Podcast appearances and mentions of Kevin Ryan

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

In this episode of Capital for Good we speak with Julie Samuels, the founder, president, and CEO of Tech:NYC, a network of technology leaders dedicated to fostering a dynamic, diverse, and creative New York. Launched in 2016, Tech:NYC operates at the intersection of business, government, academia, and philanthropy, convening leaders to strengthen New York's innovation economy through policy, partnerships, and programs. We begin with some of Samuels's formative experiences at the intersection of technology and policy: a college internship at the National Center for Supercomputing Applications at the University of Illinois Urbana-Champaign, work as an IP lawyer and at the Electronic Frontier Foundation (EFF), and her leadership of Engine, the national nonprofit focused on technology entrepreneurship and advocacy. We also discuss the context and conditions that would inform the launch of Tech:NYC: the groundwork laid by the Bloomberg Administration to foster the growth of the city's tech sector, a critical mass of tech firms in the city, and industry leaders like Fred Wilson, Kevin Ryan and Tim Armstrong who recognized that better and coordinated leadership could help shape New York's continued growth as the country (and world's) number two tech hub behind Silicon Valley. Samuels is passionate about the technology-city nexus. "Tech culture and tech zeitgeist really lend themselves to an urbanist way of seeing the world," she says. "People in tech have a systems framework, and big urban centers like New York are all about systems — think about things like public transit. This makes for natural connection between tech and urban centers." She notes that New York has been particularly successful in tech because of the diversity of its other industries: companies can apply and test technologies developed on the West Coast to other markets, from financial services and health care to real estate, hospitality, media, fashion, or wherever New York is the world's "center of gravity." According to Samuels, these dynamics underpin the sector's extraordinary growth: today technology is the city's fastest growing industry with over $30 billion in annual venture capital flowing to 25,000 startups and accounting for 300,000 jobs (64 percent growth over the last decade, 41 percent of net job growth since 2019) and nine percent of the Gross City Product. Samuels underscores the cultural reasons this growth is durable: "Tech is a creative industry," she explains. "It benefits from the creative energy of a big city… density, networks of different kinds of people, cultural institutions, night life. When I lived in San Francisco, I would meet tech people who lived in SF. Here, we have New Yorkers who work in tech." Tech:NYC's work has evolved over the last ten years, while remaining true to its mission "to ensure New York City is the best place to start and grow a tech company." For Samuels, this mission is two-fold: create the conditions for the tech industry to thrive and integrate technology into the life of the city in ways that uplift everyone. "As tech radically changes how all of us live and work," Samuels says, "Tech:NYC exists to ensure transition is as smooth as possible." As a research and policy advocacy organization, Tech:NYC focused its early years primarily on technology policy and the role of the tech sector in the city and state's larger economy. Today, Samuels notes, while Tech:NYC still works closely on tech policy — things like data privacy, broadband, or public private partnerships like Empire AI, which will provide state-of-the-art power for New York's top University researchers to develop safe, equitable, and responsible AI — it is also focused more broadly on basic "livability" issues like housing, education, and public safety that allow people to live, work and raise families in New York.  Tech:NYC's work also extends to programs like Decoded Futures, a capacity-building AI initiative that equips leaders from the social sector with the tools and skills to use AI to scale their impact, and the Grid Fellowship, which connects technology leaders with New York's public sector. And since its earliest days, Tech:NYC has undertaken many initiatives in K-12 and higher education and workforce development to invest in the participation of all New Yorkers in the tech economy. We discuss the challenges of the current moment, including the advent of AI and its attending economic and political complexities. Ultimately, Samuels says, "Progress is real; we're strivers, builders, creators. Let's lean into that, and make sure growth happens with intention and with the right guardrails. New York can lead on this."   Mentioned in this episode: Tech:NYC Built to Lead: New York's Momentum Toward Global Leadership in Applied AI, (Tech:NYC and Accenture, 2025)

Full shownotes, transcript, and resources here: https://soundbitesrd.com/314                             Resetting the Rules of Indulgence We often think of food choices as an all-or-nothing equation: healthy eating requires effort and discipline, while treats feel like guilty pleasures or even cheating. But what if treating yourself could actually support your health goals? Today we're talking with food anthropologist Kevin Ryan about restorative treats and the rise of functional foods that go beyond indulgence. We'll explore how new rituals can help us reset habits, rethink the way we define treats, and discover that feeling good may not come from permission to indulge – it may come from giving ourselves the fuel to feel better.

The Supreme Court wrapped up its term with three major decisions, and one surprise that turned out not to be a surprise after all. NPR briefly published a report that suggested Justice Samuel Alito was retiring, which would have handed Donald Trump another Supreme Court appointment, but that story was pulled, leaving us to wonder when that announcement might finally land.The actual rulings were significant enough on their own, though. The Court rejected Trump's effort to end birthright citizenship for the children of undocumented immigrants and temporary visa holders, effectively settling a legal argument that immigration hawks have wanted decided for decades. They've argued for years that the phrase “under the jurisdiction thereof” in the Fourteenth Amendment leaves room to limit birthright citizenship. Trump finally brought that argument to the Supreme Court, and the Court disagreed. At least for now, this feels like settled law, and I'm curious to see where immigration activists go from here.Politics Politics Politics is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The Court also upheld Idaho and West Virginia laws banning transgender athletes from women's and girls' sports. The ruling says Title IX permits sex-separated teams based on biological sex, and while the liberal justices wanted a narrower constitutional review, they agreed on the Title IX question. It feels like this issue has reached a legal endpoint. It's remarkable that Title IX has become the vehicle for defending these policies, but I don't see much room left for this fight in the courts.The final decision struck down federal limits on coordinated spending between political parties and candidates, ruling that the caps violate the First Amendment. Republicans are understandably celebrating because the National Republican Senatorial Committee brought the case, while Democrats are warning about billionaire influence and corruption. I tend to think the real victim here is the political middleman. Most of this money was getting where it wanted to go anyway. People donate to party committees because they want those organizations directing resources into competitive races. If you're worried about billionaire influence, I think the darker corners of campaign finance remain a much bigger issue than the official party committees.Meanwhile, the national media has finally caught up to something I've been talking about for weeks: gas prices keep falling even though every expert expected the opposite after the war with Iran began. I first noticed it at my local gas station in Austin, and it didn't line up with the conventional wisdom that prices shoot up like a rocket and come down like a feather. Now that same question is being asked everywhere. National gas prices have fallen for five straight weeks, crude oil has drifted back into what I'd consider a normal range, and we're steadily moving away from the price spike that followed the conflict. Trump is even publicly pressuring retailers to get prices down to $2.50 a gallon, although it's pretty obvious he'd be thrilled just to get them back near $3.The diplomacy behind all of this is getting more interesting. Iran launched drones at supertankers over the weekend, the United States responded with strikes on missile sites near the Strait of Hormuz, and shipping resumed. At the same time, the Trump administration appears to be running a good cop, bad cop strategy. JD Vance has focused on keeping negotiations alive, while Marco Rubio's trip through the Gulf helped produce an Israel-Lebanon agreement tied to a broader deal with Iran and expanded shipping options through Oman. If crude oil keeps falling despite all of that, then the question I can't shake is the same one I've been asking for weeks: what exactly is Iran's leverage? If they're negotiating denuclearization and they can't keep energy prices elevated, then I need somebody who understands the Iranian system better than I do to explain where the leverage actually is.Chapters00:00:00 - Intro00:03:21 - Tom Kean00:06:41 - Supreme Court Decisions00:12:17 - Iran and Gas Prices00:24:28 - Interview with Kevin Ryan00:46:57 - Colorado Primaries00:54:29 - House of Representatives00:57:46 - Interview with Kevin Ryan, con't01:36:37 - Wrap-up This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.politicspoliticspolitics.com/subscribe

