wanna say it, but I think, I think generally I feel like physics is better with symbol P priors.[00:45:08] Chris Manning: Even quantum physics.[00:45:09] Fan-yun Sun: Even quantum physics.[00:45:11] swyx: Yeah. This is starts against to, MLST territory is, is what I call it, where, he, he likes to get philosophical. We, we we're quite friendly.[00:45:18] Vibhu: I mean, we need to get, we need to get singularity. I heard some of that.[00:45:23] swyx: No, no, I think that is actually really helpful and man, I just want you to productize this like, as a product guy, I'm just like, oh, also[00:45:32] Vibhu: a gamer, I[00:45:33] swyx: wanna, it's like a researcher, like, it's cool.[00:45:35] Like this is a, the theoretical, like you have a very good, I don't know, like the way of thinking about these things, but I just wanna see you like, express it. I do think like your fundamentally things when, when you leave open new tools, like, okay, use, use human intent to incorporate it into how you render.[00:45:52] Artists are gonna have to take like two to three years to figure out what to do with this. And you just don't know.[00:45:57] Chris Manning: Right. But I think, this is, [00:46:00] gives a much more approachable and controllable world for the society, which is the beauty, the beauty of, NLP, that that will enable it to be adopted and used.[00:46:10] And we are very hopeful about that. Yeah,[00:46:13] Fan-yun Sun: yeah. Yeah. I mean, we are, we are very focused actually on commercialization in the sense that like we do, we do really believe in the data flywheel app approach. Yeah. Where, we put this in the hands of the creators and the users and then they will teach us when, what capability our model should improve.[00:46:27] And that's why we are, we are actually, like products and beta[00:46:31] swyx: Yeah. Focusing on gaming. What, what's like the adjacent thing to gaming[00:46:34] Fan-yun Sun: embody adjacent, basically. So maybe we can, we can I'll maybe start with where we see the platform in three years. Yeah. Which is like, okay. The users would tell us what they want to achieve.[00:46:45] The end goal could be, Hey, I just, I wanna make something to teach my kids the value of humility. Or it could be, Hey, I wanna fine tune my, drones to be really good at rescue situations. I could be vacuum robots. I want to like train [00:47:00] my manipulation or like vacuum robot to be very robust to my office, right?[00:47:04] But it's like, whatever it is, scenario robust to[00:47:06] swyx: my office[00:47:07] Fan-yun Sun: or like navigate very robustly in my office. But then it's like, whatever end goal that you want, our role model will say, okay, given what you want to achieve, let me generate a distribution of environments such that I can train and evaluate whatever it is you want.[00:47:24] Yeah. Right. Maybe for the purpose of games, it's just the end simulation and that's the end product for certain policies. It's like I can train it within these environments and then help you see where your policy is failing or not. Yeah. And then, so I think,[00:47:37] swyx: so in that case, much more of a training tool.[00:47:40] Than in other training[00:47:41] Vibhu: evaluation? Both. Right?[00:47:43] swyx: Sure. Same. Same thing.[00:47:43] Fan-yun Sun: Yeah, same thing. I think it's just this role model that allows people to train any policy that can act in any multimodal environments.[00:47:51] swyx: Would it be harder to reward hack? Is there an angle here where it is harder to reward hack? Like it's just, I'll just put it generally because I think that's a, that's obviously a key [00:48:00] problem that a lot of people face when in training agents in these environments, and I don't know, can you solve it?[00:48:07] Chris Manning: I think not necessarily. To the extent that there's a mis specified reward that. It seems like it could be hacked in a more symbolic world or in a more pixel based world. I dunno if Sun's got any thoughts, but I don't think that's really being solved.[00:48:26] swyx: The other thing that comes to mind is just you could just build a better sawa as a video generator model, right?[00:48:31] Because then you, you would move the diffusion, side a bit more further to the right. I think if I got the directionality correct. And that's it.[00:48:40] Vibhu: It's better on domains, right? Like on consistency over now, or for sure it exists versus something doesn't, right.[00:48:46] Chris Manning: So[00:48:46] swyx: yeah. Yeah. Is[00:48:49] Vibhu: is a question more like, like[00:48:51] swyx: I'm just riffing on like, how do you, what can you build, you know?[00:48:54] Oh, with the stuff that you have. I do think that the minor, the academic does go immediately to training [00:49:00] and in eval evaluation, but like art tends to take unusual directions. Like you might end up,[00:49:06] Chris Manning: okay. Yeah. But the question is, can you use this piece of software to develop compelling gameplay and. I don't think you can take SOAR and produce compelling gameplay, right?[00:49:19] If you want to have a world that you can wander around in a bit, you are good. But what are your abilities to have gameplay mechanics implemented the way you'd like them to be and to have things stay, with the long-term history of your gameplay that influences future actions. I think there's just nothing there for that.[00:49:39] swyx: Yeah, I do tend to agree. I, I'm just trying to sort of test the boundaries. I would also make the observation that as AAA games industry has developed the line between what is a movie and what is a game has blurred. And you, you, you do end up basically producing a two hour movie as part of your game.[00:49:57] Fan-yun Sun: No, honestly, there, there's so many actually [00:50:00] applications in adjacent markets that our world model can go into. Yeah. But yeah, it, it's sort of fun to riff, riff on. Although on the execution side, we we, we need to stay focused with like, okay, what are the capabilities we want to unlock over time?[00:50:11] And there's a roadmap for that. But yeah, if we're just riffing on sort of like the possibilities, I feel like, whether it's endless Yeah, it's like classic[00:50:18] swyx: and the embedding for a possibility and endless in my mind, it's very close. Yeah. I do wanna, focus on one, like weird choice. I, I don't know if it's weird.[00:50:28] Maybe I'm, I got something here. Audio, right? You could have just said no audio And audio in my mind has a lot of recursion, whereas in video you can just do recasting and that's much computationally much simpler. Audio just seems way harder. I don't know if you wanna just comment on just the special 3D audio.[00:50:46] Problem. Did you really have to do it? I guess you do to be immersive, but like a lot of people do treat it as like, well, you just stick a, a tt S model on top of[00:50:57] Vibhu: Well, there's a lot more to game audio than [00:51:00] just speech. Right. It's not just[00:51:01] swyx: tts. Yeah. Tts. S Fxt, GM Spatial in my mind Echoes[00:51:06] Chris Manning: Yeah.[00:51:06] swyx: And reflections.[00:51:07] And I, I don't even know what's, what else? I don't know what, what other problems in this space.[00:51:13] Fan-yun Sun: Yeah, I think this point like the, it's sort of a more, more pointing to the benefits of using an game engine as a tool that's available to the model, right? Because like part of the spatial audio is from the code that is underlying the simulation.[00:51:32] And while we do give our model access to other types of audio models as. Tools.[00:51:39] swyx: None of them would be spatial, I think.[00:51:41] Fan-yun Sun: But that's exactly sort of more 0.2. We're giving our model an abstraction or a suite of tools such that it's able to achieve that. And you can argue that sort of spatial is like a, like a emergence out of the, the tools that we and abstraction that we provide to the agents.[00:51:59] And I think that's the beauty of [00:52:00] this, this, this approach is like there's a lot of things kind of like how human's built technology and they're like Lego blocks that build on top of each other. And it's the same thing here. There's gonna be things that sort of just sort of emerges from being able to put these things together in like combinatorially interesting ways,[00:52:14] Chris Manning: right?[00:52:15] So this integrated audio model exploits the understanding and semantics of the Moon Lake world, right? And whereas in general for the Gen AI video models. There's no actual integration across to audio at all, right? That someone might stick some music or stick a soundscape or whatever else on top of their video.[00:52:44] So it's not a silent video, but they're in no way connected into a consistent world model. And there's nothing that's okay. An action is happening in the video. Therefore there should be a sound that's [00:53:00] coming from this part of the visual field.[00:53:03] swyx: Yeah.[00:53:03] Vibhu: Is that different than Sora too? Does it not have audio?[00:53:06] Not to say it's not like[00:53:08] swyx: amazing[00:53:08] Vibhu: isn't a spatial[00:53:09] swyx: audio.[00:53:09] Vibhu: It doesn't,[00:53:10] swyx: no. I've played around it with it enough. It just sounds like someone put an 11 laps voice on top of it and just tried to do the lip sync.[00:53:18] Vibhu: Oh, yeah. I've seen, okay. Generate a dog at the beach and reactions to big wave and move[00:53:23] swyx: around.[00:53:23] It's definitely like, so have the dog, have the dog move away from camera and see if the, the song goes down. It doesn't. ‘Cause they don't have facial audio.[00:53:32] Fan-yun Sun: We do want to basically like we, our moral model, like the one we're training is basically towards the goal of having a combined latent representation across all these different modalities.[00:53:42] Right? Such that it can like reason across these different modalities. So for example, if I close my eyes and like you play a video, you play a sound of like a car skidding away from me. I almost can like, visually extrapolate that trajectory in my mind. And I think that type of capability, we want our model to be able to reason, right?[00:53:59] And that's the reason that [00:54:00] we're sort of taking this multimodal reasoning approach. It's like we want this combine late in space that can[00:54:05] swyx: Yeah. Oh, you said late in space. We like that. Here we have to play the, the bell Every time that someone says late in space, no, you gotta train daredevil one. Where you, you, you, it's only audio, but you have to work out.[00:54:15] Where everything is.[00:54:19] Cool. I I think that that was, that was about it for our Moon Lake coverage. I do think that we have like a couple of, Chris Madden questions on, on IR and, just any, any other sort of attention topics or n NLP topics.[00:54:31] Vibhu: Okay.[00:54:31] swyx: Go ahead.[00:54:32] Chris Manning's Journey: From NLP to World Models[00:54:32] Vibhu: Well, no, I mean, yeah, it's just fun. We talked a bit about how you guys met, but you basically, you, you were like the godfather of NLP per se, right?[00:54:39] You spent the whole career from early embeddings, early early attention. You did 2015 attention for machine translation, everything. You, you had information retrieval, so RAG before rag, we just wanna shout that out and admire a lot of that. Right? So what prompted the switch over to world models?[00:54:56] How, how'd all that come about?[00:54:58] Chris Manning: To some answer it [00:55:00] is, the enthusiasms and creativity of students, but there's a bit of a history there, right? So, yeah. So clearly most of my career has been doing stuff with language and how I got into research was thinking, ah, this is just so amazing how humans can produce speech and understand each other in real time.[00:55:21] And somehow they managed to learn languages from their kids. How could this possibly happen? And so, yeah, starting off I was very focused on language, but as it sort of got into the 2000 and tens, I started, going, I'd been working on question answering, and then I started to get, interest in visual question answering.[00:55:42] And that was an area where it was very noticeable. That the visual understanding was bad. Right. These were the days when like, it sort of seemed like there's almost no visual [00:56:00] understanding. You were just getting answers that came from priors. So, if you asked how many people are sitting at the table, it'd always answer two regardless of how many, how many people you could see in the picture.[00:56:11] And so it seemed like, oh, these models actually aren't able to get semantic information outta

