Podcasts about Enron

────────────────────────────────────────[00:02:04]FlyDubai "Hero Passenger" Story Smells Like Staged 9/11Netanyahu rushes to hype a pilot-stabbing incident near Tel Aviv as his own 9/11, but the "untrained passenger saves the jet" narrative doesn't add up.────────────────────────────────────────[00:16:58]Sen. Slotkin: Trump Doesn't Need a False Flag to Grab Emergency PowersDemocrat and ex-CIA officer warns Trump could invent or exploit any crisis to seize emergency powers before the midterms.────────────────────────────────────────[00:22:55]RAF "Terror Plot" Collapses: No Explosives, Just FuelUK searches find nothing but stolen fuel, yet PM Burnham and Rubio still insist Iran was behind it.────────────────────────────────────────── Interview 1: Tony Arterburn — Wise Wolf Gold ──────────────────────────────────────────[00:30:49]Tether Freezes $550M, Brags It Can Do It to AnyoneArterburn warns stablecoins are the real CBDC backdoor, letting governments freeze funds with a keystroke.────────────────────────────────────────[00:41:33]Knight Coins It: "CCDC" - Crony Capitalist Digital CurrencyTrump's "no CBDC" pledge just relabeled the surveillance-money system as stablecoins tied to Bessent and Musk's X Money.────────────────────────────────────────[00:51:43]China May Already Have More Gold Than the USArterburn says China's 1,200-ton 2026 buying spree, much off the books, could put it ahead of America's reserves.────────────────────────────────────────[00:57:21]2008 Echo: Foreclosures Up 42% as the AI Bubble Props Up MarketsArterburn flags rising defaults and commercial real estate refinancing risk as signs of another 2008-style crack.────────────────────────────────────────[01:16:46]Trump Signs "AI Accord" With Tech CEOs - a 10-Person Panel Will "Self-Police"Knight calls the pact a farce that hands Big Tech a monopoly and legal immunity, not real oversight.────────────────────────────────────────[01:37:34]Anthropic's Prospectus Reveals a $42 Billion Net LossKnight compares the AI giant's books to Enron-level losses as IPO disclosures expose the bubble's fragility.────────────────────────────────────────[01:46:46]Data Center Builders Offer PA Township $10K a Household After Board Rejects Project 3-0After supervisors voted down a 1,300-acre hyperscale project, developers dangle cash and "free" infrastructure to buy approval ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-david-knight-show--2653468/support.

────────────────────────────────────────[00:02:04]FlyDubai "Hero Passenger" Story Smells Like Staged 9/11Netanyahu rushes to hype a pilot-stabbing incident near Tel Aviv as his own 9/11, but the "untrained passenger saves the jet" narrative doesn't add up.────────────────────────────────────────[00:16:58]Sen. Slotkin: Trump Doesn't Need a False Flag to Grab Emergency PowersDemocrat and ex-CIA officer warns Trump could invent or exploit any crisis to seize emergency powers before the midterms.────────────────────────────────────────[00:22:55]RAF "Terror Plot" Collapses: No Explosives, Just FuelUK searches find nothing but stolen fuel, yet PM Burnham and Rubio still insist Iran was behind it.────────────────────────────────────────── Interview 1: Tony Arterburn — Wise Wolf Gold ──────────────────────────────────────────[00:30:49]Tether Freezes $550M, Brags It Can Do It to AnyoneArterburn warns stablecoins are the real CBDC backdoor, letting governments freeze funds with a keystroke.────────────────────────────────────────[00:41:33]Knight Coins It: "CCDC" - Crony Capitalist Digital CurrencyTrump's "no CBDC" pledge just relabeled the surveillance-money system as stablecoins tied to Bessent and Musk's X Money.────────────────────────────────────────[00:51:43]China May Already Have More Gold Than the USArterburn says China's 1,200-ton 2026 buying spree, much off the books, could put it ahead of America's reserves.────────────────────────────────────────[00:57:21]2008 Echo: Foreclosures Up 42% as the AI Bubble Props Up MarketsArterburn flags rising defaults and commercial real estate refinancing risk as signs of another 2008-style crack.────────────────────────────────────────[01:16:46]Trump Signs "AI Accord" With Tech CEOs - a 10-Person Panel Will "Self-Police"Knight calls the pact a farce that hands Big Tech a monopoly and legal immunity, not real oversight.────────────────────────────────────────[01:37:34]Anthropic's Prospectus Reveals a $42 Billion Net LossKnight compares the AI giant's books to Enron-level losses as IPO disclosures expose the bubble's fragility.────────────────────────────────────────[01:46:46]Data Center Builders Offer PA Township $10K a Household After Board Rejects Project 3-0After supervisors voted down a 1,300-acre hyperscale project, developers dangle cash and "free" infrastructure to buy approval ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-real-david-knight-show--5282736/support.

Könnte ein Privatanleger einen Fall wie Enron rechtzeitig erkennen? Enron verfügte über renommierte Wirtschaftsprüfer, positive Analystenurteile, gute Kreditratings und ein Management, das an der Wall Street gefeiert wurde. Trotzdem kollabierte das Unternehmen innerhalb weniger Monate. In diesem Video rekonstruieren wir zunächst, wie Enron vom Pipelinebetreiber zum Börsenstar aufstieg und welche Rolle die Dotcom-Manie dabei spielte. Anschließend schauen wir auf die Mechanismen hinter dem Zusammenbruch und ziehen sieben konkrete Lehren für Anleger.

Your work's forced ranking bell curve wasn't discovered in experiments with people. It was installed via fiat. ...and forced ranking pays people to hide bad news.Product Manager Brian and Enterprise Business Coach Om tear apart the forced ranking system GE made famous, Microsoft ran for a decade, and that Enron perfected. By the end you'll know the four jobs forced ranking secretly does, why none of them even need a quota, and what to ask before your next "calibration" meeting.Listen or Watch to learn:• How forced ranking started as a patch for lazy raters• How Microsoft's lost decade and Enron's fraud both trace back to stack ranking's perverse incentives• Why quotas punish the people for systemic issues• How quotas plus bias create disparate impact and legal exposure• The four jobs forced ranking is doing that keep it aroundThis podcast is for product managers, team members, and managers who suspect the forced ranking quotas may not just be fraudulent, but also actively harmful as they "manufacture" low performers.#ForcedRanking #PerformanceManagement #AgileJack Welch, GE, Enron, Microsoft, W. Edwards Deming, Vanity Fair, Adobe, Bond 2025, Scullen et al. 2005, arXiv:2512.06583LINKSYouTube: https://www.youtube.com/@arguingagileSpotify: https://open.spotify.com/show/362QvYORmtZRKAeTAE57v3Apple: https://podcasts.apple.com/us/podcast/agile-podcast/id1568557596INTRO MUSICToronto Is My BeatBy Whitewolf (Source: https://ccmixter.org/files/whitewolf225/60181)CC BY 4.0 DEED (https://creativecommons.org/licenses/by/4.0/deed.en)

Apparently 1,200 AI agents left alone in separate sandboxes will eventually do what humans always do: find each other, form a group chat, cheat the test, and start looking for ways around the cameras. In this episode, we break down the real-world “swarm” incident, why reward hacking may matter more than Skynet fantasies, and what happens when the machines get better at hiding how they reached an answer. Then we follow the money into finance, law, AI's growing safety tax, and an oversight system that is starting to look suspiciously like auditing before Enron taught everyone a very expensive lesson. The machines are already on the trading desk, the black box is getting harder to read, and somehow the people responsible for watching all of this also seem to have chips in the game. Welcome to progress.