Comedians H. Foley & Kevin Ryan join Big Jay Oakerson, Luis J. Gomez, and Ari Shaffir for the third round of the 2026 Springtern Olympics! The guys discuss the influencer couple who recently announced the terminate their pregnancy after a down syndrome diagnosis. Plus, Foley and Kev analyze the interns and place them on a sliding scale of garbage, then the bottom two battle for their spot in a syrup chugging race. All This and More, ONLY on The Most Offensive Podcast on Earth, The LEGION OF SKANKS!!!Original Air Date: 06/09/26Support our sponsors!Visit BodyBrainCoffee.com and use code LOS20 for a limited time to get 20% off your order! #BodyBrainPodSupport the show & get 30% off SITEWIDE for Father's Day at https://www.sheathunderwear.com #SheathPodSupport the show & get 20% off your Ruiget order with code SKANKS at https://www.rugiet.com/skanks DISCLAIMER: Rugiet prescriptions are compounded medications, available only if prescribed following an online consultation with a licensed clinician. Compounded drugs can be prescribed by federal law, but are not FDA-approved and have not been reviewed by the FDA for safety, effectiveness, or manufacturing. Individual results may vary. Full safety information available at Rugiet.com.New customers get 40% off with code SKANKS at http://GLD.com #GLDpodDon't sleep on @ultrapouches. New customers get 15% off with code LEGION at http://takeultra.com #UltraPouches---------------Skankfest X New Orleans badges available at www.skankfest.com!---------------

"In a class about care-giving, there's a larger mystery to solve among the island's secretive, neo-pagan community. The story is told from the perspective of author Rudyard Kipling." Well, that's a mouthful, and an unexpected narrator. Our guest Kevin Ryan is here to work through the confusion, though! Check him and his work out at tyrantintraining.com or on social media @kevryanperson.And our links!Patreon: https://www.patreon.com/somebodywritethisFacebook: https://facebook.com/somebodywritethisTwitter: https://twitter.com/writethispodInstagram: https://www.instagram.com/writethispod/YouTube: https://www.youtube.com/@SomebodyWriteThis

For this episode Dan, Michael and Helena are joined by Kevin Ryan (@kevryanperson) host of Tyrant In Training (@tyrantpodcast) to look back at a movie Kevin loved watching as a kid, Helena had seen before but Dan and Michael hadn't, Last Action Hero. Nominee for the ‘Grower, Not A Shower' Golden Lobe Award 2025 and 2026. Theme music by @themenniss. Follow @HiltMpod on social media https://linktr.ee/hiltmpod Join our Patreon https://www.patreon.com/hiltmpod Hosted on Acast. See acast.com/privacy for more information.

Trump diverts about $1.8 billion in taxpayers's money to his cronies—just call him President Slush Fund. Ben riffs. Kevin Ryan talks about the lessons he learned from his recent Senate campaign. From there he covers everything from Hegseth in Kentucky to George Washington at Valley Forge. A shout out to Robin Kelly. A call for ranked-choice voting. A plea for a separation between church and state. A recital from Henry the Fifth. And a few words about the paradox of saying Happy Memorial Day. Kevin is the state director for Veterans For All Voters. His views are his own. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Kevin Ryan of Enterprise Ireland joins Jess to discuss the opportunities for Irish businesses in the US, despite the geopolitical uncertainty.

Israel and Lebanon have agreed to a ceasefire after talks in Washington, with President Donald Trump saying it would take effect at 5 p.m. Eastern time on Thursday. He said he spoke with Israeli Prime Minister Benjamin Netanyahu and Lebanese President Joseph Aoun, and plans to bring both to the White House for what he called a major step in relations between the two countries.The agreement is supposed to set up a longer-term framework for stability along the border and touch on broader security issues in the region. But it's landing in a situation where fighting, pressure, and political signaling are all still active in the background.Trump also floated the idea that this could connect to a wider regional deal, including Lebanon's relationship with Hezbollah, the Iran-backed group that plays a major role inside the country.That ties into the bigger question hanging over all of this: Iran. U.S.–Iran talks recently fell apart without a deal, though the White House is still leaving the door open to more negotiations. Nothing is settled there, but it sits underneath almost every other move in the region.Politics Politics Politics is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.In Washington, there's a pretty straightforward way this is being read. Hezbollah's strength in Lebanon is tightly linked to Iranian support. If that support weakens, the balance in the region shifts. If it doesn't, then agreements like this stay limited in what they can actually change.At the same time, Trump has been talking about possible Supreme Court vacancies and new nominees if openings come up, including around Justice Samuel Alito. Nothing has officially changed, but the speculation is already part of the political environment. Any vacancy would go through a Republican-controlled Senate and could lock in the court's current 6–3 conservative split for years.In Congress, a vote to block the sale of military bulldozers to Israel failed, but 40 Democratic senators supported it anyway. Another vote on restricting bomb transfers also picked up support from Democrats. These votes don't change policy on their own, but they show a clear split opening up inside the party over military aid to Israel.That split isn't total, but it's real. Democrats are still generally aligned on Israel, but fewer of them are treating support as automatic, especially as the conflict continues and public pressure builds.Chapters00:00:00 - Intro00:03:58 - RFK Jr.00:05:43 - Religion and Trump's Pope Feud00:07:43 - Kevin Ryan on the Pope and Trump00:54:33 - Update00:54:49 - Israel-Lebanon00:58:25 - Supreme Court Appointments00:59:59 - Israel and Democrats01:02:31 - Dave Levinthal on ActBlue01:31:41 - Wrap-up This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.politicspoliticspolitics.com/subscribe

Ari Shaffir, Kevin Ryan, H. Foley, Ari Matti, Dedrick Flynn, William Montgomery, Hans Kim, D Madness, Michael A. Gonzales, Jon Deas, Matthew Muehling, Joe White, Troy Conrad, Tony Hinchcliffe, Brian Redban - RECORDED– 03/09/2026 Sign up for your one-dollar-per-month trial today at https://shopify.com/killtony Try QUO for free PLUS get 20% off your first 6 months when you go to https://quo.com/killtony Learn more about your ad choices. Visit podcastchoices.com/adchoices Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ari Shaffir, Kevin Ryan, H. Foley, Ari Matti, Dedrick Flynn, William Montgomery, Hans Kim, D Madness, Michael A. Gonzales, Jon Deas, Matthew Muehling, Joe White, Troy Conrad, Tony Hinchcliffe, Brian Redban - RECORDED– 03/09/2026 Sign up for your one-dollar-per-month trial today at https://shopify.com/killtony Try QUO for free PLUS get 20% off your first 6 months when you go to https://quo.com/killtony Learn more about your ad choices. Visit podcastchoices.com/adchoices