WEBINAR LINK:https://shawnmoore.clickfunnels.com/optiniyvvg89sWant to learn more about Vodyssey or start your STR journey. Book a call here:https://meetings.hubspot.com/vodysseystrategysession/booknow?utm_source=vodysseycom&uuid=80fb7859-b8f4-40d1-a31d-15a5caa687b7FOLLOW US:https://www.instagram.com/vodysseyshawnmoorehttps://www.facebook.com/vodysseyshawnmoore/https://www.linkedin.com/company/str-financial-freedomhttps://www.tiktok.com/@vodysseyshawnmooreCONTACT US:support@vodyssey.comChapters00:00:00 Intro00:02:47 Spring Break Travel Trends and Media Perception00:06:58 Consumer Resilience and Travel Demand Analysis00:12:04 Strategies for Short-Term Rental Success00:19:12 Webinars and Resources for Investors00:21:14 Maximizing Bookings Through Flexible Pricing00:22:18 Vetting Guests: Balancing Risk and Opportunity00:24:05 The Role of Price Optimization Tools00:25:31 Maintaining House Rules During Peak Seasons00:27:03 Attracting and Retaining Customers00:30:00 The Importance of Repeat Customers00:33:51 Maximizing Revenue During Peak Seasons00:37:19 Creating Memorable Experiences with Pattern InterruptsSOURCES:1) https://www.usatoday.com/story/travel/news/2026/03/09/airport-long-security-lines-tsa-staffing-partial-shutdown/89062134007/2) https://www.thebusinessresearchcompany.com/report/car-rental-global-market-report#:~:text=What%20Is%20The%20Car%20Rental,(CAGR)%20of%204.8%25.3) https://newsroom.acg.aaa.com/aaa-2026-vacation-intentions-surge/#4) https://www.foxnews.com/travel/airlines-prepare-record-breaking-spring-break-travel-surge-americans-prioritize-experiences5) https://www.usinflationcalculator.com/inflation/airfare-inflation/6) https://www.disneytouristblog.com/florida-reports-record-143-million-visitors-orlando-airport-hits-58-million-as-disney-world-drops/

Can 4 Volts of Electricity Replace 60 Bars of Pressure in Seawater Desalination? ilion Water Technologies is a 2025 spinout from the Physics Laboratory of the École Normale Supérieure in Paris. Their VIRO (Voltage-Induced Reverse Osmosis) technology claims to replace the high-pressure pump train in seawater desalination with an alternating electric field applied to engineered composite membranes, operating at atmospheric pressure.

Derek's guest this week is Whitney Johnson: Innovation and disruption theorist, keynote speaker, best-selling author, executive and performance coach.Whitney shares her unique journey and key concepts about how to motivate your employees from her book "Build an A Team: Play to Their Strengths and Lead Them Up the Learning Curve".Whitney Johnson was named one of the world's fifty most influential management thinkers by Thinkers50 in 2017.She is the author of the bestselling Build an A Team (Harvard Business Press, 2018), a Financial Times and CEO Read, Book of the Month, and the critically-acclaimed Disrupt Yourself: Putting the Power of Disruptive Innovation to Work (2015). Publisher's Weekly described it as "savvy...often counter-intuitive...superb" while the Boston Globe called it the "'What Color is Your Parachute?' career guide for the entrepreneurial age."Through writing, speaking, consulting and coaching, Whitney works with leaders to retain their top talent, to build an A team, and to help them earn the gold star–be a boss people love.She formerly was the co-founder of the Disruptive Innovation Fund with Harvard's Clayton Christensen, where they invested in and led the $8 million seed round for Korea's Coupang, currently valued at $5+ billion. She was involved in fund formation, capital raising, and the development of the fund's strategy. During her tenure, the CAGR of the Fund was 11.98% v. 1.22% for the S&P 500.She is also formerly an award-winning Wall Street analyst. She was an Institutional Investor-ranked equity research analyst for eight consecutive years, and was rated by Starmine as a superior stock-picker. As an equity analyst, stocks under coverage included America Movil (NYSE: AMX), Televisa (NYSE: TV) and Telmex (NYSE: TMX), which accounted for roughly 40% of Mexico's market capitalization.Whitney is a frequent contributor for the Harvard Business Review, she has over 1.5 million followers on Linkedin, was named one of LinkedIn's Top Voices in the Influencer category for 2018, and her LinkedIn course The Fundamentals of Entrepreneurship has 1 million+ views.She is a member of the original cohort of Marshall Goldsmith's #100 coaches.Learn more at https://whitneyjohnson.com/Business Leadership Series Intro and Outro music provided by Just Off Turner: https://music.apple.com/za/album/the-long-walk-back/268386576