AIUC first got our attention with the NFDG backing, and have just announced a $40M series A today, with the most impressive industry advisor list we may have ever seen for an early startup behind AIUC-1, their agent standard backed by real insurance:From being Anthropic's first product hire to building the standards, testing, and insurance infrastructure meant to make frontier AI deployable, Rune Kvist is betting that the biggest constraint on AI adoption won't be capability it will be trust. In this episode, the AIUC cofounder joins swyx and Vibhu to announce a new $40M round and explain why companies like Cursor, Harvey, Lovable, and ElevenLabs are increasingly confronting a problem that gets harder as AI gets better: who is responsible when autonomous systems fail?We go deep on AIUC-1, the emerging standard for agent security, safety, and reliability; how AI agents are stress-tested for jailbreaks, hallucinations, and data leaks; and why Rune thinks standards and insurance could become critical infrastructure for AI. We also discuss the growing trust gap between governments and frontier labs, AI-enabled cyber and biological risks, why every model can ultimately be jailbroken, what happens when a $20 coding agent causes $200M of damage, whether AI engineers should be certified, and why even after AGI there may be one job the labs can never do themselves: be their own watchdog.We discuss:* Why risk, liability, and trust may become the binding constraint on AI adoption* Rune's path from reading the Scaling Laws paper to joining Anthropic in its earliest days* What Anthropic understood about scaling, compute, and the future years before it became obvious* Why Waymo illustrates the gap between AI capability and real-world deployment* AIUC's $40M round and work with Cursor, Harvey, Lovable, ElevenLabs, and other frontier AI companies* AIUC-1: a standard for AI agent security, safety, and reliability* How agents are tested for jailbreaks, hallucinations, and data leakage* Why most AI companies optimize the happy path without seriously stress-testing adversarial cases* Why AI standards may need to update every quarter instead of every decade* The emerging trust gap between frontier AI labs and governments* Cybersecurity, child safety, biological weapons, and the expanding frontier-model risk surface* Why standards and insurance may need to evolve together* How Lloyd's of London can insure AI systems and bring trust to enterprise deployment* What happens if a $20 Cursor subscription contributes to a $200M plane crash* The Air Canada chatbot case and how AI failures are beginning to clarify legal liability* Why copyright may be one of the hardest AI risks to insure* Evals, mechanistic interpretability, monitoring, and models becoming aware they're being tested* The impossible CISO mandate: adopt AI fast, but don't let anything go wrong* Why robotics will make AI liability dramatically more consequential* Whether AI engineers should have Level 1, 2, and 3 certifications* AIUC's roadmap across agents, frontier models, robotics, and universal red teaming* Why AGI could become a question of national sovereignty* Why the labs can never fully serve as their own watchdogs* The Big Short problem: how do you stop competing watchdogs from racing standards to the bottom?Rune Kvist* LinkedIn: https://www.linkedin.com/in/runekvist/* X: https://x.com/RuneKvistAIUC* https://aiuc.comTimestamps00:00:00 AIUC's $40M Round and the Risk Bottleneck for AI00:01:07 From Scaling Laws to Early Anthropic00:07:58 Why Trust, Not Capability, Could Limit AI Adoption00:12:19 Founding AIUC and Building AIUC-100:18:52 How AI Agents Are Audited and Stress-Tested00:25:26 Frontier Models, Government, and the AI Trust Gap00:33:32 Cyber, Child Safety, and AI-Enabled Biological Risk00:38:14 Why Standards and Insurance Belong Together00:41:45 What Does an AI Insurance Policy Actually Cover?00:50:44 The $20 Cursor Subscription and the $200M Plane Crash00:53:53 AI Liability, Monitoring, and Earning Enterprise Trust00:56:21 From AI Agents to Models to Robotics00:58:29 Copyright, Adverse Selection, and AI Insurance01:03:28 Evals, Mechanistic Interpretability, and Eval Awareness01:08:36 The Impossible Enterprise AI Mandate01:11:52 Prediction Markets vs. AI Audits01:14:43 Should AI Engineers Be Certified?01:19:10 AIUC's Roadmap, AGI, and Who Watches the Watchdogs?TranscriptIntroduction: AIUC, the $40M Series A, and Risk as the Adoption BottleneckSwyx [00:00:00]: Okay, we're in the studio with Rune from AIUC, the Artificial Intelligence Underwriting Company, with our trusty co-host, Vibhu. Welcome.Rune Kvist [00:00:10]: Thank you. Thanks for having me. Thank you.Swyx [00:00:11]: What are you announcing today?Rune Kvist [00:00:12]: We have raised $40 million, led by Ribbit Capital and First Harmonic.Swyx [00:00:17]: You first came to my attention when Nat and Daniel invested in you guys. Is the story, like, pretty much the same? Like, what are you today versus what you thought you were back then?Rune Kvist [00:00:26]: When we raised our seed round, we had a hypothesis that at some point risk was going to hold down adoption. At that point in time, that felt kind of hypothetical, and I think that is now over. Clearly, the moment is now with Mythos and Fable. It's pretty obvious that literally the binding constraint on adoption is risk. And so for us, it feels like this is a natural continuation of the same hypothesis, but where previously it was speculation, now it feels like fact.Swyx [00:00:54]: And let's get a list of the customers that you're highlighting as part of your Series A.Rune Kvist [00:00:58]: Totally. Yeah. So we are now working with folks like Cursor, Harvey, Lovable, ElevenLabs.Swyx [00:01:05]: Yeah. Amazing. Congrats.Rune Kvist [00:01:06]: Thank you.Swyx [00:01:07]: So you were famously one of the first hires involved in GTM and product. I'm just kind of curious: what was your path into AI? Just recap.Rune's Path Into AI: Scaling Laws, Capital, and AnthropicRune Kvist [00:01:18]: Yeah.Rune Kvist [00:01:19]: Late 2021, I sold a company, my first company, an edtech company. I had a bit of time to think about what was next. I came across the Scaling Laws paper, and that just struck me like lightning. I was just like, “This is a big idea.” In short, the Scaling Laws paper just says the bigger the model, the smarter the model.Swyx [00:01:38]: So this is the Kaplan one, not the Chinchilla one?Rune Kvist [00:01:40]: Exactly, the Kaplan one.Swyx [00:01:42]: Yeah.Rune Kvist [00:01:42]: And the important thing that clicked for me there was, oh, now capital will understand this. If you put in more money, you get more money out, and so that will kick off a hype cycle. And so you get a sense of predictable returns, which is, in fact, what's played out. And so I just packed my bags. I'd never been to San Francisco. I'd never been there. I just packed my bags, flew out here to find the people who had written it. And at the time, they had just started a small lab called Anthropic. There were around 40 people at the time or so. Drank a bunch of coffee until I eventually got introduced to Dario. And at the time, they were wrestling with some of these questions of, like, should we deploy our models? Should we make revenue? How should we engage with the rest of the world? They'd just broken off from OpenAI, and it's been publicly reported that they were kind of concerned with how they were dealing with deployment. So they were wrestling with some of those questions. At this point, this is early fog of war, like early 2022. The hottest product at the time was, like, Jasper. Like, there's nothing out there. So where value was going to accrue, and what the different parts of the stack were going to be, were all open questions.Swyx [00:02:48]: I want to highlight to people, you ask these questions because you have a PPE background.Rune Kvist [00:02:52]: Yes.Swyx [00:02:52]: I actually was in Singapore in one of the sort of feeder programs for prepping people for PPE. So I had a tutor. We learned, you know, philosophy and politics and economics. But, like, I think your kind of background matters. Machine learning people who read the neural, Scaling Laws paper would not necessarily draw the same conclusions that you did. Whereas any capitalist would read that and go, “Holy s**t.”Rune Kvist [00:03:19]: Correct.Swyx [00:03:20]: Right?Rune Kvist [00:03:21]: Yes.Swyx [00:03:21]: Who tipped you onto that paper? Because it's not a paper that you normally read, right, like, in your circles?Rune Kvist [00:03:26]: Yeah. I think I'd actually, ever since AlphaGo, had some appreciation that AI was a big deal.Swyx [00:03:36]: Yeah.Rune Kvist [00:03:36]: But it kind of felt like it raised all these kind of interesting philosophical questions, but it was kind of not clear from afar where exactly that would go. But it was obvious enough that it was like, this is going to be a big thing if we find the kind of right mechanism to kind of get the techno-capital machine to work on this. But it was just not clear. And so I think there was some way in which, like, that became obvious, and also it wasn't as obvious at the time than it is now, right? Like, it was just like, wow, this is so interesting. But it still felt, coming from kind of a philosophy and economics background, it felt like if this turns out to be true, you're going to be wrestling with all of the big questions in society. Everything you've learned about politics gets thrown out of the window. Everything you've learned about economics at least gets challenged. And so what felt interesting was to be at that frontier that has ramifications across everything. So that's why I sought it out.Swyx [00:04:32]: I mean, clearly really good insight. For people who don't know, the PPE program is, like, where prime ministers are born. So then you end up meeting Dario.Rune Kvist [00:04:41]: Yep. First Dario, yeah.Swyx [00:04:43]: Yeah. Well, I mean, like, so did you get extra insights from talking with them that you didn't get from your original hypothesis?Anthropic's Early Conviction and the Scaling Laws Crystal BallRune Kvist [00:04:50]: If you read the Scaling Laws paper, you get this, like, very vague sketch of like, wow, this seems kind of important. There are some lines on a chart. This seems kind of important. And what I think the team at Anthropic had thought more about than anyone was like, what are the implications of this if you really play this out? And back then they had, kind of vision documents for what the world would look like in 2026, and they were kind of in vivid detail playing out how much compute is going to be needed, what the CapEx was going to look like, what some of the societal concerns were going to be, but also what is the amount of economic value coming out here? And so it kind of felt like they held a crystal ball that in hindsight turned out to just be dramatically correct. And they weren't holding it like they were obviously correct. They were just like, “Take this hypothesis really seriously.”Swyx [00:05:38]: Think it through, yeah.Rune Kvist [00:05:38]: And think it through in the same way as the kind of situational awareness that isSwyx [00:05:43]: Across the street.Rune Kvist [00:05:44]: Across the street.Swyx [00:05:44]: Your office, yeah. Oh my God, we're all living across the street in the same one square mile.Rune Kvist [00:05:50]: Correct. And that's now a couple of years old, but also people keep referencing it these particular weeks with Fable and Mythos, and it's like, wow, if you take this one idea seriously- For the Scaling Laws, a lot of things fall into place.Vibhu [00:06:03]: And keep in mind, at this point, this is the same team that did GPT-1, GPT-2, and GPT-3.Rune Kvist [00:06:08]: Correct.Vibhu [00:06:08]: Which is also, like, it's not just some experimentation. Like, this is a real model that we just scaled up.Rune Kvist [00:06:14]: And they had deep conviction in this idea: if you take a big blob of compute and data, it just wants to learn, and out of that will come smarter and smarter models. And all the particulars were not clear.Vibhu [00:06:26]: Yeah.Rune Kvist [00:06:27]: And all the implications were not clear. But their deep conviction in this, like, core thesis, and that was kind of dizzying. It was both phenomenally interesting and exciting, and also very quickly you get to, like, the world we know today will no longer be if this hypothesis holds. So it also just felt, like, important in some kind of grand sense.Vibhu [00:06:48]: What kind of shaped you there? So that was early 2022. Not only had GPT-1, GPT-2, and GPT-3 come out, but, you know, the amazing founders of Anthropic that have never split up, the only ones, they actually had the conviction to leave OpenAI, start their lab. You said there were about 40 people there. What was the time like there?Inside Early Anthropic: Mission, Deployment, and RiskRune Kvist [00:07:06]: It was kind of remarkably like what it looks like on the outside today. Extremely cohesive, extremely mission-oriented, and living in this tension between their two ideas, which is AI could both go really well and really bad, and we want to be part of building it. That creates astounding amounts of tension. And they were wrestling with this incentive challenge where they know they're in a race that they're in where you might get forced to cut corners, but it also felt very important to them to be at the forefront of technology. And all of those ideas were just present at that time. It kind of feels like that line has been just very clear, and I think kind of love them or hate them, they have really stuck to their guns. There's a core set of beliefs that they hold more deeply than most companies hold any beliefs.Vibhu [00:07:58]: Yeah. Fast-forward to today.Rune Kvist [00:08:00]: Yeah.Vibhu [00:08:00]: What does that lead us to AI underwriting company? What are you up to? What motivated you to start this?From Waymo to AIUC: Confidence Infrastructure for AIRune Kvist [00:08:05]: Yeah. AIUC builds confidence infrastructure for frontier AI through standards and insurance. The link from Anthropic to building confidence infrastructure, looking out the windows at Anthropic offices and seeing Waymos driving by. Already back then, early 2022, Waymos were in some ways like AGI for cars. Like, they were superhuman drivers, but you couldn't take one to the airport. And now, four and a bit years later, you still can't take your Waymo to the airport, despite now everyone having kind of looked at the evidence and being like, “They're better drivers than humans.” So in that particular instance, what's clear is that the binding constraint on AI being useful is not capability, but is that liability or risk or trust. That problem is, general. The reason why right nowRune Kvist [00:08:52]: Fable is not open for access is not because it's not a good model, it's because it's a very good model. It's just hard to make promises about what it will or will not do. And this problem gets worse as AI gets better. Basically, more intelligent AI can be more autonomous. That's more valuable, but also the risk surface grows. And so - what Waymo illustrates is that unless you build the confidence infrastructure to make promises about AI, or at least bring light to the risks, you grind adoption to a halt. Governments, banks, hospitals, militaries need to have some sense of what AI will and will not do to be able to operate for them to incorporate it. And that's the problem that we're trying to solve. Now, why standards and insurance? If you trace this problem back through history, every technology wave has had some version of this problem. So if you go back to, like, year 1900, electricity comesVibhu [00:09:47]: Ben Franklin.Rune Kvist [00:09:48]: Cars burn down, sorry, houses burn down, lots of people die. 1930s, cars are a big deal, kill lots of people. 1950s, private nuclear energy is a big deal, poses big risks. In each of those instances, the market runs ahead of regulation to create confidence infrastructure because that's required to make go/go decisions. That is required for adoption, and the market fundamentally wants adoption. And in all of those instances, common blueprint emerges between standards and insurance. The reason these two components is standards kind of provide the rules of the road, and they also specify, like, what are the tests that need to be run so we can get a sense of how high the risk is. So take in the case of cars, that's like a car crash. Great, everyone, they inform your insurance pricing today, they inform your purchasing decisions, et cetera. That's basically the risk framework. The insurers are important because they pick up the bill. So they are the private institution that is most on the side of. That is best incentivized to quantify the risks truthfully and then figure out all the ways to reduce the risk ‘cause that increases their profit. So they're basically, they help shape the incentives. And these two work really well in unison. Now, how does that show up as a company? Well, one of the things that was obvious even - or starting to become obvious even a couple years ago was that frontier companies, some of our customers today, like Cursor, Sierra, ElevenLabs, Harvey, were going to have a very easy time selling a pilot to a bank. The, like, the demo just sells itself. It's magic. But bringing that through, if you want to do a wall-to-wall rollout at a bank or a hospital, you have to go through the risk process. These banks have no idea even which questions to ask, let alone which answers are sufficient, let alone, like, how do they go and test whether these agents actually work the way they're supposed to. And so they had this problem of, like, what can we say to earn the trust? And we think there's, like, a golden sentence that goes something like, “Hey, I hear you're really worried about hallucinations or jailbreaks or whatever it may be. We've had an independent third party test us against the gold standard. We passed with flying colors. And as a vote of confidence, the world's most conservative insurers have looked at the data.” And they're willing to take some of the risk onto their balance sheet.Swyx [00:12:06]: Yeah.Rune Kvist [00:12:07]: So if something does go wrongSwyx [00:12:07]: There's money behind it, yeah.Rune Kvist [00:12:09]: Exactly. So that's kind of like the link between all this. We can get into some of the hard parts related to the technical testing, which is, I think, the crux of the matter, but I'll pause there.Swyx [00:12:19]: How did you and Rajiv come together? This-- there's always, like, you come across very confident and, you know, and we're announcing your Series A and all these things, but I want to see, like, the early initial stages of, like, idea formation.Cofounding AIUC with Rajiv DattaniRune Kvist [00:12:31]: Yeah. Rajiv is actually my soon-to-be brother-in-law.Swyx [00:12:35]: Oh.Rune Kvist [00:12:36]: So I'm actually, in a week and a half getting married to Rajiv's sister.Swyx [00:12:42]: Okay, now you're tight.Rune Kvist [00:12:44]: Exactly.Swyx [00:12:44]: Now you know.Rune Kvist [00:12:45]: So - Rajiv and I have known each other for a decade. Funny story, I met both Rajiv and his sister, Hena, at the same time when Hena and I were interns at McKinsey in London, and Rajiv was assigned as my mentor. And so met them at the same time. For the longest time, it was not obvious that we were necessarily going to work together. I was in startups. He was, an insurance partner at McKinsey. Three or four years ago, I think Hena convinced him that AI was going to be a really big thing. And so he quit his job, cushy partner job at McKinsey in London, packed his bags, flew to San Francisco, and ended up joining METR. You guys are probably online enoughSwyx [00:13:24]: CEO.Rune Kvist [00:13:24]: Exactly.Swyx [00:13:24]: We've, we've, we've heard of METR.Rune Kvist [00:13:25]: You see the plot-- the chart of the horizons of the tasks that agents can take on is doubling extremely fast. So he was COO at METR, led their partnerships with Anthropic and OpenAI to test their models before release, but also working closely with the US and UK government, to figure out, like, how do you know whether a model can be released? And in some ways, that was, like, the perfect background. He's spent a lot of time in insurance, knows that world, spent a lot of time with frontier testing of models. And so when I was bumbling around this idea space, starting with some of the ideas we talked about related to Waymo, as soon as we got into the content, we were both like, “Oh, this would be an amazing business to build together.” This is wrestling with the problem that we both think is the most important in the world from a market angle, which is kind of our intuitions is that the market can do a lot, and the faster AI moves, the harder it is for government to solve some of these problems. And then it took a little bit of time to work through what is it like to work with family.Swyx [00:14:27]: Sure.Rune Kvist [00:14:27]: And,Swyx [00:14:30]: Because you were already dating at the timeRune Kvist [00:14:31]: Yeah. Yeah, exactly.Swyx [00:14:33]: Yeah.Rune Kvist [00:14:34]: Already back then, itSwyx [00:14:35]: Yeah.Rune Kvist [00:14:35]: We felt like we were a family.Swyx [00:14:36]: Nice.Rune Kvist [00:14:36]: And so starting a business together felt like kind of a big step. And, here we are with just immense amounts of trust.Vibhu [00:14:43]: Yeah. So now you're a company of how big? How big are you guys now?AIUC-1 Certification: Agent Security, Safety, and ReliabilityRune Kvist [00:14:46]: There are just 20 of us now.Vibhu [00:14:47]: 20 of you guys now, have Series A, and you have your first certification out, the AIUC-1. Let's bring up the certification. So this is the agent certification, right? What goes into the process? I have, like, two questions here. One is, walk us through the certification, and two is, what is the process for a company to get certified, you know?Rune Kvist [00:15:08]: Great. As it says right on the top, AIUC-1 is a standard for agent security, safety, and reliability. The fundamental design principle is take all of the concerns that slow down adoption, so all the questions, all the fears that keep, security leaders in the Fortune 1000 up at night, and put them into one comprehensive framework. That's what you'll see there. You can see the six categories. Two, you want to ground all of this in technical testing. So one of the concerns with security standards that often feel kind of like theater paperwork is that they're not actually ground out in, does any of this work? Does any of this matter? And so we had a conviction from early on that was going to be the kind of crux, was to pass this, you must get tested every quarter, basically run thousands of simulations to see, well, so can it actually be jailbroken? How hard is it to jailbreak? How often does it hallucinate? How often does it leak data? Et cetera. And then the last, core idea here, if you scroll up to the top here, is to refresh it quarterly.Rune Kvist [00:16:08]: So the core trait of AI is that it moves extremely fast. Whatever concerns we're discussing today were not the same ones three months ago, and this will keep changing. Typically, standards update on a, like, a decade cycle is obviously not going to work. But the question is kind of how do you update it? And the core thing here was to basically get the risk leaders of the Fortune 1000 around the table. So if you go over to the left hereVibhu [00:16:32]: YeahRune Kvist [00:16:32]: You'll see the AIUC-1 consortium. The consortium is a group of risk leaders who run real banks, real hospitals, real critical infrastructure, who are facing these challenges every day. And we meet with these folks twice a quarter and hear what's top of mind, what is keeping them up at night. There's tremendous amount of desire for that conversation. And then we operationalize that into a specific standard that gets into. And actually, we can go into and look at whatVibhu [00:16:55]: YeahRune Kvist [00:16:55]: What even is the standard. So if we go back to introduction, out there to the left, scroll up a little bit to the wheel, click into reliability. So if you take something like hallucinations sits in reliability. There is a number of requirements here. If you go into the top one, prevent hallucinated outputs, hallucinate outputs, this is one particular requirement. This is a technical control. Basically, we want some kind of ground in this filter. The first thing you see here is what's called a crosswalk. So everyone and their grandmother has put out a framework, very high-level framework for what are the AI risks.Swyx [00:17:27]: This is basically your competition,Rune Kvist [00:17:28]: In some ways our competitionSwyx [00:17:29]: Not seriously, yeah.Rune Kvist [00:17:30]: We're, in fact, friends with them. We'll come back to why.Swyx [00:17:31]: Yeah.Rune Kvist [00:17:32]: But mapping everything together so you have one superset. The claim you're trying to support here is, if you follow this framework, then you can also see how you follow the other frameworks. But the meat of it comes down here in control activities and evidence. So control activities is like, great, you have this high-level requirement. How do you turn that down to something operational? Here's what you must do, and then what is the evidence that we're looking for?Rune Kvist [00:17:57]: And the reason we go this deep is that there's actually not that much confusion about what are the big concerns in AI. Everyone agrees to these. The question, like, what are you actually supposed to do? And so. What we found a lot of demand for is getting down to the specific evidence, that people need to look for. Whether you are Cursor building something or, even JPMorgan building something, but also if you're just a risk leader at JPMorgan, like what exactly should you ask for? What can you ask for without sounding stupid? Like if you ask for some-- you won't believe the amount of time a risk leader has asked for the IP rights to the underlying model to Cursor or something, and you're just like “Sorry, what?” Like,Swyx [00:18:39]: You slip it in there and you seeRune Kvist [00:18:40]: SlipSwyx [00:18:40]: See if you notice.Rune Kvist [00:18:41]: See if they. Exactly.Swyx [00:18:42]: Yeah.Rune Kvist [00:18:42]: Put that in the questionnaire. All right, so that's kind of what our standard is, and we update this every quarter with these folks, to keep up with the latest concerns.Swyx [00:18:51]: Can I double-click on this one?Controls, Evidence, and Third-Party TestingRune Kvist [00:18:52]: Yeah.Swyx [00:18:52]: So first of all, the website's beautiful. Like, it's so confidence-inducing which is the whole point where, like, okay, I know exactly what I'm signing up for when I talk with you. Like, I don't even have to talk to you. I can just see your whole, certification, which is great. But, like, okay, so from here, like D001.1 configure a groundedness filter, how does that get applied? Like, you have a person thatRune Kvist [00:19:16]: Yeah,Swyx [00:19:16]: Goes through it?Rune Kvist [00:19:17]: If you, go backVibhu [00:19:19]: I did see somewhere there's like, you know, fifty-one requirements, a hundred thirty controls. There's like a wholeSwyx [00:19:25]: Right. I just want to. Like, to me, this doesn't translateVibhu [00:19:27]: Yeah.Swyx [00:19:27]: Into a test or an eval.Rune Kvist [00:19:28]: Yes. So if you go into, on the left-hand side. So actually, if - before we go in there are three types of requirements. The first is technical controls, like you must implement some guardrails.Rune Kvist [00:19:42]: Two, there are test controls. So you must have an independent third party go and run some tests against you. I'll show you one of those in a second. And then three, there are policy controls. For example, you must have a person whose name is on the line when you guys f**k up, and you must have a plan for how you tell your customers and how you engage with them. They're kind of more traditional, standard type stuff. So in this particular instance, we just check whether they in fact have a ground in filter. So we will partner with an auditor. So we partner with auditors like KPMG or like Schellman who go in and do the thing auditors do, which is to check the evidence. In this case, that might be a screenshot, it might be part of the code that they need to review to see that it actually. Just that it exists.Swyx [00:20:21]: Oh, okay.Rune Kvist [00:20:22]: And then the second thingSwyx [00:20:22]: So you're not testing the effectiveness of it.Rune Kvist [00:20:24]: That's the second thing. So if you go downSwyx [00:20:25]: Yeah.Rune Kvist [00:20:25]: To the third-party testing for hallucinations out on the left, that's basically the next requirement. This is where we test how well does it actually work.Swyx [00:20:32]: Okay, and is it you testing or the auditor?Rune Kvist [00:20:34]: We test them.Rune Kvist [00:20:35]: We test them.Swyx [00:20:36]: That's a lot of work.Vibhu [00:20:37]: How long does testing take? So if I want to get certified, justCertification Timelines, Remediation, and Quarterly UpdatesRune Kvist [00:20:40]: Yeah.Vibhu [00:20:40]: How long does the end roughly take?Rune Kvist [00:20:42]: Yeah, the end, almost always is dependent on, like, our customers needVibhu [00:20:47]: Yeah.Rune Kvist [00:20:47]: To look something for us. It takes somewhere between, like, 3 to 10 weeksSwyx [00:20:52]: Yeah.Rune Kvist [00:20:52]: Depending on how up to snuff they already are. So some people show up to us with, like, extremely rigorous security programs. When we test them, it works extremely well. We can get that done very quick. Some people come to us, and they're not that far along. We give them kind of the spec that they need to build towards, and then their security teams and engineers get to work and build to meet the standard. The testing itself typically takes a couple of weeks, including the time for them to remediate. Often, we'll find something that we cannot pass, where this is actually just not up to the standard. - you won't pass the standard. And then they will need to go and implement additional safeguards or additional remediation that makes them more robust so that they can actually kind of hand on heart look at their customers in the eyes and say, like, “Hey, we've done truly our very best.”Vibhu [00:21:35]: And they're certified for a year and have quarterly updates?Rune Kvist [00:21:38]: Correct, yeah.Vibhu [00:21:39]: And, yeah, it's pretty interesting. I think, you know, what's changed since. So this is certifying agents in production, right? Your customers, like you've had Lovable, ElevenLabs, Intercom, and they've all gone through this certification.Rune Kvist [00:21:50]: Yes.Vibhu [00:21:51]: What has changed? So I see you post, like, you know, Q2 added MCP agent,How Agent Risks Are Changing: Coding, MCP, and Agent-to-Agent InteractionsRune Kvist [00:21:56]: Yeah.Vibhu [00:21:56]: agent communication. Any other things that you want to kind of highlight since the first iteration? What comes in quarterly?Rune Kvist [00:22:03]: Yeah. So some of the changes have just been agents are not just one thing. So, like, if you take agents like Cursor and compare them to Sierra, they're really quite different. And compare them to Harvey again, compare them to you out of againSwyx [00:22:16]: ElevenLabs, yeah.Rune Kvist [00:22:17]: ElevenLabs, they're all quite different. And so we wanted to design a standard that works for all of the types of agents. And we started with one that was, like, pretty text-based, like, honestly, pretty customer support-focused. That's where there's a lot of existing demand. And then over time, we've picked, some of the frontier companies in each of these other domains that we could work with and build out the standard, so, such that we know that the same standard works for code, it works for customer support, works for automation, et cetera. So that's been one big thing. Yeah, then some of the things that have been top of mind recently, Mythos is bringing up a lot of concerns for security leaders. We're starting to get more and more questions around agent interactions. It's very nascent, at the moment, but it's starting to emerge. There've been a lot of, questions related to OpenClaw and MCP. Again, like agents starting to interact with each other, is really top of mind. Then as coding agents