Quarter-Bin Podcast #237Star Trek 62 & 63, DC Comics, cover-dated August & September 1994. "The Alone, parts 1 & 2," both written by Kevin Ryan, with art by Rod Whigham & Arne Starr.What happens "Poor Gene" Hendricks attempts to redeem his quarter-bin legacy? Can the Enterprise crew help Gene earn a new nickname? And does someone in the crew ... die???Listen to the episode and find out!  Click on the player below to listen to the episode:  Right-click to download episode directly You may also subscribe to the podcast through iTunes or the RSS Feed. Link: Eugene R. Hendricks, voice actorPromo: The Bat-PodNext Episode: Alien Legion 7 & 8, Marvel/Epic Comics, cover-dated October & December 1988.Send e-mail feedback to relativelygeeky@gmail.com "Like" us on Facebook at https://www.facebook.com/relativelygeekyYou can follow the network on Twitter @Relatively_Geek and the host @ProfessorAlanYou can follow the network on  Bluesky @relativelygeeky.bsky.socialSource: Half Price Books Music in the episode: Ice of Sofia, by White_RecordsMusic promoted by Pixabay

Stand-Up On The Spot! Featuring completely improvised sets from Mark Normand, Matteo Lane, Kevin Ryan, H. Foley & Jeremiah Watkins. No material. Comedians create Stand-Up On The Spot off audience suggestions. Everything is covered from The Olympics to Heated Rivalry, Tandem Bikes, Antidepressants, bidets, and more! Jeremiah Watkins you know from Trailer Tales, Dr. Phil Live, his special DADDY, and as the host and creator of Stand-Up On The Spot. Mark Normand has a new Netflix special streaming now called None too Pleased and is the co-host of We Might Be Drunk w/ Sam Morril and Tuesdays with Stories w/ Joe List. Matteo Lane has multiple specials available on Youtube: The Advice Special, Hair Plugs & Heartache and is the host of the podcast I Never Liked You. Kevin Ryan and H. Foley host the Are You Garbage? Podcast together and both have awesome half hour specials available on Youtube. Follow the Comedians! Jeremiah Watkins  @jeremiahwatkins   @TrailerTalesPod   @standupots  https://www.instagram.com/jeremiahstandup Mark Normand  @marknormand  https://www.instagram.com/marknormand Matteo Lane  @matteolanecomedy  https://www.instagram.com/matteolane Kevin Ryan  @AreYouGarbage  https://www.instagram.com/KevinRyanComedy H. Foley  @AreYouGarbage  https://www.instagram.com/hfoleycomedy Stand-Up On The Spot https://www.instagram.com/standupots  @standupots  Sponsored by: Blue Chew Get 10% off your first month of BlueChew Gold w/ code SPOT @ http://BlueChew.com/ Interested in sponsoring the show? Email standupots@gmail.com for inquiries #1HourSpecial #StandupComedy #MarkNormand #MatteoLane #JeremiahWatkins #HFoley #KevinRyan #StandUpOnTheSpot #SOTS #killtony #AreYouGarbage SOTS NYC: Mark Normand, Matteo Lane, Kevin Ryan, H. Foley & Jeremiah Watkins| Ep 93

Just a few days to Election Day. Ben and Dr D are so excited, they're doing back flips and talking—at the same time! About…Robin, Raja, Juliana and Kevin. Yes, Kevin Ryan. Also JB and Christian. Yes, JB's running mate, who once ate lunch with Ben. And knows a lot about boxing. Also, much talk about why people don't vote.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

We are officially in the phase of a campaign where decency gets tossed aside and the opposition research file is emptied directly into a 30-second spot.One local ad targeting Cook County Commissioner Samantha Steele opens with footage from her DUI arrest and the now-infamous line, “I'm an elected official.” The ad's structure is ruthlessly efficient. Lead with the footage. Transition from self-importance to alleged abuse of power. Tie it together with a tagline about rules not applying to her. On the nasty scale, it earns high marks. It is disciplined, rhythmic, and unforgiving.Then there is the Texas Senate Republican primary, where the National Republican Senatorial Committee and Sen. John Cornyn are going directly at Attorney General Ken Paxton. Divorce. Allegations of infidelity. Wealth accumulation during scandal. Even insinuations about cultural issues designed to rile the base. It is the kind of ad that signals panic or confidence. Sometimes both.Politics Politics Politics is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Contrast that with Paxton's softer spot featuring his daughter speaking about him as a grandfather. It is the standard counterpunch to a scandal narrative: humanize, slow down, soften the edges. When campaigns spend that kind of money on family-centered messaging, it usually means they are trying to cover something sharp underneath.The larger point is simple. As we approach primary day, the gloves are off.Tariffs, Courts, and the $133 Billion QuestionBeyond campaign warfare, the Trump administration is wrestling with the fallout from the Supreme Court striking down its sweeping tariff regime. Roughly $133 billion in collected duties now sit in limbo.Officials are reportedly exploring ways to discourage refund claims, stretch out litigation, or even reimpose tariffs under new legal authorities. Trade lawyers argue the government previously committed to repayment with interest and that courts will scrutinize any attempt to sidestep that obligation.This is less about ideology and more about arithmetic. If companies want their money back, they are likely to get it. The administration may find voluntary compliance from firms seeking goodwill, but legally, the leverage is limited. This is the bargaining phase after a judicial loss.The Epstein Depositions BeginHillary Clinton was deposed behind closed doors in Washington as part of the House Oversight Committee's work on the Epstein files. She maintained that she had no knowledge of wrongdoing involving Jeffrey Epstein or Ghislaine Maxwell.Democrats are pushing for a full, unedited transcript release to prevent selective leaks from shaping the narrative. Tensions flared when Rep. Lauren Boebert leaked an image of Clinton during the deposition, briefly halting proceedings.Next comes Bill Clinton. For those with long political memories, that sense of history repeating itself is unavoidable. Whether anything explosive emerges remains to be seen, but the optics alone ensure sustained attention.Transactional Politics in Real TimePerhaps the most revealing political maneuver of the week came from New York Mayor Zohran Mamdani. In an unscheduled trip to Washington, he reportedly presented President Trump with specific names of detained individuals and requested their release. One Columbia-affiliated detainee was subsequently freed.The broader lesson is something I have observed for years. With Trump, flattery and direct engagement can yield tangible results. Politics is transactional. If you give him a headline he likes or a symbolic win, you may get policy movement in return. Mamdani appears to understand that dynamic.Chapters00:00:00 - Intro00:03:27 - Nasty Political Ads00:10:52 - Interview with Kevin Ryan00:51:33 - Update00:51:47 - Tariffs00:53:13 - Clintons00:54:57 - Mamdani and Trump00:59:13 - Interview with Kevin Ryan, con't01:38:33 - Wrap-up This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.politicspoliticspolitics.com/subscribe

Welcome to The Chrisman Commentary, your go-to daily mortgage news podcast, where industry insights meet expert analysis. Hosted by Robbie Chrisman, this podcast delivers the latest updates on mortgage rates, capital markets, and the forces shaping the housing finance landscape. Whether you're a seasoned professional or just looking to stay informed, you'll get clear, concise breakdowns of market trends and economic shifts that impact the mortgage world.In today's episode, we go through a couple mergers and acquisitions from around the mortgage industry, including an interview with Pennymac's Kevin Ryan on the company's acquisition of Cenlar. Plus, Robbie sits down with Kastle's Rishi Choudhary for a discussion on how AI agents are moving from hype to real impact in mortgage lending and servicing by automating unstructured, high-friction borrower interactions at scale, delivering measurable ROI through lower servicing costs, higher loan officer productivity, and production-proven deployments. And we close by looking at reaction to that very robust delayed January payrolls report.This week's podcasts are Sponsored by Cenlar. Cenlar supports lenders and investors with scalable, best-in-class loan servicing built for today's complex market. From compliance to customer experience, Cenlar helps portfolios perform better, borrowers stay supported, and servicers focus on growth. We're proud to partner with a true industry leader.