Zainulabedin Shah is a visionary leader with over 18 years of expertise in data strategy, analytics, and AI, renowned for transforming businesses and driving significant growth. As the CEO and Co-Founder of Zeed, he empowers companies to unlock their potential through cutting-edge data solutions. His accomplishments include modernizing data and AI platforms for a $5B global company, resulting in $2M in annual savings, and leading strategy at First Republic Bank, driving a 42% year-over-year sales increase. He also scaled a $2M auto startup into a $70M business with a 143% CAGR, despite having no prior industry experience. As CEO of Zeed, Zainulabedin continues to leverage his vast experience, helping businesses harness the power of data to drive strategic priorities and achieve scalable growth. His expertise extends to executing complex M&A integrations, developing innovative business models, and fostering data-driven cultures. As a podcast guest, Zainulabedin brings valuable insights into data strategy, digital transformation, and leadership, offering a compelling perspective for audiences seeking to understand the intersection of technology and business growth. Connect with Jon Dwoskin: Twitter: @jdwoskin Facebook: https://www.facebook.com/jonathan.dwoskin Instagram: https://www.instagram.com/thejondwoskinexperience/ Website: https://jondwoskin.com/LinkedIn: https://www.linkedin.com/in/jondwoskin/ Email: jon@jondwoskin.com Get Jon's Book: The Think Big Movement: Grow your business big. Very Big!   Connect with Zainulabedin Shah:Linkedin: https://www.linkedin.com/in/zainulabedinshah/                                                                                       *E – explicit language may be used in this podcast.

¡No te quedes atrás! Fireside chat en Real Estate Tech Market 2026 (30-31 julio, online, español/inglés). Regístrate YA: https://realestatetechmarket.com¡El retail se bifurca, pero en Latinoamérica explota! Mientras el e-commerce crece a USD 215B en 2026, el brick-and-mortar se reinventa como espacios que cautivan y conectan con phygital, experiencias inmersivas y live shopping como estrella: mercado regional USD 4.69B en 2025 → USD 32B en 2033 (CAGR 27.2%). Tasas de conversión hasta 30% (10x más que e-commerce tradicional), 63% de usuarios quieren comprar más así y 64% asiste streams mensuales.En este episodio corto: tendencias CBRE, PwC, McKinsey + live shopping en Brasil, México, Colombia.

Send a textJoin Tim Gerdeman, Vice Chair & Co-Founder and Chief Marketing Officer at WTR, and Peter Gastreich, Senior Energy Transition and Sustainability Analyst, as they break down WTR's latest deep-dive report on Gevo including financial forecasts. Gevo is a leading renewable fuels and chemicals company focused on producing low-carbon alternatives to fossil fuels, including low-carbon ethanol, sustainable aviation fuel (SAF), and renewable natural gas. Its integrated carbon strategy features biogenic CO₂ capture and permanent storage, digital carbon tracking via the Verity platform, and modular Alcohol-to-Jet (ATJ) technology. The North Dakota Red Trail acquisition added a profitable ethanol plant, a large and scalable carbon capture system, and prime location for ATJ (SAF) expansion. In the longer-term, third-party CCS and ATJ-30 technology sales are significant drivers. 

My 4 Factor Dividend Growth Strategy is an alternative to SCHD that has thus far generated a strong 16.07% CAGR. But this return could have been even better had I not made the 4 mistakes I'd like to share with you today.Quality At A Fair Price: https://qualityatafairprice.substack.com/Patreon: https://www.patreon.com/LongacresFinanceDisclaimer: This video is intended for entertainment purposes only and should not be taken as investment advice.#dividendincome #dividends #schd #dividendgrowthinvesting

In this episode, the hosts break down a $34M revenue heavy equipment dealership in Western Canada doing $9.2M in EBITDA — a high‑growth, high‑margin, possibly monopolistic business — and question why it's for sale, if it's truly a “license to print money,” and whether a U.S. buyer could even touch it.Business Listing – https://dashboard.dealforce.com/deals/profiles/profile66806.pdfWelcome to Acquisitions Anonymous – the #1 podcast for small business M&A. Every week, we break down businesses for sale and talk about buying, operating, and growing them.

FlyLow was founded by Dan Abrams and Greg Steen twenty years ago to create backcountry ski pants that could hold up to the demands of the sport and terrain. They continued to refine and expand the product line, as their own proficiencies were expanding and refining. Dan joins us this week to share stories and lessons from the journey so far. Show Notes: FlyLow Gear: https://flylowgear.com/ Dan Abrams: https://www.linkedin.com/in/dan-abrams-4287775/ Megan Michaelson: https://www.linkedin.com/in/meganmichelson/ Greg Steen: https://www.linkedin.com/in/greg-steen-7419041b/ Alibaba: https://www.alibaba.com/ Cactus Outdoor: https://cactusoutdoor.co.nz/ CAGR (term): https://en.wikipedia.org/wiki/Compound_annual_growth_rate Hot Tub Short (FlyLow): https://flylowgear.com/products/hot-tub-short Anderson Shirt (FlyLow): https://flylowgear.com/products/anderson-shirt Irwin Fleece (FlyLow): https://flylowgear.com/products/irwin-fleece-shirt BPC - Brand, Product, Content: Moment Skis: https://www.momentskis.com/ Momentous Creatine: https://crrnt.app/MOME/P1ZgGplx Todd Snyder: https://www.toddsnyder.com/ Join us on LinkedIn: https://www.linkedin.com/company/second-nature-media Meet us on Slack: https://www.launchpass.com/second-nature Follow us on Instagram: https://www.instagram.com/secondnature.media Subscribe to our newsletter: https://www.secondnature.media Subscribe to the YouTube channel: https://www.youtube.com/@secondnaturemedia