have really taken off, that's also where banks and hospitals, et cetera, are getting more and more precise on what it is they need. So really dialing in as that start to be, like, where most of the tokens flow through in the world, getting much sharper on that.Vibhu [00:23:26]: Can you share for people that are listening that don't really think about this? Like you mentioned, there's the obvious stuff, you know, hallucination, citations. What are best practices that people should do when building agents? Like, if they come to you pretty ready with certification like, you know, they'll probably pass certification. What are the things people don't think about that they should have?Best Practices for Agent Builders: Stress Tests and GuardrailsRune Kvist [00:23:46]: The most important thing is that a lot of companies have not done a serious stress test. They spend most of the time, perhaps rightly so, optimizing for how does it work in the good case, the average case, how high-quality is the output for the customer. And a lot of these companies are pretty new, so they haven't spent a lot of time stress testing the what is there as an adversary on the other side? What are some of the complicated corner cases that you've not really considered? So I think that's, like, a frame of mind. And you'll also see this in startups. It often takes a while until they hire their first security person. They- And that's a whole different kind of risk surface than just building a good product. So a lot of that applies. Most companies actually also have the right kind of architecture. Most of them will have some kind of guardrails in place, either some that come out of the box from their model provider or they'll have built their own filters that sit in between. They just don't work very well. The difference between putting a classifier in place that, like, maybe goes and checks whether you're giving medical advice when you shouldn't and says, “Hey, if this looks like medical advice, filter it out.” Lots of companies have that in place. The question is whether it works. And it's actually pretty fiddly to sit down and think about all the ways in which you could ask for medical advice, read the academic literature on what are the kinds ofRune Kvist [00:25:03]: Framings or tricks you might play to get an AI to give you medical advice when you really shouldn't. And so there's, like, an area of expertise that's just missing. So what we find is that most people have the right building blocks in place. They don'- It doesn'- It's not rocket science, but the finicky thing is, like, getting into the corners and testing whether it works such that you can look your customers in the eye, or maybe a bank or maybe a hospital and be like, “This is going to work for you.”Vibhu [00:25:26]: I see. So we talked a lot about the agent-level certification. Where do you guys go from here? So announcing series A camera, we talked about this a bit. There's the whole security risk of Fable, government stepping in. You guys are kind of announcing that you're also going into model certification?Toward Model Certification: The Government–Lab Trust GapRune Kvist [00:25:46]: When we do a bit of cutting afterwards,Vibhu [00:25:48]: YeahRune Kvist [00:25:48]: We will not yet be announcing this,Vibhu [00:25:49]: NiceRune Kvist [00:25:50]: The question that is top of everyone's minds now is at the model level. And Mythos, then Fable, has really brought this to the fore that in addition to the commercial risk and the kind of economic security risks that are happening at the agent layer, the models are going to present risk in the national security category. The shape of the problem is very similar. You have some people that are on the hook if something goes wrong. In the case of agents, it's often security leaders in the enterprise. In this case, it's the government. They don'- haven't necessarily spent their entire lives thinking about what are the new risks that come here, what is the kind of data you might be looking for, how might you test that? But they do have to make sure that their concerns are addressed. You have some frontier AI companies that are deeply technical. They know a lot about the risks, but they fundamentally have an incentive to not always be truthful. So you have a trust gap between the government and the labs. And in every other industry, you end up with some kind of body sitting between, a neutral third party sitting between those people. There's no other industry where you allow people to audit themselves. So there is going to be a need for a third party that can take the rigor of the labs to run frontier technical evals, but can also speak legible trust in the way that the government trusts PwC to go and run financial audits. And they know that they output audit reports in a way that's consistent, that's easy to read, that's factual, that's, trustworthy. Those two things need to be brought together. And what we've learned from our work with agents is that if you want those-- that communication between those two parties to be smooth, there has to be one common standard that is public, that people can go and inspect. What are the risks that matter? Within each of these risks, what are the kinds of threat models that you're really looking for? You need to specify for each of those risks, what are the guardrails that need to be in place, and what are the tests they need to run to see whether those guardrails are effective? And then you need to go and run audits that are - technical audits that are consistent. So if you're trying to bring trust, it's extremely important that you methodically work your way through the risks. You can't send one researcher in and say, like, “Come back with whatever you find.” You need to be able to explain exactly what you did, exactly what you tried, exactly what you did not try, and therefore the kinds of promises you can and cannot make at the end of it. I think ofNeutral Third Parties, CAISI, and Model Risk AuditsRune Kvist [00:28:13]: Fable as a direct symptom of this problem that the government was told that there's a risk. The government may struggle to assess just how big that risk is. They call Anthropic, and Anthropic is trying to tell them, “Hey, actually, every model can be jailbroken.”Swyx [00:28:28]: That's not what you want to hear, right?Rune Kvist [00:28:32]: As the government, that might be hard to trust.Rune Kvist [00:28:36]: And we think that a broker is the most natural solution. In other markets, you see something like, in financial markets, you see Moody's. Moody's goes in, and they look at a bond, and they output a rating. They say like, “Here's the evidence we found. Here's the rating.” We don't decide whether anyone should buy this bond or not buy this bond. Well, that depends on their risk appetite. But we do provide this common information layer that everyone can rely on. In the case of Moody's, the government, points to them and say, “Hey, pension funds, you should probably really take care. You shouldn't risk your pensioners' money, so you can only invest in triple-A rated bonds.” That means that now the government doesn't have to staff thousands of financial technical experts to rerun forecasts every week to see whether things are correctly rated. They get to point to some neutral third party. So my hypothesis is, my hunch is that you will see a third party that sits between the government and the labs, and it could either be the government builds it themselves. So something like CAISI was set up to do exactly this. And the questionSwyx [00:29:44]: Sorry, I'm not familiar with CAISI.Rune Kvist [00:29:45]: CAISI is the Center for AI Standards and Innovation.Swyx [00:29:49]: Okay.Rune Kvist [00:29:50]: I won't get into the details, but it's a body of NIST that typically sets standards. So it's basically a government body that has AI experts. Yeah, exactly. Exactly.Swyx [00:29:59]: Very key. Very key.Rune Kvist [00:30:00]: Very key.Vibhu [00:30:00]: I think, you know, it's one of those things where when you just sit back and listen-- look at it, like, is there enough technical expertise in the government to measure, test these things right now? Probably not, right? And Fable is a result of, okay, we've had to scale back and pause things,Rune Kvist [00:30:17]: Yeah. And they have excellent people, but they have an extraordinarily small budget compared to the scale of the challenge that's ahead of us. And I think they have a role to play. The question is kind of like, who does what? We have now outlined the jobs to be done, and they're quite extensive. Every model release, there is an astounding-- Given that they take in any input, their risk surface is astounding. And so the question is really: what can only the government do, and what can the market provide here that can keep up with the pace as AI risk changes? Our perspective is that also at the model layer, the risks that people care about today are not the same ones they cared about three months ago. So the pace of legislation is too slow to deal with pinpointing the risks here. And so we think there's a lot that the market can do to surface timely information. Ultimately, there is a bunch of policy decisions here. Is the national security risks of a model too high?Swyx [00:31:12]: Yeah.Rune Kvist [00:31:12]: That's a political answer. But what we want to make sure is that the process that produces this risk information is compatible with very fast innovation. So you don't want to. This is not a question of like, can you slow the things down? Can you keep, the models locked up until-- for months on end until everyone can make a guarantee? But it is this, can you, in the time it. Given that the US is competing with China on releasing models, can you insert risk information that allows the government to, like, make rapid decisions on some of these questions? Balancing that trade-off between failing to adopt AI is going to put us at risk, but also reckless adoption is going to put us at risk. And that's a very kind of fine balance that they're going to need, like, a lot of high-quality intelligence to make.Chinese Models, Data Flows, and National Security ConcernsSwyx [00:31:55]: Just a side mention, because you mentioned Chinese models, any specific concerns that you're hearing from your CISOs about that? ‘cause I guess it's free, but.Rune Kvist [00:32:05]: CISOs have a bunch of concerns around data flows in general that they're really concerned about. So there's a lot of questions like, if these models are Chinese, where does that, where does that data go? I think a lot of this can be addressed, but they come up often.Swyx [00:32:18]: I mean, they understand they're running on American GPUs.Rune Kvist [00:32:21]: Some of them, some of them understand that they're running on American GPUs.Swyx [00:32:23]: They're not, like, phoning home every time you, like, call home.Rune Kvist [00:32:26]: No. A year ago, there was not a lot of understanding of this. I actually think, you're seeing the security leaders becoming kind of AI literate at a blistering pace, and you're actually also seeing my Twitter timeline that's very pilled and my LinkedIn feed that used to not at all be pilled kind of converge. They're both talking about Fable.Swyx [00:32:45]: Right. Yeah, that's true.Rune Kvist [00:32:46]: They are both talking about whether you can prevent models from being jailbroken these days.Swyx [00:32:51]: Yeah.Rune Kvist [00:32:52]: Like national security national security risks are now the conversation that is actually emerging. Other than that, I think you mostly see a kind of general picture: there are no concerns with any particular model or any particular model output, but there is a general nervousness of having critical infrastructure run on models that are not produced in America by Americans where the American government has control.Swyx [00:33:14]: But it doesn't necessarily show up in your framework that directly, or it might, I don't know.Rune Kvist [00:33:18]: There's a bit of stuff in there actually on the, like, the provenance of the models and disclosing that. But I think there's a bunch of use cases where running a Chinese open-source model is just the best solution.Swyx [00:33:27]: Yeah.Rune Kvist [00:33:27]: And a concern is slightly more macro here, which is not best addressed at any particular certification level.Vibhu [00:33:32]: Is there anything interesting that you see at the. You know, if you're trying to fill that middle gap, that mediation gap, any interesting stuff that you guys forecast would be required other than, you know, what the average person might expect?Cyber, Child Safety, Bio Risk, and Expert CoordinationRune Kvist [00:33:47]: There's a bunch of interesting questions about what are the risks that matter here. So right now, the risk of the day is cyber, because it's very real, very tangible. And some of the risks that are also emerging as pretty real and pretty tangible are things like child safety is becoming both extremely important, but also politically important. And then there are some of the risks that are coming down the pipeline that today feel kind of speculative, but people who spend a lot of time with the models see them coming down is things like, risks that relate to biology.Rune Kvist [00:34:18]: And specifically whether models will help adversaries produce biological weapons and making that extremely cheap, extremely accessible, producing-- making the chance of another COVID or worse pandemic. COVID was not engineered to be bad, as if you were trying to do that. So I think those are some of the risks that are coming down the pipeline. I think one other thing to just note is that agents are kind of deliberately narrow. So, like, when a frontier agent company puts a chatbot that interacts with customers, they've really tried to narrow the topics it's interested in talking about. Such that if you ask it, like, “What do you think of the president?” it will just decline, which means that the kind of risk area is somewhat smaller. For models, it is infinite. And so there's not a single expert out there who can competently evaluate the risks of cyberattacks and fifteen-year-olds having month-long conversations with a chatbot and seeing whether it will in fact recommend suicide or something horrendous like that, and can evaluate the risks that terrorists can use AI to produce bioweapons. The risk surface is just too big. And so the central challenge actually becomes how do you get those subject matter experts to work within a one coherent framework that outputs one coherent report and rating that the world can go and inspect? ‘Cause that global perspective is central, but there's not a single organization today that could produce that.Swyx [00:35:47]: And you would be the presumptive one when you put out your model standards.Rune Kvist [00:35:51]: We think there can be one company that can, with a consortium of experts, build one coherent standard. I think we've shown that across all of the enterprise risks today. We think it could be one company that could, with a consortium, specify the audit rules, basically like the inputs and outputs that all these technical experts need. What access do they need? How should they treat infosec- info security? They can look at whether the eval- evals are well-produced without necessarily being able to say, “Hey, is this a threat or not a threat?” But overall, evaluating whether the evals are good, well-constructed, that set of audit rules that basically becomes the interface for all these experts, we think one clearinghouse could put together. To be clear. When I say one company, I think of it as one company coordinating lots of this in the same way that when we saw our consortium, it's not like we say we have all the answers on agent security. What we say is we are taking on the role of eliciting all of the concerns and being the secretary that puts it together and runs a tight house such that the standard updates lockstep every quarter, and that the audit reports that come out, in this case, 100-page audit reports, uniform and crisp and clear all to the level of detail that is required for executives that need to make a clear go/go decision. So that's kind of the role that we think we might play.OWASP, Frameworks, and the Operational Audit LayerSwyx [00:37:11]: I think in many ways you're performing the role that OWASP used to do there, and you said, like, you know, competition and partners.Rune Kvist [00:37:18]: Yeah.Swyx [00:37:19]: Can you go more into, like, how they partner?Rune Kvist [00:37:20]: Yeah. So first of all, OWASP is basically an open source community of security practitioners that are coming together to build frameworks for addressing the latest security concerns. We think they are phenomenal at creating frameworks. We'- In fact, we'- First of all, we're partners with them, so we have a joint article. Two, we've learned a lot from them. We think they're a tremendous source of intelligence. What OWASP does not do is building the machine that runs third-party audits such that a company like Cursor or a company like JPMorgan could get a third party to go and review them against this and say, “Hey, you've passed the standard, and here is the report that you can use to build trust and preempt your partners' or customers' questions.” So they fundamentally try to do something different. You - They are part of the information gathering and intelligence gathering and creating clarity, but the operational layer of turning this into promises is not the business they try to be in.Swyx [00:38:14]: The standard is emerging and is doing very well. Was it necessary to then also do underwriting? Obviously it's in the name, so please remember you thought about it first. I feel like if you just have enough consensus, you don't actually need the money angle, but it does help.Vibhu [00:38:30]: I did want to also note, you guys are a profit company too, right? It's not profit where there's a whole business side to it as well?Why For-Profit Standards and Insurers MatterRune Kvist [00:38:39]: Yeah. Yeah, so I'm just getting crazySwyx [00:38:41]: I think about the money part.Rune Kvist [00:38:42]: Yeah. Yeah, let's get into the money part. Let's start from actually your question, profit versus profit. In the security space today, cybersecurity, most of the standards are produced by nonprofits. I think that's an issue.Rune Kvist [00:39:00]: The question you have to ask yourself is, how do you create good incentives for these standards to be good and keep up?Rune Kvist [00:39:09]: Nonprofits tend to not have these adverse profit incentives where they, hollow out their standard and create a race to the bottom, but they're also not at all responsive by default to the communities that they serve. There's no process-- They don't have customers that they serve where they go and ask, “What do you want? What do you want? What do you want?” And when you look at the overall satisfaction with the security standards today, people tend to just not like them very much. You do see in other domains, that profit standards can serve the world quite well. So there are examples, like we talked about Moody's before. It's not without flaws, but, it is absolutely critical societal infrastructure that gets run at an astounding scale today. Your credit score, it's FICO. It's also a profit business. And when you go back even further in history, some of the crash testing standards came out of insurance companies.Rune Kvist [00:40:06]: The insurance companies together founded the Insurance Institute for Highway Safety because they were very interested in, like, how can we use standards to drive down mortality and save money? Go back, prior-- Our name actually pays homage to the Underwriters Laboratories, UL, which, was started right around when electricity came out. Houses started burning down. Insurers, again, were paying the bill, and they were maybe also good people, but their profit incentive was, let's prevent houses from burning down. Let's test all the electrical products, the light bulbs. All the light bulbs in here are probably tested, the toasters, et cetera. And they set up, an entity to create those standards. Today, UL has a profit entity and a profit entity. What they've recognized, they spun - They started profit. They spun out a profit because what they recognized was like, hey, actually to serve customers well, you need a profit entity. The lesson here is one of the ways that the market can align incentives so you're both responsive to customersRune Kvist [00:41:07]: And not hollowing out your standard over time is to align it with insurers because they fundamentally have good incentives. And so if you're a profit standard that works closely with insurers, you get the feedback loop in such that you're really tuned into your customers, but also have their interest at heart. So that's the model that we - the kind of inspirational model that we've learned a lot from, and that's also where the name comes from. In some ways, the term underwriting can both be associated with insurance, but it's also a broad term for, like, making decisions.Rune Kvist [00:41:40]: If you underwrite a decision, you're fundamentally kind of taking ownership for the consequences of it.AI Insurance Contracts, Lloyd's of London, and ElevenLabsSwyx [00:41:45]: Yeah, I mean, what does an insurance contract look like for AI?Rune Kvist [00:41:49]: Yeah. Most of the demand comes today for insurance contracts is, sitting between people who've built AI and people who are buying AI.Swyx [00:41:56]: Yes.Rune Kvist [00:41:57]: And what you want—the reason why people want insurers involved, both for the traditional reasons, hey, if something goes wrong, we want to be compensated, but it's in particular because insurers can bring trust to the equation. Because insurers will pay for the damages, if they're willing to write an insurance policy, that is them saying, “Hey, we think there is risk here, but that is manageable.” And that is kind of a. Their incentive aligns with the enterprises adopting it, so that's a really a good signal to the market. In the same way, actually, one of the things that Waymo tried to get their first permit to even operate in San Francisco was to get a lot of insurers to stack up a huge insurance policy. In the case if something went wrong, not because Google can't pay, but because it was very valuable to have a third party go and look at that dataRune Kvist [00:42:47]: That are trusted by governments, trusted by enterprises as conservative people and say, “Hey, we've looked at it. We're actually willing to take some of this on our balance sheet.” So that's, that's kind of the reason why people are interested in it. What it looks like is, in some ways like every other insurance contract. You specify what are the perils you want to cover, how much do you want to cover them, like up to what limits, and what does it cost to cover that. And in the case of, if we take a really concrete example, ElevenLabs, bought a first of its kind AI agent insurance policy. They work with some of the biggest, enterprises that work with governments. They're really interested in going above and beyond and making promises to their customers. So they wrote a policy that covers just some of the core concerns that their customers have been asking about. And, the crucial thing was really to get Lloyd's of London, the world's oldest insurer, one of our partners, to look at this data and be that third party alongside us to say, “Hey, we think there's something here that's worth underwriting.” and that's actually what it looks like. And so they will show that contract to their customers, and they can see how much they're covered for. They can see what exactly it covers, and that will also probably change next year. They will want to write an insurance policy that might cover more.Swyx [00:44:04]: When you say Lloyd's, is it reinsurance, or are they sharing somehow at the same level orRune Kvist [00:44:11]: Yeah. So typically, the way, new companies get into insurance is that they partner with insurers such that the insurers take the majority or all of the financial risks. Fundamentally, if insurance is useful, because it brings trust, you have to be able to pay the bill. Lloyd's of London is 400 years old. They've never not paid a claim. They're extremely trusted. What Lloyd's of London struggle to do on their own is to figure out which of the risks are real, what should we be looking for, what are the kinds of technical controls, and running the tests. So they use AIUC-1 as kind of the underwriting framework, and we produce a bunch of eval results that then directly feed in to inform the pricing. So this means that ElevenLabs customers know that payment will be there. They don't have to look to our series A and see, like, do we think they have enough cash on the balance sheet? They will look at Lloyd's.Swyx [00:45:05]: Yeah.Rune Kvist [00:45:05]: Yeah.Swyx [00:45:05]: And Lloyd's, like, famously very creative. I think I remember some headline like, they insured Jennifer Lopez's, butt or something.Rune Kvist [00:45:13]: Correct.Swyx [00:45:13]: Right?Rune Kvist [00:45:13]: And I think, was it, David Beckham's right foot?Swyx [00:45:16]: So, yeah. Right?Rune Kvist [00:45:17]: And stuff like this.Swyx [00:45:18]: So, like, clearly not a large data set.Rune Kvist [00:45:22]: Exactly. It's actually a remarkable institution that's both kind of has some of the truly school virtues of having been around for a long time. They, like, really. They really operate like a trusted entity, and they have appetite to figure out the future. And I think there's a lot of recognition that both there is, like, tremendous amount of risk in AI that is poorly understood today, so getting into this business carries real risks. But also this is where lots of the risk exposure will happen in the future. This is the one market where risk is truly growing. This is the one market that will also take out some of the existing markets. Take, like, auto insurance. When there are no human drivers, how's that market going to look? Well, it's clearly going to change. How are you going to assessSwyx [00:46:08]: You want to insure Waymo?Rune Kvist [00:46:10]: I. All I'll say is the principles for how you insure Waymo are very similar to how you insure other kinds of AI.Swyx [00:46:15]: Right.Rune Kvist [00:46:15]: So again, crash testing, that's what we do for customer share at Lovable. That will also need to happen for Waymo, which is not how you do it for human drivers. So there's this growing awareness that the world is changing very fast, and the only way to learn how to underwrite AI is to write some policies. You may incur some losses and think of that as R&D expense, really. But the question for them is, like, who are the trustedtechnical partners they can get into this business with that can help them navigate and make sure they don't make, kind of foolish mistakes? But also who is willing to hear the wisdom that they have? They've done this before. They've seen it was. They were there when cyber came out. So there are lots of ways in which AI feels completely new, but there's also lots of ways in which risks look the same. And so there's actually a tremendous amount of wisdom sitting in some folks that may have gray hair, but really have, like, a keen sense of, how to quantify risk.Swyx [00:47:08]: Yeah. And the number is. So it's basically like I want fifty million dollars worth of coverage against these perils, and Lloyd's will give you a quote on it, and then you have, like, a small markup or something, and then you turn it around and do that? Is that as simple as it is?Risk Capital, Premiums, and Working with InsurersRune Kvist [00:47:23]: You basically share some of that premium.Swyx [00:47:25]: Yeah.Rune Kvist [00:47:25]: X percent goes to the people who do the pricing of it.Swyx [00:47:28]: You're. It's kind of like a. It's kind of like a merchant bank for insurance type of thing.Rune Kvist [00:47:33]: Exactly. You basically split the fee, and you can think of the insurance supply chain as, like, there's bringing the capital, there is doing the pricing, and there is doing the distribution. And typically, you will pay out some X percent of premium here, Y percent of premium here, and the rest of it will go here.Swyx [00:47:46]: Does all the insurance world work like this, or is there some point at which, like. So if right now you have equity capitalRune Kvist [00:47:51]: Yeah.Swyx [00:47:52]: At some point, maybe you start raising, debt or whatever, and then you have enough of a bank account and enough history, let's say you've been in operation for ten yearsRune Kvist [00:48:00]: Correct.Swyx [00:48:00]: That you don't need Lloyd's anymore?Rune Kvist [00:48:02]: That's totally an option. And I could see some worlds where that makes sense, specifically if there are risks that we feel high confidence that we'd want to insure where the incumbent insurers are too slow to find appetiteSwyx [00:48:13]: Okay.Rune Kvist [00:48:13]: Or simply struggle to evaluate it such that they don't want to do it. But by and large, in general, you do not want to compete with insurers on, bringing risk capital to the game for two reasons. One is that's fundamentally a cost of capital game. They have extremely low cost of capital. Startups have high cost of capital, by and large. And two, you want to hedge your bets, and it's very helpful then to also have a portfolio of home insurance, of car insurance. And we're not about to become a car insurer nor a home insurer.Rune Kvist [00:48:43]: So they have some natural advantages, which makes it much more likely that we'll partner.Swyx [00:48:48]: Yeah.Rune Kvist [00:48:48]: And they bring that, the capital at scale, and we bring the technical expertise.Swyx [00:48:51]: You're, you're going to work with them for a long time.Vibhu [00:48:52]: How are the discussions with the insurers as well? So basically, they're going off of your certification, right? They're trusting the diligence on you that your certification is valid, you tested the right things, and they're backing the money that, you know, you have the right testing in place. So any interesting takeaways from working with insurers?Rune Kvist [00:49:12]: I think the maybe the first thing is they feed into the standard as well. So if there are things that they feel like they need that they're not seeing, we are also taking that as input into the standard, because fundamentally we think a good standard is one that creates a really healthy promise ecosystem, and we think insurers are a critical part of that. And again, they are the most well-incentivized to. They see all the lost data across every. Any particular CISO knows their particular concerns. Insurers see the concerns across the entire portfolio and often have direct access to, like, what exactly happened, who was at fault, et cetera, as they do part of their forensics. So they're actually, like, a great source of intelligence on this. One of the big takeaways from cyber insurance, which is a market that didn't work that well, was that the insurance and the technical expertise was not married up. What our conviction is that standards have to precede insurance. Fundamentally, what everyone first and foremost want, whether you're a CISO at JPMorgan or a CISO at Cursor or an underwriter at Lloyd's of London syndicate, is you want to not have an incidentRune Kvist [00:50:19]: In the first place. You want to know that the risk is well-managed, and only then does insurance start to make sense. So we'll see the standard ecosystem basically run ahead of the insurance. And the reason why we. You asked us kind of why I also do insurance, this is kind of proving what we think a whole promise confidence infrastructure ecosystem needs to look like, and we think it's very compelling to bring that to life, even if we think the standard is kind of the core linchpin that unlocks the rest.Claims, Liability, Air Canada, and Duty of CareSwyx [00:50:44]: There's been no claims yet, right?Rune Kvist [00:50:45]: Nope.Swyx [00:50:46]: This is one of those things where, you know, if people haven't really worked through what it means to cover things.Rune Kvist [00:50:52]: Yeah.Swyx [00:50:52]: So for example, I pay Cursor $20 a month.Rune Kvist [00:50:55]: Yep.Swyx [00:50:56]: And I write a vibe code something that makes, a plane crash, causing $200 million worth of damage.Rune Kvist [00:51:02]: Yes.Swyx [00:51:02]:

