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In questo episodio del podcast della Rivista di Psicoanalisi dialogheremo con il Dott. Massimiliano Sommantico, Redattore Capo della nostra Rivista.Dopo qualche accenno storico al concetto ed alla pratica della peer rewiew, Massimiliano Sommantico ci illustrerà come avviene quello che lui definisce il "dialogo silenzioso" fra lettore ed autore anonimo. Ci descriverà quali sono le caratteristiche auspicabili dell'assetto mentale del lettore e dell'autore affinché il dialogo fra di essi sia costruttivo e possa favorire lo sviluppo ed il miglioramento di un articolo che verrà poi eventualmente pubblicato. Farà infine alcuni brevi riferimenti ai due lavori contenuti nel focus ovvero: “Ode in chiosa ai lettori anonimi, custodi silenziosi della Rivista di Psicoanalisi “ di Malde Vigneri e “La vertigine della playlist.Note sulla forma e la cura del sapere psicoanalitico” di Gaetano Pellegrini.

Nine years ago today, Mr. YLP HImself made the decision to embark on a solo podcasting career, publishing his very first episode of the YLP Podcast. Nine years later, we celebrate the pod as a whole, with the ninth anniversary show dedicated to one of Mr. YLP's closest friends. On this week's episode of the pod, the tradition continues as Mr. YLP presents his Ode to the G1 Climax tournament, as he discusses the history of the tournament, previous winners of the various iterations of the tournament dating back to 1974, who will be in this year's tournament, and most importantly, who he believes will win the G1 Climax 36 tournament, earning a spot in the main event of Wrestle Kingdom 20.EMAIL MR. YLP AT: younglionsperspective@gmail.comFOLLOW MR. YLP ON: Instagram - @ylp_podcast | X - @YLPerspectiveBUY YOUR WAR & YLP MERCH HERE: wrestle-addict-radio.shop.fourthwall.com

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

Nine years ago today, Mr. YLP HImself made the decision to embark on a solo podcasting career, publishing his very first episode of the YLP Podcast. Nine years later, we celebrate the pod as a whole, with the ninth anniversary show dedicated to one of Mr. YLP's closest friends. On this week's episode of the pod, the tradition continues as Mr. YLP presents his Ode to the G1 Climax tournament, as he discusses the history of the tournament, previous winners of the various iterations of the tournament dating back to 1974, who will be in this year's tournament, and most importantly, who he believes will win the G1 Climax 36 tournament, earning a spot in the main event of Wrestle Kingdom 20.EMAIL MR. YLP AT: younglionsperspective@gmail.comFOLLOW MR. YLP ON: Instagram - @ylp_podcast | X - @YLPerspectiveBUY YOUR WAR & YLP MERCH HERE: wrestle-addict-radio.shop.fourthwall.com

Nine years ago today, Mr. YLP HImself made the decision to embark on a solo podcasting career, publishing his very first episode of the YLP Podcast. Nine years later, we celebrate the pod as a whole, with the ninth anniversary show dedicated to one of Mr. YLP's closest friends. On this week's episode of the pod, the tradition continues as Mr. YLP presents his Ode to the G1 Climax tournament, as he discusses the history of the tournament, previous winners of the various iterations of the tournament dating back to 1974, who will be in this year's tournament, and most importantly, who he believes will win the G1 Climax 36 tournament, earning a spot in the main event of Wrestle Kingdom 20.EMAIL MR. YLP AT: younglionsperspective@gmail.comFOLLOW MR. YLP ON: Instagram - @ylp_podcast | X - @YLPerspectiveBUY YOUR WAR & YLP MERCH HERE: wrestle-addict-radio.shop.fourthwall.com

Ode (@thatsod.e / @thatsod_e) and Mo AKA Kid Licorish (@licorishislegit) welcome Nick and Maurice of the Blerd By Nature podcast for a wide-ranging crossover conversation. The guests trace their friendship back to NYC wrestling watch parties, an AEW show in Washington, D.C., and the pandemic downtime that pushed them to launch their own show covering wrestling, anime, and current television. From there the group dives into DreamCon 2026, recapping the convention's cosplay scene, the Black-owned brand Ashify, and a public debate over whether the event offers the same networking value as TwitchCon. They also unpack Tomi Adeyemi's public distancing from the Children of Blood and Bone film adaptation and the messy, leak-plagued rollout of Paramount's animated Avatar: The Last Airbender movie.The back half of the episode covers plenty of ground, including apartment heat troubles, an MTA shuttle bus detour, online criticism of comedian KevOnStage, and a stomach virus outbreak tied to fresh produce. On a lighter note, they trade stories about a Philadelphia cheesesteak trip, a new spot called House of Spells, a beach gathering in New Jersey, and encouraging updates on ongoing job searches. Nick and Maurice close things out by sharing where listeners can find Blerd By Nature across social media, YouTube, and podcast platforms, capping off a conversation that spans pop culture debates, personal milestones, and everyday frustrations.Nick and Maurice of Blerd By NatureBioCome join The Man With The Plan (Maurice) and Mr. Go With The Flow (Nicholas) as we review and react to Anime, Power Rangers and other TV shows. We'll also discuss other various topics all from the perspective of a couple brothas from NYC.Linktree: https://linktr.ee/BlerdByNature?utm_source=linktree_profile_share<sid=76c1fbc8-2236-4d90-9557-9d54518ca973Connect with the Snerdy CrewWatch, Listen, or Sponsor the show: https://beacons.ai/blackandsnerdy