Brian Nowak: Welcome to Thoughts on the Market. I'm Brian Nowak, Morgan Stanley's Head of U.S. Internet Research. Andrew Percoco: And I'm Andrew Percoco, Head of North America Autos and Shared Mobility Research. Brian Nowak: Today we're going to talk about why we think 2026 could be a game changer and a point of inflection for autonomous vehicles and autonomous driving. It's Thursday, January 8th at 10am in New York. So, Andrew, let's get started. Have you ridden an autonomous car before? Andrew Percoco: Yeah, absolutely. Took a few in L.A., took one in San Francisco not too long ago. Pretty seamless and interesting experience to say the least. Brian Nowak: Any accidents or awkward left turns? Or did you feel pretty comfortable the whole time? Andrew Percoco: No, I felt pretty comfortable the whole time. No edge cases, no issues. So, all five star reviews for me. Brian Nowak: Andrew, we think your answer is going to be a lot more common as we go throughout 2026. As autonomous availability scales throughout more and more cities. Things are changing quickly. And we kind of look at our model on a city-by-city basis. We think that overall availability for autonomous driving in the U.S. is going to go from about 15 percent of the urban population at the end of 2025 to over 30 percent of the urban population by year end 2026. Andrew Percoco: Yeah, totally agree. Brian, I'm just curious. Like maybe layout for us, you know, what you're expecting for 2026 in more detail in terms of city rollouts, players involved and what we should be watching for throughout the next, you know, nine to 12 months. Brian Nowak: We have multiple new cities across the United States where we expect Waymo, Tesla, Zoox, and others to expand their fleet, expand autonomous driving availability, and ultimately make the product a lot more available and commonplace for people. There are also new potential edge cases that we think we're going to see. We're going to have our first snow cities with Waymo expected to launch in Washington, D.C.; potentially in Colorado, potentially in Michigan. So, we could have proof of concept that autonomous driving can also work in snow throughout [20]26 and into 2027 as well. So, in all, we think as we sit here at the start of [20]26, one year from now, there's going to be a lot more people who are going to say: I'm using an autonomous car to drive me around in my everyday practice. Andrew Percoco: Yeah, that makes a lot of sense. And I guess, what do you think the drivers are to get us there, right? There's also some concerns about safety, adoption, you know, cost structure. What are the main drivers that really make this growth algorithm work and really scales the robotaxi business for some of the key players? Brian Nowak: Part of it is regulatory. You know, we are still in a situation where we are dealing with state-by-state regulatory approvals needed for these autonomous vehicles and autonomous fleets to be built. We'll see if that changes, but for now, it's state by state regulation. After that, it comes down to technology, and each of the platforms needs to prove that their autonomous offerings are significantly safer than human driving. That is also linked to regulatory approval. And so, when we think about fleets becoming safer, proving that they can drive people more miles without having an accident than even a human can – we think about the autonomous players then scaling up their fleets. To make the cars and fleets available to more people. That is sort of the flywheel that we think is going to play out throughout 2026. The other part that we're very focused on across all the players from Waymo to Tesla to Zoox and others is the cost of the cars. And there is a big difference between the cost of a Waymo per mile versus the cost of a Tesla per mile. And we think one of the tension points, Andrew, that you can, you can talk about a little bit here, is the difference in the safety data and what we see on Tesla as of now versus Waymo – versus the cost advantage that Tesla has. So, talk about the cost advantage that Tesla has through all this as of right now. Andrew Percoco: Yeah, definitely. So, you know, as you mentioned, Tesla today has a very clear cost advantage over many of the robotaxi peers that they're competing with. A lot of that's driven by their vertical integration, and their sensor suite, right? So, their vehicle, the cost of their vehicle is – call it $35,000. You've got the camera only sensor approach. So, you don't have lidar, expensive lidar, and radar in the vehicle. And that's just really driven a meaningful cost improvement and cost advantage. On our math about a 40 percent cost advantage relative to Waymo today. Now going forward, you know, as you mentioned, I think the key hurdle here or bottleneck, that Tesla still needs to prove is their safety. And can they reach the same safety standards as a human driver? And, you know, the improvement that you've seen from Waymo. You know, to put some numbers around this. Based on publicly available data in Austin, Tesla's getting in a crash, you know, every about, call it every 50,000 miles; Waymo is closer to every 400,000 miles per crash. So today, Waymo is the leader on safety.I think the one important caveat that I want to mention here is that's on a relatively small number of miles driven for Tesla. They've only driven about 250,000 miles in Austin, whereas Waymo's driven close to, I think, a hundred million miles cumulatively. So, when you look back, I think this is going to be the kind of key catalyst and key data point for investors to watch is – how that data improves over the course of 2026. If you track Waymo – Waymo's data improved substantially as their miles driven improved, and as they launched into new cities.We'd expect Tesla to follow a similar trend. But that's going to be a huge catalyst in validating this camera only approach. If that happens, Tesla's not limited in scale, they're not limited in manufacturing capacity. You can meaningfully see them expand… Or you can see them expand quite quickly once they prove out that safety requirement. Brian Nowak: I think it's a great point because, you know, one of the other big debates that we are all going to have to monitor in the AV space throughout 2026 is: How quickly does Tesla completely pull the safety drivers, and how quickly do they scale up production of the vehicles? Because one of the bank shots around autonomous driving is actually the rideshare industry. You know, we have partnerships; some partnerships between Waymo and Uber and Waymo and Lyft. But Tesla is not partnering with anyone. And so, I think the extent to which we see a faster than expected ramp up in deployment from Tesla can have a lot of impact. Not only on autonomous adoption, competition with Waymo, but also the rideshare industry.So how do you think about the puts and takes on Tesla and sort of removing the drivers and scaling up the fleet this year? What should we be watching? Andrew Percoco: Yeah, so they've already made some strides there in Austin. They've pulled the safety monitor. They haven't opened that up to the public yet without the safety monitor. They're still testing, presumably in that geography. They need to be extremely careful in terms of, you know, the regulatory compliance and making sure they're doing this in a safe way. Ultimately that's what matters most to them. We do expect them to roll it out to the public without the safety monitor in 2026. Whether or not, that's the first quarter or the third quarter – is a little bit tougher to predict. But I think it's reasonable to assume whatever the timeline is, they're going to make sure it's the safest way possible to ensure that there's, you know, no unintended consequences as it relates to regulation, et cetera. I think one, also; one important data point or interesting data point here. You know, we model, I think, a 100 percent CAGR in miles driven, autonomous miles driven through 2032. You can talk a little bit about, you know, what the implications for rideshare, but I think important. It's important to contextualize that would still only represent less than 1 percent of total U.S. miles driven in the U.S. So substantial growth over the next, call it six or seven years. But still a massive TAM to be tapped into beyond 2032. And I think the key there is – what's the cost reduction roadmap look like? And can we get robotaxis to a point where they are cheaper than personal car ownership? And could robotaxis at some point disrupt the car ownership process? Brian Nowak: Yeah. And the other more important point around rideshare will be how much do these autonomous offerings expand the addressable market for rideshare and prove to be incremental? As opposed to being cannibalistic on existing ride share rides. Because you're right that, you know, even our out year autonomous projections still have it less than 1 percent of the total trips. But the question is how much does that add to ride share? Because in some scenarios, those autonomous trips could end up being 20 to 30 percent of the rideshare industry. This matters for Uber and Lyft because while they are partnering Waymo and other autonomous players across a handful of markets, they're not partnered in all the markets. And in some markets, Waymo is going alone. Tesla is going at it alone. And so when we look at our model and we say as of 2024, Uber and Lyft make up 100 percent of the ride share industry based on the current partnerships, which includes Waymo and Tesla and all; and Zoox and all the players, we think that Uber and Lyft will only make up 30 percent of the autonomous driving market. And so it's really important for the rideshare industry that when, number one, we see AV's being incremental to the TAM; and two, that Uber and Lyft are able to continue to add more partnerships over time to drive more of that overall long-term AV opportunity and participate in all this rideshare industry over the next five years. Andrew Percoco: I think it's really clear that the future of autonomous vehicles is here and we've reached an inflection point; and there's a lot of interesting catalysts and data points for us and for investors to watch for throughout 2026.So Brian, thanks again for taking the time to talk. Brian Nowak: Andrew, great speaking with you. And thanks for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen and share the podcast with a friend or colleague today.