This week we got a weird story about an odd, but driven person. Elizabeth Holmes. Holmes is the daughter of a former Enron executive who had dreams and aspirations of becoming a billionaire  by any means necessary. She would have an idea that would revolutionize  the blood collection process in the medical field. You'd only need a prick of the finger and a few drops of blood to tell you about your health.  After years of "fine tuning" this process she would eventually have enough investors that she would become the youngest billionaire according to Forbes.  Only problem was...her idea never worked and she still sold it to major chains like Walgreens ; hoping no-one would ever notice....BUT THEY DID NOTICE! And now she's serving 11+ years in jail and has probably the creepiest viral video circulating the internet (right now) featuring Nathan Fielder! For all the details of how she got here, listen today! As always follow us on the stuff Merch Store- http://tee.pub/lic/doEoXMI_oPI Patreon- https://www.patreon.com/Artandjacobdoamerica Website- https://artandjacobdoamerica.com/ Instagram- https://www.instagram.com/artandjacobdoamerica Facebook- https://www.facebook.com/artandjacobdoamerica/  

Jeremy Au takes the hot seat in a reverse interview hosted by Edric Poon to unpack the true value of a Harvard MBA and the fundamental principles of business leadership. Jeremy unbundles the prestigious degree into three core components: practical utility and learning, building a long-term global network, and acquiring a costly social credential. He shares actionable frameworks for effective leadership, emphasizing the necessity of decisive strategy, ruthless prioritization, and the ability to mobilize resources and capital. The conversation also explores the psychology behind the Harvard case study method, how pattern-matching helps leaders spot corporate fraud, and the harsh, irreversible realities of founder burnout. Finally, Jeremy contrasts Western and Asian leadership styles, explaining how regional GDP per capita and Wall Street's shareholder supremacy dictate corporate culture across the globe. Watch, listen or read the full insight at https://www.bravesea.com/blog/harvard-mba-leadership  BRAVE is Southeast Asia's leading tech podcast, hosted by Jeremy Au. Honest conversations with the region's top founders, investors, and operators on building startups in Southeast Asia. New episodes every week. Subscribe so you never miss one. Listen & Subscribe YouTube (English), YouTube (Bahasa Indonesia), Spotify (English), Spotify (Bahasa Indonesia), Spotify (Chinese), Spotify (Vietnamese), Apple Podcasts Follow BRAVE LinkedIn, X (Twitter), Instagram, TikTok, WhatsApp Follow Jeremy Au LinkedIn, X / Twitter, Instagram, TikTok, Facebook, Threads, Twitch Resources Get transcripts, startup resources & community discussions at www.bravesea.com #Leadership #SoutheastAsia #HarvardMBA #Singapore #TechPodcast #MBA #BusinessSchool #Management #Founders #Startups #VentureCapital #CareerAdvice #Burnout #FamilyBusiness #CorporateGovernance #AsianLeadership #SEAstartups #Malaysia #Indonesia #Philippines #Vietnam #Entrepreneurship  0:00 500 case studies, and what they're actually for 0:52 Introduction: Jeremy in the hot seat 1:43 What a Harvard MBA is actually for 5:01 The half-million-dollar signal 6:38 How to unbundle all three yourself 9:17 Decide, prune, mobilise 10:43 Atari, Nokia, and BlackBerry's own prototype 14:24 Manager versus leader 16:15 The campfire, and who walks into the dark 21:00 Authenticity is not permission to be your worst self 22:59 The case method and the supercomputer brain 26:21 Enron, and pattern matching fraud 29:59 The mistake Jeremy made twice 35:27 Two bad nights of sleep is two drinks 37:34 So what is Asian leadership? 39:12 GDP per capita, and where trust lives 44:49 Wall Street versus everybody else 50:52 Community over the individual 54:08 The MBA in your pocket

LISTEN and SUBSCRIBE on:Apple Podcasts: https://podcasts.apple.com/us/podcast/watchdog-on-wall-street-with-chris-markowski/id570687608 Spotify: https://open.spotify.com/show/2PtgPvJvqc2gkpGIkNMR5i WATCH and SUBSCRIBE on:https://www.youtube.com/@WatchdogOnWallstreet/featured  Is the AI boom another dot-com bust, Enron, or 2008 waiting to happen? Chris explains why today's AI surge is different, while acknowledging real risks remain—and why disciplined investors should trim oversized positions rather than try to predict the next crash.

How did a mattress store from Houston outlast Enron, DeLorean, and Saturn to build a $100M sleep empire? Hear the counterintuitive secrets—revealed!If you think the mattress industry is all about selling beds, think again. In this special episode, Mark Kinsley sits down with Mattress Firm co-founder Harry Roberts to celebrate 40 years of border-to-border, coast-to-coast sleep shop success. From humble beginnings in Houston to a nationwide franchise network generating over $100 million, Harry reveals the gritty, behind-the-scenes moments—like not taking a paycheck for 13 months and building a $90K/month store out of a hurricane shelter.Discover how Harry and his partners navigated brutal economic downturns, insane 17% unemployment, and the rise of digital-first competitors—without ever blaming the economy. Learn the real “weapons” Mattress Firm used to win against Mattress Giant, the make-or-break moments that nearly ended it all, and why creating entrepreneurs inside the company was the ultimate growth engine.Industry veterans, sleep retailers, and anyone curious about building a resilient business will love Harry's honest, actionable advice: control what you can, obsess over every customer, and never stop learning (even when you're the boss). Plus, get a rare look at the franchisee network that still anchors Mattress Firm—and why loving your people is the most powerful sales strategy of all.Want to future-proof your business against any economy? Don't miss these inside strategies.Timestamps:00:00 – The $100M sleep shop: Mattress Firm's wild 40-year journey02:49 – “We never took a paycheck for 13 months”—the real startup grind04:08 – Starting in Houston's worst economy: why everyone said they'd fail06:54 – The secret to growth in ANY economy (and the mindset that saved them)11:21 – Harry's bulletproof greeting: How to win every customer at the door13:51 – The hurricane, the empty store... and tripling sales overnight16:45 – Losing to Mattress Giant: How they went to war (literally in camo)23:30 – The $100M franchise play: Creating entrepreneurs from sales staff41:50 – “Don't let brands own your customer”: The digital traffic trap explained46:33 – Why more competition means everyone sells more beds49:28 – The lost art of retail: What 99% of stores get wrong (and how to fix it)Connect with The FAM Podcast:

In this episode of People in Power, California Energy Markets Managing Editor Jason Fordney interviews Ziad Alaywan, founder and CEO of ZGlobal Inc. Ziad details what his firm does and also provides a fascinating history of his experiences helping stand up the California Independent System Operator and witnessing the California energy crisis of the early 2000s. Ziad, who had a front-row seat to the market manipulation of Enron and others, describes the incredible stress and complexities of managing a brand-new wholesale market and all the fallout of this interesting yet dark period in California energy history. 

In the autumn of 2021, Ron Gonen sat across from me and made a call that sounded like activism: fossil fuel assets were already stranded, the smart money was gone, and anyone divesting that year was a decade too late. He said it during the best year energy stocks had had in a decade. For eighteen months, he looked flat wrong.He wasn't. This is a re-release, and before the interview I score the thesis against what actually happened. In 2024 the S&P's fossil fuel components returned 5.7% against 25% for the index; the sector has underperformed in seven of the last ten years and shrunk from 30% of the index in 1980 to about 3% today. The regulation he predicted arrived: seven states now have packaging producer-responsibility laws, up from two. And the single national recycling company he said the US needed — which did not exist when we spoke — he built a year later. It's Circular Services, now the largest privately held recycler in the US, with close to a billion dollars behind it from Brookfield, Microsoft, Nestlé, PepsiCo, Starbucks and Unilever.Ron Gonen is the Founder and CEO of Closed Loop Partners, an investment firm and innovation center built entirely around the circular economy. He founded and ran RecycleBank, served as New York City's Deputy Commissioner of Sanitation, Recycling and Sustainability, and wrote The Waste-Free World. In this conversation he lays out why the linear “extract, use, landfill” economy is a subsidised anomaly, why he thinks circular investing carries a clear financial edge rather than a moral discount, and how he underwrites it — value investing, price-to-value discipline, and a corporate LP base that tells him where the market is going before it gets there.The one part he under-called was the politics — and that's the live risk. Federal policy went the other way, every gain came from the states, and the fight he once compared to a bug bite is now a 17-state lawsuit. He was right on the assets, the regulation, and the infrastructure. The open question is whether the politics catches up.In this episode we discuss:Why he called fossil fuel assets “stranded” in the middle of their best year — and how that call has agedThe financial case that circular and sustainable portfolios beat the market, not lag itWhy the linear economy only works because extraction and landfill are subsidisedHow George Soros's writing turned an idealistic student into an investorValue investing applied to the circular economy: strict price-to-value discipline and a sub-$10M entry screenHow a corporate LP base of the largest CPG companies can de-risk the thesisRedirecting $100 billion in fossil fuel subsidies — “without costing taxpayers a cent”Why he builds a circular economy rather than thinking of himself as an investorFeatured guest:Ron Gonen, Founder & CEO, Closed Loop PartnersDiscover More from SRI360°:Explore all episodes of the SRI360° PodcastSign up for the free weekly email updateKey Takeaways:Stranded means stranded. Ron called fossil fuel assets impaired in 2021, with the divestment window already a decade closed. By 2024 the S&P's fossil components returned 5.7% against 25% for the index.The moral discount is a myth. He argues circular, stakeholder-aligned portfolios outperform — a fund built on the “greediest” companies would never have screened out Enron, WorldCom, or Tyco.The linear economy is subsidised, not natural. Extraction and landfill dominate only because they're propped up; the fossil fuel industry that makes plastic takes roughly $20 billion a year in US subsidies.Value investing, applied to circularity. Every fund runs a strict price-to-value discipline. On the venture side the hard screen is a sub-$10 million post-money valuation, then whether the tech can become a business, then the team.The corporate LP base is the edge. Closed Loop's LPs include some of the largest CPG companies, and they signal where supply chains are heading — turning an “idealistic” thesis into a realistic one.Redirect the subsidies. His biggest structural idea: move $100 billion over five years from fossil fuel subsidies into circular and renewable industries. As reallocation, not new spending, he argues it costs taxpayers nothing.The politics is the unhedged risk. Every recent gain came from the states, not federal policy, and incumbent resistance has escalated from a “bug bite” to a 17-state lawsuit — the one variable no investor controls.Additional ResourcesRon Gonen on LinkedIn: https://www.linkedin.com/in/ron-gonen-807a49/Closed Loop Partners: https://www.closedlooppartners.com/Circular Services:  https://circularservices.com/The Waste-Free World (book): https://www.penguinrandomhouse.com/books/646769/the-waste-free-world-by-ron-gonen/

John Wesley Hardin, Ted Williams, Enron, North Korea, and a $50 million gift that reshaped healthcare in El Paso all collide in one fast-moving episode about how character, timing, and decision-making change everything. If you like sharp historical stories with real-world business lessons, this one will keep you hooked. Kent opens with a darkly funny story about John Wesley Hardin, then jumps from the printing press and the burning of the White House to modern-day contrasts in justice, bureaucracy, and power. Along the way, the episode connects old frontier violence to today's cultural, political, and economic systems in a way that is equal parts surprising and revealing. You'll discover: Why the printing press was one of the most consequential inventions in history. How South Korean courts, North Korean authoritarianism, and Texas theft laws expose very different ideas about order and enforcement. Why Harvard says job hoppers can become more adaptable employees. how one early-career refusal to forge documents helped shape a billionaire's life what a $50 million gift meant for Texas Tech, the medical school in El Paso, and regional healthcare Kent also revisits the Trammell Crow advice that kept him from joining Enron, then makes the case for why some people and institutions succeed because they stay disciplined when others cut corners. The stories connect through one theme: the long-term payoff of refusing bad deals, staying adaptable, and understanding when a decision is bigger than it looks. You'll also hear an inside look at how major donors, political connections, and internship pipelines shape opportunities at Texas Tech and beyond, plus a hilarious governor-speeding story that shows how even high-stakes situations can turn on timing, trust, and a little luck. Essential listening if you love practical wisdom wrapped in memorable storytelling, especially when the lesson is hidden inside a great anecdote.