Rime is handling over 100 million calls each month across multiple companies Also, Anthropic-backed Ode launches as AI labs bet that embedding forward-deployed engineers inside enterprises is the key to accelerating enterprise AI adoption. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Ode (@thatsod.e / @thatsod_e) and Mo AKA Kid Licorish (@licorishislegit) open this bonus episode of Black and Snerdy with their mental health check-in segment, joined by Chiquita Johnson. Mo describes managing manic and depressive stretches without health insurance or medication, leaning on years of therapy tools. Chiquita places her mental health at a seven out of ten, naming ongoing work with depression, PTSD, and anxiety after returning to therapy. Ode connects her own difficult stretch to ADHD and trauma responses that surface most in quiet moments. The three then shift into a game called Protag Therapy Session, where they assign mental health diagnoses to beloved television characters.The diagnoses begin with Martin Payne from Martin, played by Martin Lawrence, whom the group examines for antisocial and narcissistic personality traits alongside his relationship with Gina. Attention turns next to Issa Dee from Insecure, played by Issa Rae, with discussion of avoidant and dependent personality patterns, possible ADHD, and her long friendship with Molly. The episode closes on Blanca Rodriguez from Pose, played by MJ Rodriguez, examined through generalized anxiety disorder, social anxiety, and PTSD tied to the ballroom community and the HIV/AIDS era. Throughout, they trade commentary on trauma, resilience, and chosen family as reflected in each character's arc.Chronicles of a VirgoYoutube: ⁠https://www.youtube.com/@Chronicles_of_a_Virgo_podcast⁠IG: ⁠https://www.instagram.com/chronicles_of_a_virgo_podcast⁠FB: ⁠https://www.facebook.com/ChroniclesOfAVirgoPodcast/⁠Tiktok: ⁠https://www.tiktok.com/@chronicles_of_a_virgo⁠Website: ⁠https://chroniclesofavirgo.wixsite.com/my-site⁠Connect with the Snerdy CrewWatch, Listen, or Sponsor the show: ⁠https://beacons.ai/blackandsnerdy⁠⁠

Send us Fan MailDeath can be one of the clearest teachers we have—but only if we stop treating it like a distant problem.In this episode, I'm joined by ritualist and death educator Shaina Garfield, founder of Leaves With You and one of the co-facilitators of the Beyond the Veil Retreat, to talk about green burial, grief, and the surprisingly life-giving practice of planning a sacred return to Earth.We begin with Shaina's nonlinear path into this work: being diagnosed with chronic Lyme disease in college, discovering holistic healing, and following a design question that led her to create her first macrame coffin. Shaina shares why handweaving a biodegradable coffin can become so much more than an environmentally conscious funeral option—it can be a communal ritual in which every knot holds prayers, beauty, love, and memory.From there, we explore Shaina's deeply personal essay, The Return to My Earth, and the moment she realized that healing was not about transcending or escaping her body. It was about coming home to it.We talk about letting go of the lives we thought we would have, learning to hold gratitude and longing at the same time, and recognizing when the search for healing becomes another way of searching for something wrong with us.Shaina shares how plant medicine ceremony has served as a form of threshold training, why the real ceremony begins after the ceremony, and why integration and physical action matter more than continually chasing the next cure, treatment, or spiritual breakthrough. She also offers guidance for anyone curious about connecting with guides, ritual, and the unseen—even if plant medicine is not part of their path.And because this is the Ode to Joy podcast, we make space for the joy woven through it all: dance breaks, trees, water, gardens, laughter, daily acts of offering, and the practices that help us stay openhearted while living with pain and uncertainty.If you are curious about death-positive living, end-of-life planning, ritual, chronic illness, green burial, or what it means to return fully to your body and the Earth, this conversation offers both grounding and permission.Subscribe to the podcast, share this episode with someone who may need it, and leave a review so more people can find the conversation.Three Shaina Truths1. The equation of becoming requires both giving away and receiving.Whenever we cross a threshold and become a new version of ourselves, something must be released. Letting go creates the space into which the next chapter can arrive.2. Medicine is not necessarily a cure—it can be a key.No teacher, ceremony, treatment, or spiritual practice can walk the path for us. The key may open something, but we are still responsible for building the door, walking through it, and integrating what we have learned into our everyday lives.3. Our death can become our final offering to the Earth.Preparing for our sacred return is not only about deciding what happens after we die. It asks us to consider what we are cultivating within our bodies, our relationships, and our lives right now.Standout Quotes from Shaina“It's important to witness what is witnessing you, because what we're seeking is also seeking us.”“The equation of becoming means having to give away in order to receive.”“The ceremony is great, but it's really the integration and the action that make it real.”“Plant medicine is not a cure—it's a key. I'm the one who has to build the door and walk through it.”“Death is a key to experiencing more joy.”“We're looking at our death only to inform our life here today.”“We should consider every day lost on which we have not danced at least once.” —Friedrich NietzscheJournaling PromptsWhat am I being invited to give away so that I can receive what is trying to enter my life?Where has my desire to heal, grow, or improve quietly become a search for something wrong with me?What would it mean for me to return to my Earth—to my body, my needs, my limits, and the physical reality of my life?If I knew I were going to die tomorrow, what would feel complete—and what would I wish I had tended to more lovingly?How might I treat one ordinary act today—washing the dishes, preparing food, walking outside, or caring for my body—as an offering?What expectations about my life, my body, or the person I thought I would become am I ready to grieve and release?What would my own sacred return to Earth look and feel like? What does imagining it teach me about how I want to live now?Where is life already inviting me into the dance—and what keeps me from joining it?Resources MentionedShaina Garfield and Leaves With You⁠Read Shaina's essay, ⁠The Return to My Earth⁠Follow Leaves With You on InstagramLearn more about the Beyond the Veil RetreatExplore green burial and environmentally conscious end-of-life options in your local areaIn This EpisodeChronic illness as an initiation into healing, death work, and the EarthShaina's journey from industrial designer to ritualist and death educatorCreating biodegradable macrame coffinsWeaving prayers, memories, and love into a burial vesselReturning to the body after years of spiritual explorationWhen the healing journey becomes another form of self-rejectionHolding gratitude for the present while maintaining a vision for the futureThe equation of becomingLife as a series of thresholdsPlant medicine, responsibility, lineage, and discernmentWhy integration matters more than chasing spiritual experiencesConnecting with guides and the unseenLearning to live with death rather than treating it as a distant problemDance as prayer, embodiment, and connection to creationGreen burial as a physical and spiritual offeringUsing death to inform how we live todayShaina's offering at Beyond the VeilConnect with ShainaShaina Garfield is a ritualist, death educator, designer, and founder of Leaves With You. Her work helps people reconnect with death, grief, ceremony, and the natural world through ritual containers, death education, green burial exploration, and biodegradable macrame coffins.At the Beyond the Veil Retreat, Shaina will facilitate The Sacred Return to Earth, an exploration of green burial, the spiritual dimensions of decomposition, and how envisioning our return to the Earth can transform the way we live today. Support the showBuy your copy of Elena's book "Grieve Outside the Box"Follow on IG @elenabox

In this episode of Black and Snerdy, Ode (⁠@thatsod.e⁠ / ⁠@thatsod_e⁠) and Mo AKA Kid Licorish (⁠@licorishislegit⁠) are joined by fellow podcaster and friend of the show Chiquita Johnson (Chronicles of a Virgo Podcast) to share her podcast origin, therapy-driven mission, and recent health and grief struggles that shaped her return. Together, they honor the legacy of Georgie E. Johnson, tracing how Johnson Products Co. and brands like Afrosheen and Just for Me helped shape Black hair care and Black entrepreneurship before being sold to Procter & Gamble. They move into a close look at the Nolan Xavier Wells case while laying out the July Fourth timeline, the family's retention of Ben Crump, the ongoing autopsy, and troubling questions about a lone Black teen among a white friend group that have raised concerns about transparency and racial dynamics. The conversation shifts to viral pool and boat clips showing Black children being taunted, life-jacket failures, and the wider pattern that includes cases like Tamia Horsford. The group also touch on a Stanford study about AI hiring tools that disadvantage Black and Asian applicants, weave in astrology comments and show drops, and surface the tension between topical news and personal vulnerability throughout the episode. Truly an episode worth checking out. Chronicles of a VirgoYoutube: https://www.youtube.com/@Chronicles_of_a_Virgo_podcastIG: https://www.instagram.com/chronicles_of_a_virgo_podcastFB: https://www.facebook.com/ChroniclesOfAVirgoPodcast/Tiktok: https://www.tiktok.com/@chronicles_of_a_virgoWebsite: https://chroniclesofavirgo.wixsite.com/my-siteConnect with the Snerdy CrewWatch, Listen, or Sponsor the show: ⁠https://beacons.ai/blackandsnerdy⁠⁠

Intro: ‘One More Night' (excerpt) – Can  It's Too Hot For Words – Teddy Wilson & his Orchestra (2:46) Spirit of the Boogie – Kool and the Gang (4:51) Adagh Oyantid – Tamikrest (3:32) Upa, Neguinho – Edú e Bethânia (2:18)     Djomido Ma Dougbe Tche – Antoine Dougbé et l'Orchestre Poly-Rythmo de Cotonou (7:58)    Çiçek Açiyar – Derya Yildirim & Grup Şimşek (3:32)   The Vamp – Randy Brecker (5:11)   Omelebele – Dr Victor Olaiya's International All Stars (5:57)   Zomzibar – Barney Wilen (7:16)   Book of Rules – The Heptones (3:00) Cecilia – Simon & Garfunkel (2:54) Cæcilia – Fennesz (3:48) Lascia La Spina, Cogli La Rosa (from ‘The Triumph of Time and Truth') – Handel, Rattle/Berliner Philharmoniker/Bartoli (6:22) The Coast – Paul Simon (5:00) From Harmony (from ‘Ode to St Cecilia's Day') – Handel, Denecker/RedHerring Baroque Ensemble/New Baroque Times Voices (3:31)   Pyar Zindagi Hai (from ‘Muqaddar ka Sikandar' - Kalyanji Anandji, featuring Asha Bhosle,       Lata Mangeshkar & Mahendra Kapoor (7:22)   Sheba – Fatima Al Qadiri (3:18) The One For Whom I Chose Asceticism – Abida Parveen (5:09) To The Men With Hate Speech On Their Lips – Khasi-Cymru Collective (2:46) Jos Embalar O Menino – Montserrat Figueras, with Hespèrion XXI, Anon. (5:28)  Jangari – Maalem Houssam Guinia (6:09) The House Carpenter – Clarence Ashley (3:15) Ogod Anno 2000 – Tom Zé (3:55) Hypersonic Super-Asterid – Mandrake Handshake (8:34)   Playout: ‘Pogles Walk' (excerpt) – Vernon Elliott Ensemble

Hey everyone, Alex here

On this episode of Black and Snerdy, Ode (@thatsod.e / @thatsod_e) and Mo AKA Kid Licorish (@licorishislegit) sit down with Wordplay T. Jay and Icarus Gray for a bonus conversation that starts with the origins of their podcasting lane and quickly moves into hip hop culture, generational perspective, and the pressure of staying authentic in a changing media landscape. The discussion moves through Vince Staples' Cry Baby, Tierra Whack, Rapsody, J. Cole, and a full-throttle Drake critique before turning to the 2000 documentary Backstage and the 1999 Hard Knock Life tour.The review of Backstage highlights Jay-Z, DMX, Ja Rule, Method Man, Redman, Memphis Bleek, Beanie Sigel, and Dame Dash, while digging into backstage energy, performance legacy, and the uneasy truth behind some of the film's most memorable scenes. Black boy joy, hip hop maturity, performance history, and the difference between then and now all collide in a conversation that mixes sharp commentary, laughter, and plenty of pointed opinions.No Rhyme or Reason Podcast: https://www.submithub.com/link/nrorWordPlay T. Jay: https://music.wordplaytjay.comIcarus Gray: https://linktr.ee/icarusgrayWordPlay T. Jay YouTube: https://youtube.com/@wordplaytjayWordPlay T. Jay Instagram: https://instagram.com/wordplaytjayIcarus Gray YouTube: https://youtube.com/@IcarusGrayIcarus Gray Instagram: https://instagram.com/icarus_grayConnect with the Snerdy CrewWatch, Listen, or Sponsor the show: ⁠https://beacons.ai/blackandsnerdy⁠⁠

Ludwig van Beethovens "Ode an die Freude" aus seiner Neunten Symphonie wurde schon immer gerne für politische Zwecke genutzt. Am 9. Juli 1971 erklärte der Eurparat die Melodie "Freude schöner Götterfunken zur offiziellen Europahymne".

This week we talk a bit about the work of classic comics artist and writer John Byrne, from xmen to next men and everything in between. Theres also a fun delve into a one and done spider team up book that everyone should pick up from a back issue bin, and Dan marks his return to the show by asking if we would still read comics if they were digital only. All that and a bunch of great comic recommendations, stuff to check out an also shampoo talk! Great stuff to check out: John Byrne, Spider-Man, Red Sonja, American Nature #4, Mystic, Matt Bunce, Eamonn Clarke, Mega City Book Club, Zinezilla Arts Fair, Comics Assemble, She, Pat Mills, The Gods and Monsters of Headgrave, Death Metal Duck, Black Panel Press, Justin Heggs, Cam Hayden, Corpse Knight, Terrobytes, Mad Cave Comics, Ode to Kirahito, Osamu Tezuka

"The Professor" Ron Wotus joins Talking Baseball on this Rockies series and Ernie Harwell's Ode to BaseballSee omnystudio.com/listener for privacy information.

In this episode of Black and Snerdy, Ode (⁠@thatsod.e⁠ / ⁠@thatsod_e⁠) and Mo "Kid" Licorish (⁠@licorishislegit⁠) talk with Supreme Sensai about DreamCon hosting, creator finances, and postpartum pressures. The panel react to the Pooh Shiesty leaked footage and the Gucci Mane connection, break down the Ray J versus Orlando Brown viral clip and the “show all the hundreds” moment, and the Yu-Gi-Oh hygiene issue that caused a tournament to be suspended. Supreme Sensai opens up about the logistical realities of convention life and being a new parent while balancing creator work.The episode moves into a We Big Mad segment that covers invoice headaches and customer-support frustration, as well as a candid mental-health check-in on postpartum stress. A baby cameo provides an emotional beat amid the banter making for a landmark episode. Supreme Sensai is a content creator, host, and community builder known for blending gaming, culture, and entertainment. Known throughout the gaming and anime community as “Mother”, she has partnered with brands including Nike, Fortnite, and Mountain Dew while hosting major gaming events and conventions. She is also the founder of The Island, a creator community dedicated to helping the next generation of creators grow.Supreme SensaiContent Hub: https://beacons.ai/supremesensaiThe Island: https://theislandcollective.my.canva.siteConnect with the Snerdy Crew:Watch, Listen, or Sponsor the show: ⁠https://beacons.ai/blackandsnerdy⁠⁠

durée : 00:14:23 - Les émissions culturelles de France Culture - par : Marie Labory - L'été s'ouvre avec une nouvelle excitante : Madonna, reine de la pop, sort un nouvel album, "CONFESSIONS II". - équipe : Laurence Malonda, Boris Pineau, Aïssatou N'Doye, Jules Barbier, Zohra Vignais, Lise Ripoche, Mathi Adjinsoff - invités : Philippe Azoury Journaliste, critique et auteur, Carole Boinet Journaliste française Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

Dan gives the latest Ode to Mike Conley with the news that one of our favorite guests and a very effective Timberwolf is on his way to the Boston Celtics as a free agent. See omnystudio.com/listener for privacy information.

What happens when your family leaves town… and silence becomes the loudest thing in the house?This episode of The JB and Sandy Show delivers the perfect mix of laughter, chaos, and surprisingly relatable moments—from patriotic hype to personal unraveling. The energy kicks off with a special in-studio surprise as JB's daughter joins the show bright and early, setting a playful tone for everything that follows. But it's Sandy who steals the spotlight early with a bold and hilarious Ode to U.S. Men's Soccer, capturing the excitement of a massive match and leaning fully into patriotic pride. One standout moment: “Turn that pitch into a barbecue and skewer them under the lights.” It's over-the-top, funny, and exactly the kind of creative spark listeners love.As the show moves forward, the tone shifts into one of the most unforgettable segments—JB's “home alone journal.” With his wife and daughter out of the country, JB documents his gradual descent into solitude, confusion, and questionable life choices. His brutally honest reflections include gems like:“I ate shredded cheese directly from the bag like a raccoon behind a dumpster.”and“I stood in the kitchen for twenty minutes… waiting for instructions.” It's funny, a little too real, and completely relatable for anyone who's ever been thrown off their routine.The episode keeps the laughs coming with a classic childhood story from Sandy that escalates fast: “I went at him like a spider monkey.” What starts as a sandbox memory turns into a full-blown moment of chaos that had everyone cracking up. Meanwhile, listeners get a mix of local flavor and everyday life moments—from shoutouts to unexpectedly cheerful grocery store butchers to a nostalgic look back at high school traditions. One of the most jaw-dropping revelations comes when Tricia shares the original lyrics of her high school fight song—lyrics that would never make it past today's standards, but had everyone laughing in disbelief. Throughout the show, there's a steady balance of humor and heart, with moments that feel both wildly entertaining and surprisingly familiar. Memorable highlights include:“Turn that pitch into a barbecue…”“I ate shredded cheese like a raccoon…”“I stood there waiting for instructions… none came.”From patriotic energy and personal meltdowns to nostalgic stories and unexpected laughs, this episode captures everything that makes The JB and Sandy Show so addictive.Don't miss out. Be sure to subscribe, leave a review, and share this episode with someone who needs a laugh—or who knows exactly what it feels like when the house gets a little too quiet.

Dan gives the latest Ode to Mike Conley with the news that one of our favorite guests and a very effective Timberwolf is on his way to the Boston Celtics as a free agent. See omnystudio.com/listener for privacy information.

Soon, the famous orange and yellow seats that can be found on certain subway lines will be no more, as the MTA continues its process of upgrading and improving subway cars and equipment. The New York Transit Museum has organized a new exhibit, 'Ode to the Orange Seats,' that bids farewell, but also looks at the history of the bucket seats that were first introduced on R44 cars in 1971. Curator Jodi Shapiro discusses the exhibit, which includes work from 14 artists inspired by the subway. And as part of our Small Stakes, Big Opinions series, listeners weigh in on the question that perhaps most divides New Yorkers, which is the best seat on the subway and why? Photo by Argenis Apolinario: Gabriel Bautista's viral tweet with set of orange seats.  Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Gwyn and Ode talk about some cool ladies and the stuff they wrote.

What happens when a heat dome rolls into Austin… and JB is left home alone for a week? In this wildly entertaining episode of The JB and Sandy Show, things heat up fast—literally and figuratively. From a poetic deep dive into Austin's scorching weather to relationship debates and jaw-dropping stories from listeners, this episode blends humor, heart, and total unpredictability.The show kicks off with lighthearted speculation about celebrity buzz before diving straight into one of the most talked-about segments: Sandy's unforgettable “Ode to the Heat Dome.” Equal parts comedy and creativity, the performance captures the suffocating Texas summer with lines like, “You shower at eight, feel fresh and clean… by 8:04 you're a swampy machine.” It's a hilarious and painfully relatable moment that perfectly sets the tone for the episode.Meanwhile, JB shares what life looks like when his ultra-organized wife leaves town—and for once, he's the one holding it all together. From emergency cash to last-minute travel tech, JB shocks everyone with his unexpected preparedness, prompting the ultimate reaction: “Who am I married to?” But as the week goes on, even he admits the cracks may start to show. Things take a personal turn when the crew opens up the Amazing Book of Records, searching for the biggest age gap in a marriage. What follows is a mix of heartfelt and surprising stories, culminating in one listener who reveals an 18-year age difference—and a marriage that has lasted over five decades. It's a powerful reminder that sometimes the most unconventional beginnings lead to lasting love. The laughs keep coming with a candid recap of a wild bull riding event, complete with late-night dancing, free beer cutoffs, and the kind of exhaustion that leaves you wondering what day it is. One moment captures it perfectly: “I woke up and thought I was in third grade and missed the bus.”And just when you think the show couldn't get more entertaining, Sandy launches into a passionate (and hilarious) rant about TV realism—questioning everything from wardrobe choices to character authenticity in a popular Western series. It's a relatable and funny breakdown that taps into the little details we all notice but rarely say out loud. To wrap it all up, the team revisits one of the most bizarre stories of the day—a real-life vigilante dubbed the “Mexican Batman”—leaving listeners equal parts stunned and amused. From laugh-out-loud poetry and unexpected personal wins to heartfelt listener stories and off-the-wall commentary, this episode delivers everything fans love about The JB and Sandy Show. Don't miss a moment.Be sure to subscribe, leave a review, and share this episode with someone who could use a good laugh—and maybe a little relief from the heat. 

In this episode, Ode (⁠@thatsod.e⁠ / ⁠@thatsod_e⁠) and Mo aka Kid Licorish (⁠@licorishislegit⁠) welcome Jared and D'Marcus of the Black Geek Energy podcast for a Pride‑themed round of “This or That” that pits queer icons head‑to‑head. The conversation names and weighs Ryan Wilder versus Renee Montoya, North Star versus Iceman (Bobby Drake) and the implications of legacy characters coming out, Garnet's Ruby & Sapphire origin and marriage (with shoutouts to Rebecca Sugar and Estelle), and the Korra & Asami relationship versus William Clockwell and Rick Sheridan from Invincible. The show moves into Sailor Uranus & Neptune and Yuri & Victor from Yuri on Ice, and closes the bracket with One Piece favorites Bon Clay and Emporio Ivankov, including a fandom theory about Crocodile and Luffy's mother. The episode also threads in cultural moments including New York Pride, a Dyke March shoutout, a Zendaya / Spider‑Man and representation debates.The hosts and guests shift into segments that mix pop culture history and hot takes: debates about mentor/mentee dynamics in Yuri on Ice, the legacy of early Marvel representation (North Star), and the emotional stakes in Invincible's William & Rick arc. Interstitial segments include “We Big Made” complaints (from grocery prices to spam from Tractor Supply Co.) and “What's Making Us Happy” notes about Beacon website work and podcast cross‑promotion (JP Morgan VP mention appears in guest plugs). The tone throughout is celebratory and argumentative in equal measure. This is a bonus episode you dont want to miss.Connect with the Snerdy Crew: Watch, Listen, or Sponsor the show: ⁠https://beacons.ai/blackandsnerdy⁠Black Geek Energy is a weekly podcast celebrating geek culture through a Black lens. Co-hosts Jared McCullough and D'Marcus discuss comics, anime, gaming, movies, television, sci-fi, fantasy, and pop culture while spotlighting creators, actors, authors, and industry professionals from across the geek community. Every episode blends thoughtful conversations, humor, games, and unapologetic fandom.Jared is a marketing professional, lifelong geek, and co-host of Black Geek Energy. His passions include comics, anime, gaming, film, and amplifying diverse voices across geek culture.D'Marcus is a technology professional and co-host of Black Geek Energy whose love of comics, gaming, science fiction, and storytelling brings thoughtful analysis and plenty of laughs to every episode.Black Geek EnergyIInstagram: @blackgeekenergyThreads: @blackgeekenergyTikTok: @blackgeekenergyYouTube: @blackgeekenergyJ'adore Dykes PRE-ORDER: Here

“There's a dinosaur horse at the Taco Bell drive-thru.”What would you do if a giraffe showed up at a Taco Bell drive-thru? This episode of The JB and Sandy Show is packed with unforgettable stories, laugh-out-loud moments, and the kind of unpredictable fun that keeps listeners coming back for more. The show kicks off with some surprising celebrity buzz before taking a wildly entertaining turn with Sandy's long-awaited and hilarious “Ode to Gracie the Giraffe.” Inspired by the now-famous runaway giraffe, Sandy paints a colorful picture of Gracie's adventures through town, delivering memorable lines and plenty of laughs along the way. One standout moment:  It's the kind of comedic gold that fans of the show won't want to miss. Later, Sandy and Tricia proudly welcomes their daughter home from camp, where she shares her tale of entering a counselor belly-flop competition. Her fearless approach—“I'm gonna send it”—led to an epic splash, a dramatic tie for first place, and a painful but glorious finish.The conversation quickly turns into a nostalgic trip through classic diving-board antics, bringing back memories and sparking plenty of laughs. The crew also opens the latest chapter of the Amazing Book of Records, searching for listeners with the most siblings. What starts as a simple call-in topic escalates into astonishing stories of massive families. One caller shares that she's one of eight children, while another leaves the hosts stunned by revealing he's one of twelve siblings—and can still recite every brother and sister in order. The conversation becomes a fascinating look at growing up in large families and the unforgettable experiences that come with it. Plus, listeners get a heartwarming update on Gracie the giraffe, whose story had everyone rooting for a happy ending. From outrageous animal adventures and camp competition glory to incredible family stories, this episode delivers nonstop entertainment, memorable quotes, and the warm, authentic chemistry that makes The JB and Sandy Show a must-listen.Don't miss it! Be sure to subscribe, leave a review, and share the episode with friends and family so they can join in on the fun. 