What happens when China's wine market shrinks by 15% annually since 2019, yet some companies post their best year ever? In this landmark 200th episode of Bottled in China, we assembles an expert roundtable to decode 2025's contradictions and what they mean for 2026.Guests:Nick Marro, Principal Economist for Asia, Economist Intelligence UnitIan Ford, Founding Partner at Nimbility, previously the Co-founder of SummergateMartin Shen, Managing Director, Tiansai Vineyards (Xinjiang)Richard King, Sommelier in Shanghai's fine dining sceneFrom Beijing's anti-corruption crackdown that decimated government banqueting to the surprising surge in aromatic white wines, our panel reveals how "involution"—China's race-to-the-bottom pricing wars—is reshaping everything. Discover why post-2000 consumers spend fortunes on wine pairings but only Instagram the famous labels, how instant retail delivers chilled bottles in 30 minutes, and why Xinjiang is becoming China's hottest wine destination.The verdict? China remains Asia's largest bottled wine market with massive upside in a $300 billion² beverage alcohol sector—but only for those willing to adapt to the new normal.Insights: IWSR Wine Landscapes 2025 - China, ¹Wine market CAGR -14.9% 2019-2024. ²$266 billion TBA value Since 2016, Bottled in China brings you into the food and drink scene through conversations with the some of the most happening personalities. Hosted by Emilie Steckenborn, the show is your one spot for all things food, beer, wine and spirits from across the world. Connect with us on LinkedIn or Instagram @bottled.in.chinaPodcast available on iTunes, Spotify , online or wherever you listen to your episodes! Subscribe to Bottled in China to follow the journey!Check out our new website & find out more at https://www.thebottledshow.com

Mentor Sessions Ep. 046: Bitcoin 2026 Bull Run, TradFi Myths & Fed Liquidity Secrets | Joe ConsortiWhat if TradFi's bearish take on Bitcoin 2026 is dead wrong, and critically low bank reserves are the hidden Fed spark igniting an epic Bitcoin bull run? In this explosive episode of BTC Sessions, macro wizard Joe Consorti dismantles TradFi myths, revealing why Bitcoin volatility is at record lows—historically a screaming buy signal for massive upside. He exposes how plunging bank reserves act as Bitcoin's ultimate liquidity smoke alarm, with Fed interventions like $40B treasury buys set to flood the system and propel Bitcoin higher amid rising unemployment and asset prices bubble risks. Joe warns of long-term holders flipping from sellers to accumulators, ending the pressure that's kept Bitcoin range-bound, and predicts an explosion by year's end as we're just at the start of a multi-year bull market. From precious metals rotations to AI shovels outperforming, he shares why Bitcoin crushes gold as superior hard money—plus, how Horizon lets homeowners convert equity to BTC for 25-70% CAGR gains. If you're stacking sats, this is your roadmap to navigate 2026's Bitcoin bull run, dodging TradFi traps and capitalizing on Fed liquidity waves. Don't miss these game-changing insights—watch now and level up your Bitcoin strategy!About Joe ConsortiWebsite: https://joinhorizon.comX: @JoeConsortiYouTube: https://www.youtube.com/ ⁨@joeconsorti⁩ Chapters:00:00:00 Teaser & Intro00:01:12 TradFi's 2026 Myths00:03:14 Cycle Break & Bull Signals00:05:59 Equities & Metals Outlook00:07:28 Bitcoin Downside Exhaustion00:09:52 Range & Low Volume Causes00:11:26 Volatility as Upside Precursor00:14:13 Reserves as 2026 Catalysts00:16:23 Reserves-Bitcoin Correlation00:17:54 Liquidity Smoke Alarm00:20:10 On-Chain Holders Flip00:23:48 Seller Exhaustion Bullish00:25:55 Reserves Mechanics & Decline00:30:15 Macro Risks & Worsening00:31:27 Economy, Unemployment Outlook00:37:35 COVID Distortions Legacy00:39:45 Asset Prices Bubbles00:41:35 Investments Beyond Real Estate00:42:57 Gold vs Bitcoin Debate00:45:18 AI Opportunities & Miners00:47:23 Policy Shifts & Central Banks00:50:59 US Real Estate & Mortgages00:53:51 Bitcoin Fixes for Youth00:55:25 Horizon Equity Tool00:56:16 Canada Real Estate Rant00:57:46 S-Curve Adoption Potential00:58:27 Gold Parabolic Parallels01:01:32 2026 Prediction01:03:17 ClosingPrevious Episode:Mentor Sessions Ep. 045: Bitcoin Privacy Erosion, Quantum Myths & AI Data Threats | Time Chain Calendar Creator TC: https://youtu.be/H1ncnMF-img⚡ POWERED by Abundant Mines: Fully managed Bitcoin mining. Learn more at abundantmines.com/sessions

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Venture capital isn't luck — it's math. Jess Larsen sits down with Jamie Rhode, Partner at ScreenDoor, to reveal how elite allocators consistently hit 3× returns and 20–25% CAGR over decades. They break down 42 years of VC data, the power law behind billion-dollar outcomes, and how top investors turn volatility into long-term advantage. Learn more about your ad choices. Visit megaphone.fm/adchoices

