Podcasts about mccloskey

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

If you love facilitating workshops and trainings, but you know there's something more you want to say, this episode is for you.My guest is Corrin McCloskey, a healthcare executive, speaker, writer, and facilitator who has made the leap from being a fabulous facilitator into a true thought leader. Corrin joined us in Thought Leader Academy in January 2025, and in the year and a half since then, she has spoken at multiple national conferences, published writing in her field, and continued building momentum around her message: healthcare needs more human-centered, connected, and courageous leadership.This conversation is part of our Expert Trap series because Corrin's story is such a powerful example of what happens when you move beyond simply teaching helpful content and start naming what's missing in the conversation.We talk about:How Corrin shifted from facilitating strategic planning and leadership workshops to speaking on bigger stagesWhy thought leadership is less about having all the answers and more about sharing a clear perspectiveThe role of writing in expanding your ideas beyond a single talkHow to keep putting your work out there, even when it doesn't feel perfectWhat Corrin learned from both deeply affirming audience feedback and a painful experience of harassment after a speaking engagementWhy having a support system matters when you're using your voice more publiclyWhat I love about Corrin's journey is that she didn't abandon facilitation. She built on it. She took the skills she already had, added her lived experience and perspective, and stepped into a bigger conversation.That's the real invitation of thought leadership: to stop hiding behind expertise alone and start using your voice for the change you want to see.About Our Guest: Corrin McCloskey is a healthcare executive, executive coach, and national speaker focused on leadership, culture, and change management in healthcare. She serves as Vice President of Heart & Vascular and Oncology Services at Tanner Health, where she leads strategy, growth, and service line development. Passionate about helping leaders build trust and navigate complexity, Corrin frequently speaks on physician leadership, organizational culture, and leading change in healthcare. Over the past year, she has expanded her national speaking presence and contributed thought leadership focused on creating healthier, more sustainable healthcare systems.About Us: The Speaking Your Brand podcast is hosted by Carol Cox. At Speaking Your Brand, we help women entrepreneurs and professionals clarify their brand message and story, create their signature talks, and develop their thought leadership platforms. Our mission is to get more women in positions of influence and power because it's through women's stories, voices, and visibility that we challenge the status quo and change existing systems. Check out our coaching programs at https://www.speakingyourbrand.com. Links:Show notes at https://www.speakingyourbrand.com/480/ Corrin's website: https://corrinmccloskey.com/ Watch Corrin deliver her signature talk on our live show: https://www.youtube.com/live/rhDAdGR44-g?si=MulG_sPQ0-MmpLK4 Discover your Speaker Archetype by taking our free quiz at https://www.speakingyourbrand.com/quiz/Enroll in our Thought Leader Academy: https://www.speakingyourbrand.com/academy/ Connect on LinkedIn:Carol Cox = https://www.linkedin.com/in/carolcoxCorrin McCloskey (guest) = https://www.linkedin.com/in/corrinmccloskey/ Related Podcast Episodes:Episode 478: The Expert Trap: Why Great Speakers Don't Become Thought LeadersEpisode 391: Claiming Your Identity as a Speaker and Thought Leader

Rohan McCloskey refunded $350,000 in donations, gave up his salary for a year, and nearly lost everything. He's still building GoGenerosity. And he'd do it again.That kind of conviction usually comes from one of two places: delusion or proof. In Rohan's case it's the latter. One in six customers at his best-performing store donate every single time they shop. Ninety-eight percent of mystery shoppers said they were more likely to return to a brand running GoGenerosity than a competitor selling the same product. Only one merchant in his ideal customer profile has ever churned, and that was because the merchant's business hit financial difficulty, not because the product failed.Rohan is Founder and CEO of GoGenerosity, a Shopify app that turns small customer contributions at checkout into real goods delivered to charity partners. The model is cleaner than it sounds: a customer adds a $2 or $3 donation at checkout, those donations pool, and the charity receives a gift card at full retail value redeemed in-store. One hundred percent goes through. GoGenerosity charges merchants a monthly SaaS fee on top. Before all of this, Rohan ran three restaurants in Mount Maunganui through COVID, survived, and then decided to start a tech company instead.Today, we're discussing:How the GoGenerosity checkout model works in practice and why 100% of customer donations reach charity partners [05:03]The Hume mystery shopping data: 98% of shoppers were more likely to return to a brand running GoGenerosity than a direct competitor [15:26]Why one in six customers at Rohan's best-performing store donates $5 every single visit, and what two years of that data actually proves [18:07]The no-login product philosophy: why GoGenerosity deliberately has no merchant portal and sends monthly reports by email instead [28:38]Why raising capital too early nearly killed the business and what a two-year enterprise sales cycle actually costs a startup [47:35]What Rohan's psychologist told him on Christmas Day 2023 and how he kept building through a serious burnout [44:16]Connect with Rohan McCloskey | Explore GoGenerosity | Connect with Rosa Willis | Connect with Nathan BushSubscribe to the Add To Cart newsletter  SMS us to Suggest a Guest Connect with Nathan Bush Join the Add To Cart Community 

Notes and Links to Devin O'Shea's Work       Devin Thomas O'Shea is the author of The Veiled Prophet: Secret Societies, White Supremacy, and the Struggle for St. Louis, publishing with Haymarket Books on June 23, 2026. His writing is in The Nation, the Iowa Review, Slate, LA Review of Books, Boulevard, and elsewhere.    Buy The Veiled Prophet   Devin Thomas O'Shea's Website   Review and Informative Article for The Veiled Society in St. Louis Magazine     At about 1:45, Devin details book tour information and ordering information for his book, The Veiled Prophet At about 2:50, Devin talks about the truth and fiction that goes with the book At about 3:30, Devin describes his work with QAnon-related podcasts and reporting At about 5:10, Jim Caviezel (!!!) Talk At about 6:15, Devin and Pete reflect on the state of QAnon in 2026 and the American public's viewpoint  At about 13:30, Pete makes connections between the Veiled Prophets and history “rhyming” At about 18:20, The two discuss famous people from St. Louis and the McCloskey's   At about 21:40, Devin responds to Pete's asking about seeds for the book At about 24:10, The two discuss the high-level capitalists, policymakers, and "landed gentry”-Devin discusses the key years of the 1870s and beginnings of the Veiled Prophet Society At about 27:15,  At about 29:45, Pete notes the Orientalism associated with the symbology of the Veiled Prophet, and Devin expands on the early Prophet At about 32:10, The two reflect on class solidarity and racism and the “aggrieved white male” in early and modern times, with connections to the Veiled Prophet Society  At about 35:00, Devin details Alonzo Slayback, a founder of the Society, and early philosophy and symbology and capitalistic views At about 36:55, Devin responds to Pete's musings about American political parties and past and present ideas of progressivism  At about 38:10, Devin traces some early leadership in the Society and the ways in which “Mardi Gras-centric” clubs evolved/devolved   At about 41:35, Devin expands upon the idea put forth in the book, adapted from Edward Said, of Orientalism as “projected feelings into an Aladdin…framework” At about 42:55, Devin talks about Alonzo Slayback's killing At about 45:45, The two reflect on the importance of the 1904 World Fair in Saint Louis, and the fact that 11/12 board members were part of the Veiled Prophet Society At about 49:30, Mary Smith and her controversy regarding her marriage is discussed At about 51:00, Patriarchy and connections to the Society are discussed At about 52:00, The commodification of the history of the Society and Societal connections to the Manhattan Project At about 54:30, Devin responds to Pete asking about Clark Clifford and Harry Truman and connections to local and federal governments At about 56:50, Devin reflects on the life and legacy of Thomas Dooley At about 58:50, Monsanto and other St. Louis connections and Black communities' protests, including ACTION, are discussed At about 1:02:40, The famed 1972 unmasking of the Veiled Prophet is discussed At about 1:04:00, Devin talks about going to the VP Fair as a kid At about 1:04:40, The two discuss the book's ending and St. Louis “potential”      You can now subscribe to the podcast on Apple Podcasts, and leave me a five-star review. You can also ask for the podcast by name using Alexa, and find the pod on Stitcher, Spotify, and on Amazon Music. Follow Pete on IG, where he is @chillsatwillpodcast, or on Twitter, where he is @chillsatwillpo1. You can watch other episodes on YouTube-watch and subscribe to The Chills at Will Podcast Channel. Please subscribe to both the YouTube Channel and the podcast while you're checking out this episode.       Pete is very excited to have one or two podcast episodes per month featured on the website of Chicago Review of Books. The audio will be posted, along with a written interview culled from the audio. His conversation with Jeff Pearlman, a recent guest, is up now at Chicago Review.     Sign up now for The Chills at Will Podcast Patreon: it can be found at patreon.com/chillsatwillpodcastpeterriehl      Check out the page that describes the benefits of a Patreon membership, including cool swag and bonus episodes. Thanks in advance for supporting Pete's one-man show, DIY podcast and extensive reading, research, editing, and promoting to keep this independent podcast pumping out high-quality content!    This month's Patreon bonus episode is the trailer episode for Pete's limited podcast series, Rage is a Gift: Evil Empire at 30. Pete reflects on the Importance (and the power of this capital "I") of Rage Against the Machine and their seminal Evil Empire album, which is celebrating 30 years of resistance. The limited podcast series will do a deep exploration of, and reflection on, the lyrics and context of each of the 12 powerful songs on the album.     Pete has added a $1 a month tier for “Well-Wishers” and Cheerleaders of the Show.    The intro song for The Chills at Will Podcast is “Wind Down” (Instrumental Version), and the other song played on this episode was “Hoops” (Instrumental)” by Matt Weidauer, and both songs are used through ArchesAudio.com.     Please tune in for Episode 346 with Julie Buntin, whose debut, Marlena, was a finalist for the National Book Critics Circle's John Leonard Prize and longlisted for the Center for Fiction's First Novel Prize. The novel was released in ten territories worldwide and named a best book of the year by over a dozen outlets, including The Washington Post, NPR, and Kirkus Reviews.     The episode airs on July 14, Pub Day for her novel, Famous Men. This book is so, so good.     Please go to ceasefiretoday.org, and/or https://act.uscpr.org/a/letaidin to call your congresspeople and demand an end to the forced famine and destruction of Gaza and the Gazan people.    You can also donate at chuffed.org, World Central Kitchen, and so many more, and/or you can contact writer friend Ursula Villarreal-Moura directly or through Pete, as she has direct links with friends in Gaza.