In this episode, Ode (@thatsod.e / @thatsod_e) and Mo "Kid" Licorish (@licorishislegit) take on a week of viral culture and personal moments: Lil Nas X's update after a three‑month rehab stay and his public discussion of a bipolar diagnosis, Beyoncé's short documentary about Jay‑Z's multiday hair‑unlocking process prompted by Blue Ivy's insecurity, and the strange Knicks‑parade saga in which JPMorgan Chase executive Angie Baez emptied and attempted to walk off with a limited‑edition orange‑and‑blue trash can. They examine the human sides of those headlines, discuss fines tied to the trash‑can stunt, and reflect on how celebrity kids and social media factor into those stories.They also remember the late producer Tay Keith and run through standout credits, reconnect over music moments like “Holiday” and “Before I Let Go,” and serve up a comedic Ode's Anime Breakdown of Rooster Fighter that lands surprising beats. The hosts close with candid frustration about job-search algorithm ads and heartfelt teacher moments, creating an episode that mixes accountability, grief, and offbeat pop‑culture fun.Connect with the Snerdy Crew:Watch, Listen, or Sponsor the show: https://beacons.ai/blackandsnerdy⁠

Send us Fan MailIntro: Taxi Cab15. Ode to Sleep14. My Blood13. Level of Concern12. Formidable11. Lane BoyExtras: Johnny Boy, Before You Start Your Day, Friend Please (from twenty one pilots)Outro: Message Man

Heading into the Fight Night in Baku, Din Thomas makes a special appearance and the boys meet up with Ode Osbourne and GiGi Canuto to talk the many eras of MMA, UFC, and TUF.First up, Ode Osbourne returns to the show with his patented humor and optimism to talk about righting ships, the excitement of new fights, niceties throughout the UFC roster, and much more. Ode may not be competing on the IFW card as he intended, but that hasn't deterred his drive and confidence.Right after Ode, TUF standout GiGi Canuto makes her first Unfiltered appearance. With her exciting performance on episode 3 of ‘The Ultimate Fighter,' Din and Matt compare their respective memories of their time on the show now that season 34 is underway. Plus, GiGi dives into her journey from Brazil to Las Vegas.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

They feast on your fear - and it's dinner time. A new Patreon Pick month continues with a pick from our Patron Red Rich Tomato: SLEEPWALKERS (1992). In a sleepy California town, a pair of outsiders blend in while concealing their sinister, supernatural identity. As one of them forms a connection with an unsuspecting girl, their hidden agenda draws dangerous attention. Also this week: The Return of Rubberface, a weiner burns his weiner, random John Mulaney Impressions, ans the next installment of Al-Bummz with Mando Diao's Ode to Ochrasy. All this--and a whole lot more--on this week's episode of NEON BRAINIACS!! "Stop looking at me! Stop looking at me, you f---ing cat!" ----- Check out our Patreon for tons of bonus content, exclusive goodies, and access to our Discord server! ----- Sleepwalkers (1992) Directed by Mick Garris Written by Stephen King Starring Brian Krause, Mädchen Amick, Alice Krige, Jim Haynie, Cindy Pickett, Ron Perlman, and Glenn Shadix ----- 00:00 - Intro & Opening Banter 35:41 - "The Shpiel" 56:12 - Film Breakdown 01:49:38 - Sump The Brainiacs & Outro

In this bonus Watch Out Now episode of Black and Snerdy, Ode (⁠@thatsod.e⁠ / ⁠@thatsod_e⁠) and Mo "Kid" Licorish (⁠@licorishislegit⁠) break down Gore Verbinski and Matthew Robinson's film Good Luck, Have Fun, Don't Die with scene‑level attention: the diner setup at Norm's, Sam Rockwell's time‑looping man from the future, and vignettes centered on teachers Janet and Mark, Ingrid's Wi‑Fi allergy, and a grief‑and‑clone subplot. The hosts map the film's major themes including sentient AI, tech addiction and VR escape, time‑loop mechanics, and the social resonance of school violence. All while noting Black Mirror echoes of the film's story.Ode and Mo trace how the movie ties each character's backstory to the team's mission, discuss casting highlights (Sam Rockwell, Haley Lou Richardson, Zazie Beetz, Michael Peña, Juno Temple), and debate narrative choices such as the clone‑with‑ads concept and the rats/plague metaphor. The episode ends with both hosts rating the film and reflections on rewatch value.Connect with the Snerdy Crew:Watch, Listen, or Sponsor the show: https://beacons.ai/blackandsnerdy⁠

Opening Quote Sport has the power to change the world. It has the power to inspire. It has the power to unite people in a way that little else does. (Nelson Mandela) Classics Recited Ode to Sport Pierre de Coubertin The Battle for the South Pole Stefan Zweig