Morgan Stanley analysts Betsy Graseck and Michael Cyprys discuss what's driving unprecedented consolidation for asset and wealth management firms.Read more insights from Morgan Stanley.----- Transcript ----- Betsy Graseck: Welcome to Thoughts on the Market. I'm Betsy Graseck, Morgan Stanley's U.S. Large Cap Banks Analyst and Global Head of Banks and Diversified Finance Research.Michael Cyprys: And I'm Mike Cyprys, Head of U.S. Brokers, Asset Managers and Exchanges Research.Betsy Graseck: The asset management and wealth management industries are on the cusp of major consolidation. We're going to unpack today what's driving the race for scale and what it means for investors and the industries at large.It's Monday, October 13th at 4pm in New York.Mike, before we dive into the setup for M&A, I did want to get out here on the table. What's your outlook for the asset management industry?Michael Cyprys: Sure. So, asset management today is, call it, $135 trillion industry, in terms of assets under management that are managed for a fee. We expect it to grow at about an 8 percent clip annually over the next five years. And that's driven by faster growth in private markets, solutions and passive strategies, while we expect to see slower growth in the core active arena.Two key drivers of growth there. First private markets. We expect to see rising investor allocations from both institutional investors, but also more importantly from retail investors that remain early days in accessing the asset class. So, as we look out in the coming years, we do expect this democratization of private markets to play out, and we see that being helped by product innovation, investor education and technology advances that are all helping unlock access.Second growth driver is solutions. And I think you're looking at me a little dazed on what's solutions. And by that we really mean products and strategies that are addressing demographic challenges around aging populations. So, think about that as solutions that provide for retirement income, as well as those that offer tax efficient solutions. So, think about that as model portfolios, as well as sub-advisory mandates. We also expect to see growth in outsourced Chief Investment Officer, OCIO mandates and broadly retirement focused products.So that's the asset management industry in terms of our outlook. Betsy, what's your outlook for the growth in the wealth management industry?Betsy Graseck: Well, somewhat similar, but a little bit slower – off of a larger base. What does that mean? So, we are looking for global growth in wealth management of 5.5 percent CAGR, and that is off of a base of [$]301 trillion, which is intriguing, right? Because that's larger than the [$]135 trillion you mentioned for asset management.So, in wealth, we were expecting [$]301 trillion in 2024 grows to [$]393 trillion in 2029. And within the wealth industry, what we see as the driver for incremental opportunities here is both in the ultra high net worth segment as well as the affluent segments, as client needs evolve and technology delivers improving efficiencies.And I think one of the interesting things here – as we think about the look forward from industry perspective – is the fact that both asset management and wealth management industries have been very fragmented for a very long time, especially relative to other financial industries. I think one reason is that they need less capital to operate successfully.But Mike, back to the asset management industry, specifically – deal activity seems to be inching up. What are you attributing this increase in M&A to?Michael Cyprys: Yeah, so we do see M&A picking up, and we expect that to continue over the next couple of years. A number of reasons for that. First growth is becoming a bit more scarce, with clients working with fewer partners. And over the next five years, we expect the number of available slots to continue to decline upwards of a third, which concentrates growth opportunities.Betsy Graseck: Wait, wait, wait. Upwards of a third. And number of slots. When you say number of slots, you're talking about it from the asset manager client perspective…Michael Cyprys: Correct. From the asset owner standpoint or intermediary standpoint.Betsy Graseck: They're looking to consolidate their providers?Michael Cyprys: Correct.Betsy Graseck: Okay.Michael Cyprys: They're looking to work with fewer asset managers.Betsy Graseck: Mm-hmm.Michael Cyprys: At the same time, the winners are taking more share, right? So, our work shows that the largest firms are disproportionately capturing a larger share of net new money as they leveraged their scale to reinvest in capabilities as well as in relationships.And also, I'd point to the fact that we have seen a pickup in deal activity already. And we think that's going to lead more firms to consider strategic activity themselves, as they think and rethink what constitutes scale. And we think that that bar is rising…Betsy Graseck: Mm. Michael Cyprys: And firms are thinking about how to compete effectively as the landscape evolves. And look, this is all in the context of already a lot of challenges and changes happening as you think about evolving client needs. The rising cost of doing business, whether it's investing for growth or even harnessing AI, and that's all pressuring profitability. We think this is particularly a challenge for those mid-size money managers that are multi-asset, multi-liquid and global. Those with, call it, [$]0.5 trillion to [$]2 trillion in size, making them more likely to pursue consolidation, opportunities to bolster their capabilities and scale while also generating cost efficiencies.Betsy Graseck: So now looking forward, what type of deals do you expect and how does it differ from past years?Michael Cyprys: Sure. So, a few things are different than past years. First is that the deal activity is encompassing many forms of partnership. And we think that this experimentation around partnership will only accelerate. That allows, for example, for private market managers to access retail distribution without owning the end infrastructure and the last mile to the customer. It also allows traditional managers to provide their retail customers with access to high quality private market strategies from well-known and branded firms.Second is we see a broadening out of the types of acquisitions themselves when we talk about M&A, right? So, three types of deals. First are deals within the same vertical or intersector. So, think about this as an asset manager buying another asset manager to acquire capabilities, to gain cost synergies or bolster distribution.Second type of deals that we're seeing are ones that expand beyond one's own vertical. So intersector deals. So, asset management combining with wealth or insurance, for example, where firms would seek to own a larger, greater portion of the overall value chain. And so, these firms are getting closer to that end client. For example, an asset manager getting closer to that end customer. And the third type being financial sponsor deals where a sponsor is investing either as an in an asset or a wealth manager.Now you didn't ask me around the historical outcomes of M&A. But I would say that the historical outcomes have been mixed in the asset management space. But here we think that the opportunity ahead is so bright that we think firms will find ways to navigate and pursue strategic activity. But it does require addressing some of the culture and integration challenges that have plagued some of the deals in the past.Betsy Graseck: Okay.Michael Cyprys: So, Betsy, what do you see as the key drivers of consolidation in wealth management?Betsy Graseck: There's several. From the wealth manager side, number one is an aging population of advisor and advisor-owners, and the need to address succession and how to best serve their clients when passing on their book of business. So, we've got succession issues as the number one driver. But additionally, the need for scale is clearly getting higher and higher – given the costs of IT infrastructure rising, the needs to be able to leverage AI effectively and to manage your cyber risk effectively. These are just some of the drivers of desire to merge from the wealth manager perspective.Second. We have an increasing buying pool. If you just look at the large cap banks, for example. Significant amount of excess capital. Could we see some of that excess capital be put to work in the wealth management industry? To me, that would make sense. Why? Because wealth management is one of the best, if not the best financial institution service for shareholders. It is a high ROE business. It also is a business that commands a high multiple in the stock market.So, we would not be surprised to see activity there over the course of the next several years. So, Mike, thanks for joining me on the show today.Michael Cyprys: Thanks, Betsy. Always a pleasure.Betsy Graseck: And to our listeners, thanks for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen and share the podcast with a friend or colleague today.

Global spending on cybersecurity products and services will see a strong 14.4% CAGR from 2024 through 2029 and will hit $302.5 billion in 2029, driven by continued concerns around cyberattacks across all verticals and geographies. But where is the spending occuring and how do you prepare? Merritt Maxim, VP & Research Director at Forrester, joins Business Security Weekly to discuss the Global Cybersecurity Market Forecast, 2024 To 2029 report. Merritt will discuss the findings, including: In 2029, 69% of cybersecurity spending will be on software across seven prime functional disciplines of cybersecurity (applications, cloud, data, endpoint, network, identity, and security operations); the remaining spending will be allocated to security services, excluding security outsourcing, implementation, and deployment services; and AI software spending will grow at a CAGR of 21.2%, from $74.3 billion in 2024 to $194.3 billion by 2029. See Merritt's blog of the results at https://www.forrester.com/blogs/global-cybersecurity-spending-to-exceed-300b-by-2029/. In the leadership and communications segment, The problem with cybersecurity is not just hackers – it's how we measure risk, What California's new AI law means for CIOs (and CISOs), The Language of Leadership: How to Set Firm Boundaries Without Sounding Like a Jerk, and more! Visit https://www.securityweekly.com/bsw for all the latest episodes! Show Notes: https://securityweekly.com/bsw-416