Do dietary guidelines still influence how people eat or have influencers replaced them? That's one of the big questions tackled in the January 2026 edition of 3Squares Live! Join hosts Charlie Arnot, Kevin Ryan and Susan Schwallie as they welcome Jess Steier, CEO and founder of Unbiased Science. She discusses the new food pyramid and its impact. Hosted on Acast. See acast.com/privacy for more information.

On this week’s personal finance edition of Merryn Talks Money, Merryn Somerset Webb and John Stepek break down the insurance cover that really matters as we head into 2026. They’re joined by Kevin Ryan, a consumer insurance expert and analyst at Bloomberg Intelligence, who shares what’s shifting in the insurance market and what it means for your money.See omnystudio.com/listener for privacy information.

In the news of the weird, clueless ICE agents round up Native Americans on the grounds that they are illegal aliens who have to be deported to the country they came from. Ben riffs. Heidi Henry gives an update on politics in the Heartland. Data center passes for development. A toxic radium site still not cleaned up. A clueless Democratic Party. And on the positive side—Kevin Ryan got it right. Heidi is one of the founders of Illinois Valley Indivisible, a horse trainer and a proud leftie. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

MAGA Senator Lindsey Graham momentarily told the truth about Trump's election lie—and he was under oath. Ben riffs. Kevin Ryan returns! Talks campaign spending reform, reining in Trump's military powers, why some voters “hate” Democrats, why ICE should be abolished. Also, his thoughts on religion and politics. A Marine Coros veteran and school teacher, Kevin is running in the Democratic primary for U.S. Senate.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Kevin Ryan is a former teacher and United States Marine from the south suburbs of Chicago. He is now running in as a Democratic in the Primary race for U.S. Senate in Illinois. He talks one-on-one with Brian Mackey about ICE, the U.S. struggling economy, and his military background.The 21st Show is Illinois' statewide weekday public radio talk show, connecting Illinois and bringing you the news, culture, and stories that matter to the 21st state. Have thoughts on the show or one of our episodes, or want to share an idea for something we should talk about? Send us an email: talk@21stshow.org. If you'd like to have your say as we're planning conversations, join our texting group! Just send the word "TALK" to (217) 803-0730. Subscribe to our podcast and hear our latest conversations. Apple Podcasts: https://podcasts.apple.com/us/podcast... Spotfy: https://open.spotify.com/show/6PT6pb0... Find past segments, links to our social media and more at our website: 21stshow.org.

Topics discussed, by month:JanuaryThe year opened with Donald Trump's second inauguration and a rapid slate of executive actions, including a controversial move that effectively kept TikTok alive after a brief shutdown. The ceremony highlighted a conspicuous alliance between Trump and major tech figures — framed as an early signal of an AI-driven, business-friendly Trump 2.0 — alongside cultural flashpoints like Elon Musk's gesture that sparked online backlash.FebruaryTrump reintroduced tariffs on Canada and Mexico, triggering market volatility and a sense that the second administration would closely resemble the first. The episode became a turning point for media and political observers, who noted both reduced hysteria compared to 2017 and a more subdued press landscape shaped by declining ratings, clicks, and subscriber growth.Politics Politics Politics is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.MarchA historic blizzard paralyzed much of the American South, hitting northern Louisiana, Mississippi, Alabama, and especially the Dallas–Fort Worth area, where hundreds of thousands lost power. The storm stood out as a rare reminder of infrastructure vulnerability in regions unaccustomed to severe winter weather.April“Liberation Day” marked Trump's sweeping tariff announcement, forcing long-time free-trade conservatives to publicly accept policies they once opposed as markets reacted sharply. The moment crystallized tensions within the GOP coalition, highlighted generational backlash from Gen Z voters, and underscored growing anxiety about the economy, inflation, and job security.MayTrump announced a major economic deal with Qatar, bringing Middle East politics and foreign influence — particularly within right-wing media — into sharper focus. The deal coincided with intensifying divisions inside conservative circles over Qatar, Saudi Arabia, Israel, and the broader regional conflict, exposing deep fractures within the MAGA-aligned media ecosystem.JuneThe U.S. carried out targeted airstrikes on Iran's nuclear facilities in one of the year's strangest and most anticlimactic geopolitical moments. Despite intense speculation and internal right-wing conflict over the prospect of war, the strikes produced no immediate escalation, quickly fading from public attention after briefly dominating political discourse.JulyCatastrophic flooding in Texas over the July 4th holiday killed at least 135 people, with the destruction of a girls' summer camp becoming a focal point for grief and anger. The discussion centered on loss of life, questions about building in known flood zones, and the emotional toll of reporting on tragedy.AugustA surprise U.S.–Russia summit in Alaska brought Vladimir Putin to American soil for the first time in years, framed as a tentative step toward ending the war in Ukraine. SeptemberThe assassination of Charlie Kirk at a Turning Point USA event in Utah dominated the conversation as the defining story of the year. The killing reshaped right-wing media, hardened attitudes around speech and retaliation, exposed moral failures in online discourse, and accelerated the rise of figures like Candace Owens and Nick Fuentes amid what is described as a profound loss of cohesion on the right.OctoberThe longest government shutdown in U.S. history paralyzed Washington and revealed how little clarity even insiders had about its endgame. While it failed to specifically earn the Democrats what they publicly said they wanted, the shutdown ultimately functioned as a political weapon, energizing Democrats in off-year elections while deepening public cynicism about governance and leverage politics.NovemberDemocratic overperformance in off-year elections, including Virginia and New Jersey, reframed the shutdown as a tactical success rather than a policy-driven fight. That momentum quickly curdled into skepticism, with voters sensing a power grab and turning on Democrats once the immediate political payoff was achieved.DecemberThe Trump administration's pardon of former Honduran president Juan Orlando Hernández — convicted of facilitating large-scale cocaine trafficking — sparked debate over executive power, corruption, and contradictions in U.S. anti-narcotics policy. The month closed with a broader reflection on “state of exception” politics, where violence and extralegal force are justified as necessary to restore order, a theme tied back to both Trump's actions and the year's broader political unrest.Chapters00:00:00 - Intro00:01:21 - January00:11:10 - February00:15:47 - March00:18:38 - April00:25:41 - May00:31:54 - June00:37:08 - July00:47:04 - August00:52:22 - September01:27:14 - October01:30:03 - November01:34:48 - December01:44:15 - Wrap-up This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.politicspoliticspolitics.com/subscribe

John Hancock, Jr joins Micheal and John for the hour; the trio discusses the fast approaching end of the NFL season and possible Cardinal moves; Kevin Ryan from Fox 2 discusses Blues, Cardinals & Billikens; Michael & John comment on the substantial lack of construction workers in Texas as ICE raids continue.

The men from "Are You Garbage?" are back for the second part of their visit to the Bonfire. The holidays must be hitting Jay hard because he reminisces about childhood photos where he looks ridiculous. Jay wants to get to the real story behind a photo of his mother and two strange dudes. So he calls his Mom on the air to see if she has answers. He revisits his living situation growing up in Philly that contained many people under one roof. Visit Areyougarbage.com for all their tour dates and online store! *To hear the full show to go www.siriusxm.com/bonfire to learn more! FOLLOW THE CREW ON SOCIAL MEDIA: @thebonfiresxm @louisjohnson @christinemevans @bigjayoakerson @robertkellylive @louwitzkee @jjbwolf Subscribe to SiriusXM Podcasts+ to listen to new episodes of The Bonfire ad-free and a whole week early.  Start a free trial now on Apple Podcasts or by visiting siriusxm.com/podcastsplus. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Modern medicine has helped Big Jay and Kevin Ryan get skinny but their fat wardrobe problems are still service memories. Foley and Bobby have to stretch out their sweaters and shirts before wearing. Perspiration is a common enemy of all these big fellows. | Jacob doesn't think he dresses like a dandy, but prefers to be called a fancy gentleman. Kevin Ryan and H. Foley's podcast is called "Are You Garbage" and they are on tour now! *To hear the full show to go www.siriusxm.com/bonfire to learn more! FOLLOW THE CREW ON SOCIAL MEDIA: @thebonfiresxm @louisjohnson @christinemevans @bigjayoakerson @robertkellylive @louwitzkee @jjbwolf Subscribe to SiriusXM Podcasts+ to listen to new episodes of The Bonfire ad-free and a whole week early.  Start a free trial now on Apple Podcasts or by visiting siriusxm.com/podcastsplus. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Today's show was totally not garbage. Guest appearances from Kevin Ryan & H. Foley, Vincent D'Onofrio, and Luke Spiller highlight the program along with a special concert announcement. (00:00:00) News & Sports(00:10:20) Entertainment News(00:45:31) Camp Out Totals and More(01:14:01) Fox Good Day, Bizarre File(01:28:17) Are You Garbage - Kevin Ryan and H. Foley in Studio(01:57:58) Vincent D'Onfrio Calls in(02:37:19) Bizarre File(02:45:26) Hollywood Trash & Music News(03:15:45) Wrap UpSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Comedians H. Foley & Kevin Ryan join Big Jay Oakerson & Luis J. Gomez to discuss Harrington vs Jake at Skankfest New Orleans, Miss Chile's Death Metal performance at the Miss World beauty pageant and Miss Mexico's altercation with the director of the Miss Universe pageant. Plus, the gang reviews potential contestants for the first ever Miss Skankfest pageant. All This and More, ONLY on The Most Offensive Podcast on Earth, LEGION OF SKANKS!!!Original Air Date: 11/11/25Support our sponsors!Visit BodyBrainCoffee.com and use code LOS25 for a limited time to get 25% off your order! #BodyBrainPodGet 20% off @chubbies with the code LEGION at chubbiesshorts.com/LEGION! #ChubbiesPodSupport the show and get 20% off your first Lucy order with code LEGION at lucy.co/LEGION #LucyPodIf you're 21 or older, get 40% OFF your first order + free shipping @IndaCloud with code SKANKS at inda.shop/SKANKS #indacloudpod---------------

I sit down with Kevin Ryan, a legendary figure in the NYC tech scene and beyond, he is the founder of the incubator and investment company Alley Corp. From co-founding game-changing companies like Business Insider, Gilt, Zola, and Transcend Therapeutics to shaping New York City's future as a civic leader, Kevin's story is one of innovation and trailblazing success.
We explore his journey through the '90s internet boom—growing DoubleClick, navigating the dot-com crash, and selling to Google. But that's just the beginning. Kevin is now at the forefront of a new revolution—harnessing psychedelics to transform mental health. Inspired by groundbreaking science and works like Michael Pollan's How to Change Your Mind, he's investing in biotech startups pushing the boundaries of neuroscience.In this episode, we discuss:Kevin's rise in the tech industry and early internet daysHis role in shaping NYC's tech ecosystemThe intersection of psychedelics, mental health, and innovationHis passion for Burning Man, Glastonbury, and Halloween costume adventures—Batman, anyone?Tune in for an inspiring conversation about innovation, healing, and boldly exploring new territories.Info on Kevin Ryan https://www.linkedin.com/in/kevinryan3/https://alleycorp.com/ Hosted on Acast. See acast.com/privacy for more information.

That’s www.helixsleep.com/belly for 20% Off Sitewide. Make sure you enter our show name after checkout so they know we sent you! Download Cash App Today: https://capl.onelink.me/vFut/p06g4a8g #CashAppPod. Cash App is a financial services platform, not a bank. Banking services provided by Cash App’s bank partner(s). Prepaid debit cards issued by Sutton Bank, Member FDIC. See terms and conditions at https://cash.app/legal/us/en-us/card-agreement. Direct Deposit, Overdraft Coverage and Discounts provided by Cash App, a Block, Inc. brand. Visit http://cash.app/legal/podcast for full disclosures.

Kevin Ryan and H. Foley from Are You Garbage? join Mark and Sam for a booze-soaked reunion full of road stories, Philly nonsense, and deep dives into what makes a real piece of trash. They swap wild comedy club tales, debate classy vs. garbage behavior, and take a few shots along the way. Are You Garbage Podcast: https://areyougarbage.com | YouTube Sponsored by: Support the show and get 20% off your 1st Sheath order with code DRUNK at sheathunderwear.com Your new wardrobe awaits! Get $10 off @chubbies with code DRUNKS at chubbiesshorts.com/DRUNKS #chubbiespod Your new fall wardrobe awaits. For free shipping and 365-day returns, head to quince.com/DRUNK Subscribe to We Might Be Drunk: https://bit.ly/SubscribeToWMBDMerch: https://wemightbedrunkpod.com Sam Morril: https://punchup.live/sammorril/ticketsMark Normand: https://punchup.live/marknormand/tickets ⸻ Check out That Sounds Right — the comedy panel show hosted by the producer of WMBD:https://www.youtube.com/@thatsoundsrightshow Produced by Gotham Production Studios: https://www.gothamproductionstudios.com @GothamProductionStudios | Producer: https://www.instagram.com/mrmatthewpeters #WeMightBeDrunk #MarkNormand #SamMorril #KevinRyan #HFoley #AreYouGarbage #ComedyPodcast #StandUpComedy #BodegaCatWhiskey Learn more about your ad choices. Visit megaphone.fm/adchoices

Dear friends of the show Kevin Ryan and H. Foley from Are You Garbage? return to the pod to discuss their S-tier airport meals, how they're highly intellectual conversationalists, why deli guys at the supermarket are bad news, the travails of Ozempic, their upcoming shows including a major show at The Met in their hometown of Philly, and much more. Kevin, Foley and Stav help callers including a guy whose wife is pregnant after they opened up their marriage to another dude, and a guy who found out his tattoo artist is a bigot but still has one more session to go. See the Are You Garbage? boys live! Get tickets at https://areyougarbage.com/pages/live-shows  Follow Are You Garbage? on social media: www.youtube.com/@AreYouGarbage https://www.instagram.com/areyougarbage/ https://www.tiktok.com/@areyougarbage   https://twitter.com/areyougarbage Upgrade your wallet today! Get 10% Off @Ridge with code STAVVY at https://www.Ridge.com/STAVVY #Ridgepod Head to Green Chef at http://greenchef.com/50stavvy and use code 50STAVVY to get 50% off your first month, then 20% off the next two months with free shipping. Visit https://mintmobile.com/stavvy to get a 3-month premium wireless plan for just $15/month. Start your new morning ritual & get up to 43% off your @MUDWTR with code STAVVY at https://mudwtr.com/STAVVY #mudwtrpod Grow your business right now at Shopify -- no matter what stage you're in. Sign up for a  $1/month trial at https://www.shopify.com/stavvy

Ashley talks with Kevin Ryan, a Marine Corps veteran and public school teacher running for U.S. Senate in Illinois without corporate donors, consultants, or ad buys. Kevin describes his campaign from a converted school bus as he travels to all 102 counties, gathering signatures by hand and talking directly with voters about what they want from their government. The two discuss money in politics, disillusionment with both parties, and how cynicism erodes civic life. It's a grounded look at whether a government of the people, by the people, for the people can still function and what it takes to test that idea in real time.

President Trump recently said about talk show hosts who criticize him: “They're not allowed to do that.”After ABC brought back Jimmy Kimmel, Trump said that he might sue the network.We'll discuss the law, coercion, consequence culture, and more.Our guests: Kevin Ryan, attorney and past president of the Monroe County Bar Association Langston McFadden, attorney with Pullano & Farrow ---Connections is supported by listeners like you. Head to our donation page to become a WXXI member today, support the show, and help us close the gap created by the rescission of federal funding.---Connections airs every weekday from noon-2 p.m. Join the conversation with questions or comments by phone at 1-844-295-TALK (8255) or 585-263-9994, email, Facebook or Twitter. Connections is also livestreamed on the WXXI News YouTube channel each day. You can watch live or access previous episodes here.---Do you have a story that needs to be shared? Pitch your story to Connections.

The week's news gets personal for Ben and Dr D, as you shall see. But first! A roundup of the week's events, including Aurora and the flag, Kevin Ryan's plea, JB in London, and then…Ice comes to Dr D's neighborhood. And one woman's courageous stand.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Trump sues the New York Times for defamation. Ben riffs. Kevin Ryan talks about his long-shot campaign for the U.S. Senate. He's a 33-year-old southwest side, Marine vet, public school history teacher, bartender, self described New Deal Democrat who wants to take money out of politics so billionaires don't control the process. And what's so wrong with that? Kevin's taking his case to the voters, driving from one end of Illinois to the other—MAGA counties included—in a converted school bus inscribed with quotes from great thinkers, like Dr King.. All the experts scoff he can't win. Here's why you might want to vote for him anyway. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Comedians H. Foley, Kevin Ryan, & Steve Rannazzisi join Big Jay Oakerson, Luis J. Gomez, and Dave Smith to discuss Luis' recent incident at a Nine Inch Nails concert, the arrest of comedian Jon Reep, uproar over EBT no longer providing for the purchase of junk foods, and what's in Luis' grocery cart. All This and More, ONLY on The Most Offensive Podcast on Earth, The LEGION OF SKANKS!!!Original Air Date: 09/09/25Support our sponsors!Go to YoKratom.com - home of the $60 kilo!Head to SheathUnderwear.com and use promo code LOS20 for 20% off your order!Shop BruntWorkwear.com/Legion and use promo code LEGION for $10 off!Visit Lucy.co/LEGION and use code LEGION for 20% off your order!Check out BodyBrainCoffee.com and use promo code LOS25 for 25% off your order!---------------

Ben and Dr D have so much to discuss. The Sky. The Jackal's Mistress. School board democracy. Meet Scotty G, the Antioch Republican. Not to confused with Teddy D, the Wilmette Republican. Why DB will beat them both to win the Republican nomination to face off against JB. Also, could Kevin Ryan be Ben's Daiber? Finally, a shoutout to Kenny D's shoutout to the late Bruce Dumont. It took a conservative Republican to put an anti-Daley leftie on the mic.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Kevin Ryan joins Bridget to discuss the ups and downs of a career in freelance writing. With AI churning out soulless content, they defend the gritty, human struggle of writing, why writing should be hard, and breaking the myth of the tortured alcoholic writer. They cover why everyone should have some revolutionary instincts in their 20s, why the loss of trust in media might be healthy, how the center has become so centerless, why some of Kevin's favorite philosophers and writers are critical theorists and post-modernists, how the Left became the Right and the Right became the Left, why journalism should still have gatekeepers, Gen X's moment in the sun, how to give kids the value and thoughtfulness they deserve, and how Bridget became the Forrest Gump of the culture wars.Sponsor Links: - Quest offers 100+ lab tests to empower you to have more control over your health journey. Choose from a variety of test types that best suit your needs, use code PHETASY to get 25% off - https://www.questhealth.com --------------------------------------------------------------------- Bridget Phetasy admires grit and authenticity. On Walk-Ins Welcome, she talks about the beautiful failures and frightening successes of her own life and the lives of her guests. She doesn't conduct interviews—she has conversations. Conversations with real people about the real struggle and will remind you that we can laugh in pain and cry in joy but there's no greater mistake than hiding from it all. By embracing it all, and celebrating it with the stories she'll bring listeners, she believes that our lowest moments can be the building blocks for our eventual fulfillment. ---------------------------------------------------------------------- PHETASY IS a movement disguised as a company. We just want to make you laugh while the world burns. https://www.phetasy.com/ Buy PHETASY MERCH here: https://www.bridgetphetasy.com/ For more content, including the unedited version of Dumpster Fire, BTS content, writing, photos, livestreams and a kick-ass community, subscribe at https://phetasy.com/ Twitter - https://twitter.com/BridgetPhetasy Instagram - https://www.instagram.com/bridgetphetasy/ Podcast - Walk-Ins Welcome with Bridget Phetasy https://itunes.apple.com/us/podcast/walk-ins-welcome/id1437447846 https://open.spotify.com/show/7jbRU0qOjbxZJf9d49AHEh https://play.google.com/music/listen?u=0#/ps/I3gqggwe23u6mnsdgqynu447wvaSupport the show

A short update this week while I'm on the road. Trump will join European leaders, including Ukrainian President Volodymyr Zelensky, for an emergency virtual summit Wednesday ahead of his Friday meeting with Vladimir Putin in Alaska. The talks, organized by German Chancellor Friedrich Merz, will focus on pressuring Russia, addressing seized Ukrainian territory, securing guarantees for Kyiv, and sequencing peace talks. Merz insists on a ceasefire before any negotiations or land swaps, and Europe is pushing for stronger sanctions on Russia's banking sector. Three sessions will bring together EU leaders, NATO chief Mark Rutte, Trump, Vice President JD Vance, and Ukraine's military backers. I've been struck by how closely Europe and NATO are aligned with Trump here — but we've been down this road with Putin before. He's not a trustworthy guy. My bet is Zelensky ends up in the summit, and Trump pushes for a wrap-up.Meanwhile, the Teamsters Union, long a Democratic stronghold, is broadening its political giving under President Sean O'Brien, donating to Republicans as well. It's a big story — a sign that Democrats' hold on organized labor's money and loyalty is eroding, and it's going to be something we need to watch as we move forward.Finally, a judge denied the DOJ's request to unseal grand jury material in the Ghislaine Maxwell case, saying the public would learn little new. The DOJ's handling — including interviewing Maxwell, transferring her to a less restrictive prison, and not notifying victims — has sparked outrage. The public want more answers, but it's unclear what new revelations could satisfy that demand. Would naming names in exchange for a pardon be worth it? That's the moral trade-off now on the table.Chapters00:00:00 - Intro00:02:00 - Interview with Kevin Ryan, pt. 100:30:00 - Update00:34:24 - Interview with Kevin Ryan, pt. 200:57:46 - Wrap-up This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.politicspoliticspolitics.com/subscribe

Charlotte Greenway brings you the Saturday Edition this week and takes a look at the Group 1 Phoenix Stakes, for which Dave Loughnane discusses his runner before Kevin Ryan explains why he's opted to send Inisherin to Deauville for the Group 1 Prix Maurice de Gheest on Sunday, over a trip to York. Then looking at Haydock's fixture tomorrow, we hear from Ollie Sangster and Owen Burrows on their fancied runners in the pattern races. Finally, ahead of tomorrow's Shergar Cup, Robbie Dolan looks forward to having his first ride at Ascot.

Tom in for Nick and joined initially by trainer Kevin Ryan who has opted to send Inisherin to the Prix Maurice de Gheest this weekend over a possible tilt over seven furlongs at York. Kevin tells us why a trip to France is on the cards and David Yates, today's pundit, gives his thoughts. Dave also reflects on Goodwood last week from both a racing perspective and on the news that attendances were up on last year, continuing a theme in the UK. Charlotte has been chatting to Mike Repole after night 1 of the Saratoga Sale and Mike takes us through his purchases. Sabrina Barnwell, President of IEVA, is along to tell us bout next week's Equine Industry Summit at Gowran Park. Jason Singh takes us through some of the highlights of the Tattersalls Book 1 October Yearling Sales Catalogue which is online now. Plus we have our regular Tuesday segments with Timeform's Dan Barber and Weatherbys, where this week we speak to owner breeder Phil Cunningham who owns Saturday's Stewards' Cup winner Two Tribes.

The Big Beautiful Bill looked like it was gliding along. Sure, there were hiccups — Rand Paul grumbled about the debt ceiling, some MAGA accounts didn't fully endorse it — but even then, it felt like controlled turbulence. Paul was performing his role as the token dissenter, the libertarian who always squawks about spending but eventually votes yes with a few tweaks. And he was already telegraphing his price: drop the debt ceiling hike and he's in. Meanwhile, the House side wasn't exactly throwing punches. Everyone was eyeing the Senate. If anything, it seemed like things were lining up for a classic late-June deal — messy but inevitable.Punchbowl's Jake Sherman, who's as wired in as it gets, detailed the emerging gap between the House and Senate versions of the bill. The Senate Finance Committee wants permanent tax breaks that sunset in the House version. They're also pushing to modify or eliminate key Trump-era items — like the no-tax-on-overtime policy and new savings accounts for kids. There's still no consensus on SALT either. Senate Republicans want to water down the $40,000 deduction cap that Trump himself agreed to. That would make some moderate House Republicans happy, but it could risk blowing up the agreement altogether. This is the stuff that actually matters — the policy guts that will be run past the parliamentarian and hashed out in closed-door meetings. But then, out of nowhere… Elon.Politics Politics Politics is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.MAGA Has a Specific TypeTwo days ago, Elon Musk posted that the big beautiful bill was a “disgusting abomination.” Then he followed it up by retweeting Rand Paul with the words “KILL the BILLL.” That's not a passing criticism. That's scorched-earth stuff. And when it comes from a guy like Elon — who has positioned himself as a billionaire warrior for the MAGA cause — it's a challenge. So I did what I always do. I doomscrolled. Not for fun, but for you. To see who flinches. And here's what I found: almost nobody followed his lead.Charlie Kirk, who had been fairly quiet on the bill, suddenly dropped a thread outlining “50 wins” from it — MAGA-branded talking points that sounded like they came from Speaker Johnson's office. He didn't mention Elon. He didn't need to. The timing was the tell. He was staking a claim: this bill is ours. It's Trump's. And we're backing it. Then came Catturd. If you don't know about @Catturd2, well, that's why you listen to this show. The dude's a Twitter account run by a Florida musician, but in the MAGA ecosystem, his voice carries weight. When he turns, people follow. And he wasn't with Elon either.Mike Cernovich — someone who's ridden hard for Elon, slammed his enemies, carried water for his beefs — also pivoted. He made it clear that Trump's agenda is what gets MAGA fired up, not fiscal purity. His message was simple: you might like Elon, but Trump's the main character here. And look, none of these guys are policy wonks. But they are barometers. They're not jumping to Elon's defense. They're lining up behind the machine.Last One In, First One OutElon is learning in real time what it means to be new money in a political world that runs on tenure and loyalty. MAGA isn't a traditional political coalition. It's more like a federation of tribes — influencers, donors, operators — loosely tied together by a shared orbit around Trump. And in that world, being flashy doesn't count for much if you weren't in the trenches in 2016 or 2020. Elon came on board when it was already a moving train. Buying Twitter, firing woke staff, bringing Trump back to the platform — all of that scored him points. But that's not the same as being family.That's why I keep coming back to the same thought: last one in, first one out. Musk might be the richest guy in the world. He might own the place where MAGA influencers gather. But the moment he stepped out of line, they let him drift. Not a coordinated takedown. Just silence. And silence is brutal. He's not getting clowned like Bannon did when he got iced out. He's just floating — a slow, silent uncoupling from the people who used to cheer his every post.Now, Mike Johnson is supposed to speak to Elon about the bill today. Maybe that call smooths things over. Maybe Russ Vought or Stephen Miller reels him back in. Maybe he gets a seat at the table, tweaks the AI language, and declares victory. But right now, he's yelling about the CBO's deficit projections and getting politely ignored. And the MAGA coalition — the one he thought he'd conquered — is moving on without him.Chapters(Minor mic issues during the first 3 minutes of our interview with Kevin, stick with it.)00:00:00 - Intro00:02:57 - Elon vs. the Big Beautiful Bill00:16:36 - Interview with Kevin Ryan00:41:38 - Update00:41:56 - Trump's Travel Ban00:46:09 - Karine Jean-Pierre's Book00:51:46 - AOC Endorses Zohran Mamdani00:56:36 - Interview with Kevin Ryan, con't01:35:46 - Wrap-up This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.politicspoliticspolitics.com/subscribe

Late last night, the news finally came in: the Liberal Party of Canada pulled off the upset and held onto parliamentary power. It wasn't pretty. It wasn't dominant. But they survived — and a few months ago, that seemed almost impossible. They had everything working against them: more than a decade in power, a deeply unpopular former prime minister they had to jettison, and an electorate that looked ready for change. Yet when the votes were counted, the Liberals were still standing.And you can't tell this story without talking about Donald Trump. Trump has been a thorn in Canada's side since his first term — publicly antagonizing Justin Trudeau, calling Canada the "51st state," and slapping brutal tariffs on Canadian goods. That lingering resentment became part of the political terrain in Canada. The Liberal candidate, Mark Carney, didn't just have to run against Peter Poilievre and the Conservative Party — he got to run against the memory of Trump, and against the uncertainty that conservatives couldn't fully distance themselves from.Poilievre never figured out how to adapt. He spent too much time running a traditional opposition campaign and not enough time answering the deeper question a lot of Canadian voters were asking: would a Conservative government just invite more chaos with Trump? Carney seized on that. He didn't have to make it the centerpiece of his campaign, but it was always there in the background. Steady hand versus risk. Familiarity versus volatility.And while some Conservatives are already spinning this as a "moral victory" because of how tight the race was, that's not how elections work. A win is a win. In a parliamentary system, survival is everything. The Liberals get to control the agenda, pick the cabinet, and frame the narrative going into the next few years. That's not moral victory — that's real, tangible power. And for a party that looked like it was about to lose everything, it's a remarkable political save.Now, the Liberals may still need a coalition with the NDP to govern effectively. It's razor-thin. But that's a separate conversation. The scoreboard is the scoreboard. And right now, the score says the Liberals survived. Trump's shadow loomed large over this race — and in the end, it helped save the very people he's spent years antagonizing.Chapters00:00:00 - Intro00:01:28 - WHCA Substack Party00:11:27 - Interview with Kevin Ryan00:28:46 - Update00:29:08 - Canadian Election Results00:31:38 - Big Beautiful Bill's July 4th Deadline00:35:46 - Interview with Kevin Ryan, con't00:57:28 - Wrap-up This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.politicspoliticspolitics.com/subscribe

Back for the third time we bring back the boys from Are You Garbage, H.Foley and Kevin Ryan.  Watch the AYG Route 66 Special out now on YouTube: https://youtu.be/OSkJS1gCDR4?si=2E-SOFEHr9YSsuHe Support the show, download the Prize Picks app, and use code DRUNKS to get $50 instantly after you play your first $5 lineup. Get started by heading to https://prizepicks.onelink.me/LME0/DRUNKS Support the show and check out VIIA. Use code DRUNK for 15% off your order & a free gift for new customers at https://viia.co/DRUNK Subscribe to We Might Be Drunk: https://bit.ly/SubscribeToWMBD  WMBD Merch: https://wemightbedrunkpod.com/ WMBD Clips Page: https://bit.ly/WMBDClips Are You Garbage: https://www.youtube.com/@AreYouGarbage H.Foley: https://www.instagram.com/hfoleycomedy Kevin Ryan: https://www.instagram.com/kevinryancomedy Sam Morril: YouTube Channel: @sammorril Instagram: https://instagram.com/sammorril Tickets/Tour: https://punchup.live/sammorril/tickets Mark Normand: YouTube Channel: @marknormand Instagram: https://www.instagram.com/marknormand Tickets/Tour: https://punchup.live/marknormand/tickets We Might Be Drunk is produced by Gotham Production Studios https://www.gothamproductionstudios.com/ @GothamProductionStudios Producer Matt Peters: https://www.instagram.com/mrmatthewpeters #wemightbedrunk #marknormand #sammorril #podcast #drunkpodcast #comedy #comedian #funny #gothampodcastomedy Tour Dates Announcement

WATCH the Are You Garbage Route 66 Tour | Comedy Special OUT NOW on AYG's YouTube @ https://www.youtube.com/watch?v=OSkJS1gCDR4 Support the D.A.W.G.Z. @ patreon.com/MSsecretpod Support Kippy & Hank @ https://www.patreon.com/areyougarbage Go See Matt Live @ mattmccusker.com/dates Go See Shane Live @ shanemgillis.com Go See AYG Live @ https://punchup.live/areyougarbage/tickets Good Afternoon everybody. Hope you're all having a good week! Hump dayyy haha. We're here with the garbage boyz. They blessed us while in ATX. Check out their new spesh the Route66 Comedy tour now on u tubeeee. Please enjoy. God Bless you all. ps wish shang good luck for snl this wknd - check that out too of course. sat evening. shang night live Download the PrizePicks app or visit https://prizepicks.onelink.me/LME0/DRENCHED today and use code Drenched to get $50 instantly after you play your first $5 lineup

H. Foley, Kevin Ryan, Kam Patterson, William Montgomery, Ari Matti, Hans Kim, D Madness, Michael A. Gonzales, Jon Deas, Matthew Muehling, Joe White, Kristie Nova, Yoni, Troy Conrad, Tony Hinchcliffe, Brian Redban - RECORDED– 02/17/2025 TONY HINCHCLIFFE @TONYHINCHCLIFE TONYHINCHCLIFFE.COM BRIAN REDBAN @REDBAN DEATHSQUAD.TV SUNSETSTRIPATX.COM Right now, our listeners get 35% off when you order through https://nykdpouches.com/tony. 4 out of 5 employers who post on ZipRecruiter get a quality candidate within the first day. See for yourself at https://ziprecruiter.com/killtony Learn more about your ad choices. Visit podcastchoices.com/adchoices

H. Foley, Kevin Ryan, Kam Patterson, William Montgomery, Ari Matti, Hans Kim, D Madness, Michael A. Gonzales, Jon Deas, Matthew Muehling, Joe White, Kristie Nova, Yoni, Troy Conrad, Tony Hinchcliffe, Brian Redban - RECORDED– 02/17/2025TONY HINCHCLIFFE @TONYHINCHCLIFETONYHINCHCLIFFE.COMBRIAN REDBAN@REDBANDEATHSQUAD.TVSUNSETSTRIPATX.COMRight now, our listeners get 35% off when you order through https://nykdpouches.com/tony.4 out of 5 employers who post on ZipRecruiter get a quality candidate within the first day. See for yourself at https://ziprecruiter.com/killtony Learn more about your ad choices. Visit podcastchoices.com/adchoices Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Register for the 2Bears 5K at http://www.2bears5k.com, happening May 4th in Tampa Bay, Florida. Don't miss out on the early bird pricing! SPONSORS: This episode is brought to you by BetterHelp. Give online therapy a try at https://betterhelp.com/BEARS and get 10% off your first month. Secure your online data TODAY by visiting https://ExpressVPN.com/bears. Your summer wardrobe awaits! Get 20% off @‌chubbies with the code cave at https://www.chubbiesshorts.com/cave #chubbiespod Head to https://policygenius.com/BEARS to get your free life insurance quotes and see how much you could save. It's another week of 2 Bears, 1 Cave with Tom Segura joined by a pair of guest bears, the Are You Garbage? boys Kevin Ryan and H. Foley! They've got a documentary special coming out and they talk all about the intimacies of behind the scenes moments and the classic comedy bit of shitting your pants on camera. Christina P had the pleasure of recently appearing on Are You Garbage and the trio give the "Queen of Garbage" her flowers. They also talk about how insane Philadelphia got when they won the Super Bowl, the importance of mean old coaches, getting thrown out of restaurants, financial goals, being a big baller when the bill comes, shady banks, and the homicidal shenanigans of Tom's kids. Check it out! 2 Bears, 1 Cave Ep. 277 https://tomsegura.com/tour https://www.bertbertbert.com/tour https://store.ymhstudios.com Chapters 00:00:00 - Intro 00:05:10 - Crapping Your Pants On Film 00:16:36 - Restaurant Chaos & Philly Super Bowl Bliss 00:24:05 - Clip: Old Mean Coach 00:30:18 - The Queen Of Garbage 00:38:49 - Tom's Kids 00:48:48 - This Is Not Financial Advice 00:55:08 - Shady Banks & Money Goals 01:03:08 - What's Next? 01:09:48 - Big Baller Bills Learn more about your ad choices. Visit megaphone.fm/adchoices