Send us Fan MailIn this week's episode of the Digital and Dirt podcast, Ian sits down with Maureen McCloskey Geraghty to discuss the evolution of out-of-home advertising, the mindset required to build a lasting career in media, and how leadership, hustle, and adaptability continue to shape the future of the industry.

Deirdre McCloskey, premiada por el Juan de Mariana, sostiene que el despegue de Europa se explica por el triunfo de las ideas de libertad. ¿Por qué Europa? Es la gran pregunta de la historia económica. En el año 1000, China y el mundo árabe aventajaban ampliamente a un continente fragmentado y relativamente atrasado. Sin embargo, fue Europa la que en los siglos siguientes protagonizó el mayor salto en prosperidad que ha conocido la humanidad. Esta semana, en Economía para Quedarte sin Amigos, nos adentramos en la obra de Deirdre McCloskey, ganadora del Premio Juan de Mariana, para explorar su respuesta a esa pregunta junto con el subdirector del Juan de Mariana, Juan Navarrete, y el profesor de la Universidad Francisco Marroquín, Eduardo Fernández Luiña. La respuesta que da McCloskey no es la geografía, ni los recursos naturales, ni siquiera las instituciones: fueron las ideas.Música Esta semana, la protagonista de nuestra selección musical es el grupo español Nosoträsh. Y estos son los temas que hemos escuchado: "Dando Vueltas" "Voy a Aterrizar" "Completamente Sola" "Arte"

Ireland's player of the 2026 Men's Six Nations Stuart McCloskey hosts Ben Youngs and Dan Cole in his favourite Belfast pub for a deep dive into the Ireland rugby team. We get the lowdown on the world-class players in Andy Farrell's squad, the influence of Johnny Sexton & Paul O'Connell and the brewing rivalry with South Africa's Springboks.

durée : 00:27:51 - Entendez-vous l'éco ? - par : Aliette Hovine - Voix singulière de la pensée libertarienne contemporaine, Deirdre McCloskey a développé une réflexion sur le langage de la science économique. En la définissant comme rhétorique, elle en interroge la scientificité. - réalisation : Tina Iung, Sorj Leroy - invités : François Facchini Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

durée : 00:58:58 - Entendez-vous l'éco ? - par : Aliette Hovine - La loi de programmation militaire 2024-2030 doit doter le budget de la Défense de 36 milliards d'euros supplémentaires. Pourquoi ? La défense peut-elle réindustrialiser la France ? Après avoir répondu à ces questions, place au portrait d'une économiste iconoclaste, Deirdre McCloskey. - réalisation : Tina Iung, Sorj Leroy, Louise Morfouace - invités : Élie Tenenbaum Directeur du Centre des Études de Sécurité de l'IFRI, Fanny Coulomb Maîtresse de conférences HDR en économie à Sciences Po Grenoble., François Facchini Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

Pool Pros text questions hereMyth, Memory, and the Real Story Behind the WaterA Conversation with Eric Herman | Talking Pools PodcastSome voices in an industry don't simply report the story — they shape how the story is told.In this episode of Talking Pools, host Natalie Hood, Director of Education and Network Development for The Grit Game, sits down with one of the most influential storytellers the aquatic industry has ever produced: Eric Herman, Vice President of Communications for Watershape University and longtime editor of the legendary publication WaterShapes Magazine.For more than four decades, Herman has documented the evolution of pools, fountains, spas, and aquatic design — not merely as a trade reporter, but as a historian of water itself. His work spans the early days of modern pool construction journalism at Pool & Spa News, the groundbreaking launch of WaterShapes Magazine in 1999, and today's digital continuation of that legacy through watershapes.com, a library containing more than 5,000 articles chronicling the craft, science, and culture of water.But this episode isn't just about history.It's about myths — the assumptions, half-truths, and inherited wisdom that circulate through the pool industry and public perception alike.And in a conversation that moves effortlessly between science, storytelling, and cultural memory, Herman and Hood begin dismantling some of the most persistent myths surrounding swimming pools, safety, and water chemistry.A Journalist in the Deep EndEric Herman's journey into the aquatic world began not with pools, but with curiosity.His first published article in 1986 — for Orange Coast Magazine — examined the emerging microbrewery industry. Within three years, that curiosity would lead him to an interview in Los Angeles with pool industry pioneer Jim McCloskey, then editor of Pool & Spa News.The result was a career that has now stretched 40 years.At Pool & Spa News, Herman covered everything from service techniques and plaster science to drowning prevention — topics that would later shape the direction of aquatic education and professional training across the industry.When Herman and McCloskey launched WaterShapes Magazine in 1999, they intentionally broadened the conversation beyond swimming pools.The publication examined water as a design medium.Pools, fountains, ponds, streams, water parks, hot springs, landscape architecture, and hydrological design all found a home in its pages.The result was a publication that changed how aquatic professionals thought about their craft.Today, that legacy continues through the digital platform watershapes.com, publishing twice monthly and maintaining one of the most comprehensive archives of aquatic design knowledge anywhere in the world.Myth Busting BeginsHood frames the conversation around a theme she frequently explores on the show: myths in aquatics.But Herman begins by reframing the idea of myth itself.Traditionally, he explains, myths weren't falsehoods. They were symbolic stories meant to communicate deeper truths. The modern use of the word — describing something widely believed but factually incorrect — is almost the opposite.Wit Support the showThank you so much for listening! You can find us on social media:FacebookInstagramTik TokEmail us: talkingpools@gmail.com

Weather, brackets, St Patrick's day, pets helping health and Allen McCloskey in Guinness world record bookSee omnystudio.com/listener for privacy information.

FC Cincinnati fans hear him every matchday breaking down the tactics on ESPN 1530 — now broadcast analyst Kevin McCloskey joins the Flyin Lion Podcast. Kevin talks about his journey through the game as a player, coach, and executive before stepping into the booth with Tommy Gelehrter, shares stories from the early USL days of FC Cincinnati, and explains what preparation looks like before every broadcast. We also dive into the current state of FCC, the most important offseason move, what it will take to win a trophy this season, and Kevin's perspective on the future of MLS, plus some rapid-fire questions to close it out. If you love FC Cincinnati and behind-the-scenes insight from the broadcast booth, this episode is for you.

Welcome to Thursday's Rugby Daily, with Cameron Hill.Coming up, the Ireland team is named for tomorrow's game against Wales - and head coach Andy Farrell addresses rumours linking him to a role with Saracens.Gerry Thornley muses on the idea of Stuart McCloskey slotting into an Ireland back row, if required,And Mike Phillips reveals that he'd love to help Welsh rugby out of its current mess - but the WRU haven't contacted him in almost a decade.Rugby on Off The Ball with Bank of Ireland | #NeverStopCompeting

Welcome to Saturday's Rugby Daily, with Dara Smith-Naughton, LIVE from London!In tonight's pod, all the Irish reaction from Twickenham.Andy Farrell & Caelan Doris sum up a historic day for Irish rugby in London.Match heroes Stuart McCloskey & Tommy O'Brien give their immediate post-match thoughts.And England head coach, Steve Borthwick, faces the heat post-match.Rugby on Off The Ball with Bank of Ireland | #NeverStopCompeting

David McCloskey says he was once a clandestine journalist. Another way of putting it is that he once worked for the CIA.McCloskey is now a spy novelist. His first book took readers inside the CIA, now he is exploring Mossad, Israel and Iran in his new novel The Persian.On Free State, he talks about the shadow war between Israel and Iran.He explains what has happened to agencies like the CIA under Trump and why as more true Trump believers are appointed, the demand is not for truthful intelligence. They do not just believe what they see, they only see what they believe. Hosted on Acast. See acast.com/privacy for more information.

One week until meaningful soccer and the launch of a promising FC Cincinnati season! We enter Year 11 the same way as last season, with the Orange & Blue leaving the country for CONCACAF Champions Cup coverage. Soon enough, the MLS season also starts with designated players Evander, Miles Robinson, and Kevin Denkey leading a talented roster. But what are we really looking at? How promising and hopeful are we that this roster can use consistency and build from last season's hard work? We ask the FC Cincinnati radio broadcast team, Tommy G. and Kevin McCloskey, what they think about this roster and the long road ahead. (And perhaps a bit about the big tournament this summer!) Tune in and trade threads with us! #MLS #FCCincinnati #soccer Become a Patron! Subscribe to Cincinnati Soccer Talk Don't forget you can now download and subscribe to Cincinnati Soccer Talk on iTunes today! The podcast can also be found on Stitcher Smart Radio now. We're also available in the Google Play Store and NOW ON SPOTIFY! As always we'd love your feedback about our podcast! You can email the show at feedback@cincinnatisoccertalk.com. We'd love for you to join us on our Facebook page as well! Like us at Facebook.com/CincinnatiSoccerTalk.

Former CIA analyst and bestselling spy novelist David McCloskey returns to Spymasters to talk to Antonia Senior about his new thriller The Persian — a razor-sharp spy story set inside the Israel–Iran shadow war. We discuss how real-world covert operations (from sabotage to targeted assassinations) have shaped modern espionage, and how spy fiction can capture the human cost of clandestine conflict: fear, tradecraft, loyalty, identity, and moral compromise. McCloskey breaks down how he researches intelligence operations using open-source reporting and conversations with former practitioners — and why he chose to write a spy novel with no Americans at the center of the story. We also explore the culture and risk tolerance differences between intelligence services, the evolution of surveillance and remote warfare, and the perennial question: should writers “stay in their lane,” or is imagining other lives the whole point of fiction? What the Israel–Iran covert conflict looks like — and why it's perfect terrain for a spy novel The premise of The Persian: a Persian Jewish dentist recruited as a Mossad asset Researching espionage through open-source intelligence (OSINT), reporting, and real tradecraft insight Mossad vs CIA: risk tolerance, bureaucracy, operational style, and culture Remote and tech-enabled killing — drones, distance, and the changing nature of modern war Writing morally complex characters (and why the book isn't a “morality play”) Representation in fiction: writing characters outside your own experience A teaser for McCloskey's next novel: CIA and MI6 under strain — and spying on each other again David McCloskey is a former CIA analyst and the author of multiple acclaimed spy novels including Damascus Station, Moscow X, and The Seventh Floor. His work is known for its operational authenticity and insider-level realism — without losing sight of the human story. The Persian is out now (publication-day episode). Available wherever you buy books, or here: https://amzn.eu/d/5DzqbwC If you enjoy deep-dive conversations on espionage, intelligence history, covert action, tradecraft, and spy fiction, hit Follow on Spotify, or wherever you get your podcasts and leave a rating — it helps more listeners find the show. Learn more about your ad choices. Visit podcastchoices.com/adchoices

On this riveting episode of the Spybrary Spy podcast, British political journalist Tim Shipman is once again in conversation with David McCloskey, a former CIA analyst turned novelist, discussing his fourth and most ambitious book yet, The Persian. Departing from his CIA-rooted earlier work, McCloskey dives into the morally murky waters of the Israeli-Iranian shadow war. The novel, a high-stakes standalone thriller, follows a Mossad operation and an Iranian-born dentist-turned-reluctant-spy. They discuss the challenges of writing beyond American intelligence, the process of accessing former Mossad officers for research, the rich culture and contradictions of Iran, and the psychological complexity of agent-handler relationships. The episode also teases McCloskey's next book, the return of Artemis Proctor, and exciting developments for screen adaptations. So what is The Persian by David McCloskey all about, Shane? Kamran Esfahani, a dentist living out a dreary existence in Stockholm, agrees to spy for the Mossad after he's recruited by Arik Glitzman, the chief of a clandestine unit tasked with running targeted assassinations and sabotage inside Iran. At Glitzman's direction, Kam returns to his native Tehran and opens a dental practice there, using it as a cover for the Israeli intelligence agency. Kam proves to be a skillful asset, quietly earning money helping Glitzman smuggle weapons, run surveillance, and conduct kidnappings. But when Kam tries to recruit an Iranian widow seeking to avenge the death of her husband at the hands of the Mossad, the operation goes terribly wrong, landing him in prison under the watchful eye of a sadistic officer whom he knows only as the "General." And now, after enduring three years of torture in captivity, Kamran Esfahani sits in an interrogation room across from the General, preparing to write his final confession. Kam knows it is too late to save himself. But he has managed to keep one secret—only one—and he just might be able to save that. In this haunting thriller, careening between Tehran and Tel Aviv, Istanbul and Stockholm, David McCloskey delivers an intricate story of vengeance, deceit, and the power of love and forgiveness in a world of lies.   Praise for The Persian: [The Persian] builds to high drama and twists with characters you care about.… Deep and satisfying... keeps the McCloskey traits of great tradecraft and headlong dash to the end. It proves he is a great spy writer. Tim Shipman, Spybrary and The Specator It is no spoiler to say that what David McCloskey has given us in The Persian is a tragedy—a work of spy fiction that, stripped of its technological trappings, would not have been out of place on the Athenian stage. Stephen England, Author The Persian is a novel written by someone who understands not just how espionage works, but how it feels, the waiting, the second-guessing, and the quiet moments where people realise what they've traded away to stay in the game. I applaud David for writing a standalone novel rather than the familiar waters of his Artemis Proctor series. Shane Whaley Editor-In-Chief, Spybrary.com  

We're back with Mutual Presents and more misadventures with Adventures with Maisie double-feature who brings in our summer with "Nancy Hummerschlager's Vacation" and "Spike 'Romeo' McCloskey and The Milk Fund"! Learn more about your ad choices. Visit megaphone.fm/adchoices

Is David McCloskey the best spy writer of our generation?In this episode of No Limits: The Thriller Podcast, we deliver a FULL SPOILER review of The Persian by David McCloskey — breaking down the plot, characters, themes, and real-world intelligence tradecraft behind one of today's most talked-about espionage novels.Drawing on McCloskey's CIA background, The Persian pushes modern spy fiction toward deeper realism and moral complexity. We analyze how it compares to classic and contemporary masters of the genre and debate whether McCloskey belongs at the very top of modern espionage writing.⚠️ SPOILER WARNING: This episode contains complete plot spoilers for The Persian.---

We're back with Mutual Presents and more misadventures with Adventures with Maisie double-feature who brings in our summer with "Nancy Hummerschlager's Vacation" and "Spike 'Romeo' McCloskey and The Milk Fund"! Learn more about your ad choices. Visit megaphone.fm/adchoices

Welcome to Friday's Rugby Daily, I'm Cameron Hill. Coming up, the team news from the Irish provinces for this weekend's European action.Could a number of Ulster centres force their way into the Ireland squad for the Six Nations?And I'll set your rugby calendar for the coming weekend...Rugby on Off The Ball with Bank of Ireland | #NeverStopCompeting

Today Jay is joined by Utah Outliers general manager and assistant coach, Kevin McCloskey. The two discuss midseason surprises with the Utah Mammoth, unexpected MVPs, power-play woes, goaltending, and what to expect for the rest of the season for the Utah Mammoth. Then they get into the beautiful building that the Utah Outliers are playing in at Black Rock Mountain Resort

Deirdre McCloskey argues the world's jump from $2 to $50 per day in average income came from a radical 18th-century shift: equality of permission, or letting ordinary people have a go at bettering themselves. She traces how liberating human creativity through what she calls the "bourgeois deal" sparked innovation from Holland to Scotland to America, while state control stifled it elsewhere. McCloskey critiques modern economics for reducing humans to "vending machines" and argues we need "humanomics" that recognizes love, ethics, and human complexity alongside mathematical models. She challenges the field's statist turn, defends Adam Smith's complete vision beyond self-interest, and explains why India may become the next great creative economy while Europe's trillion-dollar spending plans repeat the old mistake of top-down investment instead of unleashing individual creativity.

In this riveting episode of #All2ReelToo, we explore the haunting dystopian Showtime film Harrison Bergeron (1995), set in a future where enforced #egalitarianism has created a seemingly perfect society of absolute equality. But at what cost? The sacrifice of everything that makes humanity exceptional. Featuring an outstanding cast—including Sean Astin as Harrison Bergeron, Miranda de Pencier as Phillipa, Eugene Levy as President McCloskey, Mairlyn Smith as Janet McCloskey, Howie Mandel as Charlie (of Chat with Charlie), Andrea Martin as Diana Moon Glampers, Christopher Plummer as John Klaxon, and Nigel Bennett as Dr. Eisenstock—this film poses one crucial question: Is peace truly worth the price of our humanity? Don't miss this thought-provoking journey into a chilling vision of the future. #HarrisonBergeron #DystopianFilm #Showtime #ThoughtProvoking #PodcastShow #All2ReelToo Listen now: all2reeltoo.com Support the show: https://www.patreon.com/c/cullenpark/membership https://www.teepublic.com/user/cullenpark Catch our captivating chats on: A review of Superman (2025) on Spoiler Alert! with Ryan Moore at https://www.youtube.com/watch?v=HzXIIp_ifA0&t=81s Movie Smash Podcast discussing #GhostWorld (2001): https://www.movie-smash.com/episodes/episode/32534003/episode-18-ghost-world-2001-special-guest-michael-e-cullen-ii-from-the-all2reeltoo-podcast Film Talk with Jordan Ramirez, chatting about #Once (2007): https://youtu.be/fubJGxZ3NSU?si=ptSlTewm72LTVspQ Spoiler Alert with Ryan Moore and Matt discussing #MadameWeb: https://www.youtube.com/watch?v=vRXjJGtzdlU Spoiler Alert with Ryan Moore discussing #CaptainAmericaBraveNewWorld : https://www.youtube.com/watch?v=JHvsYPsvLBM&t=1471s The Family Fright Night Horror Podcast: https://open.spotify.com/episode/7kstbpDOnLQeI8BQGLzina Enjoy eerie tunes by host Matthew Haase - https://www.youtube.com/@LimitlessMatt Support us on Patreon - https://www.patreon.com/CullenPark, shop our spooktacular merch - http://tee.pub/lic/CullenPark, and catch Mike on The Nerdball Podcast - https://pod.fo/e/ba2aa Help fund our friend Mark Klein's funeral: https://www.gofundme.com/f/honoring-mark-kleins-legacy Make a difference with these organizations: Palestine Children's Relief Fund: https://www.pcrf.net/information-you-should-know/how-to-help-palestine.html The Hi, How Are You Project : https://www.hihowareyou.org/ Trans Lifeline: https://translifeline.org/ The Hotline: https://www.thehotline.org/ Matthew Perry Foundation: https://matthewperryfoundation.org/ The Trevor Project: https://www.thetrevorproject.org/ HRC Foundation: https://www.hrc.org/hrc-story/hrc-foundation Point Foundation: https://pointfoundation.org/ Direct Relief: https://www.directrelief.org/ NAACP Legal Defense Fund: https://www.naacpldf.org/ Black Voters Matter Fund: https://www.blackvotersmatterfund.org Tahirih Justice Center: https://www.tahirih.org/ Mona Foundation: https://www.monafoundation.org/ Learn more about your ad choices. Visit megaphone.fm/adchoices

Send us a textWe trace how Adam Smith solves a historical puzzle: why Europe's path to prosperity inverted the “natural order,” and how commerce quietly dissolved feudal power to make room for liberty. The story follows incentives, from primogeniture and entail to charters, free towns, and the market's “silent and insensible” revolution.• institutions as congealed preferences and elite incentives• why Smith's natural order inverts in Europe• the physiocrats' growth model and Smith's critique• Solow's technology vs North's institutions vs McCloskey's ideas• feudal constraints primogeniture and entail suppressing agriculture• towns as islands of order through charters and fixed rents• the king–burgher alliance against barons• merchants as improvers of land and capital risk-takers• commerce introducing liberty and good government• Smith's “most important” passage and its modern relevanceIf you have questions or comments, or want to suggest a future topic, email the show at taitc.email@gmail.com ! You can follow Mike Munger on Twitter at @mungowitz

David McCloskey keeps writing spy thrillers – and the plots keep coming true. In the opening of his latest novel The Persian, Israel has just launched a surprise attack on Iran. But the author says he had already finished writing by the time conflict broke out between the two nations earlier this year. In today's episode, McCloskey speaks with NPR's Mary Louise Kelly about working at the intersection of reality and fiction, and having his work reviewed by the CIA.To listen to Book of the Day sponsor-free and support NPR's book coverage, sign up for Book of the Day+ at plus.npr.org/bookofthedayLearn more about sponsor message choices: podcastchoices.com/adchoicesNPR Privacy Policy

Let us know how you enjoyed this episode!Taking time away from your family isn't selfish—it's essential.In this episode, I'm joined by Jillian McCloskey, founder of Momcations, to talk about why moms need intentional time away and how these trips can completely transform your patience, your marriage, and your sense of self.We discuss:What a “momcation” really is and why it's different from just staying home for a breakWhy stepping away allows your partner to step up and builds their confidence tooHow kids benefit when moms take time away (spoiler: it often creates the sweetest core memories)Practical tips for overcoming mom guilt and starting small if leaving feels impossibleIf you've been waiting for the “perfect time” to take a break, this conversation will remind you why that time is now. Because when you return home recharged, everyone wins.Connect with Jillian:Website: www.momcations.coIG: @momcations.coThanks for listening!Connect and send a message letting me know what you took away from this episode: @michellepurtacoaching and follow me on threads @michellepurtacoaching!If you would like to support this show, please rate and review the show, and share it with people you know would love this show too!Additional Resources:Ready to put a stop to the arguments in your marriage?  Watch this free masterclass - The #1 Conversation Married Couples Need To Have (But Aren't)Want to handle conflict with more confidence? Download this free workbook!Wanna make communication feel easy and stop feeling like roommates so you can bring back the romance and excitement into your marriage? Learn more about how coaching here!

Lyssa Rome is a speech-language pathologist in the San Francisco Bay Area. She is on staff at the Aphasia Center of California, where she facilitates groups for people with aphasia and their care partners. She owns an LPAA-focused private practice and specializes in working with people with neurogenic communication disorders. She has worked in acute hospital, skilled nursing, and continuum of care settings. Prior to becoming an SLP, Lyssa was a public radio journalist, editor, and podcast producer. In this episode, Lyssa Rome interviews Liz Hoover about group treatment for aphasia.   Guest info Dr. Liz Hoover is a clinical professor of speech language and hearing sciences and the clinical director of the Aphasia Resource Center at Boston University. She holds board certification from the Academy of Neurologic Communication Disorders and Sciences, or ANCDS, and is an ASHA fellow. She was selected as a 2024 Tavistock Trust for Aphasia Distinguished Scholar, USA and Canada. Liz was a founding member of Aphasia Access and served on the board for several years. She has 30 years of experience working with people with aphasia and other communication disorders across the continuum of care. She's contributed to numerous presentations and publications, and most of her work focuses on the effectiveness of group treatment for individuals with aphasia.   Listener Take-aways In today's episode you will: Describe the evidence supporting aphasia conversation groups as an effective interventions for linguistic and psychosocial outcomes. Differentiate the potential benefits of dyads versus larger groups in relation to client goals. Identify how aphasia severity and group composition can influence treatment outcomes.   Edited transcript Lyssa Rome Welcome to the Aphasia Access Aphasia Conversations Podcast. I'm Lyssa Rome. I'm a speech language pathologist on staff at the Aphasia Center of California and I see clients with aphasia and other neurogenic communication disorders in my LPAA-focused private practice. I'm also a member of the Aphasia Access Podcast Working Group. Aphasia Access strives to provide members with information, inspiration and ideas that support their aphasia care through a variety of educational materials and resources.   I'm today's host for an episode that will feature Dr. Elizabeth Hoover, who was selected as a 2024 Tavistock Trust for Aphasia Distinguished Scholar, USA and Canada.   Liz Hoover is a clinical professor of speech language and hearing sciences and the clinical director of the Aphasia Resource Center at Boston University. She holds board certification from the Academy of Neurologic Communication Disorders and Sciences, or ANCDS, and is an ASHA fellow. Liz was a founding member of Aphasia Access and served on the board for several years. She has 30 years of experience working with people with aphasia and other communication disorders across the continuum of care. She's contributed to numerous presentations and publications, and most of her work focuses on the effectiveness of group treatment for individuals with aphasia. Liz, welcome back to the podcast.   So in 2017 you spoke with Ellen Bernstein Ellis about intensive comprehensive aphasia programs or ICAPs and inter professional practice at the Aphasia Resource Center at BU and treatment for verb production using VNest, among other topics. So this time, I thought we could focus on some of your recent research with Gayle DeDe and others on conversation group treatment.   Liz Hoover Sounds good.   Lyssa Rome All right, so my first question is how you became interested in studying group treatment?   Liz Hoover Yeah, I actually have Dr. Jan Avent to thank for my interest in groups. She was my aphasia professor when I was a graduate student doing my masters at Cal State East Bay. As you know, Cal State East Bay is home to the Aphasia Treatment Program. When I was there, it preceded ATP. But I was involved in her cooperative group treatment study, and as a graduate student, I was allowed to facilitate some of her groups in this study, and I was involved in the moderate-to-severe group. She was also incredibly generous at sharing that very early body of work for socially oriented group treatments and exposing us to the work of John Lyons and Audrey Holland. Jan also invited us to go to a conference on group treatment that was run by the Life Link group. It's out of Texas Woman's University, Delaina Walker-Batson and Jean Ford. And it just was a life changing and pivotal experience for me in recognizing how group treatment could not be just an adjunct to individual goals, but actually be the type of treatment that is beneficial for folks with aphasia. So it's been a love my entire career.   Lyssa Rome And now I know you've been studying group treatment in this randomized control trial. This was a collaborative research project, so I'm hoping you can tell us a little bit more about that project. What were your research questions? Tell us a little bit more.   Liz Hoover Yeah, so thank you. I'll just start by acknowledging that the work is funded by two NIDCD grants, and to acknowledge their generosity, and then also acknowledge Dr. Gayle DeDe, who is currently at Temple University. She is a co- main PI in this work, and of course it wouldn't have happened without her. So you know, Gayle and I have known each other for many, many years. She's a former student, doctoral student at Boston University, and by way of background, she and I were interested in working together and interested in trying to build on some evidence for group treatment. I think we drank the Kool Aid early on, as you might say.   And you know, just looking at the literature, there have been two trials on the evidence for this kind of work. And so those of us who are involved in groups, know that it's helpful for people with aphasia, our clients tell us how much they enjoy it, and they vote with their feet, right? In that they come back for more treatments. And aphasia centers have grown dramatically in the last couple of decades in the United States.   So clearly we know they work, but what we don't know is why they work. What are those essential ingredients, and how is that driving the change that we think we see? And from a personal perspective, that's important for me to understand and for us to have explained in the literature, because until we can justify it in the scientific terms, I worry it will forever be a private-pay adjunct that is only accessible to people who can pay for it, or who are lucky enough to be close enough to a center that can get them access—virtual groups aside, and the advent of that—but it's important that I think this intervention is validated to the scientific community in our field.   So we designed this trial. It's a randomized control trial to help build the research evidence for conversation, group treatment, and to also look at the critical components. This was inspired by a paper actually from Nina Simmons Mackie in 2014 and Linda Worrell. They looked at group treatment and showed that there were at least eight first-tier elements that changed the variability or on which we might modify group conversation treatment. And so, you know, if we're all doing things differently, how can we predict the change, and how can we expect outcomes?   Lyssa Rome So I was hoping you could describe this randomized, controlled trial. You know, it was collaborative, and I'm curious about what you and your collaborators had as your research questions.   Liz Hoover So our primary aims of the study were to understand if communication or conversation treatment is associated with changes in measures of communicative ability and psychosocial measures. So that's a general effectiveness question. And then to look in more deeply to see if the group size or the group composition or even the individual profile of the client with aphasia influences the expected outcome.   Because if you think about group treatment, the size of the group is not an insignificant issue, right? So a small group environment of two people has much more… it still gives you some peer support from the other individual with aphasia, but you have many opportunities for conversational turns and linguistic and communication practice and to drive the saliency of the conversation in a direction that's meaningful and useful and informative.   Whereas in a large group environment of say, six to eight people with aphasia and two clinicians, you might see much more influence in the needed social support and vicarious learning and shared lived experience and so forth, and still have some opportunity for communication and linguistic practice. So there's conflicting hypotheses there about which group environment might be better for one individual over another.   And then there's the question of, well, who's in that group with you? Does that matter? Some of the literature says that if you have somebody with a different profile of aphasia, it can set up a therapeutic benefit of the helper experience, where you can gain purpose by enabling and supporting and being a facilitator of somebody else with aphasia.   But if you're in a group environment where your peers have similar conversation goals as you, maybe your practice turns, and your ability to learn vicariously from their conversation turns is greater. So again, two conflicting theories here about what might be best. So we decided to try and manipulate these group environments and measure outcomes on several different communication measures. We selected measures that were linguistic, functional, and psychosocial.   We collected data over four years. The first two years, we enrolled people with all different kinds of profiles of aphasia. The only inclusion criteria from a communication perspective, as you needed some ability to comprehend at a sentence level, so that you could process what was being said by the other people in the group. And in year one, the treatment was at Boston University and Temple University, which is where Gayle's aphasia center is housed. In year two, we added a community site at the Adler Aphasia Center and Maywood, New Jersey, so we had three sites going.   The treatment conditions were dyad, large group, and then a no treatment group. So this group was tested at the same time, didn't get any other intervention, and then we gave them group treatment once the testing cycle was over. So we call that a historical control or a delayed-treatment control group. And then in years three and four, we aim to enroll people who had homogeneous profiles.   So the first through the third cycle was people with moderate to severe profiles. And then in the final, fourth cycle, it was people with mild profiles with aphasia. This allowed us to collect enough data in enough size to be able to look at overall effectiveness and then effects of heterogeneity or homogeneity in the group, and the influence of the profile of aphasia, as well as the group size.   And across the four years, we aim to enroll 216 participants, and 193 completed the study. So it's the largest of its kind for this particular kind of group treatment that we know of anyway. So this data set has allowed us to look at overall efficacy of conversation group treatment, and then also take a look at a couple of those critical ingredients. Does the size of the group make a difference? And does the composition of your group make a difference?   Lyssa Rome And what did you find?   Liz Hoover Well, we're not quite done with all of our analysis yet, but we found overall that there's a significant treatment effect for just the treatment conditions, not the control group. So whether you were in the dyad or whether you were in a large treatment group, you got better on some of the outcome measures we selected. And the control group not only didn't but on a couple of those measures, their performance actually declined. And so showing significantly that there's a treatment effect. Did you have a question?   Lyssa Rome Yeah, I wanted to interrupt and ask, what were the outcome measures? What outcome measures were you looking at?   Liz Hoover Yeah. So we had about 14 measures in total that aligned with the core outcome set that was established by the ROMA group. So we had as our linguistic measure the Comprehensive Aphasia Test. We had a primary outcome measure, which was a patient reported measure of functional communication, which is the ACOM by Will Hula and colleagues, the Aphasia Communication Outcome measure, we had Audrey Holland and colleagues' objective functional measure, the CADL, and then a series of other psychosocial and patient reported outcome measures, so the wall question from the ALA, the Moss Social Scale, the Communication Confidence Rating Scale in Aphasia by Leora Cherney and Edie Babbitt.   Lyssa Rome Thank you. When I interrupted you to ask about outcome measures. You were telling us about some of the findings so far.   Liz Hoover Yeah, so our primary outcome measures showed significant changes in language for both the treatment conditions and a slightly larger effect for the large group. And then we saw, at a more micro level, the results pointing to a complex interaction, actually, between the group size and the treatment outcome. So we saw changes on more linguistic measures. like the repetition sub scores of the CAT and verb naming from another naming subtest for the dyad group, whereas bigger, more robust changes on the ACOM the CADL and the discourse measure from the CAT for the large group.   And then diving in a little bit more deeply for the composition, these data are actually quite interesting. The papers are in review and preparation at the moment, but it looks like we are seeing significant changes for the moderate-to-severe group on objective functional measures and patient reported functional measures of communication, which is so exciting to see for this particular cohort, whose naming scores were zero, in some cases, on entrance, and we're seeing for the mild group, some changes on auditory comprehension, naming, not surprisingly, and also the ACOM and the CADL. So they're showing the same changes, just with different effect sizes or slightly different ranges. And once again, no change in the control group, and in some cases, on some measures, we're seeing a decline in performance over time.   So it's validating that the intervention is helpful in general. What we found with the homogeneous groups is that in a homogeneous large group environment, those groups seem to do a little better. There's a significant effect over time between the homogeneous and the heterogeneous groups. So thinking about why that might have taken place, we wonder if the shared lived experience of your profile of aphasia, your focus on similar kinds of communication, or linguistic targets within the conversation environment might be helping to offset the limited number of practice trials you get in that larger group environment.   So that's an interesting finding to see these differences in who's in the group with you. Because I think clinically, we tend to assign groups, or sort of schedule groups according to what's convenient for the client, what might be pragmatic for the setting, without really wondering why one group could be important or one group might be preferential. If we think about it, there are conflicting hypotheses as to why a group of your like aphasia severity might have a different outcome, right? That idea that you can help people who have a different profile than you, that you're sharing different kinds of models of communication, versus that perhaps more intense practice effect when you share more specific goals and targets and lived experiences. So it's interesting to think about the group environment from that perspective, I think,   Lyssa Rome And to have also some evidence that clinicians and people at aphasia centers can look to help make decisions about group compositions, I think is incredibly helpful.   Earlier, you mentioned that one of the goals of this research project has been to identify the active ingredients of group therapy. And I know that you've been part of a working group for the Rehabilitation Treatment Specification System, or RTSS. Applying that, how have you tried to identify the active ingredients and what? What do you think it is about these treatments that actually drives change?   Liz Hoover I'll first of all say, this is a work in process. You know, I don't think we've got all of the answers. We're just starting to think about it with the idea, again, that if we clinically decide to make some changes to our group, we're at least doing it with some information behind us, and it's a thoughtful and intentional change, as opposed to a gut reaction or a happenstance change. So Gayle and I have worked on developing this image, or this model. It's in a couple of our papers. We can share the resources for that. But it's about trying to think of the flow of communication, group treatment, and what aspects of the treatment might be influential in the outcomes we see downstream.   I think for group treatment, you can't separate entirely many of the ingredients. Group treatment is multifaceted, it's interconnected, and it's not possible—I would heavily debate that with anybody—I don't think it's possible to sort of truly separate some of these ingredients. But when you alter the composition or the environment in which you do the treatment, I do think we are influencing the relative weight of these ingredients.   So we've been thinking about there being this group dynamics component, which is the supportive environment of the peers in the group with you, that social support, the insider affiliation and shared lived experience, the opportunity to observe and see the success of some of these different communication strategies, so that vicarious learning that takes place as you see somebody else practice. But also, I think, cope in a trajectory of your treatment process.   And then we've got linguistic practice so that turn taking where you're actually trying to communicate verbally using supported communication where you're expanding on your utterances or trying to communicate verbally in a specific way or process particular kinds of linguistic targets. A then communication practice in terms of that multimodal effectiveness of communication.   And these then are linked to these three ingredients, dynamic group dynamics, linguistic practice and communication practice. They each have their own mechanism of action or a treatment theory that explains how they might affect change. So for linguistic practice, it's the amount of practice, but also how you hear it practiced or see it practiced with the other group participant. And the same thing for the various multimodal communication acts. And in thinking about a large group versus the dyad or a small group, you know you've got this conflicting hypothesis or the setup for a competing best group, or benefit in that the large group will influence more broadly in the group dynamics, or more deeply in the group dynamics, in that there's a much bigger opportunity to see the vicarious learning and experience the support and potentially experience the communication practice, given a varied number of participants.   But yet in the dyad, your opportunity for linguistic practice is much, much stronger. And our work has counted this the exponential number of turns you get in a dyad versus a large group. And you know, I think that's why the results we saw with the dyad on those linguistic outcomes were unique to that group environment.   Lyssa Rome It points, I think, to the complexity of decision making around group structure and what's right for which client, maybe even so it sounds like some of that work is still in progress. I'm curious about sort of thinking about what you know so far based on this work, what advice would you have for clinicians who are working in aphasia centers or or helping to sort of think about the structure of group treatments? What should clinicians in those roles keep in mind?   Liz Hoover Yeah, that's a great question, and I'll add the caveat that this may change. My advice for this may change in a year's time, or it might evolve as we learn more. But I think what it means is that the decisions you make should be thoughtful. We're starting to learn more about severity in aphasia and how that influences the outcomes. So I think, what is it that your client wants to get out of the group? If they're interested in more linguistic changes, then perhaps the dyad is a better place to start. If they clearly need, or are voicing the need, for more psychosocial support, then the large, you know, traditional sized and perhaps a homogeneous group is the right place to start. But they're both more effective than no treatment. And so being, there's no wrong answer. It's just understanding your client's needs. Is there a better fit?   And I think that's, that's, that's my wish, that people don't see conversation as something that you do at the beginning to build a rapport, but that it's worthy of being an intervention target. It should be most people's primary goal. I think, right, when we ask, what is it you'd like? “I want to talk more. I want to have a conversation.” Audrey Holland would say it's a moral imperative to to treat the conversation and to listen to folks' stories. So just to think carefully about what it is your client wants to achieve, and if there's an environment in which that might be easier to help them achieve that.   Lyssa Rome It's interesting, as you were saying that I was thinking about what you said earlier on about sort of convincing funders about the value of group treatment, but what you're saying now makes me think that it's all your work is also valuable in convincing speech therapists that referrals to groups or dyads is valuable and and also for people with aphasia and their families that it's worth seeking out.   I'm curious about where in the continuum of care this started for the people who were in your trial. I mean, were these people with chronic aphasia who had had strokes years earlier? Was it a mix? And did that make a difference?   Liz Hoover It was a mix. I think our earliest participant was six months post-onset. Our most chronic participant was 26 years post-onset. So a wide range. We want, obviously, from a study perspective, we needed folks to be outside of the traditional window of spontaneous recovery in stroke-induced aphasia.   But it was important to us to have a treatment dose that was reasonable and applicable to a United States healthcare climate, right? So twice a week for an hour is something that people would get reimbursed for. The overall dose is the minimum that's been shown to be effective in the RELEASE collaborative trial papers. And then, you know, but still, half, less than half the dose that the Elman and Bernstein Ellis study found to be effective. So there may be some wiggle room there to see if, if a larger dose is more effective.   But yeah, I think it's that idea of finding funding, convincing people that this is not just a reasonable treatment approach, but a good approach for many outcomes for people with chronic aphasia. I mean, you know, one of the biggest criticisms we hear from the giants in our field is the frustration with aphasia being treated like it's a quick fix and can be done. But you know, so much of the work shows that people are only just beginning to understand their condition by the time they're discharged from traditional outpatient services. And so there's a need for ongoing treatment indefinitely, I think, as your goals change, as you age, and as your wish to participate in different things changes over a lifetime,   Lyssa Rome Yeah, absolutely. And I think too, when we think about sort of the role of hope, if you know, if there is additional evidence showing that there can be change after that sort of traditional initial period, when we think that change happens the most, that can provide a lot of hope and motivation, I think, to people.   Liz Hoover yeah, we're look going to be looking next at predictors of change, so looking at our study entrance scores and trying to identify which participants were the responders versus the non-responders that you know, because group effects are one thing, but it's good to see who seems to benefit the most from these individual types of environments.   And an early finding is that confidence, or what some people in the field, I'm learning now are referring to as actually communication self-efficacy, but that previous exposure to group potentially and that confidence in your communication is inversely correlated with benefits from treatment on other measures. So if you've got a low confidence in your ability to communicate functionally in different environments, you're predicted to be a responder to conversation treatment.   Lyssa Rome Oh, that's really interesting. What else are you looking forward to working on when it comes to this data set or other projects that you have going on?   Liz Hoover Yeah. So as I mentioned, there's a lot of data still for us to dig into, looking at those individual responders or which factors or variables might make an impact. There is the very next on the list, we're also going to be looking very shortly at the dialogic conversation outcomes. So, it's a conversation treatment. How has conversation changed? That's a question we need to answer. So we're looking at that currently, and might look more closely at other measures. And then I think the question of the dose is an interesting one. The question of how individual variables or the saliency of the group may impact change is another potentially interesting question. There are many different directions you can go.   You know, we've got 193 participants in the study, with three separate testing time points, so it's a lot of data to look at still. And I think we want to be sure we understand what we're looking at, and what those active ingredients might be, that we've got the constructs well defined before we start to recruit for another study and to expand on these findings further.   Lyssa Rome When we were meeting earlier, getting ready for this talk, you mentioned to me a really valuable video resource, and I wanted to make sure we take some time to highlight that. Can you tell us a little bit about what you worked on with your colleagues at Boston University?   Liz Hoover Yes, thank you. So I'll tell you a little bit. We have a video education series. Some of you may have heard about this already, but it's up on our website so bu.edu/aphasiacenter, and we'll still share that link as well. And it's a series of short, aphasia-friendly videos that are curated by our community to give advice and share lived experiences from people with aphasia and their care partners.   This project came about right on the heels of the COVID shutdown at our university. I am involved in our diagnostic clinic, and I was seeing folks who had been in acute care through COVID being treated with people who were wearing masks, who had incredibly shortened lengths of stay because people you know rightly, were trying to get them out of a potentially vulnerable environment. And what we were seeing is a newly diagnosed cohort of people with aphasia who were so under-informed about their condition, and Nina that has a famous quote right of the public being woefully uninformed of the aphasia condition and you don't think it can get any worse until It does.   And I thought, gosh, wouldn't it be wonderful to be able to point them to some short education videos that are by people who have lived their same journey or a version of their same journey. So we fundraised and collaborated with a local production company to come up with these videos. And I'll share, Lyssa, we just learned last week that this video series has been awarded the ASHA 2025 Media Outreach Award. So it's an award winning series.   Lyssa Rome Yeah, that's fantastic, and it's so well deserved. They're really beautifully and professionally produced. And I think I really appreciated hearing from so many different people with aphasia about their experiences as the condition is sort of explained more. So thank you for sharing those and we'll put the links in our show notes along with links to the other articles that you've mentioned in this conversation in our show notes. So thanks.   Liz Hoover Yeah, and I'll just put a big shout out to my colleague, Jerry Kaplan, who's the amazing interviewer and facilitator in many of these videos, and the production company, which is Midnight Brunch. But again, the cinematography and the lighting. They're beautifully done. I think I'm very, very happy with them.   Lyssa Rome Yeah, congrats again on the award too. So to wrap up, I'm wondering if there's anything else that you want listeners to take away from this conversation or from the work that you've been doing on conversation treatments.   Liz Hoover I would just say that I would encourage everybody to try group treatment. It's a wonderful option for intervention for people, and to remind everyone of Barbara Shadden and Katie Strong's work, of that embedded storytelling that can come out in conversation, and of the wonderful Audrey Holland's words, of it being a moral imperative to help people tell their story and to converse. It's yeah… You'll drink the Kool Aid if you try it. Let me just put it that way. It's a wonderful intervention that seems to be meaningful for most clients I've ever had the privilege to work with.   Lyssa Rome I agree with that. And meaningful too, I think for clinicians who get to do the work.   Liz Hoover, thank you so much for your work and for coming to talk with us again, for making your second appearance on the podcast. It's been great talking with you.   Liz Hoover Thank you. It's been fun. I appreciate it.   Lyssa Rome And thanks also to our listeners for the references and resources mentioned in today's show. Please see our show notes. They're available on our website, www.aphasiaaccess.org. There, you can also become a member of our organization, browse our growing library of materials and find out about the Aphasia Access Academy. If you have an idea for a future podcast episode, email us at info@aphasia access.org.   Thanks again for your ongoing support of Aphasia Access. For Aphasia Access Conversations. I'm Lyssa Rome.       Resources Walker-Batson, D., Curtis, S., Smith, P., & Ford, J. (1999). An alternative model for the treatment of aphasia: The Lifelink© approach. In R. Elman (Ed.), Group treatment for neurogenic communication disorders: The expert clinician's approach (pp. 67-75). Woburn, MA: Butterworth-Heinemann   Hoover, E.L., DeDe, G., Maas, E. (2021). A randomized controlled trial of the effects of group conversation treatment on monologic discourse in aphasia. Journal of Speech-Language and Hearing Research doi/10.1044/2021_JSLHR-21-00023 Hoover, E., Szabo, G., Kohen, F., Vitale, S., McCloskey, N., Maas, E., Kularni, V., & DeDe., G. (2025). The benefits of conversation group treatment for individuals with chronic aphasia: Updated evidence from a multisite randomized controlled trial on measures of language and communication. American Journal of Speech Language Pathology. DOI: 10.1044/2025_AJSLP-24-00279   Aphasia Resource Center at BU   Living with Aphasia video series Aphasia Access Podcast Episode #15: In Conversation with Liz Hoover