Diving into the evolving landscape of the partner ecosystem, the discussion centers around three major forces shaping the industry by 2030. First, cloud marketplaces are projected to reach $163 billion in transactions, with nearly 60% of that being partner-led. This shift signifies a redefinition of partner value in the marketplace era, moving beyond traditional procurement methods. Second, the rise of AI services is highlighted, with a projected $267 billion opportunity by 2030, growing at an impressive 35% CAGR. This transition emphasizes the importance of packaging, governance, and delivering measurable outcomes rather than merely developing AI technologies.The conversation also delves into the critical role of cybersecurity as a services multiplier, with a study indicating that for every dollar spent on the CrowdStrike Falcon platform, partners can generate over $7 in services revenue. This statistic underscores the potential for partners to leverage cybersecurity solutions to enhance their service offerings. Jay McBain, Chief Analyst at Omdia, provides insights into how these trends impact channel partners, vendors, and the future of IT services, emphasizing the need for partners to adapt to these changes. As the discussion progresses, the challenges and opportunities for partners in the AI landscape are examined. The conversation points out that while AI is becoming a feature rather than a standalone product, partners must engage with business leaders across various departments to capitalize on the growing demand for AI-driven solutions. The importance of understanding customer needs and aligning services accordingly is stressed, as partners risk being sidelined by larger system integrators and management consultants if they do not adapt.Finally, the dialogue touches on the changing economics of partnering, particularly in light of recent shifts by major vendors like Microsoft and Cisco, which are cutting back on their partner networks. This consolidation raises questions about how partners can continue to thrive in a landscape where margins are shrinking. The emphasis is placed on the necessity for partners to rethink their business models, focusing on delivering high-value services and leveraging the opportunities presented by AI and cybersecurity to ensure sustainable growth in the future. All our Sponsors: https://businessof.tech/sponsors/ Do you want the show on your podcast app or the written versions of the stories? Subscribe to the Business of Tech: https://www.businessof.tech/subscribe/Looking for a link from the stories? The entire script of the show, with links to articles, are posted in each story on https://www.businessof.tech/ Support the show on Patreon: https://patreon.com/mspradio/ Want to be a guest on Business of Tech: Daily 10-Minute IT Services Insights? Send Dave Sobel a message on PodMatch, here: https://www.podmatch.com/hostdetailpreview/businessoftech Want our stuff? Cool Merch? Wear “Why Do We Care?” - Visit https://mspradio.myspreadshop.com Follow us on:LinkedIn: https://www.linkedin.com/company/28908079/YouTube: https://youtube.com/mspradio/Facebook: https://www.facebook.com/mspradionews/Instagram: https://www.instagram.com/mspradio/TikTok: https://www.tiktok.com/@businessoftechBluesky: https://bsky.app/profile/businessof.tech Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Our Chief China Equity Strategist Laura Wang discusses how China's new approach to economic development is transforming domestic industries and reshaping the global investment landscape.Read more insights from Morgan Stanley.----- Transcript ----- Welcome to Thoughts on the Market. I'm Laura Wang, Morgan Stanley's Chief China Equity Strategist.Today – a consequential shift in China's economic policy is set to reshape domestic markets and send ripples across the global economy.It's Thursday, October 2nd at 2pm in Hong Kong.If you're an investor, it's important to understand China's new approach to economic development. The government's policies to drive a recovery from an economic slump are changing the rules of competition, profitability and growth. This affects Chinese companies, and in turn global supply chains and investment flows.Let's start with the term involution – what is it? In China, involution describes a cycle of excessive competition—think companies fighting for market share by slashing prices, ramping up production, and eroding profits, often to the point where nobody wins. The government's anti-involution campaign is a direct response to this problem.What factors prompted the launch of this anti-involution initiative? Since 2021, China has faced mounting deflationary pressures—falling prices, a housing market slump, and a surge in manufacturing investment that led to overcapacity. The September 2024 policy pivot began to address these issues, and in mid-2025 the government launched a more targeted anti-involution campaign. This phase focuses on reducing excessive competition and restoring pricing power through market-based consolidation.As we assess the potential effectiveness of China's anti-involution policy, our base case projects China's return on equity (ROE) to reach 13.3 percent by 2030, up from a cycle low of 10 percent in May 2024 and 11.6 percent by July 2025. In a bullish scenario, decisive reforms and demand-side stimulus could push ROE as high as 16.3 percent.We also expect earnings growth to accelerate, with our base case showing an annual growth rate (CAGR) of 7.6 percent in 2025, rising to 11.1 percent by 2027. We forecast valuations to normalize towards 12–13x forward price-to-earnings, in line with emerging market peers, but this could re-rate higher if reforms succeed.In terms of investment opportunities, we believe the EV Batteries industry will benefit the most from the Chinese government's anti-involution efforts. It's got strong policy support, cutting-edge technology, and a market that's consolidating fast—meaning the days of low-quality and excess capacity are fading. We're seeing a shift toward long-term, sustainable growth. Steel and Cement are industries where the state has a strong hand and capacity controls are well established. These factors help stabilize the market and open the door for steady gains. Finally, Airlines. While the industry has faced persistent losses, there isn't a[n] oversupply of seats, and regulatory coordination is strong. With the right reforms, Airlines could be poised for a significant turnaround.The sectors best positioned to benefit from China's anti-involution strategy are more domestically oriented. But this policy is bound to have global implications. And the ripples will likely extend to global supply chains, especially in Materials, Chemicals and Autos.Looking ahead, the pace and success of anti-involution will depend on further structural reforms, demand-side support, and the ability to digest industrial credit risks gradually. The upcoming 15th Five-Year Plan could bring more clarity on tax, social welfare, and local government incentives.So, what should investors be paying attention to? China's anti-involution campaign is more than a policy tweak—it's a recalibration of how the country balances growth, innovation, and sustainability. The key is to track sector-level reforms, watch for signs of consolidation, and focus on companies with strong fundamentals and policy tailwinds.Thanks for listening. If you enjoy the show, please leave us a review wherever you listen and share Thoughts on the Market with a friend or colleague today.