On this episode of Black and Snerdy, Ode (@thatsod.e / @thatsod_e) and Mo "Kid" Licorish (@licorishislegit) celebrate Father's Day by ranking the most legendary Black dads in pop culture history. They are joined by guests Matt Scott (@MattScottGW) and Mari Forth (@MariTalks2Much) from the Wrestling Kickback Podcast to breakdown the legacy of icons like Uncle Phil from The Fresh Prince of Bel-Air, Carl Winslow from Family Matters, and the comedic brilliance of Michael Kyle from My Wife and Kids. They debate which fathers provided the best life lessons and which ones, like Lucius Lyon from Empire or the real-life Joe Jackson, left a more complicated mark on the culture.The group explores a wide range of archetypes, from the authoritative warmth of Mufasa in The Lion King to the relatable neighborhood energy of Ray Campbell and Floyd Henderson. They highlight specific moments of Black excellence in parenting on screen while also touching on the influence of massive stars like Beyoncé and Michael Jackson. This conversation is a deep dive into the TV characters who shaped a generation, offering a mix of nostalgia, humor, and sharp cultural analysis.Show notes and links: You can find Matt Scott @MattScottGW on InstagramYou can find Mari Forth @MariTalks2Much on Twitter and BlueskyBuy a custom tumbler from Mari: https://maricrafts2much.bigcartel.comRecap Kickback: https://recapkickback.comCrime Seen: https://crimeseenpod.comThe Pride Has Spoken: https://robhasawebsite.com/?s=the+pride+has+spokenPod Friends: https://robhasawebsite.com/shows/reality-tv-rhapups/pod-friends/

The sudden US government shutdown of Anthropic's Fable model has tech insiders reeling and rival global labs surging ahead. This episode breaks down the unexpected political power play rattling the future of AI innovation. The Fable 5 Export Controls Harm US Cyber Defense Anthropic CEO says government should block dangerous AI The Real Reason Anthropic's Models Are Offline: A Six-Year-Old Trump Grudge (21) Pete Hegseth on X: "Three months ago, @DeptofWar kicked @AnthropicAI out of our building—forever. Every passing day proves why that was the right move.

The sudden US government shutdown of Anthropic's Fable model has tech insiders reeling and rival global labs surging ahead. This episode breaks down the unexpected political power play rattling the future of AI innovation. The Fable 5 Export Controls Harm US Cyber Defense Anthropic CEO says government should block dangerous AI The Real Reason Anthropic's Models Are Offline: A Six-Year-Old Trump Grudge (21) Pete Hegseth on X: "Three months ago, @DeptofWar kicked @AnthropicAI out of our building—forever. Every passing day proves why that was the right move.

The sudden US government shutdown of Anthropic's Fable model has tech insiders reeling and rival global labs surging ahead. This episode breaks down the unexpected political power play rattling the future of AI innovation. The Fable 5 Export Controls Harm US Cyber Defense Anthropic CEO says government should block dangerous AI The Real Reason Anthropic's Models Are Offline: A Six-Year-Old Trump Grudge (21) Pete Hegseth on X: "Three months ago, @DeptofWar kicked @AnthropicAI out of our building—forever. Every passing day proves why that was the right move.

The sudden US government shutdown of Anthropic's Fable model has tech insiders reeling and rival global labs surging ahead. This episode breaks down the unexpected political power play rattling the future of AI innovation. The Fable 5 Export Controls Harm US Cyber Defense Anthropic CEO says government should block dangerous AI The Real Reason Anthropic's Models Are Offline: A Six-Year-Old Trump Grudge (21) Pete Hegseth on X: "Three months ago, @DeptofWar kicked @AnthropicAI out of our building—forever. Every passing day proves why that was the right move.

The sudden US government shutdown of Anthropic's Fable model has tech insiders reeling and rival global labs surging ahead. This episode breaks down the unexpected political power play rattling the future of AI innovation. The Fable 5 Export Controls Harm US Cyber Defense Anthropic CEO says government should block dangerous AI The Real Reason Anthropic's Models Are Offline: A Six-Year-Old Trump Grudge (21) Pete Hegseth on X: "Three months ago, @DeptofWar kicked @AnthropicAI out of our building—forever. Every passing day proves why that was the right move.

Ode to the The NY Knicks, champs again after a 53-year drought...Scuba snorkeling with Jerry during Scarlet....Sly Stone inspired Dancin' in the Streets....Blast off to the epic Sugaree era....Sugar Mag into Eyes instrumental from heaven

On this Bonus episode of Black and Snerdy, Ode (⁠@thatsod.e⁠ / ⁠@thatsod_e⁠) and Mo "Kid" Licorish (⁠@licorishislegit⁠) open in full victory mode as they recap the Knicks winning the NBA Finals and what it felt like watching the city go feral in real time. They talk packed Brooklyn bars, the post-game chaos in the streets, and how “Empire State of Mind” by Jay-Z and Alicia Keys becomes the unofficial soundtrack once the final buzzer hits. The memory lane detour includes Modell's nostalgia, a World Cup side-note, and the moment the vibe shifted when Donald Trump showed up with heavy security.From there, the birthday recap turns into a full June highlight reel: MoMA on a free Friday, a Marsha P. Johnson tribute and Pride love, and then the weekend run through brunch spots and restaurants in Bed-Stuy. Pop culture comes back around through a Beyoncé Grammys comparison, plus a Donald Glover-inspired Wu-Tang Clan name generator story that produces a hilariously mismatched rap name and a gift to match.

A quick update after quite a long pause. Lately I've been:1.⁠ ⁠Noodling with some new episodes! They might be shorter and scrappier but they'll keep taking you to more low-down places and the people who live there2.⁠ ⁠Imagining a physical version of Lowlines - a place to get low in. As I explore this - and all things related re. body, people, and place - I've been writing about it on my Substack under the title of GET LOW. Find it at: lowlines.substack.com3.⁠ ⁠Getting juiced about joining the Hub & Spoke Audio Collective! They are a collective of independent audio makers, all under the umbrella of a shared love of place and the hyperlocal. I've picked out a show from the Hub & Spoke stable that I thought might flick your switches. It's called ‘Ode to Village Life' from Rumble Strip - and I love how it captures the essence of place in the most everyday kind of ways. What makes a place feel like a place is so often made up of such ordinary elements that we might not always think about, but if removed, the whole scaffolding of that place can shift.