Shane Whaley and author I.S. Berry (The Peacock and the Sparrow) welcome spy thriller author Dan Fesperman to talk about his latest novel, Pariah. What happens when a disgraced stand-up comedian becomes a CIA asset in a fictional Eastern European country? Listen/Watch On. Topics covered include: The real-world politics that inspired Pariah How cancel culture shapes protagonist Hal Knight Building a believable fictional Eastern/Central European setting (Bolrovia!) Why did Dan Fesperman choose to create a fictional country rather than base Pariah in a real country? Humour in serious spy fiction Do spy novels need to have a geopolitical canvas? Food in spy novels. Chimney cake anyone? Why Dan Fesperman's audiobook producer stopped him from singing one of the songs referenced in Pariah. Dan Fesperman also reveals that his next novel will feature Winter Work's Emil Grimm; he also shares his thoughts on what makes a spy novel and the guests give a shoutout to the unsung real-life spies. Dan Fesperman's Pariah is perfect for fans of le Carré, McCloskey, Paul Vidich and for readers craving spy fiction with depth, nuance and laughs. Grab your copy of Pariah now and join the conversation in t

®Ha dedicato una vita allo studio del rapporto tra economia e borghesia, risultati pubblicati in una imponente trilogia: Le virtù borghesi, Dignità borghese, Eguaglianza borghese (trilogia pubblicata in italiano da Silvio Berlusconi editore). I titoli spiegano in poche parole l'intero compito che la McCloskey ha deciso di intraprendere: rivalutare, nella storia dell'economia e delle società moderne, il ruolo che ebbe la borghesia. Classe sociale disprezzata a lungo da artisti e intellettuali europei, ritenuta responsabile (con il capitalismo) della povertà finanziaria, dello scadimento morale, delle guerre, e non solo. Da Platone a Trump, l'economista statunitense ci guida lungo secoli di stereotipi legati alla borghesia, inserisce il dubbio sul rapporto tra etica e mercati, ci illustra il legame tra dignità e libertà individuale, dallo sviluppo di idee e dall'innovazione. Oltre il capitalismo, oltre l'accumulazione, esiste una ricchezza dovuta soprattutto all'”invenzione del modo di inventare”. Prima emissione: 2 luglio 2025

On this episode of Alternative Power Plays, Buchanan's Alan Seltzer and John Povilaitis welcome Stephen McCloskey, Residential Energy Efficiency Analyst at Cape Light Compact. Cape Light Compact is an energy services organization operated by the 21 towns on Cape Cod, Martha's Vineyard and Dukes County in Massachusetts. In his role, McCloskey helps with the administration of its energy efficiency programs for single-family residential customers.During their conversation, the trio take a deep dive into Cape Light Compact's energy efficiency programs, specifically the Cape and Vineyard Electrification Offering, or C-V-E-O, and how they're working to decarbonize the communities they serve. They discuss the unique challenges and opportunities with decarbonization at a smaller scale, the process for customers to adopt greener energy options and how Cape Light is making a difference not just in New England but is actually setting an example for communities well beyond the Northeast.To learn more about Cape Light Compact, visit: https://www.capelightcompact.orgTo learn more about Stephen McCloskey, visit: https://www.capelightcompact.org/staff/stephen-mccloskey/To learn more about Alan Seltzer, visit: https://www.bipc.com/alan-seltzerTo learn more about John Povilaitis, visit: ⁠https://www.bipc.com/john-povilaitis

Mark McCloskey and his wife, Patricia, almost lost everything for simply defending their lives and St. Louis home from the mob. But they fought back, won, and are now helping fellow patriots who are experiencing the weaponization of justice, explains Mark McCloskey in an exclusive interview with Alex Newman for The New American’s Conversations That ... The post Mark McCloskey, Who Protected His Home Against BLM and Antifa, Now Defending J6ers appeared first on The New American.

Send us a textFirst, a look at various stories from across the nation regarding 2nd Amendment rights, such as Mr. McCloskey in St. Louis finally (after 5 years) has his AR-15 returned to him.Then, Wall St. executives are deathly afraid of supporting gun control for fear of Trump having them arrested.New Jersey politicians attempt to exempt themselves from their own gun control laws.MAIN STORYThe ATF is using AI to finish their illegal gun registry, in direct violation of the Firearm Owners Protection Act of 1986 which forbids the creation and maintenance of one.Royce explains why it's time to severely punish everyone involved with this illegal action.https://bearingarms.com/tomknighton/2025/08/04/mccloskeys-finally-get-back-what-was-theirs-n1229482 https:/The Gun Site9-Lane 25 yard indoor Shooting Range, Gun Store, Training classesSHOOTINGCLASSES.COMOnline business operations platform for firearms instructors, trainees, and Shooting RangesSicarios Gun ShopFirearms, Accessories, Ammo, Safes, and more!Glover Orndorf and Flanagan Wealth Mgmt.Wealth management servicesWJS GunsGun and Outdoor Shop, ammo, accessories, fishing tackle, moreFreedom GunsFirearms, Ammunition, Accessories, Training classes Control Jiu-Jitsu/MMAJiu-Jitsu/MMA Training in Melbourne, FLThe American Police Hall of FameMuseum and Shooting Center (open to public), Law Enforcement and Civilian TrainingCounter Strike TacticalBest Little Gun Store in Melbourne, Florida! Veteran Owned and Operated 321-499-4949Go2 WeaponsManufacturers of AR platform rifles for military and civilian. Veteran Owned and OperatedEar Care of MelbourneNeed hearing aids? Go to the audiologists that gave Royce his hearing back!Quantified PerformanceQuantified Performance, LLC is focused on building safe, high performing keepers and bearers.Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.Support the showGiveSendGo | Unconstitutional 2A Prosecution of Tate Adamiak Askari Media GroupBuy Paul Eberle's book "Look at the Dirt"Paul Eberle (lookatthedirt.com)The Deadly Path: How Operation Fast & Furious and Bad Lawyers Armed Mexican Cartels: Forcelli, Peter J., MacGregor, Keelin, Murphy, Stephen: 9798888456491: Amazon.com: BooksVoice of the Blue (buzzsprout.com)

Bestselling author John Grisham and co-author Jim McCloskey wrote about the challenges of exonerating a person who is wrongfully convicted. Princeton Library, Centurion, and Labyrinth Books in Princeton, New Jersey, sponsored this event. Learn more about your ad choices. Visit megaphone.fm/adchoices

Bestselling author John Grisham and co-author Jim McCloskey wrote about the challenges of exonerating a person who is wrongfully convicted. Princeton Library, Centurion, and Labyrinth Books in Princeton, New Jersey, sponsored this event. Learn more about your ad choices. Visit megaphone.fm/adchoices

Milton interviews student J.P. McCloskey about his off-Broadway experience in the Stephen Metcalfe play Strange Snow. J.P. identifies a major challenge: after months of rehearsals without set or props, he felt lost during tech rehearsal. The solution involves building specific relationships to the physical environment through "talking out" what you see and feel about the space.J.P. shares his character breakthrough: moving from himself to the character by giving the character activities outside the play - imagining him at a donut shop, playground, or going through morning routines. This progression from "seeing him in the world" to "thinking like him" to "being him" solved the common problem of character separation.The discussion covers building traumatic backstory by approaching it both from the character's present perspective and experiencing it as it happened, emphasizing the importance of knowing which elements require deeper investment.

Send us a textHaving grown up in New Jersey, Matthew “Matt” McCloskey moved to Fort Collins in 2020. After five years, he now considers Colorado his home.McCloskey first started playing in his pre-teens, performing in open mics at around 13 years old. His parents, who were also musicians, frequently took him to a local coffee shop for the open mic there, and he's never stopped playing gigs.McCloskey started writing songs by the time he reached his late teens, collaborating with his high school band and writing his own material. Before moving to Colorado, he played in a rock band called The Punch Bowl with Ryan Harford, Chris “Softy” Pertain, and Chris Amato. They released a self-titled album in 2018 before taking an indefinite break, reuniting in 2024 for a three-night local tour.McCloskey changes the balance of originals and covers in his shows depending on how long they last. For much longer gigs that last at least three hours, he'll typically perform more covers, but for gigs that are fewer than or around two hours, he'll balance originals and covers as much as he can. Thank you for listening to The Mountain-Ear Podcast, featuring news and culture from peak to peak! Additional pages are linked below!If you want to be involved in the podcast or paper, contact our editor at info@themountainear.com and/or our podcast host at media@themountainear.com! Head to our website for all of the latest news from peak to peak! SUBSCRIBE ONLINE and use the coupon code PODCAST for A 10% DISCOUNT for ALL NEW SUBSCRIBERS! Submit local events to promote them in the paper and on our website! Find us on Facebook @mtnear and Instagram @mtn.ear! Listen and watch on YouTube today! Share this podcast around by scrolling to the bottom of our website home page or by heading to our main hub on Buzzsprout!Thank you for listening!

This week on SOI: - Matt's mom Jeanenne joins the Shores - Jeanenne's journal that Mike read, and then named her “Poetgirl.” - We are each an I, not a we. Gollam is a we. - Poetgirl, poema - We are either a male soul or a female soul - We are each a poem written by God - What has caused the revolt against sexuality - What makes your life force increase, and what makes it decrease Find us here: Jeanenne McCloskey - https://www.rivendellcounseling.com / https://merefemininity.substack.com/p/poetgirl x.com/mattmccloskey x.com/michaelvaclav All Matt's Links - https://solo.to/mattmccloskey All Michael's Links - https://solo.to/michaelvaclav Sovereign Goods - www.etsy.com/shop/SovereignThreadGoods Cafe Medici - mediciroasting.com/?srsltid=AfmBOo…9eDe2OliQmjTc2A

More of our conversation with CIA analyst turned best-selling spy novelist David McCloskey. He and his old CIA associates, John & Jerry, look at CIA fact vs. fiction and how McCloskey brings their experiences to his stories. Also, some German stuff.

Familiar favourite Bygnal Dutson from Open Sky in Zion returns to the pod today, but this time he's joined by his General Manager, Wes McCloskey.Today's episode is all about the nitty gritty of running a glamping business as the GM. What roles and responsibilities does a GM carry out? What's the hardest part of the job? What's Wes' advice to prospective glamping GMs?Open SkyGlampitect North AmericaThe Glamping Insider (Nick's newsletter)Posh OutdoorsSage Outdoor AdvisoryNick's email: nick@posh-outdoors.com

Utah Jazz & Utah Hockey Club playoff futures Jazz TV PxP Craig Bolerjack Whole World News

On Thursday's Rugby Daily, Richie McCormack has the latest - and pretty significant - contract news from Leinster, and we hear from Leo Cullen on the influence of their NIQ players. Rob Baloucoune is back for Ulster, who hand a 200th cap to Stuart McCloskey.Andy Farrell's left the door open for his son to be part of the Lions tour of Australia. And Ellie Kildunne reaches as landmark for England this week in the Six Nations, as Scott Bemand previews the Italian test.

The epizootic of 1872 was a massive outbreak of a flulike illness primarily among horses in North America, Central America, and some islands in the Caribbean. Research: "WHEN A FLU REINED IN NEW YORK." States News Service, 28 Apr. 2020. Gale General OneFile, link.gale.com/apps/doc/A622209555/GPS?u=mlin_n_melpub&sid=bookmark-GPS&xid=2bf7de71. Accessed 3 Feb. 2025. Andrews, Thomas G. “Influenza’s Progress: The Great Epizootic Flu of 1872-73 in the North American West.” Utah Historical Quarterly. Vol. 89. No. 1. Andrews, Thomas G. “The Great Horse Flu of 1872-1873.” The Bill Lane Center for the American West. Stanford University. https://west.stanford.edu/events/great-horse-flu-1872-1873 Andrews, Thomas. “The Great Horse Flu of 1872-1873.” Bill Lane Center for the American West Stanford Department of History. 5/4/2023. https://west.stanford.edu/events/great-horse-flu-1872-1873 Bierer, Bert W. “History of Animal Plagues of North America.” USDA. 1939. https://archive.org/details/CAT75660671/page/22/mode/1up Department of Health, the City of New York. “Report on the Epizootic Influenza Among Horses in 1872-73.” https://archive.org/details/reportdepartmen05unkngoog/page/n259/mode/1up Durkin, Kevin. “The Great Epizootic of 1872.” Reprinted from SustainLife: uarterly Journal of the Ploughshare Institute for Sustainable Culture. Fall 2012. https://www.heritagebarns.com/the-great-epizootic-of-1872 Freeberg, Ernest. “The Horse Flu Epidemic That Brought 19th-Century America to a Stop.” Smithsonian. 12/4/2020. https://www.smithsonianmag.com/history/how-horse-flu-epidemic-brought-19th-century-america-stop-180976453/ Judson, A B. “History and Course of the Epizoötic among Horses upon the North American Continent in 1872-73.” Public health papers and reports vol. 1 (1873): 88-109. Judson, A.B. “Report on the Origin and Progress of the Epizootic among Horses in 1872, With a Table of Mortality in New York (Illustrated with Maps). The Veterinarian : a monthly journal of veterinary science. Volume 47 (Vol. 20 of Fourth Series), January - December 1874. https://archive.org/details/s2023id1378227/page/492/mode/1up Kelly, John. "Why the long face? Because in 1872, nearly every horse in Washington got very ill." Washingtonpost.com, 5 Nov. 2016. Gale OneFile: Business, link.gale.com/apps/doc/A468927553/GPS?u=mlin_n_melpub&sid=bookmark-GPS&xid=26db57c2. Accessed 3 Feb. 2025. Kheraj, Sean. “The Great Epizootic of 1872-73.” NiCHE. https://niche-canada.org/2018/05/03/the-great-epizootic-of-1872-73/ Kheraj, Sean. “The Great Epizootic of 1872–73: Networks of Animal Disease in North American Urban Environments.” Environmental History, July 2018, Vol. 23, No. 3 (July 2018). Via JSTOR. https://www.jstor.org/stable/10.2307/48554105 Law, James. “Influenza in Horses.” Report of the Commissioner of Agriculture, 1872. 1874. https://archive.org/details/reportofcommissi1872unit/page/203/mode/1up Lazarus, Oliver. “The Great Epizootic of 1872: Pandemics, Animals, and Modernity in 19th-Century New York City.” The Gotham Center for New York City History. 2/25/2021. https://www.gothamcenter.org/blog/the-great-epizootic-of-1872 Liautard, A.F. “Report on the Epizootic, as it Appeared in New York.” Report of the Department of Health, the City of New York. https://archive.org/details/reportdepartmen05unkngoog/page/n295/mode/1up McCloskey, Patrick J. “The Great Boston Fire & Epizootic of 1872.” Dakota Digital Review. 12/3/2020. https://dda.ndus.edu/ddreview/the-great-boston-fire-epizootic-of-1872/ McClure, James P. “The Epizootic of 1872: Horses and Disease in a Nation in Motion.” New York History , JANUARY 1998, Vol. 79, No. 1 (JANUARY 1998). Via JSTOR. https://www.jstor.org/stable/23182287 McShane, Clay. “Gelded Age Boston.” The New England Quarterly , Jun., 2001, Vol. 74, No. 2 (Jun., 2001). Via JSTOR. https://www.jstor.org/stable/3185479 Morens and Taubenberger (2010) An avian outbreak associated with panzootic equine influenza in 1872: an early example of highly pathogenic avian influenza? Influenza and Other Respiratory Viruses 4(6), 373–377. Powell, James. “The Great Epizootic.” The Historical Society of Ottawa. https://www.historicalsocietyottawa.ca/publications/ottawa-stories/momentous-events-in-the-city-s-life/the-great-epizootic Sack, Alexandra, et al. "Equine Influenza Virus--A Neglected, Reemergent Disease Threat." Emerging Infectious Diseases, vol. 25, no. 6, June 2019, pp. 1185+. Gale In Context: Opposing Viewpoints, dx.doi.org/10.3201/eid2506.161846. Accessed 3 Feb. 2025. Stolte, Daniel. “UA Study on Flu Evolution May Change Textbooks, History Books.” University of Arizona. https://news.arizona.edu/news/ua-study-on-flu-evolution-may-change-textbooks-history-books See omnystudio.com/listener for privacy information.

In this episode of the Homegrown Podcast, host Joey Haselmayer welcomes Craig McCloskey, a nutrition and health expert, to discuss various aspects of men's health, fitness, and nutrition. Craig shares insights from his upbringing, his journey into the health and wellness field, and the importance of nutrition in sports performance. The conversation delves into the cultural dynamics of health and wellness among men, the impact of diet on performance, and the effects of alcohol and low testosterone on overall health. Key TakeawaysMen often face cultural barriers in pursuing health and wellness.Alcohol consumption can negatively impact testosterone levels.Awareness of diet is crucial for performance and health.Holistic living can be a gateway to better health choices.Understanding the effects of food choices can empower better decisions.Lower testosterone can lead to various health issues in men. Sleep is crucial for testosterone levels and overall health.Sedentary lifestyles can significantly lower testosterone levels.Maintaining muscle mass requires regular physical activity and proper nutrition.Quality of sleep can be more important than quantity.A cool sleeping environment enhances sleep quality.Nutrition impacts sleep and recovery processes.Daily movement is essential for preserving muscle function as we age.Testosterone-boosting nutrients are found in animal-based foods.Avoiding processed foods can help maintain hormonal balance.Understanding individual needs is key to optimizing health. Glycine is essential for good sleep and is found in collagen.A nose-to-tail approach to eating ensures adequate nutrient intake.Keeping the bedroom cool can improve sleep quality.Protein is crucial for muscle mass and overall health.Sourcing local foods can enhance nutritional quality.Creatine supports not only muscle health but also brain function.Supplements should complement a well-rounded diet, not replace it.Eating whole foods is vital for optimal health.Understanding the role of organs in nutrition is important.Find Craig McCloskey HERE.Find Craig on Instagram HERE.Find Homegrown on Instagram HERE.Find Liz Haselmayer on Instagram HERE.Find Joey Haselmayer on Instagram HERE.Shop real food meal plans and children's curriculum HERE.Get  exclusive podcast episodes HERE.Shop natural home goods on Haselmayer Goods HERE.

Matt and Frank welcome in the Bass Fishing Hall Of Fame auction winner, Joe McCloskey for a special edition of Day 4.