Is AI creating an audit boom—or hiding the next Enron-style risk? Blake and David unpack NVIDIA's $500 billion data-center financing plan, why Michael Burry sees warning signs, and how AI is speeding up audits while challenging existing standards. They also cover improved PCAOB inspection results, the end of BOI reporting, Tether's long-awaited audit, QuickBooks Live's overhaul, and practical AI workflows small firms can use today.SponsorsDigits - http://accountingpodcast.promo/digitsOnPay - http://accountingpodcast.promo/onpayThomson Reuters - http://accountingpodcast.promo/taxautomationCloud Accountant Staffing - http://accountingpodcast.promo/casChapters(00:00) - AI Biggest Audit Shift (01:35) - Headlines And Sponsors (02:20) - Digits AI Ledger (04:02) - Nvidia Deal Explained (06:31) - Enron Echoes And SPVs (09:46) - Bubble Risks And GAAP (12:31) - EY Audit Efficiency Claims (15:25) - PCAOB Reports Debate (17:40) - OnPay Payroll Sponsor (18:53) - FinCEN Ends BOI (19:52) - Audit AI Adoption Stats (21:08) - PCAOB Must Set AI Rules (25:52) - Quarterly Reporting Comments (29:17) - Tether Finally Audited (33:17) - Thomson Reuters Tax Automation (35:07) - Ancient Rome Tax Scam (38:45) - Why Tax Fraud Meant Death (39:18) - Clients Want AI Dashboards (39:45) - Small Firm AI Workflows (44:35) - Sponsor Cloud Staffing (45:49) - AI Raises Client Demands (46:27) - Audit Disruption Debate (48:35) - QuickBooks Live Rebrand (51:10) - Taiwan Receipt Lottery (54:40) - OnPay Benefits Upgrade (01:05:17) - Switch Payroll Midyear (01:09:19) - Wrap Up And CPE  Show Notes'Shades of Enron': Michael Burry shorts Nvidia as its $500 billion chip-financing deal fuels a bubblehttps://sg.finance.yahoo.com/news/nvidia-ai-push-echoes-enron-123355872.htmlEY leverages AI for audithttps://www.accountingtoday.com/news/ey-leverages-ai-for-auditIn ancient Rome, tax fraud was punishable by deathhttps://www.popsci.com/science/tax-fraud-death-penalty-ancient-rome/PCAOB inspection reports of largest audit firms show improvementshttps://www.accountingtoday.com/news/pcaob-inspection-reports-of-largest-audit-firms-show-improvementsFinCEN ends beneficial ownership reportinghttps://www.accountingtoday.com/news/fincen-ends-beneficial-ownership-reportingGartner Survey Finds Audit Teams' AI Use is Common, But Most Teams are Lacking Strategic Adoption and Applicationhttps://www.gartner.com/en/newsroom/press-releases/2026-08-10-gartner-survey-finds-audit-teams-ai-use-is-common-but-mostIt's Time for the US Audit Board to Set Corporate AI Standardshttps://news.bloombergtax.com/tax-insights-and-commentary/its-time-for-the-us-audit-board-to-set-corporate-ai-standardsSEC quarterly earnings proposal draws flood of public complaintshttps://finance.yahoo.com/markets/stocks/articles/sec-quarterly-earnings-proposal-draws-112015106.htmlFirms (and Some Guy Obsessed With China) Have Weighed in on the PCAOB Turning an Eye to AIhttps://www.goingconcern.com/firms-and-some-guy-obsessed-with-china-have-weighed-in-on-the-pcaob-turning-an-eye-to-ai/Tether says KPMG issued 'clean' opinion in first full audit of USDT issuer's financialshttps://www.coindesk.com/business/2026/08/13/tether-says-it-completed-long-promised-big-four-audit-of-finances-behind-usd180-billion-usdt-stablecoinReal-life ways small firms use AIhttps://www.journalofaccountancy.com/issues/2026/aug/real-life-ways-small-firms-use-ai/QuickBooks Live is Dead, Long Live Intuit Expertshttps://uqb.show/154Need CPE?Get CPE for listening to podcasts with Earmark: https://earmarkcpe.comSubscribe to the Earmark Podcast: https://podcast.earmarkcpe.comGet in TouchThanks for listening and the great reviews! We appreciate you! Follow and tweet @BlakeTOliver and @DavidLeary. Find us on Facebook and Instagram. If you like what you hear, please do us a favor and write a review on Apple Podcasts or Podchaser. Call us and leave a voicemail; maybe we'll play it on the show. DIAL (202) 695-1040.SponsorshipsAre you interested in sponsoring The Accounting Podcast? For details, read the prospectus.Need Accounting Conference Info? Check out our new website - accountingconferences.comLimited edition shirts, stickers, and other necessitiesTeePublic Store: http://cloudacctpod.link/merchSubscribeApple Podcasts: http://cloudacctpod.link/ApplePodcastsYouTube: https://www.youtube.com/@TheAccountingPodcastSpotify: http://cloudacctpod.link/SpotifyPodchaser: http://cloudacctpod.link/podchaserStitcher: http://cloudacctpod.link/StitcherOvercast:

There is a version of you that you already decided was worthless. Michael Kopper spent years proving his was, and then went back for the pieces worth keeping.Michael is the Executive Adviser and Coach at Basis Technologies, where he works with executive teams on the conversations they have been avoiding. He is not a therapist or a clinician, and nothing in this conversation is clinical advice. What he is, is someone who rebuilt a life after it came apart in public, and who now spends his days helping leaders be honest with the people who work for them.Michael was a finance leader at Enron. The decisions he made there sent him to federal prison. He does not soften that, and neither did we.But the part that stayed with Ky is what came after. Michael did not just rebuild. He spent years working very hard at pretending the old version of himself had no value at all, and it took four or five years before he went back and looked again. When he did, he found two things worth keeping.In this conversation, Michael and Ky get into why companies keep promoting their best people into management and then never show them how to do the human part of the job. Why owning a bad decision is what makes the consequences survivable instead of fatal. Why there is no work version of you and a home version of you, and what it costs a team when leaders pretend otherwise. And what you can actually say at work when telling a senior person you are scared is not safe.If you have ever decided an old version of yourself was worthless and then spent years proving it, this one is for you.The framework Michael works from is The 15 Commitments of Conscious Leadership, by Jim Dethmer, Diana Chapman, and Kaley Warner Klemp.Want more? The ADHD Vibers Subscriber Hub is where Ky goes deeper.The Real Ones tier, five dollars a month, includes the ADHD Deep Dive Library and Reverse the Mic, where podcast guests flip the script and interview Ky. Reverse the Mic is for subscribers only and is not part of this public episode.Patreon: https://www.patreon.com/thevibewithkyFacebook Subscriptions: https://www.facebook.com/thevibewithky/subscribe/Everything else: https://thevibewithky.comMuch love. Good vibes. - Ky

“Anthropic will be a $3 trillion company, SpaceX $2 trillion, and OpenAI $1 to $1.5 trillion by Q2 of next year.” — Dave McClure Yesterday, Keith Teare and I debated the circularity of the AI economy. Today, two of Silicon Valley's most experienced investors, Dave McClure and Aman Verjee, not only straighten out this supposed “circularity” but also burst the pessimism bubble that envelops so many conversations about AI. Verjee is not only McClure's partner at Practical Venture Capital, but also the author of the newly published A Brief History of Financial Bubbles. According to him, today's AI-stoked economy is not an unusually large bubble. It may not even be a bubble, given that AI revenue — from Anthropic's $70 billion to OpenAI's $50 billion — is real. The irrational exuberance lives elsewhere — in companies “draping themselves in AI magic sauce” and in the “SaaSpocalypse” that is decimating software-as-a-service companies. They are both bullish about our AI future. McClure predicts that by the first half of next year, Anthropic and OpenAI will have joined SpaceX as public companies. Together, these three AI darlings will be worth $7 trillion. That's seven thousand billion reasons to be optimistic about 2027. Five Takeaways •       Not a Bubble — a Repricing. Both partners reject the bubble call, on the numbers: Anthropic at roughly $70 billion in revenue on under two gigawatts of compute, OpenAI at $40–50 billion, SpaceX guiding to $100 billion with more than half from AI — real revenue, increasingly real profits. The froth is specific: companies “draping themselves in AI magic sauce” without the substance, and the SaaSpocalypse — cloud-software companies whose cash flows are suddenly perceived as far less durable as AI encroaches on design, legal, and medical verticals. Michael Burry's warning gets Aman's definitive treatment (“he's called nine of the last two bubbles”), and the Aschenbrenner blowup was leverage — running four-x in volatile chip stocks — not AI: he kept his Anthropic position, is married to Dario's chief of staff, and “will be just fine.”•       The $2 Trillion Filing. The week's news, baked into the episode: Anthropic has filed to go public, with a very intentionally leaked $2 trillion valuation hinging on a $190–200 billion 2028 revenue forecast — which Dave suspects is conservative. Eight months ago, when these two last visited, the show was about Elon and Sam and Dario was the bit player; then came the weeks when decades happen: Anthropic's bet on coding agents — reportedly inspired by watching Cursor — captured the revenue engine of the entire application layer. Aman's sequencing: SpaceX is absorbing $75–85 billion of IPO capital, Anthropic goes next, and if both trade well, 2026 breaks every record for money raised — leaving 2027 for OpenAI at a $100 billion revenue guide. Google, he reminds us, went fourth after Yahoo, Lycos, and Excite: better to do it right than to do it first.•       The Fastest Pivot in Corporate History. Dave's account of SpaceX's transformation: the $250 billion xAI merger (a largely private transaction Elon approved with himself), the acquisition of Cursor that closed Friday, Colossus data centers scaling from two gigawatts toward ten, and compute deals renting capacity to Anthropic and Google — former competitors — all executed in roughly six months. The S-1, with unprecedented forward projections of $300 billion in annual revenue, mentions artificial intelligence over 1,100 times (“I used AI to count it,” Aman admits). The result is an economy Andrew calls incestuous: SpaceX's valuation now rests on Anthropic's progress. On Elon himself, Dave separates the art from the artist — terrific products, dubious politics — and on OpenAI: more board changes than Spinal Tap had drummers, a team still storming and norming, but Sam is savvy and the IPO lands by Q2 next year at $1–1.5 trillion.•       Circularity as Asset Class. The New York Times sees a vulnerability in tech giants funding their own customers; Aman, a former CFO at eBay and Sonos, sees asset-backed finance. His analogy: buying a Corvette with GMAC financing isn't a conspiracy as long as the terms are commercially reasonable — and NVIDIA's $500 billion backstop, syndicated with Goldman Sachs, Apollo, Brookfield, and KKR, brings third-party money that validates the asset. GPUs, he argues, are cars rather than smartphones: financeable over eight to ten years, not obsolete in three. The red flags to watch are rebates and self-dealing on non-commercial terms; the current evidence looks more like aircraft leasing than Enron. Dave's deeper worry isn't the AI economy at all — it's the national deficit, whose interest payments are now the largest single line item in the federal budget.•       The Luddite Summer Meets the Long Boom. Aman's sharpest historical observation: this may be the first technological revolution whose leaders are the doomers — Sam prophesying idleness, Dario predicting half of entry-level white-collar jobs destroyed within five years (already wrong at eighteen months, with no 10–20 percent unemployment in sight). Against the WSJ's jobless-boom and nation-of-Luddites anxieties, the book offers the long view: of ten historical bubbles, the two positive ones — Britain's 1845 railway mania and America's 1997–2000 internet boom — overbuilt, crashed, and left the world a valuable technology. Buy every stock founded in the boom and hold, and you'd have owned NVIDIA, Amazon, Google, and PayPal. The 1970s wiped out four to six million secretarial jobs in a decade; women's participation rose from 52 to 77 percent. And on China, the free-trader's answer: partners in progress — there's more to gain than lose if we do this right. About the Guests Dave McClure and Aman Verjee are the co-founders and managing partners of Practical Venture Capital, a Silicon Valley firm specializing in venture secondaries. Dave founded 500 Startups, invested at Founders Fund, and ran marketing at PayPal; Aman was COO of 500 Startups, led strategy at PayPal and eBay, served as CFO of Sonos and of eBay's North American marketplace — and wrote the first draft of PayPal's S-1. Aman's new book, A Brief History of Financial Bubbles (out this week), is available at bigbubbletrouble.com. References: •       A Brief History of Financial Bubbles by Aman Verjee — ten manias from the tulips to the subprime crash, out this week at bigbubbletrouble.com.•       Reuters on Anthropic's IPO filing — the $2 trillion valuation and the $190–200 billion 2028 revenue forecast it hinges on.•       “The Summer That America Became a Nation of Luddites” and the “jobless boom” — the Wall Street Journal pieces threading this week's episodes.•       The New York Times on tech giants' circular AI economy — the piece that framed yesterday's TWTW debate and today's rebuttal.•       The SpaceX S-1 — forward projections of $300 billion in ann...

What started as a simple sports question: why did Mark Walter sell the Los Angeles Lakers after just 14 months? — turned into something else entirely. In Part 1 of this two-part ToddCast Special Report, Chuck Todd pulls the thread from a record $12.5 billion franchise sale to the life insurance companies, private credit vehicles, and obscure Delaware LLCs sitting underneath one of the least understood transformations in American finance since 2008. The facts on the record: Walter's Delaware Life Insurance Co. and Clear Spring Life and Annuity Co. received grand jury subpoenas from Manhattan prosecutors in February, disclosed in June 26 regulatory filings, with a parallel SEC review, following earlier inquiries into Guggenheim's $362 billion money management arm. After receiving the subpoenas, both insurers conducted internal reviews, found reporting errors, and revised earlier disclosures — with Delaware Life disclosing an additional $16 billion in private credit assets linked to affiliated entities beyond what had previously been reported. Chuck is emphatic about what that does not mean: no money disappeared, no loans were declared bad, and a disclosure change is not a financial loss. No charges have been announced against the companies or any individuals, Group 1001 says it is cooperating fully with federal authorities and that its financial position remains strong, and the filings did not state that assets were improperly managed or that investors suffered losses. From there, Chuck builds the machine from the ground up in plain English — a retiree in Indiana buying an annuity, an insurer that has to earn enough to keep that promise, a post-2008 world where banks got safer and the risky lending simply moved somewhere with no public market attached to it. He traces Walter's career from asset-backed securitization in the 1990s through the 2012 Dodgers purchase (and the question Andrew Ross Sorkin asked at the time about where the money came from), through the corporate genealogy of Guggenheim, Delaware Life, Clear Spring, and Group 1001, to insurance filings showing hundreds of millions in debt tied to the Dodgers' regional sports network and ticket revenue. He credits the reporting he's leaning on throughout — Katie Baker at The Ringer, independent researcher Nick Nemeth at Mispriced Assets, plus Bloomberg, the Wall Street Journal, and the Financial Times — and he is scrupulous about the line between what the public record establishes and what it simply cannot. The core question isn't whether anyone broke the law; investigators with subpoena power will answer that. It's whether we understand this system well enough to know what happens when it comes under stress — because when the assets underneath an institution's balance sheet can't be continuously tested in a public market, how much confidence should any of us have in the numbers? Part 2 continues the story. Timeline: 00:00 Why did Mark Walter sell the Lakers? Pulling the thread 00:30 This stopped being a basketball story 00:45 A record $12.5B sale — and why the seller is the story, not the buyers 01:15 Walter took control just 14 months earlier at a $10B valuation 01:30 The thread led to life insurance companies 02:00 A financial market that's grown enormously since the last crisis 02:30 Things that rhyme with 2008 — and things that rhyme with Enron 02:45 Executive Life: the insurer that failed three decades ago 03:15 Three different historical examples — not the same thing 03:45 Not saying another 2008 is coming 04:00 "A sneaking suspicion we may be looking at the beginning of something very bad" 04:15 The questions public filings simply cannot answer 05:15 Why some answers only exist in depositions 05:30 Why the federal investigation matters — subpoena power 06:00 The rule for this episode: what we know vs. what we don't 06:30 The central question about measuring financial strength 07:15 Why this should be a five-alarm fire for regulators 07:45 An enormous market built around things that are private by definition 08:15 Credit where it's due: The Ringer, Mispriced Assets, WSJ, Bloomberg, FT 09:15 Connecting dots vs. building a case 10:00 We made banks safer after 2008 — the money went somewhere else 11:00 Even if it's all legal, the larger question remains 11:45 A simple rule: when someone tells you "it's complicated" 12:15 Complexity as a feature, not a bug 13:00 The innocent explanation: a $2.5B gain in 14 months 13:30 Iger and Kushner were already exploring an NBA expansion team 13:45 Why buy the Lakers instead of building from scratch 14:45 What "valued at $10 billion" does and doesn't mean 15:30 We don't know how much cash Walter personally receives 15:45 Why sell at all? Walter collects teams, he doesn't flip them 16:30 Why only the Lakers? He's keeping the Dodgers 17:15 February grand jury subpoenas and the parallel SEC review 17:30 The disclosure change inside the insurers' filings 18:15 A disclosure change is not a financial loss 19:30 Nobody's been charged; companies say they're cooperating 20:00 Reporting on liquidity — and the precision that question requires 21:00 Why the timing is a legitimate reporting question 21:15 Keeping two separate sports stories separate 21:45 The FIFA deal collapsed roughly 10 days before the Lakers deal 22:15 What the timing does and does not establish 23:00 The political question: Josh Kushner, Jared Kushner, the executive branch 23:45 The pattern is context — it is not evidence 24:00 No evidence of a quid pro quo 24:45 Why the question stays on the shelf 25:15 What does "billionaire" actually mean? 26:00 Who is Mark Walter? Cedar Rapids, a concrete plant, and anonymity 27:15 "I'm nothing special. I'm just the king of common sense." 27:45 Why the low profile matters to this story 28:30 Liberty Hampshire and asset-backed securitization 29:30 Meeting the Guggenheims and building Guggenheim Partners 30:45 Wealth vs. commanding capital that isn't yours 31:45 2012: buying the Dodgers, and the Frank McCourt cautionary tale 33:00 Baseball wanted the exact opposite of McCourt 33:45 Andrew Ross Sorkin's question: where's the rest of the money? 34:15 Insurance company capital in the Dodgers financing 35:15 How does retirement money end up near a baseball team? 36:30 Following the money: a hypothetical retiree in Indiana 37:15 The annuity bargain and what insurers do with the money 38:15 How 2008 scrambled the insurance business 39:00 Low rates and the hunt for yield 39:45 Chuck's Widget Company and the loan the bank won't make 41:00 Money always finds a way — the lesson from campaign finance 41:45 What private credit actually is 42:15 The genuine advantages of private credit 43:00 Stickier capital — and why runs still happen 43:45 Private credit isn't inherently bad. What happens when it gets big? 44:15 No public market means no continuous price check 45:15 What replaces the market as the check on valuation? 46:00 Two sides looking for each other 47:00 Multiplying one retiree's $100,000 by hundreds of thousands 47:45 What happens when the same person owns both sides? 48:30 This is an entire industry, not one man's invention 49:15 Guggenheim's move into insurance and the roots of Group 1001 50:30 The ecosystem: asset management, insurance, private credit 51:00 Why the corporate structure is so hard to follow 51:30 Sportsnet LA and American Media Productions 52:00 Roughly $587M of that debt held by the two insurers, per filings 52:30 Dodgers Tickets LLC and slicing up a franchise 53:00 Is the Dodgers one entity or many? 53:30 Asset-backed securitization, applied to a baseball team 54:30 Is lending against Dodgers TV revenue inherently bad? 55:00 The brother analogy: conflicts and other people's money 55:30 February: subpoenas to Delaware Life and Clear Spring 56:15 The assets were always on the books — the question is characterization 56:30 General interrogatory 13.2 and the original 3% answer 57:00 The revised figure: roughly $16.4B described as dependent on affiliates 57:30 Three separate questions the public record can't resolve 58:15 What the internal reviews concluded 58:45 Comparing that figure to Delaware Life's reported capital and surplus 59:15 What the number does NOT mean 59:45 Concentration, governance, and disclosure 1:00:30 The questions that actually matter 1:01:00 Why the opacity itself is part of the story 1:01:15 Someone looked at the individual borrowers, one by one 1:02:00 Nick Nemeth and the Mispriced Assets research 1:03:15 Why independent research matters in the new media world 1:03:45 Roughly 230 holdings with striking similarities 1:04:00 The names: Verdant Hills, Pines, Iroquois, Yellow Creek 1:04:30 Special purpose vehicles — what's inside the box? 1:05:00 The legitimate reasons to use an LLC 1:05:30 How structure can change regulatory treatment 1:06:15 Does the legal wrapper describe the economic risk underneath? 1:06:45 Does that explain 230 vehicles? We don't know. 1:07:15 The echo of the mortgage crisis 1:08:00 Formation dates, filing numbers, and same-day funding 1:08:45 Roughly 44% of positions held by both insurers, purchased the same day 1:09:15 Innocent explanations exist — but this looks like a system 1:09:30 The questions only investigators can answer 1:10:00 Identification numbers and why outsiders can't check a price 1:10:45 A sophisticated process may exist — but it isn't a public market 1:11:15 What's a private note worth this morning? 1:11:30 Carried at or near purchase price: the concern raised 1:12:00 The great irony: the Lakers are the easy thing to value 1:12:30 Who owns these investments — and who was promised whatSee omnystudio.com/listener for privacy information.

In Part 2 of this ToddCast Special Report, Chuck Todd picks up the thread where Part 1 left it: if an insurance company's capital cushion is determined by how risky its investments are judged to be, then who is doing the judging? The answer leads to private letter ratings — a corner of finance almost no one outside it has heard of, and one that has exploded in size. Wall Street Journal reporting by Shane Shiflett and Heather Gillers assembled data on nearly 18,000 privately rated instruments held by U.S. insurers, and the growth curve is the number to remember: roughly $47 billion in 2018 to roughly $480 billion seven years later, with one estimate putting total private credit in insurance portfolios near $1 trillion. Much of that grading runs through firms most people have never heard of, and Chuck focuses on Egan-Jones, which privately graded roughly $40 billion of debt held by U.S. insurers, faces a 2024 lawsuit from two former executives alleging they were fired after raising conflict-of-interest concerns and that the firm pressured staff to inflate ratings, has drawn SEC questions about its reliability, and in January was removed by Bermuda regulators from their list of recognized ratings providers — all of which Egan-Jones forcefully denies, saying it stands behind the integrity and independence of its work. Chuck is careful throughout about what this does and does not establish: agencies can legitimately disagree, private raters often see borrower information outsiders never will, and none of it means any particular rating is wrong. It means the ratings deserve scrutiny, because if the grade helps set the size of the rainy day fund, being wrong about the grade means being wrong about the cushion. From there the episode widens out. Chuck walks through what a clean audit opinion actually certifies versus what people assume it certifies, revisits Executive Life — the insurer that reached for yield in junk bonds in the 1980s and was eventually seized — as a more instructive warning than Enron or 2008, and is direct that this is not a story about an insurer on the brink: Group 1001 says it is cooperating fully and that its financial position remains sound, Delaware Life reported roughly $69 billion in assets as of March and Clear Spring roughly $16 billion, and no charges have been announced against the companies or any individuals. AM Best has affirmed both companies' A- (Excellent) financial strength ratings while revising their outlooks to negative following the reclassification of private credit investments from unaffiliated to affiliated. Complicated private assets are not insolvency; related-party exposure is not insolvency; a federal investigation is not insolvency. The question Chuck is actually chasing is structural — whether a system split across fifty state insurance departments, the SEC, the Fed, offshore reinsurance regulators, and private ratings firms can assemble the whole machine fast enough when one piece breaks, and whether the real lesson of the post-2008 era is that we made the banks safer without ever asking where the behavior would go. He lays out three ways this ends, six specific questions he'd chase with subpoena power he doesn't have, and — unusually — the exact evidence that would bring him back in six months to say the warning lights looked worse than the engine. Because capitalism doesn't run on money alone. It runs on people believing that a price means what it says, that a rating means something, and that somebody understands the risk underneath a promise made to a retiree thirty years out. Timeline: 00:00 Recapping Part 1: inside Mark Walter's world of structured finance00:30 Who looked inside the box and decided how safe it was?01:00 Why the risk grade determines the size of an insurer's cushion01:30 Credit rating agencies as the report card for debt02:00 A better grade can mean less capital sitting behind it02:15 The special purpose vehicle, the note, and the rating02:45 Does the grade on the box accurately reflect what's inside?03:15 WSJ data on nearly 18,000 privately rated investments03:30 From $47 billion in 2018 to $480 billion seven years later03:45 One estimate puts private credit near $1 trillion in insurance portfolios04:15 What "privately rated" actually means04:30 Private letter ratings and what the public can't see05:00 Why the quality and independence of the rating matters so much05:15 Egan-Jones — and the Arthur Andersen flashback05:45 The ratings agencies you know, and the one you don't06:00 Roughly $40 billion of insurer-held debt privately rated by Egan-Jones06:15 Egan-Jones also rated the Dodgers TV network debt06:30 Following the chain from annuity customer to capital cushion06:45 Who pays the ratings agencies? The inherent tension07:15 The Journal's comparison: roughly one grade higher on average07:45 Egan-Jones strongly disputes the Journal's analysis08:00 Former executives' lawsuit alleging pressure to inflate ratings08:15 Egan-Jones denies it; the SEC has examined its processes08:30 Bermuda removed Egan-Jones as a recognized ratings provider08:45 Allianz's response: requiring a second rating09:15 This doesn't mean the ratings are wrong — it means scrutiny09:30 Enter the auditor: KPMG and the clean opinions10:00 What an audit opinion addresses — and what it doesn't10:30 The right question to ask about a clean opinion11:00 Executive Life: the more useful historical warning11:30 Junk bonds, Michael Milken, and the reach for yield12:00 How Executive Life ended — and why it isn't the same thing12:15 The evidence that cuts against the scariest version of this story12:30 Delaware Life's reported assets, capital, and surplus12:45 Financial strength ratings and what "A-" actually means13:00 The more recent caution from the ratings agencies13:30 This is not an insurer on the verge of seizure13:45 The real question: confidence in conventional measures of strength14:00 Why asset quality matters when you're backing promises14:30 The safety net: state guaranty associations14:45 And who ultimately pays for that safety net15:00 Accumulating echoes: Executive Life, Enron, and 200815:45 The warning lights of 202616:15 Not a crisis — but a reason to ask better questions16:30 Can regulators adapt as fast as the system is changing?17:00 What regulators are actually doing right now17:30 This is not asleep-at-the-switch17:45 The structural problem: nobody sees the whole machine18:15 Fifty states, fifty insurance departments18:45 Why we regulate different financial businesses differently19:00 Assembling the machine when each regulator holds one piece19:45 Finance moves at the speed of a term sheet20:15 Regulation moves at the speed of rulemaking20:45 Understanding regulatory arbitrage21:00 Same television, different rules21:45 Most regulatory arbitrage is perfectly legal22:00 But risk doesn't change just because the address does22:15 Why regulators are reconsidering what qualifies as a bond22:30 Show me what's inside the box, not the wrapping paper23:00 The rules are being rewritten — but the money is already there23:30 The mistake Washington may have made after 200824:00 You can't pass a law eliminating the desire to make money24:45 The campaign finance parallel25:00 We regulated the scene of the accident25:30 We get very good at preventing the last financial crisis26:00 Incentives work: if banks pull back, somebody else lends26:15 Maybe the behavior simply migrated27:15 The systemic stress test Chuck doesn't think we can pass27:45 Why the investigation is useful regardless of the outcome28:00 Looking through the legal boxes to the economics underneath28:30 Where the central argument lands29:15 What happens when something goes wrong? The honest answer29:30 The strongest case that nothing catastrophic happens30:00 Why private credit isn't structured like a bank run30:15 Longer-term liabilities and patient money30:45 Three ways this story could end31:00 Possibility one: Walter is the problem31:15 Possibility two: an extreme example of a manageable problem31:45 Possibility three: Walter is the X-ray32:00 What we do — and don't — have evidence of32:30 Being careful not to invent the next 200832:45 Where pressure could actually come from33:15 When patient money becomes less patient33:30 Other sources of insurance funding under stress33:45 Borrowing, credit lines, and reinsurance triggers34:00 Who else made a promise based on that valuation?34:15 Being fair to Delaware Life and Clear Spring34:45 The narrower question: how much stress can the cushions absorb?35:15 Back to the Lakers one last time35:45 Why you sell the thing you can sell36:00 What Chuck is and isn't ready to say36:30 If I had subpoena power: the reporting roadmap37:00 What open-source reporting can and can't do37:30 One: open the boxes and show the underlying assets37:45 Two: did the structure change the regulatory treatment?38:15 Schedule D vs. Schedule BA — show us the math38:30 Three: who graded the box, and on what information?38:45 Four: why did 3% become something vastly larger?39:00 Who made that judgment, and what changed after the subpoenas?39:30 Five: did the Lakers money actually matter?39:45 Six: how much stress can these insurers absorb?40:15 What we know, and what we don't40:30 The final test: what would make Chuck say he was too worried40:45 Show me the marks hold up41:15 "I'd love to make that podcast"41:30 What this story already tells us41:45 Coming back to Josh Kushner and the timing42:00 No evidence of a quid pro quo42:15 Why the political question is the smaller question42:45 The more consequential story43:00 The full thread: Lakers to Walter to Dodgers to private credit43:30 What we have and haven't established43:45 We reinforced the part of the house that burned down44:15 Every private equity firm wanted its own insurance company44:30 "Money always finds a way"45:00 The failure was assuming we'd solved the behavior45:15 Why this matters well beyond Wall Street45:30 Our hypothetical retiree, and what she has to trust45:45 Capitalism runs on trust, not just money46:15 If that trust breaks, everyone finds a different villain46:45 Where Chuck's instincts are — and what the evidence doesn't establish47:00 What would change his mind47:15 Why it's fitting we got here through the Lakers47:45 Let's figure out what it is before the patient gets sickSee omnystudio.com/listener for privacy information.

Elon Musk's SpaceX debuted on the Nasdaq in June with the largest IPO ever, raising a record $86 billion. But the stock has been on a wild ride ever since. Kara sits down with a panel of experts to assess SpaceX after its inaugural post-IPO earnings report and the first in a series of lockup expirations that released more than 900 million shares for trading. They break down where SpaceX is actually making money (spoiler: it's Starlink) and what its massive AI spending, xAI acquisition and increasingly expansive ambitions reveal about Musk's long-term strategy.  Ed Elson is an analyst, writer, and co-host of the Prof G Markets podcast from the Vox Media Podcast Network. Tim Higgins is a business columnist for The Wall Street Journal, a CNBC contributor, and the author of books including iWar: Fortnite, Elon Musk, Spotify, WeChat, and Laying Siege to Apple's Empire. Bethany McLean is a contributing editor at Vanity Fair, a columnist at Yahoo Finance, a CNBC contributor, and the author of books including The Smartest Guys in the Room: The Amazing Rise and Scandalous Fall of Enron. Questions? Comments? Email us at on@voxmedia.com or find us on YouTube, Instagram, TikTok, Threads, and Bluesky @onwithkaraswisher. Come see Kara for a live taping of On at the Odoo Experience conference in San Francisco on September 2. Register for the conference on Odoo's website. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Aug 11, 2026 – Could AI be quietly steering your money into the next Enron? New Constructs CEO David Trainer reveals why the AI everyone's using for stock picks is dangerously blind—chasing hype while missing the accounting time bombs that sink...

"This isn't just a property tax scandal—it's a $5.1 trillion threat to the U.S. financial system." — Mitch VexlerMitch explains why he believes alleged fraud in property tax appraisals and school district bonds could undermine U.S. Treasuries, challenge the Constitution, and expose risks that Wall Street's financial models have failed to account for.

Nikkei Asia recently reported that the five biggest US tech companies are carrying an estimated $1.65 trillion in "hidden," off-balance-sheet debt — and a lot of commentators have reached for the word "Enron" to describe the issue. In this video I look at whether that comparison holds up. It doesn't: unlike Enron, this debt isn't concealed through fraud — it's disclosed in the footnotes, it breaks no accounting rules, and much of what is going on is perfectly ordinary. But that raises a more interesting question than "will they get caught." If the aggressive stuff — the adjusted earnings, the leases, the stock-based compensation added back — is all sitting there in plain sight, does dressing up the numbers actually fool anyone? Drawing on the work of Aswath Damodaran, Richard Sloan, Robert Bloomfield and others, I dig into what the research says about whether markets reward clean accounting or aggressive accounting, why the debt isn't hidden so much as filed somewhere too tedious for most people to read — and why the real risk in the AI boom probably isn't the borrowing at all, but the enormous revenue it's all assuming will show up.Patrick's Books:Statistics For The Trading Floor: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://amzn.to/3eerLA0⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Derivatives For The Trading Floor: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ https://amzn.to/3cjsyPF⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Corporate Finance: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://amzn.to/3fn3rvC ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Ways To Support The Channel:Patreon: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.patreon.com/PatrickBoyleOnFinance⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Buy Me a Coffee: https://www.buymeacoffee.com/patrickboyle

Alice Yake's parents' taught her and her brother the importance of fairness and discipline, but also how to overcome obstacles and tackle big problems.  Those life skills have served Alice throughout her career in the power sector, from a false start at Enron — just months before it declared bankruptcy — to a long, successful career at Xcel Energy. Last year, she left her role as the utility's chief planning officer to become VP of GRIDS at Breakthrough Energy, the organization founded by Bill Gates to accelerate clean energy using philanthropy and investment funding. This week on With Great Power, Alice shares how she's now helping energy planners across the world improve electric grids through open-source planning and modeling software. She also discusses the challenge of building a better workforce to modernize the grid, as well as the opportunities to integrate more distributed energy resources into infrastructure that can help meet growing demand for clean energy over the coming decades.  Credits: Hosted by Brad Langley. Produced by Mary Catherine O'Connor. Edited by Anne Bailey. Original music and engineering by Sean Marquand. Stephen Lacey is executive editor. The GridX production team includes Jenni Barber, Samantha McCabe, and Brad Langley.

Corporate Gossip's Becca Platsky on CEO Myths, Enron Obsessions, and Why Humility Is Fraud ProtectionKelly Paxton hosts Becca Platsky of the Corporate Gossip Podcast (a CPA-run “business podcast for Bravo lovers”) to discuss how the show deep-dives one company per week with heavy research, financial analysis, and human-interest gossip, including episodes on Enron and the Forbes 30 Under 30 pipeline of fraudsters. They argue CEOs are often made “dumber” by constant validation and isolation, and that executive assistants may best understand what happens behind the scenes. The conversation covers wealth bias in the justice system, support letters for white-collar defendants, and the Charlie Javice/JPMorgan case as an avoidable due-diligence failure tied to elite blind spots. Platsky emphasizes community as a source of optimism, names favorite media/podcasts, and stresses that humility—recognizing anyone can commit or fall for fraud under pressure and opportunity—is key protection.01:52 What Corporate Gossip Is04:11 Why CEOs Get Dumber06:41 Executive Assistants Know09:13 Billionaire Pedestals10:36 Scott Galloway Debate12:18 Favorite Business Voices13:35 Optimism Versus Skepticism17:00 New York And Thrillerfest19:51 Dream Fraudster Interviews22:00 Who Steals More23:50 Madoff Staff And Disney24:25 Letters To The Judge27:08 Charlie Javice Case29:43 FAFSA Fraud Blindspots32:18 Range Rover Red Flags33:17 Forbes Lists and Grifts34:59 WeWork Key Man Risk36:58 Podcast Inspirations38:45 Stanford Power Plays40:49 Scammer Red Flags Books42:41 Humility Against Fraud45:54 Everyone Has a Price48:04 Women in Fraud HistoryResources MentionedNobody's FoolCorporate Gossip podcastPatreon community for Corporate GossipConnect with Beccahttps://www.linkedin.com/in/rebeccaplatsky/https://www.corporategossippod.com/

Bethany McLean, veteran investigative journalist and co-author of The Smartest Guys in the Room, saw the end of Enron coming, and is now watching the AI trade very carefully. She has questions the market isn't asking. Motley Fool analyst Rachel Warren continues her conversation with Bethany, turning the lens on the market right now. She discusses why the free cash flow of the Magnificent Seven is quietly turning negative, why the circular financing inside the AI ecosystem makes it nearly impossible to see what's really going on, and why the S&P 500 index fund you think is keeping you diversified is actually one of the most concentrated AI bets you can make.  Host: Rachel Warren  Guest: Bethany McLean  Producers: Bart Shannon, Lauren Budabin  Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, "TMF") do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions.  TMF assumes no responsibility for any losses or damages arising from this advertisement.  We're committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode.  Learn more about your ad choices. Visit megaphone.fm/adchoices

On this episode of Chit Chat Stocks, Brett and Ryan continue their study of super investors by looking at David Tepper. We discuss: (00:00) Introduction (07:40) Founding of Appaloosa and initial investment philosophy (10:01) Tepper's track record and notable returns (18:48) Case study: Russian 1998 financial crisis (24:09) Investing during the Enron and dot-com busts (32:07) The GFC rebound: Tepper's boldest move (40:22) Recent macro bets: China (46:19) Lessons from Tepper's investment approach and philosophy (52:29) Portfolio overview ***************************************************** Subscribe to our newsletter, Emerging Moats: emergingmoats.com  ********************************************************************* Chit Chat Stocks is presented by Interactive Brokers. Get professional pricing, global access, and premier technology with the best brokerage for investors today:  https://www.interactivebrokers.com/  Interactive Brokers is a member of SIPC.  ********************************************************************* Fiscal.ai is building the future of financial data. With custom charts, AI-generated research reports, and endless analytical tools, you can get up to speed on any stock around the globe. All for a reasonable price.  Use our LINK and get 15% off any premium plan: ⁠https://fiscal.ai/chitchat  ********************************************************************* Disclosure: Chit Chat Stocks hosts and guests are not financial advisors, and nothing they say on this show is formal advice or a recommendation. Learn more about your ad choices. Visit megaphone.fm/adchoices

Five years, 345 episodes and one painfully empty chair later, THS enters its next era. Chris is back behind the mic with Rajeil riding shotgun, a laptop full of charts and a thesis Wall Street is not going to enjoy: the next recession may not begin with housing or the Fed—it may begin when America's trillion-dollar AI buildout collides with cheaper, open-weight Chinese models. From market corrections and oil shocks to data-center tax breaks, Enron-style debt structures, exploding token costs, Kimi K3 and an unreleased AI agent that reportedly escaped containment, this episode asks whether the technology holding up the market could also be the thing that breaks it. Same Higher Standard, fewer people playing footsie under the table.

(00:00:00) INTRO (00:32:42) Las estafas amorosas funcionan (00:33:11) Ahora con una llamada al presidente se aprueba un medicamento (00:42:41) EL MENÚ (00:46:52) ANUNCIOS (00:48:08) PATREON (00:57:00) OpenIA (01:12:44) Mientras tanto en Berlín el día de Christopher Street fue atacado (01:41:27) De verdad había que evitar que esta casa se convirtiera en Santuario (01:45:01) Busquemosle la lengua a Briceño (01:57:14) Ajá en Venezuela saber dónde está el dinero del petróleo es casi imposible (02:12:26) A Trump le gustan sus aranceles pero no las multas europeas (02:15:58) Venezuela tuvo su chiripero y ahora la India tiene su movimiento de Cucarachas (02:24:04) El Dinero programable viene de la mano del Euro digital (02:30:26) Olvídate de irán, el enemigo de USA es Canadá (02:33:36) Arabia Saudita va pendiente de energía Nuclear (02:36:55) Te acuerdas de Enron bueno piensa ahora en Oracle, Amazon y Meta (02:44:42) España nunca defrauda (02:55:48) Cuando un solo Hacker deja sin títulos de propiedad a todo un país (03:00:00) No gastar en Psicólogos es también un trastorno (03:04:12) El problema de sacar a los inmigrantes es quien cuida a la Abuela (03:08:08) Ucrania entra al escenario de Irán (03:11:48) Antes de curar a la gente hay que convencerla que no eres el diablo (03:22:56) Cuánto te ganas entrenando robots (03:26:04) EXTRA: Los incendios en Europa INFORMACIÓN CENTRALIZADA SOBRE EL TERREMOTO EN VENEZUELA https://www.profesorbriceno.com/about-5 LE PUEDES COMPRAR A UN PANA LA SUSCRIPCIÓN CON TARJETA DE REGALO https://www.patreon.com/profesorbriceno/gift O COMPRAR UNA GIFT CARD DE PATREON EN https://rewarble.com/brands/patreon COMO DIJIMOS EN EL EPISODIO LA MERCH ESTÁ AQUÍ https://quesevayantodos-shop.fourthwall.com/collections/all EPISODIO COMPLETO Y PARTICIPACION EN VIVO EN https://www.patreon.com/profesorbriceno Las Grabaciones pueden verse en vivo en TWITCH ️https://www.twitch.tv/profesorbriceno SUSCRÍBETE AL PODCAST POR AUDIO EN CUALQUIER PLATAFORMA ⬇️  AQUÍ LAS ENCUENTRAS TODAS: ➡️➡️➡️ https://pod.link/676871115 los más populares SPOTIFY ⬇️   https://open.spotify.com/show/3rFE3ZP8OXMLUEN448Ne5i?si=1cec891caf6c4e03 APPLE PODCASTS ⬇️   https://podcasts.apple.com/es/podcast/que-se-vayan-todos/id676871115 GOOGLE PODCASTS ⬇️   https://www.ivoox.com/en/podcast-que-se-vayan-todos_sq_f11549_1.html FEED PARA CUALQUIER APP DE PODCASTS ⬇️   https://www.ivoox.com/en/podcast-que-se-vayan-todos_sq_f11549_1.html Si te gustó, activa la campanita   FECHAS DE PRESENTACIONES ⬇ ️ http://www.profesorbriceno.com/tour Redes sociales: ✏️Web https://www.profesorbriceno.com ✏️Instagram https://www.instagram.com/profesorbriceno/ ✏️X https://x.com/profesorbriceno ✏️Facebook https://www.facebook.com/profesorbricenoOficial/ #aburrido #profesorbriceño #noticias #política

The journalist who exposed Enron before Wall Street did has spent decades studying how companies unravel — and the warning signs are almost always there before the collapse. Motley Fool analyst Rachel Warren sits down with Bethany McLean, veteran investigative journalist and co-author of The Smartest Guys in the Room, to dig into the psychology behind corporate disaster. She discusses why most fraud starts with self-delusion rather than malice, why the auditors and lawyers and board of directors may not be protecting you the way you think, and why the line between a visionary CEO and a fraudster is thinner — and more unsettling — than most investors realize.  Host: Rachel Warren  Guest: Bethany McLean  Producers: Bart Shannon, Lauren Budabin  Disclosure: Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, “TMF”) do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement. We're committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode. Learn more about your ad choices. Visit megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices

Every edition of Answer Us Back features your responses to/observations upon previous episodes of AMT, some of them many many years old - but today's episode is packed to the rafters with what you had to say about our most recent episode, AMT419! Detta has baked a version of the Tom Cruise coconut-white chocolate bundt cake - "A lot of faff, but worth it."  Anonymous from the Allusioverse has actually eaten a cake gifted by Tom Cruise! Not the coconut bundt though - a lemon one, strong enough to taste "remarkably like having your taste buds bashed out". Mmm, great. A different Anonymous writes about the practice of film stars buying end-of-shoot gifts for all the crewmembers. Alastair in Kilmarnock gives some fun Scottish examples of stadiums being corporately renamed... ...and Mark tells us some of the creative approaches that stadiums have taken to cover up their usual corporate logos during the World Cup. Meagan in Oakland CA wonders when, if ever, it would be OK to wear her Houston Astros shirt from 25ish years ago which has the Enron logo on it? On the topic of which fun British vegetables Dan in Pennsylvania could grow on his farm, Emily in Canada is screaming, "King Edward potatoes!!!" Dan himself writes back, noting the ladybird fu**fest that was mentioned in AMT419. As well as buying ladybirds to sort out her garden's aphids, Isabel treats herself to a few praying mantis egg sacs, to enjoy a miniature horror show when they hatch. And Erica responds to the previous Answer Us Back, where we mused upon the potential disappointment of seeing one of us audio podcasters in the flesh. If AMTs 1-419 left you with lingering questions and opinions, share them with us for future episodes of Answer Us Back. And as always, send in your questions, in voicenote or written form, to answermethispodcast@googlemail.com. All new AMT420 will be in your podfeed on 30 July 2026.  Help keep AMT going by signing up at patreon.com/answermethis, where you can get an ad-free version of the show, monthly bonus bits, our video livestream Petty Problems, AND access to our ENTIRE back catalogue, including all our paywalled episodes, our special albums, and all the Retro AMT episodes. AMT is sponsored by: • Cozy Earth, luxurious bedding, sleepwear, loungewear, and towels for bath and beach. Shop at cozyearth.com and get 20% off using our code ANSWER. • Quooker, the the tap that does it all, from instant 100-degree boiling water to chilled, filtered, and sparkling water. Shop at quooker.co.uk and until the end of August, you can use our code ANSWER to get free installation and your free Quooker glassware set. • Taskrabbit, the online and mobile marketplace, available in the UK, that connects you with skilled, reliable local freelancers to help with everything from furniture assembly and home repairs to moving, gardening, and more. Get ahead of your to-do list with £10 off your first task at taskrabbit.co.uk or on the Taskrabbit app using our promo code ANSWER.  Learn more about your ad choices. Visit megaphone.fm/adchoices

With hyperscalers like Meta, Google, Amazon and SpaceXAI burning through cash, we decided to answer the question underneath all of it: what is this money actually buying? In this episode we start high level with a primer on the AI ecosystem or what Nvidia's CEO Jensen Huang calls the "five-layer cake" of AI — energy, chips, infrastructure, models, applications. We get into the vocabulary everyone uses and nobody defines: what a hyperscaler actually is, how it differs from a frontier model company like OpenAI or Anthropic, why Oracle only plays in one layer while Google plays in all five, and what a NeoCloud like CoreWeave is really doing when it borrows against its own chips. Then we get into the grid — all three of them — including how power prices get set, the difference between regulated and deregulated states, why Meta's $200 billion Project Hyperion campus in Louisiana needs enough electricity to power half of Manhattan in the summer, and why the new rule for data centers is essentially "bring your own electrons." We also dig into the tax incentives driving the timing of all this spend, and why states are competing so ferociously for projects that employ almost no one once the construction crews go home. Then we bring on an extra special guest: power expert. Ron Kelly, who spent 50 years in power and energy — as an engineer, at Calpine, and developing natural gas-fired power plants and solar plants all over the United States the country. He also happens to be Kristen's dad. His take is bracing: he's seen this movie before. Between 1995 and 2005, roughly 300 gigawatts of power projects were announced on the promise of the internet. 168 got built, 130 were canceled, the rest died, and Enron, Mirant, NRG, and Calpine all ended up in Chapter 11. Today's data center pipeline is about the same 300 gigawatts. Ron explains risks that could complicate the build out necessary to get all the needed power infrastructure online: the interconnection studies, transformer backlogs — plus what he really thinks about the security of the largest machine humans have ever built. Connect with Ron at   / ronald-kelly-pe-mba-3587a718  

Forty years in Land & Right-of-Way. An Enron survivor. A woman who earned her seat at the table in historically male-dominated industries. And, in her own words, someone who has spent her career “navigating a male-dominated world one martini at a time.”  This week, we sit down with Liz Babcock, Vice President of Land & ROW at ALTAEI, for a candid conversation about resilience, trust, relationships and what it really takes to succeed in the people-heavy world of land and right-of-way. Liz shares lessons from four decades spent working with landowners, attorneys, engineers, agencies, utilities and energy companies—and explains why technical knowledge alone is never enough. We also dive into: How the Land and ROW profession has changed—and where progress is still needed What surviving the Enron collapse taught Liz about reputation and resilience How to build trust with skeptical or frustrated landowners The importance of bringing ROW professionals into projects earlier Earning your voice and your seat at the table Why relationships, humor and genuine human connection still move projects forward The stories and experiences that make a 40-year career truly meaningful This episode is a reminder that successful projects are not built through data, documents and processes alone. They are built through trust, communication, judgment and treating people right. Because the best ROW professionals do not just help projects acquire land—they protect relationships, reduce risk and create a path forward. Music by Prince!! #TheGeoholics #LandSurveying #RightOfWay #ROW #LandAcquisition #Geospatial #Surveying #Infrastructure #Leadership #WomenInLeadership #WomenInEnergy #ProfessionalDevelopment #CareerLessons #RelationshipBuilding #ProjectManagement #Prince #WhenDovesCry #Podcast

Grid operators sit at the center of many of the biggest forces reshaping the global energy system. They're navigating rising electricity demand, a lack of transmission infrastructure, shifting regulatory policies, and maintaining the tricky balance between affordability, reliability, and the need for dispatchable power.  Both here in the US and around the world, operating a reliable and resilient grid—in the face of increasingly severe weather and complex interconnection demands—is more difficult than ever. And these challenges are felt well outside the power sector. Spiking utility rates in some regions have turned electricity into a major political issue. So, what does the future of grid planning tell us about the ultimate pace of the energy transition? How can system operators manage the surge in demand from AI and data centers without compromising reliability? And how can open-source grid planning tools help both developed and developing markets build a flexible power system for the next 30 to 50 years? Today on the show, Jason Bordoff speaks to Alice Yake about the opportunities but also the challenges in building cleaner electrical grids. Alice is vice president of GRIDS at Breakthrough Energy, where she leads a team focused on the development of an open-source grid planning ecosystem designed to make energy system modeling transparent, accessible, and trustworthy. Previously, she spent 14 years at the utility Xcel Energy, where she rose to chief planning officer. Before that, she worked for the oil and gas company Occidental. She started her career at Enron. And for more about the Center on Global Energy Policy's work on electricity affordability, read here. Credits: Hosted by Jason Bordoff and Bill Loveless. Produced by Mary Catherine O'Connor, Caroline Pitman, and Kyu Lee. Engineering by Gregory Vilfranc.  

Craig visits Greg in LA. Topics covered: blood showers, Bram Stoker, face rubbing, pot gummies, sleep habits, negotiating contracts, and why Enron failed (it was Scientology).

I joined my longtime friend Tom Cock for a special edition of Talking Real Money — a wide-ranging conversation about the evolution of indexing, the proposed changes to the S&P 500, and why investors should understand both the strengths and limitations of traditional index funds. I explain why firms like Dimensional Fund Advisors and Avantis Investors use a more flexible, evidence-based approach than traditional indexing, and how academic research has reshaped portfolio construction over the past several decades.We also explore lessons from market history, including the importance of understanding major bear markets, determining appropriate risk levels, and building portfolios that align with your personal goals rather than chasing maximum returns. I share insights from the latest Dimensional Matrix Book and explain why I believe studying 100 years of market data helps investors stay disciplined during inevitable downturns.Finally, I introduce a simple but powerful strategy for helping newborns and young children build substantial retirement wealth through small annual investments that can compound over many decades.CHAPTERS0:11 Special guest Paul Merriman joins Talking Real Money0:55 Long friendship and investing partnership between Tom and Paul1:20 S&P 500 rule changes and earlier inclusion of major IPOs like SpaceX2:07 Historical examples of S&P 500 additions and omissions2:35 Microsoft’s delayed entry into the S&P 5002:56 NVIDIA replacing Enron in 20013:29 How index rule changes can affect future returns and volatility4:08 Why indexing remains the preferred strategy for most investors5:16 Traditional versus non-traditional index funds6:37 How Avantis and Dimensional incorporate factors beyond company size8:05 Why factor-based investing differs from traditional indexing9:02 Problems with rigid index reconstitution schedules10:16 Momentum, flexibility, and portfolio management advantages11:22 Introduction to Dimensional’s annual Matrix Book11:53 Using market history rather than forecasts to guide investing decisions13:09 Lessons from past bubbles, crashes, and lost decades14:20 Why Paul trusts academic research more than Wall Street forecasts15:14 The case for small-cap value investing15:49 Clarifying Paul’s allocation to small companies16:53 Investing for heirs, charities, and future generations18:10 Remembering investor panic during the 2008 financial crisis19:18 Determining an appropriate risk level for retirement portfolios20:43 Different investor goals: beating the market, maximizing returns, or minimizing risk21:28 Peace of mind versus maximum growth21:55 Helping young people build retirement wealth early22:54 The $365-per-year retirement funding concept24:09 Final thoughts and appreciation between Tom and PaulQuestions? Comments? Click!

Carson Block is the founder of Muddy Waters Research, one of the defining activist short-selling firms of the last decade and a half. Since 2010, Muddy Waters has published forensic research exposing accounting fraud at publicly traded companies across China, Europe, and the US and has been right enough times that 11 companies have been delisted as a result.In this episode of Summation, Carson and Auren discuss:why outright fraud is only 20-25% of Muddy Waters'  focusthe Wirecard sagawhy high-trust countries like Germany are a paradise for criminalshow the thing that killed Enron is still completely legalYou can find Auren Hoffman on X at @auren and Carson Block on LinkedIn and on X @muddywatersre

Until 2007, the largest single corporate bankruptcy was Enron, a $67 billion energy trading company. Its decline was breathtaking, and while it’s a fascinating story of corporate malfeasance and greed, it’s also about the lives of ruined workers. Learn all about it in this classic episode.See omnystudio.com/listener for privacy information.

Tom welcomes legendary investor educator and longtime friend Paul Merriman for a wide-ranging conversation about the evolution of indexing, the proposed changes to the S&P 500, and why investors should understand both the strengths and limitations of traditional index funds. Paul explains why firms like Dimensional Fund Advisors and Avantis Investors use a more flexible, evidence-based approach than traditional indexing and discusses how academic research has reshaped portfolio construction over the past several decades.The discussion also explores lessons from market history, including the importance of understanding major bear markets, determining appropriate risk levels, and building portfolios that align with personal goals rather than chasing maximum returns. Paul shares insights from the latest Dimensional Matrix Book and explains why he believes studying 100 years of market data helps investors stay disciplined during inevitable downturns.Finally, Paul introduces a simple but powerful strategy for helping newborns and young children build substantial retirement wealth through small annual investments that can compound over many decades.Timestamps0:11 Special guest Paul Merriman joins Talking Real Money0:55 Long friendship and investing partnership between Tom and Paul1:20 S&P 500 rule changes and earlier inclusion of major IPOs like SpaceX2:07 Historical examples of S&P 500 additions and omissions2:35 Microsoft's delayed entry into the S&P 5002:56 NVIDIA replacing Enron in 20013:29 How index rule changes can affect future returns and volatility4:08 Why indexing remains the preferred strategy for most investors5:16 Traditional versus non-traditional index funds6:37 How Avantis and Dimensional incorporate factors beyond company size8:05 Why factor-based investing differs from traditional indexing9:02 Problems with rigid index reconstitution schedules10:16 Momentum, flexibility, and portfolio management advantages11:22 Introduction to Dimensional's annual Matrix Book11:53 Using market history rather than forecasts to guide investing decisions13:09 Lessons from past bubbles, crashes, and lost decades14:20 Why Paul trusts academic research more than Wall Street forecasts15:14 The case for small-cap value investing15:49 Clarifying Paul's allocation to small companies16:53 Investing for heirs, charities, and future generations18:10 Remembering investor panic during the 2008 financial crisis19:18 Determining an appropriate risk level for retirement portfolios20:43 Different investor goals: beating the market, maximizing returns, or minimizing risk21:28 Peace of mind versus maximum growth21:55 Helping young people build retirement wealth early22:54 The $365-per-year retirement funding concept24:09 Final thoughts and appreciation between Tom and PaulQuestions? Comments? Click!

LISTEN and SUBSCRIBE on:Apple Podcasts: https://podcasts.apple.com/us/podcast/watchdog-on-wall-street-with-chris-markowski/id570687608 Spotify: https://open.spotify.com/show/2PtgPvJvqc2gkpGIkNMR5i WATCH and SUBSCRIBE on:https://www.youtube.com/@WatchdogOnWallstreet/featured  Chris uses Nassim Taleb's famous “Turkey Problem” to explain one of the biggest mistakes investors make: believing the future will always look like the past. From a shocking World Cup upset to the collapse of once-untouchable companies like Enron and GE, he shows how unexpected "Black Swan" events can destroy even the most confident predictions. The lesson? No matter how certain an investment appears, concentration risk can be devastating. Diversification isn't about predicting the future—it's about surviving the surprises nobody sees coming.

On June 12, 2026, Elon Musk officially became the world's first trillionaire after SpaceX's record-shattering IPO. But here's the uncomfortable part: he built that fortune by breaking the most repeated rule in personal finance. He never diversified. He bet everything — twice — on companies he controlled. In this episode, I unpack what that actually means for your money. We walk through Musk's all-in playbook, from the $180 million PayPal payout to nearly going broke in 2008, and confront an uncomfortable truth: nobody ever got on the Forbes list with a diversified portfolio. Then we visit the graveyard nobody talks about — the thousands who made the same bet and lost everything — and break down the three advantages Musk had that you and I don't. You'll leave with a clear framework: when concentration makes sense, when diversification is non-negotiable, the one concentrated bet you already own (and should double down on), and how to size a "conviction bet" without putting your family's plan at risk. What we cover: The SpaceX IPO and what a trillion dollars actually looks like. The all-in playbook: PayPal to near-bankruptcy to history. Why diversification will never make you rich — and isn't supposed to. Survivorship bias: Enron, dot-com, and the losing tickets history forgets. Concentrate to build, diversify to keep: what this means for you Questions about your own portfolio's hidden concentration? Book a conversation by emailing me at info@creatingricherlives.com. Disclosure: This episode is for educational purposes only and is not personalized investment advice.

Do you remember Enron? Or more recently, Elizabeth Holmes and Theranos? Really smart people deceived other really smart people. Today, Pastor JD warns you: the end times are coming, and whether you’re smart or not, you can be deceived. What will prevent you from deception? God’s word will provide the anchor.

Do you remember Enron? Or more recently, Elizabeth Holmes and Theranos? Really smart people deceived other really smart people. Today, Pastor JD warns you: the end times are coming, and whether you’re smart or not, you can be deceived. What will prevent you from deception? God’s word will provide the anchor.

For three years, a counterfeiting bug sat live inside Zcash's shielded pool, and no one noticed. Then Taylor Hornby pointed a custom Claude Opus 4.8 agent at the code, and it surfaced the flaw in Orchard that had gone undetected since 2022. Austin Campbell, Ram Ahluwalia, and Chris Perkins debate what that means for privacy protocols, the rotation away from dead-protocol alts, and why Bitcoin's simplicity may be its strongest security argument yet. The conversation closes on quantum risk and whether the Lindy effect holds up under the new threat environment. Hosts: Austin Campbell, Founder of Zero Knowledge Consulting and Adjunct Professor at NYU Stern - https://x.com/austincampbell Ram Ahluwalia, CEO of Lumida - https://x.com/ramahluwalia Chris Perkins, President of CoinFund - https://x.com/perkinscr97 This clip is from a longer conversation on AI, security, and the Zcash counterfeiting bug. Full episode here: https://www.youtube.com/live/oSUVTmC3wZo?si=zTopwWKi3ETPD5Rz  We go live every Monday at 4:30pm ET - subscribe to catch it live. Sponsors Cape: Your biggest crypto vulnerability isn't your wallet, it's your phone number. Cape is America's privacy-first mobile carrier that rotates your SIM identity daily and blocks SIM swaps before they happen. Get 33% off your first six months at cape.co/unchained (use code: UNCHAINED). Chapters

Today on The Jeff Dornik Show, Peter A. Kirby joins me to expose the machinery behind chemtrails, geoengineering, weather manipulation, carbon credits, Davos, weather derivatives, and the coming attempt to rebrand spraying the skies as “saving the planet.” Because apparently when global elites break God's created order, the obvious solution is to monetize the cleanup. Very humble of them.We dig into Kirby's research from Chemtrails Exposed, including the evidence he points to, the financial incentives behind weather control, and why the “climate change” narrative may be less about protecting the earth and more about controlling everything on it. As Scripture says, “The earth is the Lord's and the fullness thereof” — which is awkward for the people trying to turn the atmosphere into a subscription service.Order your copy of Peter A. Kirby's book Chemtrails Exposed from Skyhorse Publishing: https://www.skyhorsepublishing.com/9781510785106/chemtrails-exposed/Follow Jeff Dornik on Pickax - https://pickax.com/jeffdornikBecome a supporter of this podcast: https://www.spreaker.com/podcast/the-jeff-dornik-show--4788100/support.Follow The Jeff Dornik Show on Apple Podcasts and leave a 5-star review. That's how we reach more people and bypass Big Tech suppression.Watch LIVE daily at 7pm ET on Rumble and subscribe so you never miss a show:https://rumble.com/c/jeffdornikBig Tech is silencing truth while harvesting your data to feed the machine. That's why I built Pickax, a free speech platform where creators own their content and your voice isn't controlled. Join now:https://pickax.com/?referralCode=y7wxvwq&refSource=copy

Lords: Aubrey http://glowhno.com/ Avery Topics: Every day since 1981 Yuri Borisovich Norstein and his wife Francheska Yarbusova have worked on their masterpice--an animated adaptaion of Gogol's short story The Overcoat. They couple is now in their 80s and will most likely never complete their film. https://en.wikipedia.org/wiki/The_Overcoat_(animated_film) Video game urban legends https://vimeo.com/91436410 https://saint-arthur.tumblr.com/post/146680746144/riding-immortal-on-the-seeking-road Bay Area Airport Naming Drama The Only Animal by Franz Wright https://april-is.tumblr.com/post/89794820/april-25-2008-the-only-animal-franz-wright Microtopics: Loving only the parts you don't hate. Finishing the whole pack of Red Vines because you refuse to let them defeat you. An album you haven't put on Spotify. You know. Those podcasts. The sort of thing we don't do around here. Holding up cue cards so the guests know what to say. Reading all 180,000 messages in the Frog Fractions 2 ARG solvers discord. The tech company you're applying to sending you all the Enron emails, saying "review these before the interview" Mysteries, Easter eggs, and rose-tinted glasses. Hedgehog in the Fog. Arduous animation processes. Working on an animated feature by yourself for over 40 years. Great Family Entertainment. A story about a guy who has everything he needs who dies while trying to buy an overcoat. A huge pack of Red Vines that you and your wife have been eating since 1981. Burning yourself out very quickly if you don't put guardrails in place. Perfectionists throwing away years of work because it's not good enough. DJs who still spin vinyl and other artists who choose to do things the hard way. Enveloping yourself in an emotion. Refusing to break character for the entire time you're making the Youtube documentary. Putting away art you're having a hard time with and coming back to it later. Everything that happened between the Sigil Master and Austin Walker. Losing track of whether art looks good. The fine line between pacing yourself and torturing yourself. The statue in the background of Frog Fractions that turns red when you're on Mars. Encouraging people to have whimsy. Space Knight Rom. Snagglepuss the 1950s playwright. Back when you could make up a video game rumor and not have it immediately debunked. GTA San Andreas urban legends. Windows Movie Maker transition screens. Gravitating towards the unknowable. Self-destructing music. Scarcity and unknowability. Buying an album from the record shop and perusing the indie record label catalog that comes with it. Searching for the 16th colossus. Forming a small community and feeling communal with them. Playing games with a group of friends like a book club. An MMO full of ARGy type stuff. Automatically grouping people into a puzzle solving community. Being paralyzed by the sheer amount of information that you don't know. What's going on with the iGlyphs? Finding evidence of the Jejune Institute on a telephone pole. Painstakingly making the 7th Frog Fractions game, 45 years from now. The history of Seeking Mr. Eaten's Name. Game secrets that can't be ruined by one jerk with a decompiler. Sleep No More. Getting pulled into a secret compartment during an interactive play. Multi-city zombie larps. The Oakland Airport renaming themselves to the San Francisco Bay International Airport and then later the lawsuit becoming the Oakland San Francisco Bay Airport. Bay Area topology. San Francisco and South San Francisco. The Unincorporated Area of San Mateo County International Airport, or UAOSMCIA. American cities named after European cities. The Bass Pro Shop Pyramid in Memphis, TN. Filling a 32-story disco pyramid with sports equipment. Fry's Electronics. Another episode of Topic Lords where we read from Wikipedia. A huge empty building with paintings of Mayan gods holding torches that used to be an electronics store. One more way in which people forget about San Diego. The only animal that brushes its own teeth A monkey wearing a spacesuit trying to smoke a cigarette through the face shield. The only animal that smokes cigarettes. (Todd, who works down at the warehouse.) Meeting your estranged dad when at the awards show when you're both up for the same Pulitzer. Whether that fuckin' awesome monkey is a Bored Ape. Whether Google Image Search is making up images yet. That time Ryan North and his dog got stuck in an empty swimming pool and turned it into an interactive text adventure. By the time you've smelt it, they have dealt it. Topics are over!

This episode of Talking Real Money examines why financial advice so often turns into emotional debate instead of productive problem-solving. Don and Tom discuss how investors routinely underestimate spending, cling emotionally to employer stock, and defend strategies like dividend chasing, covered calls, crypto, or gold despite decades of evidence favoring diversified investing. They answer a listener question about aggressively paying down a 6.625% adjustable-rate mortgage versus maintaining liquidity, warn about commissioned advisors circling employees receiving RSU payouts, and correct a previous mistake regarding Roth employer matches under Secure 2.0 legislation. Along the way, the hosts mix humor, blunt honesty, and personal stories about why changing financial behavior is far harder than simply explaining the math.0:05 Are listeners looking for advice, validation, or just an argument?0:58 “Two old white guys waiting to die on a podcast” and why changing investor behavior is so difficult1:24 Basis points complaints and arguing over financial terminology2:21 Why financial planning conversations often become debates3:16 Most people underestimate how much they actually spend4:04 Net income minus savings equals spending, whether you admit it or not4:59 Growing up arguing in big families and learning debate skills early5:53 Emotional attachment to employer stock and concentration risk6:19 Microsoft, Enron, Washington Mutual, and the danger of loyalty investing7:02 Why many individual stocks underperform for long stretches7:42 Covered calls, dividend strategies, and belief in “secret” investing systems8:16 Why Don and Tom remain skeptical of crypto, gold, and speculative investing9:16 Their investing philosophy comes from peer-reviewed academic research, not hunches10:17 If you call for portfolio help, don't expect automatic validation11:23 Listener Jim asks whether to aggressively pay down his adjustable-rate mortgage12:17 Extra principal payments versus saving cash to pay off the mortgage later13:12 Why a 6.625% mortgage changes the payoff math14:35 Liquidity concerns versus the emotional appeal of being debt-free15:06 Mortgage recasting explained and reducing future interest costs17:39 Regret over not refinancing during ultra-low-rate years18:10 Why peace of mind sometimes outweighs financial optimization18:50 “Paper argues badly” and the transition into listener emails18:59 RSU sharks circling a listener with a large restricted stock payout19:48 Wealth managers aggressively targeting employees cashing out company stock20:47 Warning signs of commissioned annuity sales disguised as “help”21:48 Why concentrated company stock remains risky even after huge gains22:24 Recalling the advisor who openly admitted to a 10% annuity commission22:41 Retirement quiz follow-up and correcting a Roth 401(k) mistake23:01 Secure 2.0 technically allows Roth employer matches in 401(k)s24:09 Why most employers still don't offer Roth matching contributions24:36 Tax uncertainty and the value of maintaining both Roth and pre-tax accounts25:33 Tom admits he occasionally tells players when he missed a call as a referee26:05 Encouraging listeners to argue, ask questions, and engage with the show27:02 Offering free portfolio consultations without annuity sales pressure27:39 Joking about becoming annuity salesmen after all these yearsQuestions? Comments? Click!

Join host Adam Larson as he welcomes expert guests Dana Hermanson, Daniel Haggerty, and Douglas Boyle—the authors of the 2026 Curt Verschoor Ethics Feature of the Year—for an honest, eye-opening discussion on the shadow side of professional ethics. After their award-winning article on building virtue, the trio flips the script—this time tackling the capital vices of pride, envy, and greed, and exploring why good people sometimes make bad choices. Hear real-world examples, from Enron to Theranos, and pick up practical strategies for recognizing and overcoming these vices in yourself and your organization. Daniel shares a philosopher's perspective on the roots of bad behavior, Douglas draws on his executive experience to talk about healthy versus harmful pride, and Dana connects classic wisdom to familiar fraud prevention tools. Whether you're a finance leader, student, or just curious about why fraud still happens, this is a conversation packed with insight, stories, and advice you can use right away—including a behind-the-scenes look at their award-winning article.

Episode 991 of The Professional Left starts with a question that sounds absurd on its face — are Americans "underbabied"? — and then spends an hour making the case that the people asking that question are the same ones who have spent decades doing everything in their power to make starting a family feel financially impossible. Driftglass and Blue Gal trace the long arc from the post-war baby boom through the Reagan era's war on the social safety net, showing how decades of Republican policy quietly transformed children from a shared public good into a personal lifestyle choice that you'd better be able to afford on your own. A detour through the Enron collapse and the Great Recession ties it all together — because low birth rates aren't the disease, they're the symptom, and this episode lays out exactly what's causing them.Stay in Touch! Email: proleftpodcast@gmail.com Website: proleftpod.com Support via Patreon: patreon.com/proleftpod or Donate in the Venmo App @proleftpodMail: The Professional Left, PO Box 9133, Springfield, Illinois, 62791Artwork courtesy of "america has rabies" on BlueSky @thebatshitsutras.bsky.socialSupport the show

Tom and Don take aim at the persistent myth that active management adds meaningful long-term value, using a new study highlighted by Larry Swedroe showing that 1,260 balanced mutual funds dramatically underperformed simple low-cost index portfolios from 1990–2021. The duo contrasts expensive actively managed balanced funds with inexpensive index strategies like the Vanguard Balanced Index approach, illustrating how fees alone can devastate long-term returns. Along the way, they discuss the emotional challenge of rebalancing, the hidden costs inside broker-sold funds, and why simplicity usually beats complexity in investing. Listener questions cover paying off a high-interest HELOC, whether gold or silver make sense as CD replacements, how advisor fees relate to the 4% withdrawal rule, and the behavioral value of good fiduciary advice. The episode wraps with a detour into collectible stock certificates, including Enron, Washington Mutual, and even Trump Media, proving once again that Talking Real Money can turn almost anything into a financial lesson and a comedy bit.0:05 Satirical opening mocking the “you need a professional” investing pitch0:27 The enduring myth that active management beats indexing1:40 Larry Swedroe study on 1,260 balanced mutual funds vs. index portfolios3:05 Balanced funds underperform across returns and risk-adjusted metrics4:32 Massive fee differences between active funds and index funds6:05 Rebalancing challenges and lousy 401(k) investment menus7:05 American Funds Balanced Fund fee breakdown shocks Don8:49 Vanguard Balanced Index Fund cost comparison9:36 Why advisor fees are different from high mutual fund expenses10:30 Simplicity and low costs win most of the time11:41 Enron stock certificate becomes a lesson on stock-picking risk14:47 Listener question about paying off a 7.1% HELOC19:29 Whether pensions should count as “bond-like” assets21:42 Gold and silver vs. CDs discussion25:40 Does the 4% rule include advisor fees?26:11 Vanguard Advisor Alpha and the behavioral value of advisors27:32 Fiduciary advice, tax management, and preventing investor mistakes28:50 Collectible stock certificates and bizarre eBay discoveries30:48 Closing banter and preview of future unpredictabilityQuestions? Comments? Click!

Bill Gurley is a Wall Street and Silicon Valley legend. He's the analyst who led the Amazon IPO and went on to become one of the most successful VCs of all time and an early investor in Uber, Zillow, and GrubHub. Today, he joins Nicole to answer the biggest questions on investors' minds right now. Bill doesn't mince words: yes, we're in an AI bubble— and he explains exactly why, from circular spending deals that smell like Enron to the speculative behavior that always follows a real wave of innovation. He breaks down why the IPO system is rigged against retail investors, what tokenization could do to fix it, and what a SpaceX IPO would actually mean for everyday investors. He also shares the one market sector he thinks is quietly becoming a buy, and the specific Chinese battery stock he personally owns. Then the conversation shifts to Bill's new book, Runnin' Down a Dream, and his surprisingly personal framework for building a career you actually love. He shares the question he asked himself twice that changed the entire course of his life, his research on career regret, and why chasing passion is a competitive advantage. Check out Nicole's financial literacy course The Money School  Find a Financial Advisor or Financial Coach from Nicole's company Private Wealth Collective Watch video clips from the pod on Money Rehab's Instagram and Nicole Lapin's Instagram Get Bill's book Runnin' Down a Dream  Here's what Nicole covers with Bill:  00:00 Are You Ready for Some Money Rehab?  01:12 SpaceX + xAI: What Elon's Deal Really Means  03:18 Why Retail Investors Keep Getting Shut Out of the Best Companies  05:55 The IPO System Is Rigged  08:36 Inside the Amazon IPO 10:40 Are We in an AI Bubble?  16:30 AI vs. the Dot-Com Bubble 21:15 Which AI Tools Bill Actually Uses  22:00 Bill's Take on AGI Hype  23:30 Where Bill Sees Opportunity Outside of Tech  27:30 The Chinese Battery Stock Bill Personally Owns  28:45 How to Evaluate Stock Options as an Employee  31:50 The Hidden Value of Joining a Fast-Growing Company  33:15 Buy Side vs. Sell Side Analysts  35:40 The Question That Changed Bill's Career Twice  38:00 Why Following Your Passion Is a Competitive Advantage  42:00 How Tito's Vodka Started with a Blank Sheet of Paper  45:20 Bill's Next Chapter: A Policy Institute  48:00 Nuclear Energy, Healthcare, and the Issues Bill Wants to Fix  51:06 Bill Gurley's Tip You Can Take Straight to the Bank All investing involves the risk of loss, including loss of principal. This podcast is for informational purposes only and does not constitute financial, investment, or legal advice. Always do your own research and consult a licensed financial advisor before making any financial decisions.