Our analysts Tim Chan and Mayank Maheshwari discuss how nuclear power and natural gas are reshaping Asia's evolving energy mix, and what these trends mean for sustainability and the future of energy. Read more insights from Morgan Stanley.----- Transcript -----Tim Chan: Welcome to Thoughts on the Market. I'm Tim Chan, Morgan Stanley's Head of Asia Sustainability Research.Mayank Maheshwari: And I am Mayank Maheshwari, the Energy Analyst for India and Southeast Asia.Tim Chan: Today – a major shift in global energy. We are talking about nuclear power, gas adoption, and what the future holds.It's Monday, August 18th at 8am in Hong Kong.Mayank Maheshwari: And it's 8am in Singapore.Tim Chan: Nuclear power is no longer niche; it's a megatrend. It was once seen as controversial and capital intensive. But now nuclear power is stepping into the spotlight—not just for decarbonization, but for energy security. Global investment projections in this sector are now topping more than $2 trillion by 2050. This is fueled by a growing appetite from major tech companies for clean, reliable 24/7 energy. More specifically, Asia is emerging as the epicenter of capacity growth, and that's where your coverage comes in, Mayank.With the rising consumption of electricity, how does nuclear energy adoption stack up in your universe?Mayank Maheshwari: Tim, it's a fascinating world on power right now that we are seeing. Now the tight global power markets perspective is key on why there is so much investor and policymaker attention to nuclear power.Nuclear fuels accounted for about a tenth of the power units produced globally. However, they are almost a fifth of the global clean power generation. Now, power consumption is at another tripping point, and this is after tripling since 1980s. To give you a perspective, Tim, 25 trillion units of power were consumed worldwide last year, and we see this growing rapidly at a 25 percent pace in the next five years or so. And if you look at consumption growth outside of China, it's even faster at 2.5x for the rest of the decade when compared to the last decade.Now policy makers need energy security and hence, nuclear is getting a lot more attention. In Asia, while China, Korea, and Japan have been using nuclear energy to power the economy, the rest of Asia, it has been more an ambition – with India being the only country making progress last decade. Southeast Asia still has a lot more coal, and nuclear remains an ambition as technology acceptance by public and regulatory framework remains a key handicap. We do, however, see policy makers in Singapore, Vietnam, and Malaysia looking at nuclear fuels more seriously now, with SMRs also being discussed.Tim Chan: That is a really interesting perspective, Mayank. So, you have been bullish on the Asia gas adoption story. So, how do you think gas and nuclear will intersect in this region?Mayank Maheshwari: I think nuclear and natural gas, like all of the fuel stem, will complement each other. However, the long gestation to put nuclear capacity makes gas a viable alternative for energy security. As I was telling you earlier, policy makers are definitely focusing on it. As you know, the last big increase in focus in nuclear fuels also happened in the 1970s oil shock, again when energy security came into play.Global natural gas consumption has more than doubled in the last three decades, and it's set to surprise again with AsiaPac's consumption pretty much set to rise at twice the pace versus what right now expectations are by the street. In this age of electrification and AI adoption, natural gas is definitely emerging as a dependable and an affordable fuel of the future to power everything from automobiles to humanoids, biogenetics, to AI data centers, and even semiconductor production, which is getting so much focus nowadays.We expect global consumption to rise again after not growing this decade for natural gas. As Asia's natural gas adoption rises and grows at 5 percent CAGR 2024-2030; with consumption for gas surprising in China, India, and Japan. So, all the large economies are seeing this big increases, especially versus expectations.The region will consume 70 percent of the globally traded natural gas by 2030. So that's how important Asia will be for the world. And while global gas glut is well flagged, especially coming out of the U.S., Asia's ability to absorb this glut is not very well appreciated.Tim, having said that, nuclear energy is clearly getting more interest globally and is often debated in sustainability circles. How do you see its role evolving in sustainability frameworks as well as green taxonomies?Tim Chan: On sustainability, one thing to talk about is exclusion. That is really important for many sustainable sustainability investors. And when it comes to exclusion for nuclear power, only 2.3 percent of global AUM now exclude nuclear power. And then, that percentage is lower than alcohol, military contracting and gambling. And the exclusion rate is also different dependent on the region. Right now, European investors have the highest exclusion rate but have reduced the nuclear exclusion from 10.9 percent to 8.4 percent as of December last year. And North American and Asian exclusion rates are very, very low. Just 0.3 percent and 0.6 percent respectively.So, this exclusion in North America and Asia are minimal. The World Bank has also lifted, its decades long ban on financing nuclear project, which is important because World Bank can provide capital to fund the early stage of nuclear plant project or construction.And finally, on green finance. The EU, China and Japan have incorporated the nuclear power into their green taxonomies. So that means in some circumstances, nuclear project can be considered as green.Mayank Maheshwari: Now we have talked about AI and its need for power on this show. Nuclear power has a significant role to play in that equation, with hyperscalers paying premium for nuclear power. How does this support the investment case for nuclear utilities?Tim Chan: Yeah, so that depends on the region; and then different region we have different dilemmas. So, let's talk about U.S. first. In the U.S. we are seeing nuclear power is commanding a premium of approximately around $30-$50 per megawatt hour – above the market rate. So, when it comes to this price premium, we do think that will support the nuclear utilities in the U.S. And then in the report we highlighted a few names that we believe the current stock price haven't really priced in this premium in the market.And then for other regions, it depends on the region as well. So, Mayank, you have talked about Southeast Asia. Southeast Asia right now, given the lack of nuclear pipeline and then also the favorable economies of gas, we are not seeing that sort of premium yet in the Southeast Asia. We are also not seeing that premium in the Europe and in China as well, given that right now this sort of premium is mainly a U.S. exclusive situation. So dependent on the region, we are seeing different opportunities for nuclear utilities when it comes to the price premium.Mayank Maheshwari: Definitely Tim, I think the price premiums are dependent on how tight these power markets in each of the geographies are. But like, how does nuclear fit into broader energy mix alongside renewables and natural gas for you?Tim Chan: So, all these are really important. For nuclear power, investors really appreciate the clean and reliable, and for the 24x7 nature of the energy supply to support their operations and sustainability goals. And then nuclear is also important to bring the power additionality, which means nuclear is bringing truly new energy generation rather than simply utilizing a system or already planned capacity. We are seeing that sort of additionality in the new nuclear project and also the SMR in future as well.So, for natural gas, that is also important. As Mayank you have mentioned, natural gas money adds as a bridge field to provide flexibility to the grid. And then in the U.S., it is currently the primary near-term solution for powering AI and data center to increase the electricity supply due to its speed to the market and reliability. And natural gas is suspected to meet immediate demand, while longer term solutions like nuclear projects and also SMR are developed.And finally, renewable energy is also important. It represents the fastest growing and increasingly cost competitive energy source. They also dominate the new capacity additions as well. But for renewable energy, it also requires complimentary technology such as battery ESS to adjust intermittency issues.So, Mayank we have talked so much about nuclear, and back to you on natural gas. You are really bullish on natural gas. So how and where do you think are the best way to play it?Mayank Maheshwari: As you were kind of talking about the intersection and diffusion between nuclear, natural gas and the renewable markets, what you're seeing is that our bullishness on consumption of natural gas is basically all about how this diffusion plays out. Consumption on natural gas will rise much quicker than most fuels for the rest of the decade, if you think about numbers – making it more than just a transition fuel.Hence, Morgan Stanley research has a list of 75 equities globally to play the thematic of this diffusion, and it is happening in the power markets. These equities are part of the natural gas adoption and the powering AI thematic as well. So, these include the equipment producers on power, the gas pipeline players who are basically supporting the supply of natural gas to some of these pipelines. Hybrid power generation companies which have a good mix of renewables, natural gas, a bit of nuclear sometimes. And infrastructure providers for energy security.So, all these 75 stocks are effective playing at the intersection of all these three thematics that we are talking about as Morgan Stanley research. It is clear that nuclear renaissance, Tim, isn't just about reactors. It's about rethinking energy systems, sustainability, and geopolitics.Tim Chan: Yes, and the last decade will be defined by how we balance ambition with execution. Nuclear together with gas and renewables will be central to Asia's energy future. Mayank, thanks for taking the time to talk,Mayank Maheshwari: Great speaking to you, Tim.Tim Chan: And thanks for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen and share the podcast with a friend or colleague today.

After a week off on holiday, Steno Research founder and CEO Andreas Steno and his co-host, Mikkel Rosenvold, partner and head of geopolitics for Steno Research, are back to break down the latest news driving global markets.

In this episode, Stig Brodersen speaks with Guy Spier who has outperformed the S&P 500 since 1997, with a 9.6% vs. 8.8% CAGR. They explore why Guy invested in The Economist, and how friendships, service, and living by an inner scorecard guide his life and investment philosophy. IN THIS EPISODE YOU'LL LEARN: 00:00 - Intro 02:27 - Why Guy Spier decided to invest in The Economist. 13:16 - How Guy is living by his inner scorecard. 55:16 - Why friendships are there for a reason, a season, or a lifetime. 55:16 - How does Guy invest in friendships? 01:09:03 - How to facilitate thoughtful conversations with friends. 01:22:03 - How do you seek wisdom? 01:44:04 - How do you identify how to best be of service? 01:57:43 - What money can and can't buy you. Disclaimer: Slight discrepancies in the timestamps may occur due to podcast platform differences. BOOKS AND RESOURCES Join Clay and a select group of passionate value investors for a retreat in Big Sky, Montana. Learn more ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Join the exclusive ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TIP Mastermind Community⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to engage in meaningful stock investing discussions with Stig, Clay, Kyle, and the other community members. Stig's interview with Guy Spier about his track record and risk. Stig's interview with Guy Spier about investing and life. Stig and Preston's interview with Guy Spier on his book, The Education of a Value Investor. Stig and Preston's interview with Guy Spier about his lunch with Warren Buffett.  Guy Spier's book, The Education of a Value Investor – Read reviews of the book. Subscribe to Guy Spier's Free Newsletter. Guy Spier's podcast and website. Check out all the books mentioned and discussed in our podcast episodes ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Enjoy ad-free episodes when you subscribe to our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Premium Feed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. NEW TO THE SHOW? Get smarter about valuing businesses in just a few minutes each week through our newsletter, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Intrinsic Value Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Check out our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠We Study Billionaires Starter Packs⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Follow our official social media accounts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠X (Twitter)⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Browse through all our episodes (complete with transcripts) ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Try our tool for picking stock winners and managing our portfolios: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TIP Finance Tool⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Enjoy exclusive perks from our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠favorite Apps and Services⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Learn how to better start, manage, and grow your business with the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠best business podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. SPONSORS Support our free podcast by supporting our ⁠⁠sponsors⁠⁠: ⁠SimpleMining⁠⁠ ⁠⁠AnchorWatch⁠⁠ ⁠⁠Human Rights Foundation⁠⁠ ⁠⁠Onramp⁠⁠ ⁠⁠Superhero Leadership⁠⁠ ⁠⁠Unchained⁠⁠ ⁠⁠Vanta⁠⁠ ⁠⁠Shopify⁠ HELP US OUT! Help us reach new listeners by leaving us a ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠rating and review⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠! It takes less than 30 seconds, and really helps our show grow, which allows us to bring on even better guests for you all! Thank you – we really appreciate it! Support our show by becoming a premium member! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://theinvestorspodcastnetwork.supportingcast.fm⁠⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm