Podcasts about lps

Fix Leaky Gut, Boost Testosterone & Slash Endotoxins with Spore-Based Probiotics | Kiran KrishnanYour bad gut bacteria might be the reason your testosterone, your immune system, and even your sperm count are struggling, and most probiotics never survive long enough to fix it. This episode reveals which strains actually make it through your stomach acid alive, and what happens once they do. Go To JustThriveHealth.com/asprey for a free 90 day supply of bitters with your next subscription. Host Dave Asprey sits down with research microbiologist Kiran Krishnan, co-founder of Microbiome Labs, the leading microbiome therapeutics brand among healthcare professionals. He has published multiple peer-reviewed studies, holds global patents, and has spent 20 years building companies focused on the science of the microbiome. His work centers on spore-based probiotics, the rare strains proven to survive the stomach's brutal acidity and actually rebuild the gut from the inside out. Kiran and Dave break down why 98 percent of conventional probiotics die before they ever reach your gut, and why spore-forming bacteria are different. They dig into the "gelding effect," the well-documented pathway where endotoxins from bad gut bacteria shut down testosterone production and drive up cortisol, and how fixing your microbiome can reverse it. They cover the connection between endotoxemia and nearly every major marker of aging, metabolism, and inflammation, why butyrate acts like a natural GLP-1 for fat loss, how Akkermansia can upregulate mitochondria and improve blood sugar control, and the surprising role vitamin K2 plays in bone density and functional medicine. This is biohacking at the cellular level, using ancient biology, fasting-adjacent metabolic pathways, and precision supplementation to optimize human performance from the gut up. You'll Learn: Why 98 percent of probiotics die in your stomach before they ever work What the "gelding effect" is and how gut bacteria can shut down testosterone How endotoxins drive inflammation, cortisol, and accelerated aging Why butyrate functions like a natural, low-cost alternative to GLP-1 drugs How Akkermansia improves mitochondrial function and blood sugar control The overlooked link between your microbiome and vitamin K2 production Why spore-based probiotics can survive gastric acid when most others cannot How 90 days of gut repair can measurably reduce circulating endotoxins Keywords: best probiotics that survive stomach acid, spore based probiotics benefits, gelding effect testosterone, endotoxins and testosterone, how to lower endotoxins, LPS gut bacteria, Akkermansia GLP-1 natural, gut bacteria and belly fat, vitamin K2 bone density, Kiran Krishnan microbiologist, Just Thrive probiotic, leaky gut symptoms, microbiome and testosterone, fecal transplant benefits, Dave Asprey, biohacking, longevity Resources: • Go To JustThriveHealth.com/asprey for a free 90 day supply of bitters with your next subscription • Learn More About All Of Just Thrive's Offerings At: https://justthrivehealth.com/ • Get My 2026 Clean Nicotine Roadmap | Enroll for free at https://daveasprey.com/2026-clean-nicotine-roadmap/ • Dave Asprey's Latest News | Go to https://daveasprey.com/ to join Inside Track today. • Danger Coffee: https://dangercoffee.com/discount/dave15? • My Daily Supplements: SuppGrade Labs (15% Off) • Favorite Blue Light Blocking Glasses: TrueDark (15% Off) • Dave Asprey's BEYOND Conference: https://beyondconference.com • Dave Asprey's New Book – Heavily Meditated: https://daveasprey.com/heavily-meditated • Join My Substack (Live Access To Podcast Recordings): https://substack.daveasprey.com/ • Upgrade Labs: https://upgradelabs.com Thank you to our sponsors! - ZenBud | Dave's Nervous System Biohack. Visit zenbud.health and use code DAVE15 at checkout for a discount. - BodyHealth | Visit BodyHealth.com and use code DAVE20 for 20% off your first purchase. - Redmond Real - Leaf Toothpaste | Go to https://redmond.com/asprey and use code ASPREY for 15% off your first order. - Show notes - ELITE Performance Coaching | If you'd like to discover where you may be addicted to struggle, allergic to success, and what may be standing between you and your next breakthrough, visit FastestChange.com Timestamps: 00:00 – Trailer 00:38 – Kiran Intro 02:01 – Stomach Acid & Probiotics 05:25 – Fauci & Spore Bacteria 13:58 – Losing Gut Diversity 19:01 – How Butyrate Is Made 22:11 – Dave's Personal Stack 24:00 – Quorum Sensing 31:26 – Endotoxins Explained 37:13 – Charcoal & Binders 39:41 – SIBO & Gut Bacteria 45:03 – Discovering Vitamin K2 49:33 – Gelding Effect & Testosterone 54:51 – Akkermansia & Weight Loss 01:02:17 – Role of Bitters 01:04:47 – Just Thrive Gift See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Welcome back to the Alt Goes Mainstream podcast.We were live from Berlin, which becomes the “capital of private capital” in June as the private equity's industry leaders make the annual pilgrimage to the city for one of the marquee private equity conferences, SuperReturn Berlin.Much of the SuperReturn conference is centered on fundraising. GPs take up every available space — from hotel rooms to Tiny Space cabins that line the parking spots on Budapester Strasse outside of the InterContinental conference venue — to conduct meetings with LPs.With Prosek Partners and former Bloomberg TV journalist Deirdre Bolton as my producer, along with her team, we took over a Tiny Space cabin to hold big conversations with some of the industry's leading alternative asset managers.Our first conversation was with Apax Co-CEOs Andrew Sillitoe and Mitch Truwit.Apax is one of the pioneers in the private equity industry. The firm's rich history dates back to the 1970s, when its founders, Alan Patricof (US), Sir Ronald Cohen (UK), and Maurice Tchénio (France), came together to establish the first US-UK partnership firm in private equity. During that time period, the firm backed Steve Jobs and the first iteration of Apple. The UK and US firms merged in 1981, laying the foundation for Apax.Today, Apax stands at over $80B in aggregate funds raised. The firm underwent its second leadership transition in 2014, when Andrew and Mitch were elected as Co-CEOs, succeeding Martin Halusa, who became Chairman.Apax sits in a unique position. They are a scaled platform that focuses on the middle market. They operate across three sectors, Tech, Services, and Digital / Consumer, infusing a digital DNA and value creation team into everything they do. Their platform spans “a mile wide and a mile deep,” which is what much of the conversation between Andrew, Mitch, and me unpacked.We had a fascinating discussion about the current state of private equity and the middle market, why Apax focuses on “density-driven business models,” why the firm focuses on carveouts in the middle market, what's underappreciated about the middle market, why it's important to “buy in the right neighborhood and fix it up,” and how the firm's core values of “having impact through insight and tenacity” drive every decision they make.BiosAndrew Sillitoe has been Co-CEO of Apax since 2014. He is Chairman of the Apax Global Investment Committee and the Digital Investment Committee, amongst others. He is also a member of the Apax Executive Committee. He has been based in London since joining the Firm in 1998, focusing on Tech & Telco investments.Andrew has been involved in a number of investments including Inmarsat, Intelsat, King, Orange Switzerland, TIVIT, TDC and Unilabs.Prior to joining Apax, Andrew was a consultant at LEK. Andrew holds an MA in Politics, Philosophy and Economics from the University of Oxford and an MBA from INSEAD.BoardsAndrew has previously served on the boards of Inmarsat, King, Intelsat, Orange Switzerland and TDC.Mitch Truwit is Co-CEO of Apax, based in New York.Prior to joining Apax in 2006, Mitch was the President and CEO of Orbitz Worldwide between 2005 and 2006 and was the Executive Vice President and Chief Operating Officer of priceline.com between 2001 and 2005.Mitch is a graduate of Vassar College where he received a BA in Political Science. He also holds an MBA from the Harvard Business School.BoardsMitch serves as a Board member of Openlane and Trade Me. Prior boards include Advantage Sales & Marketing, Assured Partners, Dealer.com, Bankrate, Garda World, Hub International, Trader Canada, Boats Group and Quality Distribution Inc.Mitch serves on the charitable boards of the Apax Foundation, the John McEnroe Tennis Project, Posse and StreetSquash.Thanks, Andrew and Mitch, for a fascinating conversation and for sharing your expertise, wisdom, and passion at the intersection of investing and operating in private equity.Show Notes00:00 Meet Apax co-CEOs, Andrew Sillitoe and Mitch Truwit00:26 Andrew's Origins at Apax00:47 Private Equity Then vs Now01:25 Apax Growth and Values01:45 Curiosity as a Differentiator02:04 Mitch's Operator Background02:56 Why Mitch Joined Apax03:40 Defining the Middle Market04:14 Why Sub-Billion EV Works04:59 Middle Market Talent Gap05:20 Carve Outs as a Strategy05:29 TRADER Corporation - Canada App Turnaround06:12 Scaled Platform Advantage07:14 Digital DNA and AI Wave07:50 Top Line Growth Lever08:36 Add-ons and TAM Expansion09:33 ECI Case Study Roll Up10:07 Integration Over Collection10:28 Exit Options in a Bigger PE World10:59 Building for Multiple Buyers11:45 Fund Size Discipline12:34 Choosing Returns Over AUM13:16 Understanding Firm DNA14:01 Global Micro Investing14:49 Making Global Pods Work15:50 Scale Specialization Flexibility17:08 Where to Invest Now19:23 Buying Complexity for Value20:15 Moats and Investment Committee22:13 Why Middle Market Excites Them23:19 Future of PE and AI at Scale24:50 Impact Insight Tenacity Culture25:54 Obligation to Dissent Story26:55 Aspirational Brand Analogy27:48 Wrap Up and Thanks

Richard McGirr talks to Chad Ackerman as he shares his journey from building a community of LPs at Left Field Investors to coaching operators and investors on mastering deal structures. You'll discover how simplifying complex arrangements like preferred equity and deal tranching can dramatically increase your chances of closing deals, while reducing your risk and aligning incentives for all parties involved. Chad Ackerman Founder of Chad Ackerman Real Estate Based in: Dublin, Ohio Where to find them: https://chadackermanrealestate.com/ https://www.linkedin.com/in/chad-ackerman-8089a8a Book your free demo today at bill.com/bestever and get a $100 Amazon gift card. Visit https://malabarhillcapital.com/ for more info. Podcast production done by⁠ ⁠Outlier Audio Learn more about your ad choices. Visit megaphone.fm/adchoices

Our guest on This Week in Radio Tech episode 809 is Tim Berry, Chief Engineer at WUOT-FM, the public radio station at the University of Tennessee in Knoxville. WUOT combines NPR news with classical and jazz music, much of it still played live from CDs and occasionally from the station’s enormous collection of LPs. Tim gives us a tour of the control room, performance area, technical center, and an extraordinary music library that also includes thousands of historic 78 RPM records. We’ll see one of Tennessee’s earliest Audio over IP installations, built around Axia Livewire technology and operating for about 15 years. Tim also maintains more than 20 analog and digital amateur radio repeater sites throughout East Tennessee. Join us for a fascinating look at preserving broadcasting’s rich history while planning the technical upgrades that will carry WUOT into the future. Show Notes:Pioneers & Engineers - The WUOT Story Guest:Tim Berry, CBRE, CBT - Chief Engineer at WUOT-FM & WUTK-FM "UT's College of Rock!" Host:Kirk Harnack, The Telos Alliance, Delta Radio, Star94.3, South Seas, & Akamai BroadcastingFollow TWiRT on Twitter and on Facebook - and see all the videos on YouTube.TWiRT is brought to you by:Broadcasters General Store, with outstanding service, saving, and support. Online at BGS.cc. Broadcast Bionics - making radio smarter with Bionic Studio, visual radio, and social media tools at Bionic.radio.Aiir, providing PlayoutONE radio automation, and other advanced solutions for audience engagement.Angry Audio and the new USB Phone Gizmo - Put VoIP callers on-the-air The new MaxxKonnect RMT416 Multi Tuner - 4 to 16 AM/FM/WB/HD web-connected tuners in 1 RU Subscribe to Audio:iTunesRSSStitcherTuneInSubscribe to Video:iTunesRSSYouTube

Our guest on This Week in Radio Tech episode 809 is Tim Berry, Chief Engineer at WUOT-FM, the public radio station at the University of Tennessee in Knoxville. WUOT combines NPR news with classical and jazz music, much of it still played live from CDs and occasionally from the station's enormous collection of LPs. Tim gives us a tour of the control room, performance area, technical center, and an extraordinary music library that also includes thousands of historic 78 RPM records. We'll see one of Tennessee's earliest Audio over IP installations, built around Axia Livewire technology and operating for about 15 years. Tim also maintains more than 20 analog and digital amateur radio repeater sites throughout East Tennessee. Join us for a fascinating look at preserving broadcasting's rich history while planning the technical upgrades that will carry WUOT into the future.

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president could still fire commissioners, as the Court now permits, but if those firings broke quorum, the agency would be unable to proceed until replacements were confirmed. The guardrail would

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.There was an issue with this only going to paid subscribers, so sending it again. Apologies to those who get it twice. I appreciate being paid so feel free to upgrade if you enjoy TWTW.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president

Host Brian Walsh takes up ImpactAlpha's top stories with editor David Bank. Up this week: A look at the cool tech investors seeking sustainable solutions to help billions beat the heat; why impact LPs are buying and selling stakes in the secondaries market; and, debriefing this week's call, which asked whether faith-aligned investors can become known for what they are for, not just what they're againstTo try ImpactAlpha Edge, ⁠⁠⁠⁠click here⁠⁠⁠⁠. RSVP for next week's Call.This week's stories:“Cool tech fund looks to India for sustainable solutions to beat the heat,” by Jessica Pothering“Liquidity for sellers, discounts for buyers in budding impact secondaries market,” by Amy Cortese“Helping faith-aligned investors direct their assets toward ‘human flourishing,'” by Erik Stein. Watch the full video replay.

Host Brian Walsh takes up ImpactAlpha's top stories with editor David Bank. Up this week: A look at the cool tech investors seeking sustainable solutions to help billions beat the heat; why impact LPs are buying and selling stakes in the secondaries market; and, debriefing this week's call, which asked whether faith-aligned investors can become known for what they are for, not just what they're againstTo try ImpactAlpha Edge, ⁠⁠⁠⁠⁠click here⁠⁠⁠⁠⁠. ⁠RSVP for next week's Call⁠.This week's stories:“⁠Cool tech fund looks to India for sustainable solutions to beat the heat⁠,” by Jessica Pothering“⁠Liquidity for sellers, discounts for buyers in budding impact secondaries market⁠,” by Amy Cortese“⁠Helping faith-aligned investors direct their assets toward ‘human flourishing⁠,'” by Erik Stein. Watch the ⁠full video replay⁠.

What does it take to write the very first check into a company that has almost nothing to show yet, sometimes not even a finished idea?Afore Capital helped invent the pre-seed category. When Gaurav Jain and Anamitra Banerji started the firm ten years ago, "pre-seed" was almost a slight, a label for founders who couldn't raise a proper seed round. They set out to build the world's largest pre-seed fund anyway, closing $47 million on a $40 million target, and every fund since has closed above plan. Afore now runs more than $500 million across four funds, with top-quartile DPI on the first three. The idea has become so mainstream that when Sequoia launched its latest fund, it said, "I guess we're pre-seed investors too."The real substance of the conversation is how Gaurav thinks. He is clear about what matters most in venture, and the order tends to surprise people. Being in the very best companies matters more than anything else, ownership comes after that, and the entry price that so many investors fixate on matters least, because fifty per cent of zero is still zero. He is also convinced that the genuine bottleneck is talent. There is a great deal of money in the world and very few people who can build something truly large, which is why at the earliest stage founders tend to choose their investors as much as investors choose them. You give a founder a million dollars with no collateral, and then you still have to convince them to take it. A pre-seed pitch, he says, is almost entirely storytelling with very little data behind it.If you want to understand how the earliest checks actually get written, and what it really costs to say no, this episode is worth your time.00:00 - Trailer01:00 - From Dehradun to Google to starting Afore02:08 - The Waterloo co-op that talked him out of every job03:18 - Back when "pre-seed" was an insult05:44 - When Sequoia said "I guess we're pre-seed investors too"07:26 - Afore's three products, and the experiments that failed09:01 - Hightouch was a travel company when they invested11:02 - Goldcast: no visa, no money, funded anyway12:07 - The through line is always the team14:44 - The Ramp miss17:24 - "Founders pick us more than we pick them"18:45 - The constraint isn't capital, it's talent22:24 - The Solana miss, when it was still Loom Protocol24:46 - Ramp's Super Bowl ad, the buses, his wife's business25:32 - What he looks for in founders28:50 - Coachability, happy ears, and the Mom Test31:28 - The biggest mistake: falling in love with the idea35:04 - The three things that matter, and "50% of zero is still zero"39:25 - "100% storytelling, 0% data"41:25 - Investing in India, and the fear of being dumb capital44:41 - "Sign the deal before Monday"47:26 - One engineer now does the job of 2051:43 - Raising from LPs, the undiscussed part of VC-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

. Hoy sacamos del baúl una joya de 1973: el LP "I've Got the Blues" de nuestro viejo lobo Lowell Fulsom, editado bajo el sello Jewel Records con la referencia LPS 5009.

Episode #281 See what others have to say about the deal and join the conversation: https://passivepockets.com/forums-listing/discussion/new-deal-dlp-capital-preferred-credit-fund/ Check out the DLP Preferred Credit Fund for yourself: https://passivepockets.com/directory/deals/dlp-preferred-credit-fund/ This Episode In this special LP Deal Review episode, Chris Lopez is joined by Adam Cranmer and Pascal Wagner to evaluate DLP Capital's Preferred Credit Fund with Don Wenner, founder and CEO of DLP Capital. Don walks through the fund's strategy, target return profile, underwriting process, borrower standards, and how DLP approaches development, construction, bridge, mezzanine, and preferred equity lending in today's market. The discussion digs into why DLP focuses on housing that is affordable for working families, how the firm thinks about lending in high-growth Sunbelt markets, and what separates its Preferred Credit Fund from a senior secured lending fund. Don also addresses several of the key diligence questions LPs should be asking right now, including geographic concentration risk in Florida and Texas, loan-to-value and loan-to-cost metrics, borrower concentration, third-party validation, fund administration, internal controls, and how rising interest rates could affect the fund's risk profile. After Don leaves the conversation, Chris, Adam, and Pascal break down the fund from an LP perspective. They discuss what they like about DLP's track record, reporting, borrower quality, and institutional infrastructure, while also highlighting the risks they are watching closely, including mezzanine exposure, state concentration, self-dealing concerns, fees, macro uncertainty, and whether the return spread is attractive enough compared to risk-free alternatives. The episode closes with a broader conversation about how LPs should think about risk, liquidity, debt versus equity, and portfolio construction in an uncertain investing environment. Key takeaways: How DLP's Preferred Credit Fund targets monthly income through private real estate credit Why DLP focuses on housing affordability, experienced borrowers, and Sunbelt growth markets How Don compares mezzanine and preferred equity risk to senior secured lending fund risk What LPs should ask about loan-to-value, loan-to-cost, borrower concentration, and fund-level controls Why third-party audits, appraisals, loan tapes, and investor reporting matter in debt fund diligence How experienced LPs think about DLP's strengths, yellow flags, fees, concentration risk, and macro exposure Why each investor needs a clear portfolio thesis before choosing between cash, Treasuries, debt funds, or equity deals Join a community of passive investors. Start your FREE 7-day trial: https://passivepockets.com/?utm_source=youtube&utm_medium=description&utm_campaign=none Listen to the PassivePockets Podcast Anywhere: https://lnk.to/passivepockets Subscribe to the Passive Investing Newsletter: https://www.biggerpockets.com/email-subscribe?utm_source=youtube&utm_medium=description&utm_campaign=none Join BiggerPockets for free: https://www.biggerpockets.com/signup?utm_source=owned_media Disclaimer The content of this podcast is for informational purposes only. All host and participant opinions are their own. Investment in any asset, real estate included, involves risk, so use your best judgment and consult with qualified advisors before investing. You should only risk capital you can afford to lose. Past performance is not indicative of future results. This podcast may contain paid advertisements or other promotional materials for real estate investment advisers, investment funds, and investment opportunities, which should not be interpreted as a recommendation, endorsement, or testimonial by PassivePockets, LLC or any of its affiliates. Viewers must conduct their own due diligence and consider their own financial situations before engaging with any advertised offerings, products, or services. PassivePockets, LLC disclaims all liability for direct, indirect, consequential, or other damages arising out of reliance on information and advertisements presented in this podcast.

In this special episode of Tank Talks, recorded live during Toronto Tech Week at Moomoo Canada's flagship store in Yorkville, Matt Cohen sits down with two of venture's sharpest data and investment minds for an unfiltered conversation on the state of private markets.Peter Walker, Senior Director of Insights at Carta, brings the hard numbers from 60,000+ companies and 3,000+ US venture funds, revealing the stark reality behind valuation markups, unicorn deterioration, and the widening dispersion between top-tier and median deals.John Rikhtegar, Vice President at Northleaf Capital Partners and former RBC investor, offers the LP perspective on why trust matters more than ever, why emerging managers are bearing the brunt of capital allocation challenges, and how disciplined pacing and vintage diversification separate winning funds from the rest.Together, they tackle the 4.3 trillion-dollar NAV overhang, the brutal graduation rates for 2021 vintage funds, whether valuations have permanently shifted, and why the ATM analogy might be the best way to understand AI's impact on venture careers.If you're a GP raising capital, an LP sorting through manager pitches, or just trying to make sense of where venture is headed, this episode is a must-listen.The Great LP Reset: Trust Over Performance (08:05)* Why LPs are letting go of newer relationships while sticking with 15-year partners.* The COVID furlough analogy: why junior and newer team members are the first to go.* How trust became the ultimate table stakes in today's fundraising environment.The 4.3 Trillion Dollar NAV Problem (12:33)* Why SpaceX's IPO would return only 10% of capital deployed over the last decade.* The staggering number of unicorns still sitting on stale marks from 2021.* What happens when 50% of unicorn down rounds become the new normal.Valuation Dispersion Is Breaking the Model (17:38)* Seed valuations jumped from $15M post-money (2022) to $24M (2025).* Series A went from $46M to nearly $80M in the same period.* Why the gap between the top decile and the median has never been wider.* How GPs must adapt ownership expectations or get priced out of deals.The Unicorn Graveyard: Stale Marks and Deteriorating Assets (19:28)* December 2021: 640 unicorns on Carta; 85% of current US unicorns.* 30% have raised new up-rounds; of the rest, half raised down rounds of 50% or more.* How GPs are forced to tell LPs that their “trophy assets” are no longer real.Pacing, Reserves, and Portfolio Construction (22:53)* Why disciplined 3-4 year deployment beats 18-month “firehose” strategies.* The 80/20 reserve debate: why leading rounds can become a net negative.* How “deal 13” is just as likely to succeed as “deal 12”, and why slightly larger portfolios make sense.LP Diligence: It's Not About the Marks (31:55)* Why TDPI and DPI are just 2 of 100 mosaic factors in LP decision-making.* How LPs now go company-by-company, not fund-by-fund.* The importance of founder references, especially from failed companies.Canada vs. The US: A Fractal Problem (40:44)* Why every market (Toronto, Sydney, London, Seattle) faces the same “Silicon Valley problem.”* The importance of domestic liquidity and secondary markets over chasing US LPs.* Why returns, not international capital, will ultimately scale Canadian firms.AI and the Future of Venture Careers (44:44)* The ATM analogy: AI will eliminate tasks, not jobs.* Why the role of the investor becomes more important as noise and froth increase.* How family offices are shifting their mix between fund investing and direct deals.Retail Access to Private Markets: Feature or Bug? (53:27)* Why illiquidity in private markets is a feature, not a bug.* The absurdity of allowing crypto “shitcoins” but blocking friends from investing in startups.* Why “401k-entrance” to private equity is a bigger story than retail venture access.About the GuestsPeter Walker is the Senior Director of Insights at Carta, where he leads the team responsible for analyzing data from over 60,000 companies and 3,000+ venture funds. His work on valuations, liquidity, and fundraising trends is widely cited across the venture ecosystem. He is a regular speaker at industry events and writes extensively on LinkedIn about the intersection of data and venture capital.Connect with Peter Walker on LinkedIn: linkedin.com/in/peterjameswalkerLearn more about Carta: carta.comJohn Rikhtegar is a Vice President at Northleaf Capital Partners, joining in early 2026 after a distinguished career at RBC and as an operator at Shopify and in the UK. He brings a unique blend of LP and operational perspectives, with deep expertise in due diligence, portfolio construction, and the dynamics of emerging manager investing.Connect with John Rikhtegar on LinkedIn: https://www.linkedin.com/in/johnrikhtegar/Learn more about Northleaf Capital Partners: https://www.northleafcapital.com/Connect with Matt Cohen on LinkedIn: https://ca.linkedin.com/in/matt-cohen1Visit the Ripple Ventures website: https://www.rippleventures.com/ This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit tanktalks.substack.com

Ben, Jeff and Markisan celebrate one of their all-time favorite bands - Neurosis!* They discuss how the music of Neurosis came into their lives and what it has meant to them over the years. They also talk about the recent reformation of the band with former Isis vocalist/guitarist Aaron Turner and how the new record has impacted the metal universe. Then, they dig deep into the extraordinary Neurosis discography, ranking all 12 LPs (with nods to the Sovereign EP and Jarboe collab) and analyzing the riffs, experimentations, emotion, energy and influence of each album. Welcome to Neurosisology, where all structures collapse, mysteries unfold.*Also check out our awesome long-form dialogue from June 22, 2023 with Neurosis's Steve Von Till!THANK YOU to Evoken for allowing us to use a section from their song, The Last of Vitality, as our opening theme song!

Inter-dimensional music lovers of the world and beyond welcome to part 3 of this 4 track E.P of this 1970s episodic excursion that sets out this week to seek out the building blocks from what we have so far played to define the sweet rhymes and wonderful rhymes that stacked the building blocks of soul music time that culminated not only the laying the foundations for soul music artists to evolve but! Just who benefited from allowing the genre to arise as fast as it fell a mere two years later… Fear not!  For on this day! We are going to concentrate on the trip so hip! You are going feel the Space dust in your pocket, see evil Knievel in your garden and Trip on the twister set in your front room. Welcome home to your memories served purely by my record collection and LPs fuelled via my passion to simply make you feel good. Enjoy

In this episode we sit down with Justin and Sean from Sweeney's Tavern. Located in the historic Franklinton neighborhood, this community bar boasts creative craft cocktails, classic beers (aka "Dad" beers), a record player and plenty of shenanigans. And there is Malört, lots of it; Malört shots, Malört infusions, Malört cocktails. So dig out your LPs and head to Sweeney's for a good time and Malört, if you dare.

Welcome back to the Alt Goes Mainstream podcast.Today's podcast takes us to the heart of Mayfair in London, where Blackstone Private Wealth COO Farhad Karim shared the firm's history and evolution in Europe. He took a walk down memory lane to discuss the firm's 25th anniversary in Europe as we walked through Berkeley Square from Blackstone's current office to their new office at the other end of the square, highlighting how the firm has become the largest owner of commercial real estate in Europe and the importance of building a local presence in the region.Farhad took on the role of Chief Operating Officer of Blackstone Private Wealth in 2024 after a career at Blackstone that included serving as Chairman and Chief Operating Officer of Blackstone Europe and holding a senior leadership role in the firm's Real Estate business.Farhad and I had a fascinating discussion about the evolution of Blackstone's business in Europe and the firm's Private Wealth business globally. We covered:Why it's important to “meet people where they are at.”What Farhad learned from his experience as chairman of Blackstone Europe.Building and expanding Blackstone's Private Wealth business.How Blackstone will continue to be a pioneer in private wealth.The next phase of product innovation in the wealth channel.How an international perspective has shaped Farhad's approach to building the Private Wealth business.Harmonizing the institutional and private wealth businesses when delivering solutions to LPs.The human element of working with wealth.What it means to be “relentless.”Perspectives on evergreen funds.The scale of opportunity, information, and access.Thanks, Farhad, for sharing your wisdom, expertise, and passion about private markets and private wealth.Show Notes00:33 A Message from Our Sponsor, Ultimus Fund Solutions02:14 Farhad's Blackstone Journey03:37 Speed and Certainty Culture04:07 Real Estate to Wealth Channel Parallels05:04 Building for Local Markets06:16 On-the-Ground Coverage Worldwide07:45 Education at Scale08:52 How Well Advisors Understand Private Markets10:45 Early Innings Adoption12:09 Packaging Private Markets Products13:46 Simplicity vs Customization14:39 Consolidation and Institutionalization19:14 Global Trends Localization19:33 Scale and Deal Competition20:11 AI Advantage in Investing20:53 Portfolio Ops AI Playbook21:42 Private Markets Risk Setup22:17 Noise Versus Facts22:57 Fighting False Narratives23:42 Wealth Channel Narrative24:18 Why Private Markets Matter25:10 Investing Through Geopolitics26:25 Evergreen Versus Drawdown27:21 Discipline Over Structure28:28 Semi-liquid as a Feature29:17 Evergreen for Founders30:39 Evergreen Mindset and Compounding32:01 Owning the Narrative Direct35:22 Fiduciary Seriousness Balance36:15 Relentless Culture Explained38:39 Closing Footnotes(Timestamp 02:46.7): Largest owners of commercial real estate in Europe.(Timestamp 31:33.0): Reference to Class I annualized, inception-to-date return from January 2017.A Word from Our Sponsor, UltimusThis episode of Alt Goes Mainstream is brought to you by Ultimus, the full-service fund administrator and transfer agent powering asset managers in private and public markets. As alts go mainstream, you need real expertise to handle complex fund structures, connect with key distribution partners, and handle sophisticated compliance, reporting, and transparency demands.That's Ultimus: high-tech, high-touch solutions for over 450 clients and 2,500 funds with $775B in assets under administration. Backed by an expert team of over 1,200 employees, they place client service at the core of their business, helping you navigate complexity during your fund structuring or launch and then supporting you through every stage of growth. Whether you're already in the market or thinking about entering private wealth, you can trust their team's deep expertise in retail alternatives to help you reach your goals.Learn more at ultimusfundsolutions.com or email info@ultimusfundsolutions.com.We thank Ultimus for their support of alts going mainstream.

This Episode Pat Zingarella joins Chris Lopez to share the story behind Invest Clearly, a platform built to bring more transparency to the private real estate investing world. Pat's journey started like many BiggerPockets listeners: learning through podcasts, buying his first small multifamily property, making painful mistakes, and slowly realizing how hard it can be for LPs to know who they can trust. Pat walks through the lessons from his first fourplex, including inherited tenants, COVID-era nonpayment, poor screening decisions, and the difference between blaming real estate versus recognizing where his own due diligence fell short. He also shares how a later experience working under a high-profile real estate figure exposed him to the darker side of the industry and helped shape his view that LPs need better tools, better transparency, and better ways to validate sponsors before wiring capital. Chris and Pat dig into how Invest Clearly works today: a directory of GPs, verified LP reviews, proof-of-investment requirements, and a growing database designed to help investors compare sponsor experiences in one place. They also discuss why reviews matter, what happens when operators try to suppress negative feedback, and why community-driven transparency can help separate strong sponsors from bad actors. Key takeaways: How Pat went from BiggerPockets listener to active investor to building Invest Clearly What his first fourplex taught him about screening, reserves, trust, and due diligence Why private real estate needs more transparency around GP track records and LP experiences How Invest Clearly verifies reviews and helps LPs research sponsors Why negative reviews, legal threats, and transparency are becoming bigger issues in the industry How communities like PassivePockets and tools like Invest Clearly can help LPs make better-informed decisions Join a community of passive investors. Start your FREE 7-day trial: https://passivepockets.com/?utm_source=youtube&utm_medium=description&utm_campaign=none Listen to the PassivePockets Podcast Anywhere: https://lnk.to/passivepockets Subscribe to the Passive Investing Newsletter: https://www.biggerpockets.com/email-subscribe?utm_source=youtube&utm_medium=description&utm_campaign=none Join BiggerPockets for free: https://www.biggerpockets.com/signup?utm_source=owned_media Disclaimer The content of this podcast is for informational purposes only. All host and participant opinions are their own. Investment in any asset, real estate included, involves risk, so use your best judgment and consult with qualified advisors before investing. You should only risk capital you can afford to lose. Past performance is not indicative of future results. This podcast may contain paid advertisements or other promotional materials for real estate investment advisers, investment funds, and investment opportunities, which should not be interpreted as a recommendation, endorsement, or testimonial by PassivePockets, LLC or any of its affiliates. Viewers must conduct their own due diligence and consider their own financial situations before engaging with any advertised offerings, products, or services. PassivePockets, LLC disclaims all liability for direct, indirect, consequential, or other damages arising out of reliance on information and advertisements presented in this podcast.

Defence investing has been one of the hottest topics in European private equity over the past year. Firms including Warburg Pincus, PEI Group owner Bridgepoint, Carlyle Group and Tikehau Capital have all launched strategies or are mulling them, while LPs such as AkademikerPension, PensionDanmark, M&G Investments, PenSam and Finnish pension insurer Varma have either already invested in PE defence strategies or are considering doing so. In this episode, senior editor Adam Le sits down with EMEA editor for investor intelligence Joe Marsh to delve into the types of strategies LPs are looking for in the defence arena; the challenges that come with exiting defence assets; the role that ESG plays in LPs' investment policies; and why the themes of security, sovereignty and resilience are increasingly on investors' minds. Find all Private Equity International's defence-related coverage here.

This Week In Startups is made possible by: CLA - www.claconnect.com/withyou Northwest Registered Agent - www.northwestregisteredagent.com/twist Agree.com - www.agree.com Today's show: Forget the triple-triple-double-double-double; the new bar for startups hoping to raise venture capital has reached the stratosphere, though our venture panel is worried that startups are focusing too much on today's problems that may not become companies tomorrow. During a lively VC roundtable, Cowboy's Aileen Lee, Floodgate's Mike Maples, and Lerer Hippeau's Ben Lerer joined Alex to dig into exiting pre-AI startups, rising valuations, token spend, why they are keeping their funds small, and whether the government just tripped OpenAI and Anthropic! Guest Links: Aileen Lee https://x.com/aileenlee Cowboy VC https://cowboy.vc Mike Maples https://x.com/m2jr Floodgate https://www.floodgate.com Bene Lerer https://www.linkedin.com/in/benjlerer Lere Hippeau https://www.lererhippeau.com Timestamps: 0:00 Aileen Lee, Mike Maples, and Ben Lerer join the show 5:13 Venture liquidity returns: what SpaceX/Stripe distributions mean for LPs 9:13 Bending Spoons prices IPO at $29/share, roughly $18.4B valuation 10:31 Agree.com - Stop chasing invoices and automate your entire contract-to-cash stack. Go to https://agree.com and tell them Jason sent you to get 50% off for life! 12:09 "Companies get bought, not sold" — Ben on taking first offers seriously 17:41 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at https://Plaud.ai/twist and use code TWIST for 10% off! 19:34 Mutiny's burn-the-boats AI pivot with Jaleh Rezaei 20:19 Northwest Registered Agent - Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at https://www.northwestregisteredagent.com/twist 22:15 Mike's KeepSafe story: the "rule of 70" and profit-first companies 25:12 The new growth bar: 5x, 4x replaces triple-triple-double-double 28:55 Fund size is your strategy: why Floodgate and Lerer Hippeau stay small 30:11 CLA - Innovation takes balance. CLA's CPAs, consultants, and wealth advisors can help you get from startup to where you want to end up. Get started now at https://www.claconnect.com/withyou 37:39 The $100M Series A: Starcloud, General Intuition, Scale Cognition, Scout AI 40:35 King-making rounds and why mega-seeds destroy optionality 54:11 Open-weight models: the GLM-5.2 moment and going model-agnostic 55:30 Why fine-tuning open models is a treadmill, with Cursor/Kimi as an example 1:03:28 Grading the Trump administration on Mythos and Fable 1:06:33 Rising anti-AI sentiment, the wealth gap, and lessons from social media 1:11:43 Raising kids in the post-intelligence era 1:12:35 Where to find the panel and what each firm is investing in Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp Follow Lon: X: https://x.com/lons Follow Alex: X: https://x.com/alex LinkedIn: ⁠https://www.linkedin.com/in/alexwilhelm Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis Check out all our partner offers: https://partners.launch.co/ Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland Check out Jason's suite of newsletters: https://substack.com/@calacanis Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com

Brandon Sedloff and Aaron Gershenberg sit down in California's wine country to explore three decades of venture capital evolution. Aaron, CEO and managing partner at Pinegrove Venture Partners, shares his unconventional path from economic development work and real estate consulting to building SVB Capital into a $10 billion platform, then relaunching after the bank's collapse as Pinegrove, backed by Sequoia Heritage and Brookfield. They discuss: - How Aaron used Monte Carlo analysis to project fund performance and justify additional capital during the dot-com crash - Why he structured distribution-only fee models for anchor LPs instead of traditional management fees and carry - The mechanics of becoming a FOIA blocker to attract pension fund capital - How Pinegrove positions across seed, Series A, Series B, credit, and secondaries to capture alpha at different stages - Why the 2024–2026 vintage may deliver the fastest value creation Aaron has seen in his career This episode offers a roadmap for institutional investors navigating venture exposure, LP sentiment shifts, and the structural innovations that have reshaped fund economics over the past 25 years. Topics: (00:00:00) - Intro (00:03:20) - Growing up between Uganda, Kenya and New Jersey (00:10:50) - Africa's influence and giving back (00:15:40) - Question authority and the unstructured path (00:18:30) - Real estate consulting and the sales pivot (00:21:10) - Breaking into venture in the mid-'90s (00:32:00) - Joining Silicon Valley Bank (00:33:30) - Building community through cycling and kiteboarding (00:37:00) - Launching SVB Capital (00:40:15) - Innovative fund structures and FOIA blockers (00:44:20) - Scaling through three eras: 2000–2023 (00:49:00) - SVB's collapse and rebuilding as Pine Grove (00:50:20) - Partnering with Sequoia Heritage and Brookfield (00:56:30) - Pine Grove's platform and strategies today (01:02:30) - AI conviction and the 2024–2026 vintage (01:09:10) - What keeps you up at night Links: Aaron on LinkedIn - https://www.linkedin.com/in/aaron-gershenberg-7361b23/ Pinegrove Venture Partners - https://pinegrove.vc/ Brandon on LinkedIn - https://www.linkedin.com/in/brandonsedloff/ Juniper Square - https://www.junipersquare.com/

Oklahoma Farm Bureau, the state's largest generalist farm and ranch organization, with a presence in all 77 counties, runs one of the most surprising and effective rural entrepreneurship programs in the country. What started with census data showing rural population decline turned into a state-designated rural business accelerator, a $5.75M rural venture fund, and a statewide technical assistance network. In this conversation, the team shares the origin story, the program structure, the wins, and the hard-won lessons about communicating economic development work to people who've never heard the jargon and don't need to.Topics CoveredThe origin story: how census data, a legislative RFP, and a visionary board turned Farm Bureau into a rural accelerator operatorResults to date: 42 startups, 36 rural communities, 129 jobs created, $20M+ raised, a 95% post-graduate survival rateOklahoma Grassroots Rural and Ag Business Accelerators: a six-month, hybrid (25% in-person) program built for people with farms, families, and full-time jobsSSBCI technical assistance: one-on-one coaching split across western (Sadie) and eastern (Garrett) OklahomaCurriculum work with Oklahoma FFA to support student-run "legacy businesses" and build an agribusiness pathway for the next generationLaunch Rural OK: the resource hub, interactive map, statewide conferences, and the "resource round robin" format that replaced traditional trade-show boothsHow the team finds entrepreneurs: not by going direct to founders, but by building relationships with the first people they call for help (chambers, colleges, legislators, lenders)The venture fund deep dive: how OKFB partnered with Generation Food Rural Partners Fund to become the first fund in USDA history permitted to operate this way, investing only in Oklahoma while giving LPs a return across a $48M national fundA founder story: how a health-tech air filtration startup pivoted into food processing through a single introduction made during the accelerator's boot camp stageWhy "we're on your team for the long haul" and what follow-on support looks like after the six-month program endsThe real barrier in rural economic development: not lack of resources, but communication and trust, and why repeating your story, over and over, in plain language, is the jobHow other states can get started: walk into your local Farm Bureau office, or call Oklahoma Farm Bureau directlyResources: Connect with AmarieLaunch Rural OK

Host Brian Walsh takes up ImpactAlpha's top stories with editor Jessica Pothering. Up this week: How a new playbook for shared prosperity is being written in Zambia, where attempts are being made to redirect its mineral wealth toward local small and growing businesses; what SpaceX and other IPOs mean for Impact LPs and the field of impact investing; and this week's deal spotlight shines a light on investors designing nature-based investments around natural cycles.To try ImpactAlpha Edge, ⁠⁠⁠⁠click here⁠⁠⁠⁠.This week's stories:"Zambia centers small businesses in its bid for a more inclusive economy," by Lucy Ngige"SpaceX, Anthropic IPOs set to unlock billions in liquidity for impact LPs," by Amy Cortese"Investors learn to design nature-based investments around natural cycles," by Erik Stein“Danone-backed Livelihoods lands €124 million for its fourth nature-based fund,” by Lucy Ngige

Host Brian Walsh takes up ImpactAlpha's top stories with editor Jessica Pothering. Up this week: How a new playbook for shared prosperity is being written in Zambia, where attempts are being made to redirect its mineral wealth toward local small and growing businesses; what SpaceX and other IPOs mean for Impact LPs and the field of impact investing; and this week's deal spotlight shines a light on investors designing nature-based investments around natural cycles.To try ImpactAlpha Edge, ⁠⁠⁠⁠⁠click here⁠⁠⁠⁠⁠.This week's stories:"⁠Zambia centers small businesses in its bid for a more inclusive economy⁠," by Lucy Ngige"⁠SpaceX, Anthropic IPOs set to unlock billions in liquidity for impact LPs⁠," by Amy Cortese"⁠Investors learn to design nature-based investments around natural cycles⁠," by Erik Stein“⁠Danone-backed Livelihoods lands €124 million for its fourth nature-based fund⁠,” by Lucy Ngige

What if aging isn't simply your body “wearing out”… but your body losing the ability to repair itself? In this episode, Dr. Andrew Salzman joins Dr. Josh Axe to explain why chronic inflammation, leaky gut, and depleted NAD may quietly drain the very energy your cells need to heal, think, move, and survive. Uncover what's really going on in your body with advanced biomarker testing for hormones, thyroid, and metabolism— plus a 1-hour consultation with a Senior Health Advisor! →  http://mybloodwork.com Thank you to our sponsors! Sunlighten Sauna: https://get.sunlighten.com/axepodcast Manukora Manuka Honey: https://manukora.com/axe Caraway Home: carawayhome.com/drjoshaxe (Use code DRJOSHAXE) for an exclusive discount Watch The Dr. Josh Axe Show every Monday & Thursday on YouTube: https://www.youtube.com/@drjoshaxe?sub_confirmation=1

In this episode, Chris Lopez welcomes Christine Kwasny back to the show to break down the Risk Radar, a visual due diligence tool she built to help LP investors better understand where risk shows up in a private real estate deal. The tool grew out of Christine's Substack, Net Zero Is a Win, where she publishes retrospective deal analyses on what went right, what went wrong, and what investors may have been able to identify in the original offering materials. Christine walks through the Risk Radar's three major categories: what is fixed at closing, what is sponsor driven, and what is market driven. Chris and Christine discuss how LPs can evaluate GP team history, “cockroach” risks, going-in cap rates, debt terms, reserves, expense assumptions, capital stack structure, waterfalls, exit cap rates, supply and demand, rent growth, absorption, and vacancy. They also explore why retrospective analysis is one of the best ways to test whether risk was visible up front, why market timing can dominate long-term outcomes, and how tools like AI may help investors gather better data without outsourcing their own judgment. Disclaimer The content of this podcast is for informational purposes only. All host and participant opinions are their own. Investment in any asset, real estate included, involves risk, so use your best judgment and consult with qualified advisors before investing. You should only risk capital you can afford to lose. Past performance is not indicative of future results. This podcast may contain paid advertisements or other promotional materials for real estate investment advisers, investment funds, and investment opportunities, which should not be interpreted as a recommendation, endorsement, or testimonial by PassivePockets, LLC or any of its affiliates. Viewers must conduct their own due diligence and consider their own financial situations before engaging with any advertised offerings, products, or services. PassivePockets, LLC disclaims all liability for direct, indirect, consequential, or other damages arising out of reliance on information and advertisements presented in this podcast.

Elizabeth Ziman, who performs as Elizabeth and the Catapult, is a singer-songwriter from Brooklyn. Over the past twenty years, she and a slowly rotating cast of musical friends have released six LPs, full of songs that offer a neat, often unexpected blend of the witty and the vulnerable. Her latest release is called Responsible Friend, "about slowing down in a world that keeps accelerating. It's a commitment to friends, family, and self, at a time when everyone seems to be carrying more than they can reasonably hold" (Bandcamp). Elizabeth and the Catapult play in our studio.  Set list: 1. 50/50 2. When the Doctor Needs A Doctor 3. I Love You Still Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

What happens when a consulting firm decides to start leading M&A transactions and, separately, writing checks into the very deals it consults on? Clint Simkins of DPO&Co joins host Greg Hawver to answer that question, tracing the firm's evolution from a strategy consulting shop into a fully integrated platform spanning consulting, QoE and transaction advisory services, principal investing, and a $100 million fund raise. Clint explains how scrutinizing value creation plans — including spotting internal contradictions that other LPs never get to — is the first place DPO looks when evaluating a deal. He also details how DPO's commercial HVAC roll-up has completed 20 transactions in just 22 months. Tune in for a rare look inside a firm that has built a compounding edge across every stage of the independent sponsor ecosystem. Connect and Learn More☑️ Clint Simkins | LinkedIn☑️ DPO&CO | LinkedIn☑️ McGuireWoods | LinkedIn | Facebook | Instagram | X☑️ Subscribe Apple Podcasts | Spotify | Amazon MusicThis podcast was recorded and is being made available by McGuireWoods for informational purposes only. By accessing this podcast, you acknowledge that McGuireWoods makes no warranty, guarantee, or representation as to the accuracy or sufficiency of the information featured in the podcast. The views, information, or opinions expressed during this podcast series are solely those of the individuals involved and do not necessarily reflect those of McGuireWoods. This podcast should not be used as a substitute for competent legal advice from a licensed professional attorney in your state and should not be construed as an offer to make or consider any investment or course of action.

A lot of LP investors learned hard lessons over the last few years. In this episode, Travis Watts breaks down what really happened during the multifamily downturn and why so many deals struggled when interest rates changed faster than expected. Travis shares his experience as a full-time LP investor involved in roughly 30 deals across multiple asset classes. He explains why self-storage performed more resiliently, what surprised investors about floating-rate debt, and why LPs are asking much better questions today before investing in deals. Key topics and takeaways: Why interest rate cap renewals blindsided many operators How floating rate debt created pressure across multifamily portfolios Why self-storage held up better during the downturn What LP investors are paying attention to now Why multifamily recovery will likely be slow instead of a fast rebound How lower leverage and cleaner debt structures are changing new deals Guest Information: Travis Watts LinkedIn: Search “Travis Watts” on LinkedIn Call To Action: If you are an LP investor or interested in passive real estate investing, connect with Travis Watts on LinkedIn to continue the conversation.

It's another packed week in tech with Gareth and Ted covering stories ranging from niche gadgets to major software changes that could affect millions of users. This week's show include an industrial-grade vinyl cutter that lets music lovers press their own records at home, Lenovo's surprisingly audio-focused new Android tablet, new legislation designed to make the internet safer for children, Microsoft Teams becoming a little too aware of where you're working, and fresh criticism of Windows 11's Media Player. With Gareth Myles and Ted Salmon Join us on Mewe RSS Link: https://techaddicts.libsyn.com/rss Direct Download | iTunes | YouTube Music | Stitcher | Tunein | Spotify  Amazon | Pocket Casts | Castbox | PodHubUK News Sick of scrounging in thrift stores for LPs or paying $40 for a new album? This pro vinyl cutter lets you make your own — but it's an absolute beast Lenovo Tab Plus Gen 2 launches with 9 JBL speakers and a 12.1" LCD with Dolby Vision New rules to protect children online Microsoft Teams will use Wi-Fi connectivity to automatically update your work location Windows 11's New Media Player Uses 3.5x More RAM, Charges for Popular Video Codecs Banters: Knocking out a Quick Bant Microsoft is killing Office 2021 in 2026, and it's pushing hard for 365  Alternate article - Microsoft is killing Office 2021 in October to push you onto Microsoft 365, how to fight back Bought Report Bellemond Magnetic Kent Paper Screen Protector for Samsung Galaxy Tab & 15 Pen Tips for Samsung Galaxy S-Pen Bargain Basement: Best UK deals and tech on sale we have spotted EF ECOFLOW DELTA 3 Max Portable Power Station, 2048Wh LiFePO₄ Battery, 2400W X-Boost Output, w/code £698.28 - WL49S3M2 Motorola Razr 60 Ultra £799.99 from £1,099.00 (£160 x 5 months for me) UGREEN Nexode 140W 25000mAh Laptop Power Bank Fast Charging Portable Charger - Prime Exclusive - Sold by UGREEN GROUP LIMITED UK / FBA - £49.99 XIAOMI 17 512GB/12GB, £749 from £999 (£149.80 x 5 months for me) CORSAIR CX750 80 PLUS Bronze Non Modular Low-Noise ATX 750 Watt Power Supply (Black) £54.98 Anker Prime 250W USB-C Charger £109 from £169.99 - not seen quite this cheap before soundcore Boom 3i by Anker Rugged Bluetooth Outdoor Speakers, IP68 Waterproof, 50W Black - Sold by AnkerDirect FBA - Early Prime Day Deal - £49.99 Kindle Colorsoft Signature Edition (32GB) Bundle with No Ads. & Amazon Fabric Cover & Wireless Charging Dock - £234.97 from £344.97 reMarkable Starter Bundle – reMarkable 2 Tablet | Includes 10.3" Writing Tablet, Marker Plus Pen with Built-in Eraser - Prime Members Price - £339.99 Main Show URL: http://www.techaddicts.uk | PodHubUK Contact:: gareth@techaddicts.uk | @techaddictsuk Gareth - @garethmyles | Mastodon | Blusky | garethmyles.com | Gareth's Ko-Fi Ted - tedsalmon.com | Ted's PayPal | Mastodon | Ted's Amazon YouTube: Tech Addicts

In this episode with Dr. David Jockers, you'll discover the most researched cancer-supporting food backed by over 500 studies and why it has been used for over 5,000 years across traditional healing systems. You'll get a clear breakdown of how this powerful root works at a cellular level to influence inflammation, detoxification, and metabolic health. You'll learn how chronic inflammation, blood sugar imbalance, and gut-derived toxins like LPS can silently drive disease progression in the body. The episode explains how this food helps regulate insulin sensitivity, strengthen the gut lining, and support the body's natural detox pathways. You'll also hear how it interacts with key biological systems that influence long-term immune and metabolic resilience. Finally, you'll go deeper into its role in modulating major cancer-related pathways including apoptosis, angiogenesis, and mitochondrial function. Dr. Jockers also shares practical guidance on how to use it in everyday meals and supplementation for optimal absorption and effectiveness. You'll walk away understanding how pairing it with fats, black pepper, and proper dosing can significantly enhance its benefits.   In This Episode:  00:00 Inflammation Reset Teaser 00:12 Cancer Fighting Root Reveal 00:57 Coaching and Contact Info 03:30 Why Turmeric Matters 05:23 Curcumin and Blood Sugar 06:49 Gut Health and Endotoxin 09:22 Antioxidant and Anti Inflammatory Power 13:00 How Turmeric Fights Cancer 15:30 Best Ways to Take Turmeric 19:31 Safety Tips and Wrap Up 21:50 Final Thanks and Reviews   What if getting clearer, more hydrated, and naturally radiant skin didn't require harsh chemicals or complicated routines? Pureance is a clean, organic skincare line designed to support healthier-looking skin using powerful botanicals like bakuchiol, tremella mushroom, and kakadu plum to help smooth the appearance of fine lines, deeply hydrate, and brighten uneven tone. It's formulated to support a more youthful glow while being gentle on the skin, and in the episode users shared noticeable improvements in texture and hydration within weeks of use. You can try it at https://pureance.com and get 35% off with code JOCKERS at checkout.     JoyMode is a clinically formulated nitric oxide support blend designed to improve blood flow, sexual performance, and cardiovascular health—all without prescriptions or side effects. Backed by a peer-reviewed study cited in the episode, users reported improved erection hardness, better stamina, and noticeably stronger performance within a short period of daily use. It's built with clinical doses and no proprietary blends, so you know exactly what you're getting. Try it at https://tryjoymode.com/drjockers  and get 20% off your order with code DRJOCKERS at checkout.   "Curcumin targets 10 major factors involved in cancer development."  ~ Dr. Jockers     Subscribe to the podcast on: Apple Podcast Stitcher Spotify PodBean TuneIn Radio     Resources: Visit https://pureance.com and get 35% off with code JOCKERS at checkout. Visit https://tryjoymode.com/drjockers  and get 20% off your order with code DRJOCKERS at checkout.   Connect with Dr. Jockers: Instagram – https://www.instagram.com/drjockers/ Facebook – https://www.facebook.com/DrDavidJockers YouTube – https://www.youtube.com/user/djockers Website – https://drjockers.com/ If you are interested in being a guest on the show, we would love to hear from you! Please contact us here! - https://drjockers.com/join-us-dr-jockers-functional-nutrition-podcast/ 

What if building generational wealth wasn't about where you started—but about the decisions you make today? In this episode, Wendy Yee and Evon Mattison share how they grew from single-family investing into a multifamily portfolio of more than 600 doors valued at over $100 million. Drawing from over 40 years of combined real estate experience, they discuss their transition from LPs to GPs, the lessons learned from market downturns, the importance of transparency and credibility when raising capital, and why consistency, discipline, and taking action matter more than waiting until you're ready. They also reveal how they attract investors, build lasting relationships, leverage social media and education, and use multifamily investing as a vehicle to create freedom, stability, and a legacy that outlives them. If you're an investor or entrepreneur looking to scale your impact, strengthen your mindset, and build wealth with purpose, this conversation delivers practical insights you can apply immediately.5 Key takeaways from this episode1. Wealth Building Starts with Intention and Action Wendy and Evon emphasize that building generational wealth isn't about coming from wealth—it's about taking consistent action, staying disciplined, and committing to a long-term vision. 2. Credibility Is Earned Through Transparency Investors trust operators who openly share both wins and losses. The couple explains how honesty, transparency, and investing their own capital helped establish trust with investors. 3. Capital Raising Is a Skill That Can Be Learned Despite years of real estate experience, they initially felt uncomfortable raising capital. Through education, mentorship, and consistent practice, they learned how to confidently present opportunities and build investor relationships. 4. Strong Fundamentals Matter More Than Chasing Deals Their investing philosophy is rooted in conservative underwriting, risk management, and letting the asset speak for itself rather than pursuing deals simply to increase unit counts or transaction volume. 5. Relationships Drive Long-Term Success Whether with investors, partners, or tenants, genuine relationships are at the center of their business. Personal connection, consistent communication, and serving others create trust that compounds over time.About Tim MaiTim Mai is a real estate investor, fund manager, mentor, and founder of HERO Mastermind for REI coaches.He has helped many real estate investors and coaches become millionaires. Tim continues to help busy professionals earn income and build wealth through passive investing.He is also a creative marketer and promoter with incredible knowledge and experience, which he freely shares. He has lifted himself from the aftermath of war, achieving technical expertise in computers, followed by investment success in real estate, management skills, and a lofty position among real estate educators and internet marketers.Tim is an industry leader who has acquired and exited well over $50 million worth of real estate and is currently an investor in over 2700 units of multifamily apartments.Connect with TimWebsite: Capital Raising PartyFacebook: Tim Mai | Capital Raising Nation Instagram: @timmaicomTwitter: @timmaiLinkedIn: Tim MaiYouTube: Tim Mai

In this episode, we provide a marketing update, followed by a brief update on the exploit. We then dive deeper into a couple of bigger topics, such as dynamic and referral fees, protocol owned liquidity.Swap now https://swap.thorchain.org/ THORChain is a decentralized crypto exchange. THORChain is the first and biggest DEX for Bitcoin. You can use any self custody wallet to swap and there's no KYC required.Timestamps:00:00:00 Intro00:02:00 Marketing update00:04:00 "KOL" talk and bang for buck00:06:00 Getting new chains added is super important for getting brand-new users00:09:00 New Affiliate page on swap.thorchain.org00:11:00 Kenton is thinking the affiliate API should be permissioned00:12:00 Chad B starts, 3.19.1 fully adopted00:14:00 1 day, enable signing and churn00:16:00 KeyVerify talk — when should we move on if it doesn't work?00:17:00 KeyVerify will be disabled after this moment00:18:00 Kenton asks about the exact order of turning things back on00:20:00 THORChain is decentralized — it's obvious00:21:00 Nodes had to do a lot of steps with developers00:23:00 AI made this so much faster for us00:24:00 Over time, we will have a more professional node operator base00:26:00 Devs have been working nonstop on separate issues00:27:00 Post-mortem is coming, hopefully within 2–3 weeks00:29:00 We do a very good job being public, but that is often used against us00:30:00 When we get going again, we will be testing the dynamic fee model with select partners00:31:00 Applies to all THORNames00:34:00 Chad says he is not sure who is correct on dynamic fees00:37:00 Start simple and tweak it as we get more info00:39:00 Kenton: It should be obvious00:40:00 SwapKit rev-share program discussion00:45:00 Stable-to-stable swaps should be neutral but result in more volume00:46:00 Kenton: Stablecoin idea should be great00:48:00 Denny: Stable-to-stable will be amazing for point-of-sale applications00:50:00 Kenton: Dynamic fees may be really helpful for direct integrations00:51:00 These features are bound to "click" with partners00:54:00 Lots of exciting things are coming!00:55:00 XMR testing update: Going well!00:56:00 Huginn update: Pointed it at Serai00:57:00 Monero may be coming within 1–2 months00:59:00 XMR actually works!!01:01:00 RUNE question from the audience about governance01:03:00 Kenton breaks down liquidity pools01:05:00 It is not hopium — THORChain has fundamentals01:07:00 This protocol is actually real and useful01:11:00 TON Wallet question from the audience01:12:00 We are reaching out to everyone!01:13:00 POL transition: Protocol-Owned Liquidity01:14:00 Kenton thinks 25% POL is what is needed01:18:00 Chad B: Where do you stand on POL?01:20:00 Bull market POL could get very crazy01:23:00 Dev fund could make much more money and the treasury could go away01:25:00 We are moving away from a hard cap01:27:00 Denny gives his thoughts on LPs01:30:00 LPs withdraw when things turn around?01:35:00 We didn't have data about AMMs when we first started01:41:00 The scalability of THORChain in terms of liquidity and developers01:45:00 Possible incentive pendulum tweaks01:48:00 Price/volume graph comparison01:53:00 Stock trading on-chain — KYC?01:55:00 Perhaps companies will push for permissionless01:58:00 Stocks02:02:00 How have Maya devs been doing?02:06:00 Outro02:09:00 Attempt to attack Chad Barraford

Europe's challenge isn't a lack of entrepreneurs. It's making sure enough capital reaches them.In this episode, David Cruz e Silva speaks with Jaap Vriesendorp, Managing Partner at Marktlink Capital, one of Europe's most active LPs in venture capital, about why backing European innovation matters, how to build a resilient venture portfolio and what separates the best fund managers from the rest.Jaap shares the thinking behind Marktlink's venture strategy, from vintage diversification and secondaries to manager selection and portfolio construction. He also explains why scale matters in private markets, how the firm uses data science and AI in its investment process and why many LPs make the mistake of running out of capital for their best-performing managers.The conversation also covers emerging managers, long-term capital formation and why Europe deserves more credit as a venture ecosystem.Key highlights:Why European entrepreneurs should back European entrepreneursHow one of Europe's most active VC LPs approaches venture investingThe role of primaries, secondaries and vintage diversificationWhat Jaap looks for in emerging managersWhy scale matters in private marketsHow data science and AI support investment decisionsThe biggest mistakes fund-of-funds investors makeWhy long-term capital is critical to venture successTimestamps:(00:00) Why Europe needs more capital flowing into innovation(02:00) Introduction and Jaap Vriesendorp's background(05:00) From McKinsey to launching a venture fund-of-funds(08:00) The merger that created Marktlink Capital(10:00) Building a platform backed by entrepreneurs(14:00) Why scale matters in private markets(17:00) Product strategy across venture, private equity, co-investments and private credit(23:00) How Marktlink uses data science and AI in investing(29:00) Marktlink's venture investment strategy(30:00) Vintage diversification, primaries and secondaries(33:00) Why annual funds help secure long-term LP capital(37:00) What Marktlink looks for in emerging venture managers(40:00) Why Europe deserves more credit as a venture ecosystemFurther listening:⁠⁠⁠E347: The $26B CIO Who Turned Superforecasting Into Alpha - How I Invest with David Weisburd⁠⁠⁠Learn more about the Love Tomorrow Summit and the programmes EUVC is curating, and secure your tickets ⁠⁠here⁠⁠.

This week on Swimming with Allocators, Kate Simpson joins Earnest and Alexa to share her journey from starting as a history major at the UNC endowment to leading the venture strategy at multi-asset OCIO firm GEM. She explains how she learned institutional investing, specialized in private markets, and refined her craft at Parish Capital and Truebridge, including fund-of-funds due diligence, reference work, and the power of platforms and networks. The conversation dives into how to build a venture program from scratch, why alignment, patience, and resource intensity matter, and how GEM uses a barbell approach across top-tier scaled platforms and emerging managers while avoiding the “crowded middle.” Kate breaks down how LPs evaluate managers (source, pick, win), why fund math and ownership are critical, and how today's AI-driven cycle, secondary markets, and companies staying private longer are reshaping ventures. Also, don't miss Nick Cassin from Sidley as he explains the rapid growth of the private-fund secondary market, what's driving the surge in secondary and continuation vehicle (CV) transactions, and how new types of capital providers are stepping in as lead investors to provide liquidity to private-market participants. Highlights from this week's conversation include: Starting at UNC Endowment With No Finance Background (0:31)   Transitioning from TrueBridge to Gem and Taking on a Leadership Role (6:10) Advice for Building a New Venture Program and Aligning Stakeholders (10:12) Democratization of Venture Access and Barbell Strategy for Manager Selection (12:38) Sourcing and Evaluating New Venture Managers with a High-Volume Funnel (16:26) Secondaries Market Boom and Macro Dynamics Driving Liquidity Needs (21:00) Rise of Continuation Vehicles and Structural Evolution of Secondaries (23:36) How to Approach a First LP Meeting and Importance of Fund Math (26:03) Defining Early Versus Later Stages and Gem's Seed and Micro Fund Threshold (28:13) Normalization of Secondary Liquidity for Founders and Early Investors (35:24) Future Opportunities in Smaller Funds and the Dynamic Early Ecosystem (36:12) Final Thoughts and Takeaways (40:12) GEM is an independent investment management firm that provides customized solutions for long-term investors worldwide. Since 2007, we have sought to deliver superior risk-adjusted returns to our clients by combining disciplined investment research and active portfolio management with exceptional service and enduring partnership. With a global platform, broad institutional investment capabilities, and an experienced team, we design portfolios to meet the unique needs of each investor we serve. For more information, visit www.geminvestments.com. Sidley Austin LLP is a premier global law firm with a dedicated Venture Funds practice, advising top venture capital firms, institutional investors, and private equity sponsors on fund formation, investment structuring, and regulatory compliance. With deep expertise across private markets, Sidley provides strategic legal counsel to help funds scale effectively. Learn more at sidley.com. Swimming with Allocators is a podcast that dives into the intriguing world of Venture Capital from an LP (Limited Partner) perspective. Hosts Alexa Binns and Earnest Sweat are seasoned professionals who have donned various hats in the VC ecosystem. Each episode, we explore where the future opportunities lie in the VC landscape with insights from top LPs on their investment strategies and industry experts shedding light on emerging trends and technologies.  The information provided on this podcast does not, and is not intended to, constitute legal advice; instead, all information, content, and materials available on this podcast are for general informational purposes only. Learn more about your ad choices. Visit megaphone.fm/adchoices

Part I: The Architecture of the Guest ExperienceLa Bottega Collective designs and produces the physical and sensory touchpoints of the luxury hotel stay, from bathroom formulations and textiles to amenities, gifting, and retail, working with 15,000 properties across 117 countries, from the world's most recognized hotel groups such as Aman and Four Seasons, to the finest independent properties such as Passalacqua and Il San Pietro di Positano. Tommaso Pacini, CEO of La Bottega Collective, argues that the guest experience is not a collection of amenities but a coherent sensory language, and that the hotels who understand this are the ones building something guests cannot find, replicate, or buy anywhere else.In Part I of this episode, Tommaso walks through how La Bottega Collective reads a property before designing a single touchpoint, why the choice between licensed and fully custom product programs is ultimately a question of time and conviction rather than budget, and how the most effective guest experience artifacts extend the emotional memory of a stay well beyond checkout.Thank you La Bottega Collective for making this episode possible. Learn more and get in touch with La Bottega Collective ⁠here⁠.Follow La Bottega Collective on Instagram ⁠here⁠.Part II: The Developer's Playbook: Building a €3B European Lifestyle & Luxury Hotel Portfolio with David ZisserEpisode starts at (17:22)David Zisser is the founder of Omnam, a €3 billion European hotel development and investment platform with a portfolio concentrated in lifestyle and luxury assets across Italy and key European markets. His recent projects include the Edition Lake Como, W Rome, which he credits with catalyzing what W Hotels internally called its 2.0 positioning, and the Hotel Bauer Venice, acquired out of a bankruptcy process in partnership with Mohari Hospitality and flagged with Rosewood. He is currently developing a proprietary hotel brand, with a Paris property featuring Pharrell Williams as creative director serving as its first expression.Omnam operates across the full development stack, from site identification and capital structuring through to brand selection, design intent, and operational oversight. Omnam's LPs include institutional investor Bain Capital, and Mohari Hospitality, with whom David has built a partnership centered on a shared conviction about where luxury hospitality is heading. Omnam has worked with several major third party operators, and that breadth of exposure now informs both its underwriting discipline and its decision to build its own brand from a position of genuine industry knowledge rather than ego.In this episode, Nadine sits down with David to explore what it really takes to build a multi-billion euro development platform in luxury hospitality, from navigating fundraising from institutional capital and large family offices to acquiring one of Venice's most storied hotels out of bankruptcy.INTERVIEW HIGHLIGHTSDavid's deal framework, and why any project where success is contingent on factors outside Omnam's control is a passHow the Hotel Bauer acquisition came together out of a bankruptcy process, with competing global bidders, layered political dynamics, and a timeline that tested everyone involvedUltra-luxury brand dilution and which operators are most exposed as generational wealth transfer acceleratesDavid's view on ADR stabilization, total in-hotel spend capture, and why the P&L conversation that matters most is not the one most investors are havingWhy David believes hotel operators should exit F&B operations, and what a properly aligned fee structure looks like from an owner's perspectiveThe tension at the center of building a scalable brand from a singular, heritage-driven flagship assetWhat David learned from managing institutional capitalLearn more about Omnam's portfolio ⁠here⁠.Follow Omnam on Instagram ⁠here⁠.

In this episode, Adam Torres interviews Ron Biscardi, Co-Founder & CEO of iConnections. Ron discusses the evolution of the iConnections platform, the importance of relationship-driven business building, and how technology is helping connect leading LPs and GPs within the alternative investment ecosystem. Follow Adam on Instagram at https://www.instagram.com/askadamtorres/ for up to date information on book releases and tour schedule. Apply to be a guest on our podcast: https://missionmatters.lpages.co/podcastguest/ Visit our website: https://missionmatters.com/ More FREE content from Mission Matters here: https://linktr.ee/missionmattersmedia Learn more about your ad choices. Visit podcastchoices.com/adchoices

What if the thing limiting AI growth isn't chips or power, but wastewater treatment capacity?In this episode of KP Unpacked, KP Reddy and Nick unpack why water infrastructure is the next bottleneck. Jacobs has a $22.7B backlog weighted toward water. AECOM intends to double its water business in three years. Stantec's water practice is its single largest vertical. Meta just built a $70M wastewater plant in Idaho. TSMC broke ground on a 15-acre water reclamation facility in Phoenix targeting 90% recycling. The CHIPS Act, EV gigafactories, and hyperscaler water-positive commitments are pulling wastewater treatment capacity onto private campuses at a scale AEC hasn't seen since the petrochemical buildout of the 70s.KP and Nick reveal Shadow's bet in the space: Western Chemicals, which uses duckweed (a plant that doubles in size every 24 hours) grown on wastewater to filter nitrogen and phosphorus while producing ethanol fuel. The insight? Wastewater treatment consumes 2% of global electricity using heavy machinery to do what biology does for free. Then they pivot to why big ideas need big capital (raising $1M for pre-con AI versus $100M for modular wastewater plants), why college grads complaining about no job offers have recency bias ($250K signing bonuses for 22-year-olds was never normal), and why skepticism from engineering firm LPs is actually an anti-signal Shadow should lean into.Key questions answered:Why is water the next infrastructure constraint after data centers and power?What's Shadow's water infrastructure bet, and what is duckweed?How does duckweed double in size every 24 hours and filter wastewater for free?Why does wastewater treatment consume 2% of global electricity?Why are private companies building their own wastewater plants now?Should founders raise $1M seed rounds or $100M for big infrastructure ideas?Is the college grad job crisis real, or just recency bias from the 2010s?Why is skepticism from engineering LP firms an anti-signal for Shadow?What's the difference between alpha (non-consensus bets) and beta (consensus with upside)?How does Founders Fund operate with only 4 partners managing billions?What happened with the Vinod Khosla/Cloudflare co-founder drama?Why do co-founder breakups kill more startups than bad products?If you're wondering where infrastructure investment flows after data centers, trying to understand why wastewater suddenly matters, or deciding whether to raise incrementally or swing for $100M on a big idea, this episode will show you why the next constraint is already visible, and capital is moving faster than you think.Listen now.

Legendary venture capitalist Vinod Khosla joins Mukesh Bansal on SparX, for one of the most wide-ranging and provocative conversations on the future of technology, investing, and humanity. Vinod makes bold claims: AI will replace doctors within 5 years, colleges as we know them are obsolete, space-based data centers don't make sense, India's IT and BPO industry faces an existential threat - and yet, AI may be the greatest opportunity India has ever seen. And ultimately, AI will free humanity from servitude to survival.In this episode, Vinod shares his contrarian investment philosophy, including why he wrote a $50M check to OpenAI in 2019 when it had no product, no revenue, and no business plan — and why he sent an apology letter to his LPs along with it.

How can passive investors distinguish trustworthy real estate operators from those who simply know how to market themselves? In this episode of the Real Estate Investor Podcast, host Gary Lipsky sits down with Pat Zingarella, CEO of Invest Clearly, a public directory and review platform for private real estate investments. In their conversation, Pat explains how his experience working for a fraudulent real estate investor showed him the need for greater transparency across the industry. He shares how Invest Clearly verifies that reviewers have invested with the sponsors they evaluate, why communication breakdowns remain the most common investor complaint, and how verified reviews can help responsible GPs stand apart. Gary and Pat also discuss the importance of evaluating the operator before the deal, reporting unsuccessful investments honestly, and the LPs' responsibility to conduct proper due diligence. Tune in to explore the changing capital-raising environment, the growing cost of converting prospective investors, and why more leads cannot replace trust, with Pat Zingarella.Key Points From This Episode:Background about Pat and why he founded Invest Clearly.Learn how verified reviews help strong operators stand out.Discover why communication matters more than a perfect record.Find out what makes Invest Clearly stand out from other companies.Hear how sponsors should address poor-performing deals.Uncover the sponsor red flags investors often overlook.Understand why LPs must take ownership of due diligence.Explore what Pat is planning next for Invest Clearly.Get insights into how transparency fosters trust with investors.Unpack why and how investor conversion has changed.Links Mentioned in Today's Episode:Pat Zingarella on LinkedInPat Zingarella EmailInvest ClearlyAsset Management Mastery Facebook Group Invest SmartBreak of Day Capital Break of Day Capital InstagramBreak of Day Capital YouTubeGary Lipsky on LinkedIn

Omar Morales is a top South Florida real estate broker specializing in land and multifamily asset deals that move hundreds of millions and reshape neighborhoods. In this episode◾️How incentive structures drove overleveraged investors to ruin in 2021 and 2022◾️Why parts of Miami's rental market are a bloodbath for owners but a goldmine for renters◾️Where the nation's largest multifamily funds are deploying capital right now◾️The “land play” hidden inside suburban office buildings◾️Why a West Palm Beach multifamily deal just got 37 offers◾️What Omar is quietly building through Miami Dealmakersa content flywheel he believes will be his biggest long-term assetIf you want to understand how real money moves through South Florida real estate, this is the episode you can't miss.◾️ Timestamp00:00 Miami real estate in 2026 where things stand 03:47 How cheap capital destroyed investors in 2021–2022 08:20 The herd mentality that wrecked multifamily deals 10:48 Omar's path from analyst to top South Florida broker 14:56 Why parts of Miami's rental market are a bloodbath right now 19:20 The affordable housing crisis and where people are actually moving 22:42 The hidden land play inside suburban office buildings 28:50 What the biggest multifamily funds are buying right now 32:59 Why contrarian investing is hard to sell to LPs 36:15 How Omar thinks about wealth, risk, and brokerage vs. investing 39:47 Miami Dealmakers building a content flywheel as leverage 47:04 The future of Miami as a city 47:12 What Omar is building next

Two roughs boys escape the high school tyranny of panty-masked Principal Montoya and form overachieving garage rock band Twin Peaks. Wild Onion is one of a handful of solid LPs they put out in a half-decade span before disappearing.

In this Community Roundtable, Chris Lopez sits down with PassivePockets members Pascal Wagner, Adam Cranmer, and Christy Burakovsky for a candid investor-to-investor conversation on how they're allocating capital right now and what would make them change course. Pascal frames the dilemma many LPs are feeling: with risk-free rates near 5% and major macro signals flashing red (record debt loads, expensive public markets, and uncertainty around where rates settle), does it still make sense to allocate to interest-rate-sensitive commercial real estate? He shares how he's thinking about portfolio construction with fresh liquidity and why he's prioritizing stable income and downside protection before chasing upside. Adam and Christy offer counterweights: where fear can create opportunity, why liquidity matters, and how they're approaching “safer” yield today (short-duration debt funds, notes, treasuries) while keeping dry powder for dislocated assets. The conversation also explores where each of them sees asymmetric opportunity: distressed commercial, non-performing loan strategies, medical office, assisted living tailwinds, and long-term fixed-rate debt structures that avoid the five-to-seven-year refinance trap. Key Takeaways Why some LPs are pausing syndication allocations and leaning into cash/T-bills and what would change their mind The “income-first” portfolio approach: build stable cash flow, then take higher-upside bets Where investors are hunting opportunity: distress, NPLs, office dislocation, medical office, and long-term fixed-rate debt plays Why HUD-style long-term amortizing debt can change the risk profile of a deal dramatically Mezz vs. leveraged first-lien funds: the real differentiator is control of the underlying collateral The underrated skill in 2026: staying liquid enough to act when the “no-brainer” window opens Disclaimer The content of this podcast is for informational purposes only. All host and participant opinions are their own. Investment in any asset, real estate included, involves risk, so use your best judgment and consult with qualified advisors before investing. You should only risk capital you can afford to lose. Past performance is not indicative of future results. This podcast may contain paid advertisements or other promotional materials for real estate investment advisers, investment funds, and investment opportunities, which should not be interpreted as a recommendation, endorsement, or testimonial by PassivePockets, LLC or any of its affiliates. Viewers must conduct their own due diligence and consider their own financial situations before engaging with any advertised offerings, products, or services. PassivePockets, LLC disclaims all liability for direct, indirect, consequential, or other damages arising out of reliance on information and advertisements presented in this podcast.

David Zhou, co-founder of The Side Letter and host of Superclusters, shares lessons from his journey as a founder, venture investor, LP, and educator. He explains how sophisticated limited partners evaluate venture funds, why consistent decision-making frameworks matter, and how emerging managers can stand out in an increasingly crowded market. David discusses common mistakes new LPs make, the metrics that matter when evaluating venture performance, and why successful investors develop discipline around both entering and exiting investments. He also shares practical advice for fund managers seeking LP support, emphasizing the importance of understanding investor motivations before ever making a pitch. In this episode, you'll learn: [02:35] How David accidentally became an entrepreneur and investor [03:42] Why venture capital appeals to people who love imagining the future [06:52] The story behind Superclusters and educating emerging LPs [11:21] Common mistakes first-time LPs make when evaluating funds [15:25] Why investors need consistent frameworks instead of chasing excitement [23:04] Which venture fund metrics actually matter and when [30:24] The three disciplines every great fund manager needs [32:25] Why the first LP meeting should never be a pitch [35:22] How to identify and build a unique competitive advantage [39:57] Understanding the motivations behind different types of LPs [44:03] How The Side Letter helps LPs make better investment decisions The nonprofit organization David is passionate about: Friends of Children with Special Needs About David Zhou David Zhou is the co-founder of The Side Letter, a platform that helps limited partners source, evaluate, and understand venture capital funds. He is also the host of Superclusters, a podcast focused on helping emerging LPs learn from experienced investors and better navigate the venture capital ecosystem. Before becoming an LP and venture ecosystem educator, David was a founder and venture investor. Through his writing, investing, and podcasting, he has become a respected voice on venture fund evaluation, LP decision-making, and emerging manager investing. About The Side Letter The Side Letter is a platform built to help limited partners make more informed venture capital investment decisions. The company provides LPs with tools, research, data, and educational resources designed to improve fund sourcing, diligence, and portfolio construction. By helping investors access better information and stronger evaluation frameworks, The Side Letter aims to reduce information asymmetry within the venture capital ecosystem and empower a new generation of sophisticated LPs. Subscribe to our podcast and stay tuned for our next episode.

In "Is Organized Tech Destroying the Small Logistics Entrepreneur" Joe Lynch and Nicholas Antoine, Co-Founder, Co-CEO, and Managing Partner of Red Arts Capital, discuss how mid-market logistics companies can leverage emerging automation and strategic "moats" to successfully survive and compete against tech-heavy enterprise giants. About Nick Antoine Nicholas Antoine is the Co-Founder, Co-CEO, and Managing Partner of Red Arts Capital, a private equity firm he co-founded in 2015 - at age 26 - to invest exclusively in supply chain and logistics businesses. A Princeton graduate, Nick began his career as an equity research analyst at Princeton Global Asset Management before joining Ariel Investments in Chicago, where he served as Chief of Staff to the Chairman and CEO of the $17 billion asset manager. At Red Arts, he leads fundraising, research, and investment thesis development, building one of the few Black-founded and -led PE firms in the country and one of the top-performing, ranked #7 on Bloomberg's 2025 Best-Performing U.S. Buyout Funds. Nick is a member of YPO and a board trustee of The Studio Museum in Harlem and WTTW (PBS Chicago). About Red Arts Capital Red Arts Capital is a Chicago-based private equity firm focused exclusively on partnering with North American supply chain and logistics businesses. Founded in 2015 by Nick Antoine and Chad Strader, Red Arts is a 100% Black-owned firm investing across the "supply chain economy" - freight, transportation, warehousing, contract packaging, and related middle-market companies with strong growth potential. In 2023, the firm closed its latest fund oversubscribed at $270M, above its $225M target, backed by institutional LPs including Prudential Financial, the University of Chicago's Office of Investments, and funds managed by Neuberger Berman. Red Arts pairs a sector-focused thesis with a belief that diversity drives performance - women represent roughly half the firm. Key Takeaways: Is Organized Tech Destroying the Small Logistics Entrepreneur In "Is Organized Tech Destroying the Small Logistics Entrepreneur" Joe Lynch and Nicholas Antoine, Co-Founder, Co-CEO, and Managing Partner of Red Arts Capital, discuss how mid-market logistics companies can leverage emerging automation and strategic "moats" to successfully survive and compete against tech-heavy enterprise giants. Firm Profile & Focus: Founded in 2015, Red Arts Capital is a 100% Black-owned, Chicago-based private equity firm that focuses exclusively on North American supply chain, logistics, and middle-market infrastructure businesses. Target Investment Profile: Unlike venture capital firms that hunt for speculative "hockey stick" growth, Red Arts invests $50M to $100M+ into established, profitable middle-market companies (typically family-owned with $100M to $500M in revenue) to provide liquidity and operational scaling. Strong Institutional Backing: Validating their sector-focused thesis, the firm closed its 2023 fund oversubscribed at $270M (surpassing its $225M target) backed by premier LPs like Prudential Financial and the University of Chicago. The Concept of "Organized Tech": Nick defines "organized technology" as a modern third form of power alongside organized people and organized capital. Large enterprise players use their scale and massive resources to deploy tech—and partner with startups for free trials—giving them a distinct, systemic advantage. An Opportunity, Not a Death Sentence: Organized tech is not inherently destroying small logistics entrepreneurs; rather, the risk lies in a lack of adaptability. Because AI and automated tools are becoming rapidly commoditized and affordable, small business survival depends on an entrepreneurial willingness to experiment. Building Defensive "Moats": To avoid competing strictly on commoditized pricing, successful logistics companies must build defensible moats. This includes high-touch customer service, strong cultural values that lower driver turnover, or geographic asset density (like uniquely zoned cross-dock terminals) that competitors cannot easily replicate. Outsized Returns from Small Tech Investments: Technology adoption doesn't require a massive overhaul to significantly impact the bottom line. In one LTL case study, Red Arts introduced a simple automated software tool to capture missed, manual accessorial charges, plugging a major revenue leak and yielding massive profit returns. Learn More About Is Organized Tech Destroying the Small Logistics Entrepreneur Nicholas Antoine | Linkedin Red Arts Capital | Linkedin Red Arts Capital Bloomberg executive profile Investing in Supply Chain Solutions with Nick Antoine of Red Arts Capital | Impact Podcast Black Professionals in PE & Finance spotlight | McGuireWoods Fund close coverage | $270M, Business Wire Organized Technology: A New Power Defining The American Dream | Forbes The Logistics of Logistics Podcast If you enjoy the podcast, please leave a positive review, subscribe, and share it with your friends and colleagues. The Logistics of Logistics Podcast: Google, Apple, Castbox, Spotify, Stitcher, PlayerFM, Tunein, Podbean, Owltail, Libsyn, Overcast Check out The Logistics of Logistics on Youtube

Get my new book: https://bronsonequity.com/fireyourselfDownload my new special report - How to Use Inflation to Your Advantage - www.bronsonequity.com/inflationJoin host Bronson Hill for this special webinar replay from The 2026 Passive Investors Summit on the Mailbox Money Show. In this expert panel, Bronson is joined by four seasoned operators and investors sharing real talk on navigating the current multifamily market, capital deployment, due diligence, cash flow strategies, and emerging opportunities amid economic shifts.Panelists:Tyson Cobb (Timberview Capital) – orthopedic surgeon turned investor, focused on building physician networks and strong deal flow.Param Baladandapani (Generational Wealth MD) – retired radiologist and mentor helping physicians achieve financial freedom through real estate.Mike Morawski – 30-year real estate veteran with a focus on southeast multifamily and market cycle timing.Aleksey Chernobelskiy (GP LP Match) – founder connecting LPs with high-quality GPs and providing deal flow transparency.The panel discusses everything from vetting operators and conservative underwriting to AI applications in real estate, tax strategies, and why disciplined, long-term investors are well-positioned for the next cycle.TIMESTAMPS0:43 - Episode Overview | Wealth Forum2:01 - Host and Panelist Introductions3:48 - Current Market Overview: Threats, Opportunities, and LP Capital Trends5:01 - Panelist Backgrounds10:00 - Investor Psychology, Market Cycles, and Recovering from Losses15:54 - Deal Diligence and Vetting Lessons from Recent Years21:33 - Poll Results and Wire Fraud Warning22:36 - Bronson's Deal Evaluation Framework (Market > Operator > Deal)23:44 - Importance of Cash Flow in Today's Market28:34 - Broader Opportunities, Risks, and Geopolitical Factors (Oil, Baby Boomers, Senior Housing)32:33 - AI's Impact on Real Estate, Jobs, and Investor Tools41:41 - Personal Investments Outside Core Business (Precious Metals, Crypto, Asset Allocation)46:50 - Q&A: Spotting Operators with Realistic Projections51:42 - Lightning Round: Is This Like 2008 in Multifamily?52:01 - Panelist Contact Info and Closing RemarksConnect with the Guests:Tyson CobbWebsite: timberviewcapital.comMobile: 563-209-8488Email: tyson@timberviewcapital.comParam BaladandapaniWebsite: gwcapital.comPassive Investment Due Diligence Resource: gwcapital.com/guideMike MorawskiLinkedIn: https://www.linkedin.com/company/mikemorawski2Instagram: @mike.morawski.54Email: mike@mikemorawski.comAleksey ChernobelskiyWebsite: gplpmatch.comEmail: aleksey@gplpmatch.com#MultifamilyInvesting#PassiveIncome#RealEstateDueDiligence#CashFlowStrategies#WealthBuilding

Follow me @samirkaji for my thoughts on the venture market, with a focus on the continued evolution of the VC landscape.Welcome back to another episode of Venture Unlocked, the podcast that takes you behind the scenes of the business of venture capital.In this episode, I'm joined by three deep tech investors and friends of the show, Nate Williams, Sunil Nagaraj, and Guy Perelmuter, for a roundtable on the state of deep tech and the changing venture landscape. We dig into what deep tech really means today, why it's suddenly attracting so much capital, and how economics, government tailwinds, and AI as a “killer app” have pulled these once niche technologies into the mainstream. We also explore the growing concentration of capital in a handful of hyperscale winners, the tension between consensus vs. non-consensus investing, and what all of this means for emerging managers, LPs, and founders operating at the zero-to-one stage.Thanks for listening to another episode of Venture Unlocked. I hope you enjoyed this conversation with Nate, Sunil, and Guy. If you'd like to get Venture Unlocked content straight to your inbox, go to ventureunlocked.substack.com and sign up, or head over to Apple Podcasts or Spotify and subscribe. Thanks again for listening.Nate Williams is the Founder and Managing Partner of DeepTech seed firm UNION (Union Labs, Union Peak VC funds) and formerly served as an Entrepreneur-in-Residence (EIR) at Kleiner Perkins focusing on vertical “Physical AI” opportunities across Climate/Resilience, PropTech, and Mobility. Nate has made over 40 early-stage investments, including Urban Sky, Butlr, Antimatter (acquired by Databricks), Proxy (acquired by Oura), Ruby Robotics (acquired by Intuitive Surgical) and Klue (acquired by Medtronic). Before transitioning to full-time VC, Nate built a track record as a hands-on operator with senior leadership roles across startup, growth, and turnaround stages, culminating in successful exits for 4Home (to Motorola, 2010), Motorola Mobility (to Google, 2012), Motorola Home (to ARRIS, 2013), and August Home (to Assa Abloy, 2017). Earlier in his career, Nate was an Analyst in the Digital Home Group at Intel Corp. Nate holds an MBA from UCLA Anderson School of Management and a Bachelor's degree in Comms from the University of Connecticut.Sunil Nagaraj is the Founder and Managing Partner of Ubiquity Ventures, a seed-stage venture firm investing in “software beyond the screen,” including robotics, AI, industrial automation, and frontier technologies. Prior to founding Ubiquity, Sunil spent over a decade at Bessemer Venture Partners, where he invested in companies across cloud computing, developer tools, and emerging technologies. He is widely recognized for his early conviction in deep tech and infrastructure-driven innovation before it became mainstream in venture capital.Guy Perelmuter is the Founder and Managing Partner of GRIDS Capital, a venture firm focused on deep tech, AI, and advanced industrial technologies. With a background spanning engineering, technology, and investing, Guy has built his career around backing highly technical founders tackling complex global problems. He is known for his insights into the convergence of AI, infrastructure, and industrial transformation, as well as his emphasis on technical depth and long-term value creation in venture investing.Timestamps:Topics in this conversation include:* Definition of Deep Tech by Technical Prowess and Advanced Engineering (2:51)* Hardcore Technology, Difficulty to Build, and Hardware Misconceptions (3:51)* Drivers Of Deep Tech Tailwinds: Maturing Technologies and Government Push (6:12)* Excess Investor Interest After SpaceX and Other Breakout Successes (9:18)* Historical Analogy to Electrification and AI as New Infrastructure Layer (14:43)* Need For Specialized Deep Tech Expertise and New VC Org Structures (19:36)* Schizophrenic Risk-on Behavior and King-making of Consensus Winners (22:08)* Why Normal M and A and IPO Outcomes Still Matter For Smaller Funds (26:53)* Fund Proliferation, New Managers, and What Will Prove Transient (28:49)* Access Capital, Hollywood-ization of Venture, and Coming Bust Risks (33:34)* Consensus Growth Obsession, 10x Expectations, and Metric Distortions (38:02)* How Seed Managers Adapt and Curate Downstream Capital for Portfolios (41:01)* Founder-led Investor Selection and Power Shifting To Specialist Seed GPs (44:53)* Myths About VC Impact, Trend Surfing, and Overstated GP Influence (48:18)* Final Thoughts and Takeaways (53:11)Follow me @SamirKaji and give me your insights and questions with the hashtag #ventureunlocked. If you'd like to be considered as a guest or have someone you'd like to hear from (GP or LP), drop me a direct message on X. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit ventureunlocked.substack.com

Not all chronic cough, globus, or voice changes are due to reflux, so how do you distinguish laryngopharyngeal symptoms (LPS) from true laryngopharyngeal reflux disease (LPRD)? In this episode of the BackTable ENT & Allergy podcast, Dr. Ashley Agan interviews laryngologist Dr. Inna Husain about how nuanced diagnostic definitions and a careful clinical approach can improve patient outcomes and avoid both under- and overdiagnosis. Together, they discuss the differences between GERD and LPRD, review the importance of detailed patient histories, endoscopic findings, and the evolving role of biomarkers like pepsin. --- Get the BackTable apphttps://www.backtable.com/app --- Timestamps 00:00 - Introduction02:14 - LPS Versus LPR Basics06:34 - GERD Versus LPRD11:28 - Clinic Workup and Scoping18:02 - San Diego Consensus Debate24:14 - Testing Over Empiric PPIs31:45 - Managing Proven Reflux34:59 - Stroboscopy Before Surgery36:10 - Pepsin Therapies and Tests39:54 - What Counts as Abnormal Reflux44:24 - Tapering Off PPIs Safely50:12 - Long Term Plan and Dietitians55:39 - GLP One Drugs and Reflux57:34 - Menopause Rhinitis and Hormones01:00:09 - Final Pearl For ENTs --- More about this episode They outline contemporary workup strategies, including the San Diego Consensus on Bravo testing, 24-hour pH impedance, and alternatives for negative reflux testing. The conversation covers management strategies, from selective PPIs and lifestyle tailoring to emerging therapies and the impact of GLP-1 drugs, helping ENT specialists refine their approach to complex laryngopharyngeal complaints. --- Resources San Diego Consensus for LPS and LPRD:https://doi.org/10.14309/ajg.0000000000003482 Dr. Inna Husainhttps://innahusainmd.com/ --- BackTable ENT & Allergy is the go-to podcast for otolaryngologists, allergists, and head and neck surgeons. Download the free BackTable app to get early access to new episodes, cases, and courses curated by physicians in your specialty. ► https://www.backtable.com/app

Send us Fan MailLEARN THE CAPITAL RAISING STRATEGIES AND FRAMEWORKS used by alternative asset professionals: go.fundraisecapital.coThis episode of Making Billions with Ryan Miller & Aman Verjee delivers the secondary market playbook that gives managers a structural advantage over every fund ignoring this shift.How do venture secondaries solve LP liquidity problems in 2026? Former PayPal and eBay CFO Aman Verjee reveals the exact system for buying into elite VC deals at 70% below market value. Fund managers face a quiet crisis: DPI timelines stretching 10-12 years while LPs demand exits far sooner. What separates fund managers who retain LP trust from those who lose it? Verjee breaks down how to audit your fund structure today, identify liquidity gaps before they become emergencies, and build relationships with secondary buyers years before you need them. He shares the due diligence framework used to evaluate SpaceX, Anthropic, and Canva positions when information is limited and markets are opaque.[THE HOST]: Ryan Miller is a fund manager, capital strategist, and former CFO turned angel investor in technology and energy. He is the founder of Fund Raise Capital and Aequor Capital Partners, and has mentored over 1,000 fund managers across private equity, private credit, venture capital, real estate, and alternative assets globally.[THE GUEST]: Aman Verjee has more than 20 years of financial and operational experience from both private and public technology companies. He has been a member of the management teams at some of the most successful companies in the world, including PayPal, eBay, 500 Startups and Sonos. His new book, A BRIEF HISTORY OF FINANCIAL BUBBLES, comes out in December.Subscribe on YouTube:https://www.youtube.com/channel/UCTOe79EXLDsROQ0z3YLnu1QQConnect with Ryan Miller:Linkedin: https://www.linkedin.com/in/rcmiller1/Instagram: https://www.instagram.com/ryanmilleroffical/X: https://x.com/_MakingBillionsWebsite: https://making-billions.com/Support the showSupport the showDISCLAIMER: This podcast is for entertainment and general informational purposes only — not legal, financial, tax, or investment advice. Nothing herein constitutes a solicitation or offer to buy or sell any security or investment product. Past performance does not indicate future results. Always consult qualified legal, financial, and tax professionals before making any investment decision. NAME NOTICE: "Making Billions with Ryan Miller" reflects the profile and aspirations of guests featured — it is not a promise, projection, guarantee, or representation of any financial result, income, or outcome for any listener, viewer, or reader. Most individuals who consume this content do not raise any particular amount of capital, and many achieve no financial result whatsoever. "Fund Raise Capital" is a brand identifier only — it is not a promise, guarantee, or representation that any member, subscriber, or listener will raise capital, attract investors, or achieve any financial or professional outcome. This show does not constitute a business opportunity, franchise, investment program, or offer of any product or service of any kind. No part of this show should be construed as a solicitation for investment in any way. Guest views are their own and do not necessarily reflect those of the show or host. Host and/or guests may hold positions in assets discussed. This episode may contain paid sponsorships, advertisements, or endorsements. Sponsored content is identified where...

What happens when a real estate syndication exits and all that bonus depreciation comes back into play? In this episode, Nate Sosa and Thomas Castelli break down depreciation recapture, cost segregation, and the tax implications GPs and LPs need to understand before selling a deal. Topics discussed include: - Bonus depreciation and cost segregation - Depreciation recapture mechanics - 1245 vs. 1250 vs. 1231 gains - 1031 exchanges in syndications - Refinancing strategies - Partial asset dispositions - LP communication and tax planning - Time value of money and tax deferral Request a free discovery meeting: go.therealestatecpa.com/mlre Get the Ultimate Guide for Real Estate Syndications: go.therealestatecpa.com/mlreultimateguide Submit your questions to: go.therealestatecpa.com/question The Major League Real Estate podcast is for general information purposes only and is not intended to provide, and should not be relied on for, tax, legal, investing, financial, or accounting advice. Information on the podcast may not constitute the most up-to-date legal or other information. No reader, user, or listener of this podcast should act or refrain from acting on the basis of information on this podcast without first seeking legal and tax advice from counsel in the relevant jurisdiction. Only your individual attorney and tax advisor can provide assurances that the information contained herein – and your interpretation of it – is applicable or appropriate to your particular situation. Use of, and access to, this podcast or any of the links or resources contained or mentioned within the podcast show and show notes do not create a relationship between the reader, user, or listener and podcast hosts, contributors, or guests. Any mention of third-party vendors, products, or services does not constitute an endorsement or recommendation. You should conduct your own due diligence before engaging with any vendor.