This Classic American Tapestry episode is a reprise of Episode 13 from August 2021. It opens with Bruce Springsteen's 2026 “Streets of Minneapolis” and then explores protest music, its global origins and examples from Beethoven's celebration of the rights of man in the 9th Symphony's “Ode to Joy” and Irish songs of rebellion then shifting focus to American protest music from “Yankee Doodle” to abolitionist songs to labor anthems to the great Civil Rights songs of mid-20th century America to anti-war songs during the Viet Nam War era down to today and songs seeking racial justice as we explore American patriotic music and the freedom of which it sings – American freedom holidays on The American Tapestry Project.

Dr. Nick Tiller is an exercise scientist at the Lundquist Institute at Harbor-UCLA, a two-decade ultrarunner, and the author of The Skeptic's Guide to Sports Science and the new The Health and Wellness Lie. In this conversation: why ultrarunning is, by Nick's cheerful admission, not actually good for you, and why we keep signing up anyway; the red flags that should trip your bullshit detector in 2026; the great protein panic and how a "health halo" turns a Pop-Tart into a recovery food; what the evidence does and very much doesn't say about AG1; KT tape, cupping, and the slippery ethics of selling someone a placebo; and how to stay skeptical without curdling into a cynic whose brain has fallen out. This episode is brought to you by LMNT,  the new Lemonade Iced Tea flavor has been quietly fixing our hydration and our 4pm coffee regrets; grab a free sample pack with any order at drinklmnt.com/UltraSignup. Featured race: the Ode to Laz Michigan Backyard Ultra, a 4.167-mile loop run every hour on the hour through 8,000 acres of Holly State Recreation Area in Holly, Michigan, on Saturday, July 18. The only way to win is to be the last runner standing, which is why the motto is "finishing last means the most." If you're backyard-curious but not ready to sign over your soul, the Oak Flats 3-hour option lets you dip in for one, two, or three loops. It's a championship-affiliated race, so the winner takes a silver ticket toward the USA national backyard team. Registration closes Thursday, July 16. Sign up at UltraSignup.com. The Trailhead is part of the UltraSignup Podcast Network.  

Want to know what kind of reader you are? TAKE OUR QUIZ: https://www.currentlyreadingpodcast.com/quiz   In this episode of Currently Reading, Kaytee and Meredith discuss their bookish moments of the week, and then tell you about three current reads each. For this week's episode, our current reads span the years from 1963 to 2026, ranging from murdery goodness to literary fiction to non-fiction about our bodies. For our Deep Dive, we discuss what it means to us to go into a book with no prior knowledge whatsoever. We'll always end with our Before We Go segment, where we shout out a Bookish Friend of the week or talk about a specific small piece of our reading lives that we want to share with you. Today, Kaytee tells us about stocking our summer TBRs, and Meredith enters "fragrance corner" but makes it bookish.   00:00 Welcome to Currently Reading 01:34 Bookish Moments of the Week 2:25 Funlenry Bath Lamp https://a.co/d/0eAYfrXE 06:38 Current Reads 06:46 Missing by E.A. Jackson (Meredith) https://bookshop.org/a/79394/9781668079805 12:28 Harriet Tubman: Live in Concert by Bob the Drag Queen (Kaytee) https://bookshop.org/a/79394/9781668061978 16:33 The Ending Writes Itself by Evelyn Clarke (Meredith) https://bookshop.org/a/79394/9780063444614 22:10 Replaceable You by Mary Roach (Kaytee) https://bookshop.org/a/79394/9781324050629 26:21 The Wall by Marlen Haushofer (Meredith) https://bookshop.org/a/79394/9780811231947 36:32 Honey Bee Mine by Sarah T. Dubb (Kaytee) https://bookshop.org/a/79394/9781668037874 40:29 Deep Dive: Going Into a Book "Blind" 53:59 Before We Go 01:04:38 Wrap-Up 1:01:25 Ode to Perfume https://www.odetoperfume.com/  #books #reading #currentlyreading #podcast #currentreads ❤️ Support Us: Become a Bookish Friend on Patreon | https://patreon.com/currentlyreadingpodcast  Grab Some Merch on Zazzle | http://www.zazzle.com/store/currentlyreading Shop Bookshop dot org | https://bookshop.org/shop/currentlyreading Bookish Friends Receive: The Indie Press List with a curated list of five books hand sold by the indie of the month. June's IPL is brought to you by one of our beloved repeat stores, Schuler Books in Grand Rapids, MI. Love and Chili Peppers with Kaytee and Rebekah - romance lovers get their due with this special episode focused entirely on the best selling genre fiction in the business All Things Murderful with Meredith and Elizabeth - special content for the scary-lovers, brought to you with the behind-the-scenes insights of an independent bookseller From the Editor's Desk with Kaytee and Bunmi Ishola - a quarterly peek behind the curtain at the publishing industry The Bookish Friends Facebook Group - where you can build community with bookish friends from around the globe as well as our hosts Connect With Us: The Show: Instagram | https://instagram.com/currentlyreadingpodcast Website | https://currentlyreadingpodcast.com/ Email | hello@currentlyreadingpodcast.com Substack | https://currentlyreadingpodcast.substack.com/ Youtube | https://www.youtube.com/@currentlyreadingpodcast Threads | https://www.threads.net/@currentlyreadingpodcast The Hosts and Regulars: Meredith | https://instagram.com/meredithmondayschwartz Kaytee | https://instagram.com/notesonbookmarks Mary | https://instagram.com/maryreadsandsips Roxanna | https://instagram.com/roxannathereader Production and Editing: Megan Phouthavong Evans | https://instagram.com/mostofmegansreads/

Ode aan dichter Lieke Marsman door huisdichter Ingmar Heytze | Na 40 jaar stopt Koert Lindijer als correspondent Afrika | Adelheid Roosen komt met voorstelling over rouw | Youp van 't Hek schreef boekje 'Vertrokken Vrienden'

Gwyn and Ode talk about magical Marie Condo-ing.

Dan and Gaardsy review the Top 5 before we get the news that legendary Twin Cities sports reporter Larry Fitzgerald, Sr has passed away. Jonny Athletic joins to continue the Ode and then continues his appearance with Wolves and NBA discussion. See omnystudio.com/listener for privacy information.